Frequency correlation of probe waves backscattered from small scale ionospheric irregularities generated by high power HF radio waves

NASA Astrophysics Data System (ADS)

Puchkov, V. A.

2016-09-01

Aspect sensitive scattering of multi-frequency probe signals by artificial, magnetic field aligned density irregularities (with transverse size ∼ 1- 10 m) generated in the ionosphere by powerful radio waves is considered. Fluctuations of received signals depending on stochastic properties of the irregularities are calculated. It is shown that in the case of HF probe waves two mechanisms may contribute to the scattered signal fluctuations. The first one is due to the propagation of probe waves in the ionospheric plasma as in a randomly inhomogeneous medium. The second one lies in non-stationary stochastic behavior of irregularities which satisfy the Bragg conditions for the scattering geometry and therefore constitute centers of scattering. In the probe wave frequency band of the order of 10-100 MHz the second mechanism dominates which delivers opportunity to recover some properties of artificial irregularities from received signals. Correlation function of backscattered probe waves with close frequencies is calculated, and it is shown that detailed spatial distribution of irregularities along the scattering vector can be found experimentally from observations of this correlation function.

Shallow slip amplification and enhanced tsunami hazard unravelled by dynamic simulations of mega-thrust earthquakes

PubMed Central

Murphy, S.; Scala, A.; Herrero, A.; Lorito, S.; Festa, G.; Trasatti, E.; Tonini, R.; Romano, F.; Molinari, I.; Nielsen, S.

2016-01-01

The 2011 Tohoku earthquake produced an unexpected large amount of shallow slip greatly contributing to the ensuing tsunami. How frequent are such events? How can they be efficiently modelled for tsunami hazard? Stochastic slip models, which can be computed rapidly, are used to explore the natural slip variability; however, they generally do not deal specifically with shallow slip features. We study the systematic depth-dependence of slip along a thrust fault with a number of 2D dynamic simulations using stochastic shear stress distributions and a geometry based on the cross section of the Tohoku fault. We obtain a probability density for the slip distribution, which varies both with depth, earthquake size and whether the rupture breaks the surface. We propose a method to modify stochastic slip distributions according to this dynamically-derived probability distribution. This method may be efficiently applied to produce large numbers of heterogeneous slip distributions for probabilistic tsunami hazard analysis. Using numerous M9 earthquake scenarios, we demonstrate that incorporating the dynamically-derived probability distribution does enhance the conditional probability of exceedance of maximum estimated tsunami wave heights along the Japanese coast. This technique for integrating dynamic features in stochastic models can be extended to any subduction zone and faulting style. PMID:27725733

Paracousti-UQ: A Stochastic 3-D Acoustic Wave Propagation Algorithm.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Preston, Leiph

Acoustic full waveform algorithms, such as Paracousti, provide deterministic solutions in complex, 3-D variable environments. In reality, environmental and source characteristics are often only known in a statistical sense. Thus, to fully characterize the expected sound levels within an environment, this uncertainty in environmental and source factors should be incorporated into the acoustic simulations. Performing Monte Carlo (MC) simulations is one method of assessing this uncertainty, but it can quickly become computationally intractable for realistic problems. An alternative method, using the technique of stochastic partial differential equations (SPDE), allows computation of the statistical properties of output signals at a fractionmore » of the computational cost of MC. Paracousti-UQ solves the SPDE system of 3-D acoustic wave propagation equations and provides estimates of the uncertainty of the output simulated wave field (e.g., amplitudes, waveforms) based on estimated probability distributions of the input medium and source parameters. This report describes the derivation of the stochastic partial differential equations, their implementation, and comparison of Paracousti-UQ results with MC simulations using simple models.« less

Schumann resonance transients and the search for gravitational waves

NASA Astrophysics Data System (ADS)

Silagadze, Z. K.

2018-02-01

Schumann resonance transients which propagate around the globe can potentially generate a correlated background in widely separated gravitational-wave detectors. We show that due to the distribution of lightning hotspots around the globe, these transients have characteristic time lags, and this feature can be useful to further suppress such a background, especially in searches of the stochastic gravitational-wave background. A brief review of the corresponding literature on Schumann resonances and lightnings is also given.

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth.

PubMed

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

NASA Astrophysics Data System (ADS)

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

The influence of planetary-wave transience on horizontal air motions in the stratosphere

NASA Technical Reports Server (NTRS)

Salby, Murry L.

1992-01-01

The influence of transience of the planetary-wave field on the horizontal air motions and tracer distributions in the stratosphere was investigated in equivalent barotropic calculations. Two classes of transience are considered: a monochromatic traveling wave, representative of discrete components such as the 5- and 16-day waves, and a second-order stochastic process representative of broadband variability. The response to each of these forms of unsteady forcing is investigated in terms of the characteristic time scale of the transience. Results are presented, and the implications these results have on stratospheric behavior are discussed.

Rogue waves in a multistable system.

PubMed

Pisarchik, Alexander N; Jaimes-Reátegui, Rider; Sevilla-Escoboza, Ricardo; Huerta-Cuellar, G; Taki, Majid

2011-12-30

Clear evidence of rogue waves in a multistable system is revealed by experiments with an erbium-doped fiber laser driven by harmonic pump modulation. The mechanism for the rogue wave formation lies in the interplay of stochastic processes with multistable deterministic dynamics. Low-frequency noise applied to a diode pump current induces rare jumps to coexisting subharmonic states with high-amplitude pulses perceived as rogue waves. The probability of these events depends on the noise filtered frequency and grows up when the noise amplitude increases. The probability distribution of spike amplitudes confirms the rogue wave character of the observed phenomenon. The results of numerical simulations are in good agreement with experiments.

Stochastic model of temporal changes of wind spectra in the free atmosphere

NASA Technical Reports Server (NTRS)

Huang, Y. H.

1974-01-01

Data for wind profile spectra changes with respect to time from Cape Kennedy, Florida for the time period from 28 November 1964 to 11 May 1967 have been analyzed. A universal statistical distribution of the spectral change which encompasses all vertical wave numbers, wind speed categories, and elapsed time has been developed for the standard deviation of the time changes of detailed wind profile spectra as a function of wave number.

The influence of Stochastic perturbation of Geotechnical media On Electromagnetic tomography

NASA Astrophysics Data System (ADS)

Song, Lei; Yang, Weihao; Huangsonglei, Jiahui; Li, HaiPeng

2015-04-01

Electromagnetic tomography (CT) are commonly utilized in Civil engineering to detect the structure defects or geological anomalies. CT are generally recognized as a high precision geophysical method and the accuracy of CT are expected to be several centimeters and even to be several millimeters. Then, high frequency antenna with short wavelength are utilized commonly in Civil Engineering. As to the geotechnical media, stochastic perturbation of the EM parameters are inevitably exist in geological scales, in structure scales and in local scales, et al. In those cases, the geometric dimensionings of the target body, the EM wavelength and the accuracy expected might be of the same order. When the high frequency EM wave propagated in the stochastic geotechnical media, the GPR signal would be reflected not only from the target bodies but also from the stochastic perturbation of the background media. To detect the karst caves in dissolution fracture rock, one need to assess the influence of the stochastic distributed dissolution holes and fractures; to detect the void in a concrete structure, one should master the influence of the stochastic distributed stones, et al. In this paper, on the base of stochastic media discrete realizations, the authors try to evaluate quantificationally the influence of the stochastic perturbation of Geotechnical media by Radon/Iradon Transfer through full-combined Monte Carlo numerical simulation. It is found the stochastic noise is related with transfer angle, perturbing strength, angle interval, autocorrelation length, et al. And the quantitative formula of the accuracy of the electromagnetic tomography is also established, which could help on the precision estimation of GPR tomography in stochastic perturbation Geotechnical media. Key words: Stochastic Geotechnical Media; Electromagnetic Tomography; Radon/Iradon Transfer.

Probabilistic tsunami inundation map based on stochastic earthquake source model: A demonstration case in Macau, the South China Sea

NASA Astrophysics Data System (ADS)

Li, Linlin; Switzer, Adam D.; Wang, Yu; Chan, Chung-Han; Qiu, Qiang; Weiss, Robert

2017-04-01

Current tsunami inundation maps are commonly generated using deterministic scenarios, either for real-time forecasting or based on hypothetical "worst-case" events. Such maps are mainly used for emergency response and evacuation planning and do not include the information of return period. However, in practice, probabilistic tsunami inundation maps are required in a wide variety of applications, such as land-use planning, engineer design and for insurance purposes. In this study, we present a method to develop the probabilistic tsunami inundation map using a stochastic earthquake source model. To demonstrate the methodology, we take Macau a coastal city in the South China Sea as an example. Two major advances of this method are: it incorporates the most updated information of seismic tsunamigenic sources along the Manila megathrust; it integrates a stochastic source model into a Monte Carlo-type simulation in which a broad range of slip distribution patterns are generated for large numbers of synthetic earthquake events. When aggregated the large amount of inundation simulation results, we analyze the uncertainties associated with variability of earthquake rupture location and slip distribution. We also explore how tsunami hazard evolves in Macau in the context of sea level rise. Our results suggest Macau faces moderate tsunami risk due to its low-lying elevation, extensive land reclamation, high coastal population and major infrastructure density. Macau consists of four districts: Macau Peninsula, Taipa Island, Coloane island and Cotai strip. Of these Macau Peninsula is the most vulnerable to tsunami due to its low-elevation and exposure to direct waves and refracted waves from the offshore region and reflected waves from mainland. Earthquakes with magnitude larger than Mw8.0 in the northern Manila trench would likely cause hazardous inundation in Macau. Using a stochastic source model, we are able to derive a spread of potential tsunami impacts for earthquakes with the same magnitude. The diversity is caused by both random rupture locations and heterogeneous slip distribution. Adding the sea level rise component, the inundated depth caused by 1 m sea level rise is equivalent to the one caused by 90 percentile of an ensemble of Mw8.4 earthquakes.

Scattering theory of stochastic electromagnetic light waves.

PubMed

Wang, Tao; Zhao, Daomu

2010-07-15

We generalize scattering theory to stochastic electromagnetic light waves. It is shown that when a stochastic electromagnetic light wave is scattered from a medium, the properties of the scattered field can be characterized by a 3 x 3 cross-spectral density matrix. An example of scattering of a spatially coherent electromagnetic light wave from a deterministic medium is discussed. Some interesting phenomena emerge, including the changes of the spectral degree of coherence and of the spectral degree of polarization of the scattered field.

Stochastic generators of multi-site daily temperature: comparison of performances in various applications

NASA Astrophysics Data System (ADS)

Evin, Guillaume; Favre, Anne-Catherine; Hingray, Benoit

2018-02-01

We present a multi-site stochastic model for the generation of average daily temperature, which includes a flexible parametric distribution and a multivariate autoregressive process. Different versions of this model are applied to a set of 26 stations located in Switzerland. The importance of specific statistical characteristics of the model (seasonality, marginal distributions of standardized temperature, spatial and temporal dependence) is discussed. In particular, the proposed marginal distribution is shown to improve the reproduction of extreme temperatures (minima and maxima). We also demonstrate that the frequency and duration of cold spells and heat waves are dramatically underestimated when the autocorrelation of temperature is not taken into account in the model. An adequate representation of these characteristics can be crucial depending on the field of application, and we discuss potential implications in different contexts (agriculture, forestry, hydrology, human health).

Upper Limits on the Stochastic Gravitational-Wave Background from Advanced LIGO's First Observing Run

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Beer, C.; Bejger, M.; Belahcene, I.; Belgin, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, A. S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Campbell, W.; Canepa, M.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, H.-P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conti, L.; Cooper, S. J.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, E.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Daw, E. J.; Day, B.; Day, R.; De, S.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Essick, R. C.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fernández Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fong, H.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kennedy, R.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, Whansun; Kim, W.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lovelace, G.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGrath, C.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Mytidis, A.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Rhoades, E.; Ricci, F.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schlassa, S.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T. J.; Shahriar, M. S.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson, S. P.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tao, D.; Tápai, M.; Taracchini, A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tippens, T.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tse, M.; Tso, R.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2017-03-01

A wide variety of astrophysical and cosmological sources are expected to contribute to a stochastic gravitational-wave background. Following the observations of GW150914 and GW151226, the rate and mass of coalescing binary black holes appear to be greater than many previous expectations. As a result, the stochastic background from unresolved compact binary coalescences is expected to be particularly loud. We perform a search for the isotropic stochastic gravitational-wave background using data from Advanced Laser Interferometer Gravitational Wave Observatory's (aLIGO) first observing run. The data display no evidence of a stochastic gravitational-wave signal. We constrain the dimensionless energy density of gravitational waves to be Ω0<1.7 ×10-7 with 95% confidence, assuming a flat energy density spectrum in the most sensitive part of the LIGO band (20-86 Hz). This is a factor of ˜33 times more sensitive than previous measurements. We also constrain arbitrary power-law spectra. Finally, we investigate the implications of this search for the background of binary black holes using an astrophysical model for the background.

Upper Limits on the Stochastic Gravitational-Wave Background from Advanced LIGO's First Observing Run.

PubMed

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Yvert, M; Zadrożny, A; Zangrando, L; Zanolin, M; Zendri, J-P; Zevin, M; Zhang, L; Zhang, M; Zhang, T; Zhang, Y; Zhao, C; Zhou, M; Zhou, Z; Zhu, S J; Zhu, X J; Zucker, M E; Zweizig, J

2017-03-24

A wide variety of astrophysical and cosmological sources are expected to contribute to a stochastic gravitational-wave background. Following the observations of GW150914 and GW151226, the rate and mass of coalescing binary black holes appear to be greater than many previous expectations. As a result, the stochastic background from unresolved compact binary coalescences is expected to be particularly loud. We perform a search for the isotropic stochastic gravitational-wave background using data from Advanced Laser Interferometer Gravitational Wave Observatory's (aLIGO) first observing run. The data display no evidence of a stochastic gravitational-wave signal. We constrain the dimensionless energy density of gravitational waves to be Ω_{0}<1.7×10^{-7} with 95% confidence, assuming a flat energy density spectrum in the most sensitive part of the LIGO band (20-86 Hz). This is a factor of ∼33 times more sensitive than previous measurements. We also constrain arbitrary power-law spectra. Finally, we investigate the implications of this search for the background of binary black holes using an astrophysical model for the background.

Searching for the stochastic gravitational-wave background in Advanced LIGO's first observing run

NASA Astrophysics Data System (ADS)

Meyers, Patrick

2017-01-01

One of the most exciting prospects of gravitational-wave astrophysics and cosmology is the measurement of the stochastic gravitational-wave background. In this talk, we discuss the most recent searches for a stochastic background with Advanced LIGO--the first performed with advanced interferometric detectors. We search for an isotropic as well as an anisotropic background, and perform a directed search for persistent gravitational waves in three promising directions. Additionally, with the accumulation of more Advanced LIGO data and the anticipated addition of Advanced Virgo to the network in 2017, we can also start to consider what the recent gravitational-wave detections--GW150914 and GW151226--tell us about when we can expect a detection of the stochastic background from binary black hole coalescences. For the LIGO Scientific Collaboration and the Virgo Collaboration.

Stochastic three-wave interaction in flaring solar loops

NASA Technical Reports Server (NTRS)

Vlahos, L.; Sharma, R. R.; Papadopoulos, K.

1983-01-01

A model is proposed for the dynamic structure of high-frequency microwave bursts. The dynamic component is attributed to beams of precipitating electrons which generate electrostatic waves in the upper hybrid branch. Coherent upconversion of the electrostatic waves to electromagnetic waves produces an intrinsically stochastic emission component which is superposed on the gyrosynchrotron continuum generated by stably trapped electron fluxes. The role of the density and temperature of the ambient plasma in the wave growth and the transition of the three wave upconversion to stochastic, despite the stationarity of the energy source, are discussed in detail. The model appears to reproduce the observational features for reasonable parameters of the solar flare plasma.

Convective and diffusive ULF wave driven radiation belt electron transport

NASA Astrophysics Data System (ADS)

Degeling, A. W.; Rankin, R.; Elkington, S. R.

2011-12-01

The process of magnetospheric radiation belt electron transport driven by ULF waves is studied using a 2-D ideal MHD model for ULF waves in the equatorial plane including day/night asymmetry and a magnetopause boundary, and a test kinetic model for equatorially mirroring electrons. We find that ULF wave disturbances originating along the magnetopause flanks in the afternoon sector can act to periodically inject phase space density from these regions into the magnetosphere. Closely spaced drift-resonant surfaces for electrons with a given magnetic moment in the presence of the ULF waves create a layer of stochastic dynamics for L-shells above 6.5-7 in the cases examined, extending to the magnetopause. The phase decorrelation time scale for the stochastic region is estimated by the relaxation time for the diffusion coefficient to reach a steady value. This is found to be of the order of 10-15 wave periods, which is commensurate with the typical duration of observed ULF wave packets in the magnetosphere. For L-shells earthward of the stochastic layer, transport is limited to isolated drift-resonant islands in the case of narrowband ULF waves. We examine the effect of increasing the bandwidth of the ULF wave driver by summing together wave components produced by a set of independent runs of the ULF wave model. The wave source spectrum is given a flat-top amplitude of variable width (adjusted for constant power) and random phase. We find that increasing bandwidth can significantly enhance convective transport earthward of the stochastic layer and extend the stochastic layer to lower L-shells.

An upper limit on the stochastic gravitational-wave background of cosmological origin.

PubMed

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2009-08-20

A stochastic background of gravitational waves is expected to arise from a superposition of a large number of unresolved gravitational-wave sources of astrophysical and cosmological origin. It should carry unique signatures from the earliest epochs in the evolution of the Universe, inaccessible to standard astrophysical observations. Direct measurements of the amplitude of this background are therefore of fundamental importance for understanding the evolution of the Universe when it was younger than one minute. Here we report limits on the amplitude of the stochastic gravitational-wave background using the data from a two-year science run of the Laser Interferometer Gravitational-wave Observatory (LIGO). Our result constrains the energy density of the stochastic gravitational-wave background normalized by the critical energy density of the Universe, in the frequency band around 100 Hz, to be <6.9 x 10(-6) at 95% confidence. The data rule out models of early Universe evolution with relatively large equation-of-state parameter, as well as cosmic (super)string models with relatively small string tension that are favoured in some string theory models. This search for the stochastic background improves on the indirect limits from Big Bang nucleosynthesis and cosmic microwave background at 100 Hz.

Detection methods for non-Gaussian gravitational wave stochastic backgrounds

NASA Astrophysics Data System (ADS)

Drasco, Steve; Flanagan, Éanna É.

2003-04-01

A gravitational wave stochastic background can be produced by a collection of independent gravitational wave events. There are two classes of such backgrounds, one for which the ratio of the average time between events to the average duration of an event is small (i.e., many events are on at once), and one for which the ratio is large. In the first case the signal is continuous, sounds something like a constant hiss, and has a Gaussian probability distribution. In the second case, the discontinuous or intermittent signal sounds something like popcorn popping, and is described by a non-Gaussian probability distribution. In this paper we address the issue of finding an optimal detection method for such a non-Gaussian background. As a first step, we examine the idealized situation in which the event durations are short compared to the detector sampling time, so that the time structure of the events cannot be resolved, and we assume white, Gaussian noise in two collocated, aligned detectors. For this situation we derive an appropriate version of the maximum likelihood detection statistic. We compare the performance of this statistic to that of the standard cross-correlation statistic both analytically and with Monte Carlo simulations. In general the maximum likelihood statistic performs better than the cross-correlation statistic when the stochastic background is sufficiently non-Gaussian, resulting in a gain factor in the minimum gravitational-wave energy density necessary for detection. This gain factor ranges roughly between 1 and 3, depending on the duty cycle of the background, for realistic observing times and signal strengths for both ground and space based detectors. The computational cost of the statistic, although significantly greater than that of the cross-correlation statistic, is not unreasonable. Before the statistic can be used in practice with real detector data, further work is required to generalize our analysis to accommodate separated, misaligned detectors with realistic, colored, non-Gaussian noise.

Crossing the threshold

NASA Astrophysics Data System (ADS)

Bush, John; Tambasco, Lucas

2017-11-01

First, we summarize the circumstances in which chaotic pilot-wave dynamics gives rise to quantum-like statistical behavior. For ``closed'' systems, in which the droplet is confined to a finite domain either by boundaries or applied forces, quantum-like features arise when the persistence time of the waves exceeds the time required for the droplet to cross its domain. Second, motivated by the similarities between this hydrodynamic system and stochastic electrodynamics, we examine the behavior of a bouncing droplet above the Faraday threshold, where a stochastic element is introduced into the drop dynamics by virtue of its interaction with a background Faraday wave field. With a view to extending the dynamical range of pilot-wave systems to capture more quantum-like features, we consider a generalized theoretical framework for stochastic pilot-wave dynamics in which the relative magnitudes of the drop-generated pilot-wave field and a stochastic background field may be varied continuously. We gratefully acknowledge the financial support of the NSF through their CMMI and DMS divisions.

On square-wave-driven stochastic resonance for energy harvesting in a bistable system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Dongxu, E-mail: sudx@iis.u-tokyo.ac.jp; Zheng, Rencheng; Nakano, Kimihiko

Stochastic resonance is a physical phenomenon through which the throughput of energy within an oscillator excited by a stochastic source can be boosted by adding a small modulating excitation. This study investigates the feasibility of implementing square-wave-driven stochastic resonance to enhance energy harvesting. The motivating hypothesis was that such stochastic resonance can be efficiently realized in a bistable mechanism. However, the condition for the occurrence of stochastic resonance is conventionally defined by the Kramers rate. This definition is inadequate because of the necessity and difficulty in estimating white noise density. A bistable mechanism has been designed using an explicit analyticalmore » model which implies a new approach for achieving stochastic resonance in the paper. Experimental tests confirm that the addition of a small-scale force to the bistable system excited by a random signal apparently leads to a corresponding amplification of the response that we now term square-wave-driven stochastic resonance. The study therefore indicates that this approach may be a promising way to improve the performance of an energy harvester under certain forms of random excitation.« less

Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Afrough, M.; Agarwal, B.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allen, G.; Allocca, A.; Altin, P. A.; Amato, A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Angelova, S. V.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Atallah, D. V.; Aufmuth, P.; Aulbert, C.; AultONeal, K.; Austin, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Bae, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Banagiri, S.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barkett, K.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bawaj, M.; Bayley, J. C.; Bazzan, M.; Bécsy, B.; Beer, C.; Bejger, M.; Belahcene, I.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Bero, J. J.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bode, N.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonilla, E.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bossie, K.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Canepa, M.; Canizares, P.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Carney, M. F.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerdá-Durán, P.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chase, E.; Chassande-Mottin, E.; Chatterjee, D.; Cheeseboro, B. D.; Chen, H. Y.; Chen, X.; Chen, Y.; Cheng, H.-P.; Chia, H.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, A. K. W.; Chung, S.; Ciani, G.; Ciolfi, R.; Cirelli, C. E.; Cirone, A.; Clara, F.; Clark, J. A.; Clearwater, P.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Cohen, D.; Colla, A.; Collette, C. G.; Cominsky, L. R.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-Carrión, I.; Corley, K. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, E.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Canton, T. Dal; Dálya, G.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davis, D.; Daw, E. J.; Day, B.; De, S.; DeBra, D.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Demos, N.; Denker, T.; Dent, T.; De Pietri, R.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; De Rossi, C.; DeSalvo, R.; de Varona, O.; Devenson, J.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Dreissigacker, C.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dupej, P.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Estevez, D.; Etienne, Z. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fee, C.; Fehrmann, H.; Feicht, J.; Fejer, M. M.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Finstad, D.; Fiori, I.; Fiorucci, D.; Fishbach, M.; Fisher, R. P.; Fitz-Axen, M.; Flaminio, R.; Fletcher, M.; Fong, H.; Font, J. A.; Forsyth, P. W. F.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Ganija, M. R.; Gaonkar, S. G.; Garcia-Quiros, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, D.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; Goncharov, B.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Gretarsson, E. M.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Halim, O.; Hall, B. R.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hinderer, T.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hreibi, A.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kapadia, S. J.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, K.; Kim, W.; Kim, W. S.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kinley-Hanlon, M.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Knowles, T. D.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kumar, S.; Kuo, L.; Kutynia, A.; Kwang, S.; Lackey, B. D.; Lai, K. H.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, H. W.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Linker, S. D.; Littenberg, T. B.; Liu, J.; Lo, R. K. L.; Lockerbie, N. A.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macas, R.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña Hernandez, I.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Markowitz, A.; Maros, E.; Marquina, A.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Mason, K.; Massera, E.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McCuller, L.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McNeill, L.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Mejuto-Villa, E.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, B. B.; Miller, J.; Millhouse, M.; Milovich-Goff, M. C.; Minazzoli, O.; Minenkov, Y.; Ming, J.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moffa, D.; Moggi, A.; Mogushi, K.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muñiz, E. A.; Muratore, M.; Murray, P. G.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Neilson, J.; Nelemans, G.; Nelson, T. J. N.; Nery, M.; Neunzert, A.; Nevin, L.; Newport, J. M.; Newton, G.; Ng, K. K. Y.; Nguyen, T. T.; Nichols, D.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; North, C.; Nuttall, L. K.; Oberling, J.; O'Dea, G. D.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Okada, M. A.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ormiston, R.; Ortega, L. F.; O'Shaughnessy, R.; Ossokine, S.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Page, M. A.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, Howard; Pan, Huang-Wei; Pang, B.; Pang, P. T. H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Parida, A.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patil, M.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pirello, M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Pratten, G.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rajbhandari, B.; Rakhmanov, M.; Ramirez, K. E.; Ramos-Buades, A.; Rapagnani, P.; Raymond, V.; Razzano, M.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Ren, W.; Reyes, S. D.; Ricci, F.; Ricker, P. M.; Rieger, S.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romel, C. L.; Romie, J. H.; Rosińska, D.; Ross, M. P.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Rutins, G.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sanchez, L. E.; Sanchis-Gual, N.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheel, M.; Scheuer, J.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schulte, B. W.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Seidel, E.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D. A.; Shaffer, T. J.; Shah, A. A.; Shahriar, M. S.; Shaner, M. B.; Shao, L.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, L. P.; Singh, A.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Somala, S.; Son, E. J.; Sonnenberg, J. A.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staats, K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stevenson, S. P.; Stone, R.; Stops, D. J.; Strain, K. A.; Stratta, G.; Strigin, S. E.; Strunk, A.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Suresh, J.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Tait, S. C.; Talbot, C.; Talukder, D.; Tanner, D. B.; Tao, D.; Tápai, M.; Taracchini, A.; Tasson, J. D.; Taylor, J. A.; Taylor, R.; Tewari, S. V.; Theeg, T.; Thies, F.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tonelli, M.; Tornasi, Z.; Torres-Forné, A.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tsang, K. W.; Tse, M.; Tso, R.; Tsukada, L.; Tsuna, D.; Tuyenbayev, D.; Ueno, K.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walet, R.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, J. Z.; Wang, W. H.; Wang, Y. F.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessel, E. K.; Weßels, P.; Westerweck, J.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Wilken, D.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wysocki, D. M.; Xiao, S.; Yamamoto, H.; Yancey, C. C.; Yang, L.; Yap, M. J.; Yazback, M.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2018-05-01

The detection of gravitational waves with Advanced LIGO and Advanced Virgo has enabled novel tests of general relativity, including direct study of the polarization of gravitational waves. While general relativity allows for only two tensor gravitational-wave polarizations, general metric theories can additionally predict two vector and two scalar polarizations. The polarization of gravitational waves is encoded in the spectral shape of the stochastic gravitational-wave background, formed by the superposition of cosmological and individually unresolved astrophysical sources. Using data recorded by Advanced LIGO during its first observing run, we search for a stochastic background of generically polarized gravitational waves. We find no evidence for a background of any polarization, and place the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background. Under log-uniform priors for the energy in each polarization, we limit the energy densities of tensor, vector, and scalar modes at 95% credibility to Ω0T<5.58 ×10-8 , Ω0V<6.35 ×10-8 , and Ω0S<1.08 ×10-7 at a reference frequency f0=25 Hz .

Seismic Attenuation and Stiffness Modulus Dispersion in Porous Rocks Containing Stochastic Fracture Networks

NASA Astrophysics Data System (ADS)

Hunziker, Jürg; Favino, Marco; Caspari, Eva; Quintal, Beatriz; Rubino, J. Germán.; Krause, Rolf; Holliger, Klaus

2018-01-01

Understanding seismic attenuation and modulus dispersion mechanisms in fractured rocks can result in significant advances for the indirect characterization of such environments. In this paper, we study attenuation and modulus dispersion of seismic waves caused by fluid pressure diffusion (FPD) in stochastic 2-D fracture networks, allowing for a state-of-the-art representation of natural fracture networks by a power law length distribution. To this end, we apply numerical upscaling experiments consisting of compression and shear tests to our samples of fractured rocks. The resulting P and S wave attenuation and modulus dispersion behavior is analyzed with respect to the density, the length distribution, and the connectivity of the fractures. We focus our analysis on two manifestations of FPD arising in fractured rocks, namely, fracture-to-background FPD at lower frequencies and fracture-to-fracture FPD at higher frequencies. Our results indicate that FPD is sensitive not only to the fracture density but also to the geometrical characteristics of the fracture length distributions. In particular, our study suggests that information about the local connectivity of a fracture network could be retrieved from seismic data. Conversely, information about the global connectivity, which is directly linked to the effective hydraulic conductivity of the probed volume, remains rather difficult to infer.

Stochastic acceleration of electrons. I - Effects of collisions in solar flares

NASA Technical Reports Server (NTRS)

Hamilton, Russell J.; Petrosian, Vahe

1992-01-01

Stochastic acceleration of thermal electrons to nonrelativistic energies is studied under solar flare conditions. We show that, in turbulent regions, electron-whistler wave interactions can result in the acceleration of electrons in times comparable to or shorter than the Coulomb collision time. The kinetic equation describing the evolution of the electron energy distribution including stochastic acceleration by whistlers and energy loss via Coulomb interactions is solved for an initial thermal electron energy spectrum. In general, the shape of the resulting electron distributions are characterized by the energy E(c) where systematic energy gain by turbulence equals energy loss due to Coulomb collisions. For energies less than E(c), the spectra are steep (quasi-thermal) whereas above E(c), the spectra are power laws. We find that hard X-ray spectra computed using the electron distributions obtained from our numerical simulations are able to explain the complex spectral shapes and variations observed in impulsive hard X-ray bursts. In particular, we show that the gradual steepening observed by Lin et al. (1981) could be due to a systematic increase in the density of the plasma (due to evaporation) and the increasing importance of collisions instead of the appearance of a superhot thermal component.

Statistical properties of two sine waves in Gaussian noise.

NASA Technical Reports Server (NTRS)

Esposito, R.; Wilson, L. R.

1973-01-01

A detailed study is presented of some statistical properties of a stochastic process that consists of the sum of two sine waves of unknown relative phase and a normal process. Since none of the statistics investigated seem to yield a closed-form expression, all the derivations are cast in a form that is particularly suitable for machine computation. Specifically, results are presented for the probability density function (pdf) of the envelope and the instantaneous value, the moments of these distributions, and the relative cumulative density function (cdf).

Improved Upper Limits on the Stochastic Gravitational-Wave Background from 2009-2010 LIGO and Virgo Data

NASA Astrophysics Data System (ADS)

Aasi, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Accadia, T.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Affeldt, C.; Agathos, M.; Aggarwal, N.; Aguiar, O. D.; Ain, A.; Ajith, P.; Alemic, A.; Allen, B.; Allocca, A.; Amariutei, D.; Andersen, M.; Anderson, R.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C.; Areeda, J.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Austin, L.; Aylott, B. E.; Babak, S.; Baker, P. T.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barbet, M.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bauchrowitz, J.; Bauer, Th. S.; Behnke, B.; Bejger, M.; Beker, M. G.; Belczynski, C.; Bell, A. S.; Bell, C.; Bergmann, G.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Beyersdorf, P. T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biscans, S.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bloemen, S.; Blom, M.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bond, C.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, Sukanta; Bosi, L.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brückner, F.; Buchman, S.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burman, R.; Buskulic, D.; Buy, C.; Cadonati, L.; Cagnoli, G.; Bustillo, J. Calderón; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K. C.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Castiglia, A.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Celerier, C.; Cella, G.; Cepeda, C.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chu, Q.; Chua, S. S. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C.; Colombini, M.; Cominsky, L.; Constancio, M.; Conte, A.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corpuz, A.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coughlin, S.; Coulon, J.-P.; Countryman, S.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dahl, K.; Canton, T. Dal; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daveloza, H.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Dayanga, T.; Debreczeni, G.; Degallaix, J.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Dhurandhar, S.; Díaz, M.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Donath, A.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dossa, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dwyer, S.; Eberle, T.; Edo, T.; Edwards, M.; Effler, A.; Eggenstein, H.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Endrőczi, G.; Essick, R.; Etzel, T.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fehrmann, H.; Fejer, M. M.; Feldbaum, D.; Feroz, F.; Ferrante, I.; Ferrini, F.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gair, J.; Gammaitoni, L.; Gaonkar, S.; Garufi, F.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, C.; Gleason, J.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gordon, N.; Gorodetsky, M. L.; Gossan, S.; Goßler, S.; Gouaty, R.; Gräf, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Groot, P.; Grote, H.; Grover, K.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gushwa, K.; Gustafson, E. K.; Gustafson, R.; Hammer, D.; Hammond, G.; Hanke, M.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hart, M.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Heptonstall, A. W.; Heurs, M.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Hooper, S.; Hopkins, P.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hu, Y.; Huerta, E.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh, M.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Iyer, B. R.; Izumi, K.; Jacobson, M.; James, E.; Jang, H.; Jaranowski, P.; Ji, Y.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karlen, J.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Keiser, G. M.; Keitel, D.; Kelley, D. B.; Kells, W.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, C.; Kim, K.; Kim, N.; Kim, N. G.; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Koehlenbeck, S.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kremin, A.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, A.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Kwee, P.; Landry, M.; Lantz, B.; Larson, S.; Lasky, P. D.; Lawrie, C.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C.-H.; Lee, H. K.; Lee, H. M.; Lee, J.; Leonardi, M.; Leong, J. R.; Le Roux, A.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B.; Lewis, J.; Li, T. G. F.; Libbrecht, K.; Libson, A.; Lin, A. C.; Littenberg, T. B.; Litvine, V.; Lockerbie, N. A.; Lockett, V.; Lodhia, D.; Loew, K.; Logue, J.; Lombardi, A. L.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Lubinski, M. J.; Lück, H.; Luijten, E.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macarthur, J.; Macdonald, E. P.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Mageswaran, M.; Maglione, C.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Manca, G. M.; Mandel, I.; Mandic, V.; Mangano, V.; Mangini, N.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Martinelli, L.; Martynov, D.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; McLin, K.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Meinders, M.; Melatos, A.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyers, P.; Miao, H.; Michel, C.; Mikhailov, E. E.; Milano, L.; Milde, S.; Miller, J.; Minenkov, Y.; Mingarelli, C. M. F.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Moesta, P.; Mohan, M.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nagy, M. F.; Kumar, D. Nanda; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nelemans, G.; Neri, I.; Neri, M.; Newton, G.; Nguyen, T.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Ochsner, E.; O'Dell, J.; Oelker, E.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oppermann, P.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Padilla, C.; Pai, A.; Palashov, O.; Palomba, C.; Pan, H.; Pan, Y.; Pankow, C.; Paoletti, F.; Paoletti, R.; Paris, H.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Pedraza, M.; Penn, S.; Perreca, A.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pierro, V.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poeld, J.; Poggiani, R.; Poteomkin, A.; Powell, J.; Prasad, J.; Premachandra, S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Qin, J.; Quetschke, V.; Quintero, E.; Quiroga, G.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Raja, S.; Rajalakshmi, G.; Rakhmanov, M.; Ramet, C.; Ramirez, K.; Rapagnani, P.; Raymond, V.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Reid, S.; Reitze, D. H.; Rhoades, E.; Ricci, F.; Riles, K.; Robertson, N. A.; Robinet, F.; Rocchi, A.; Rodruck, M.; Rolland, L.; Rollins, J. G.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Salemi, F.; Sammut, L.; Sandberg, V.; Sanders, J. R.; Sannibale, V.; Santiago-Prieto, I.; Saracco, E.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R.; Scheuer, J.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siellez, K.; Siemens, X.; Sigg, D.; Simakov, D.; Singer, A.; Singer, L.; Singh, R.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Son, E. J.; Sorazu, B.; Souradeep, T.; Sperandio, L.; Staley, A.; Stebbins, J.; Steinlechner, J.; Steinlechner, S.; Stephens, B. C.; Steplewski, S.; Stevenson, S.; Stone, R.; Stops, D.; Strain, K. A.; Straniero, N.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, R.; ter Braack, A. P. M.; Thirugnanasambandam, M. P.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C. V.; Torrie, C. I.; Travasso, F.; Traylor, G.; Tse, M.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Urbanek, K.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Vallisneri, M.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van der Sluys, M. V.; van Heijningen, J.; van Veggel, A. A.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Verma, S. S.; Vetrano, F.; Viceré, A.; Vincent-Finley, R.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vyachanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Walker, M.; Wallace, L.; Wang, M.; Wang, X.; Ward, R. L.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Wiesner, K.; Wilkinson, C.; Williams, K.; Williams, L.; Williams, R.; Williams, T.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yancey, C. C.; Yang, H.; Yang, Z.; Yoshida, S.; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, Fan; Zhang, L.; Zhao, C.; Zhu, X. J.; Zucker, M. E.; Zuraw, S.; Zweizig, J.; LIGO; Virgo Collaboration

2014-12-01

Gravitational waves from a variety of sources are predicted to superpose to create a stochastic background. This background is expected to contain unique information from throughout the history of the Universe that is unavailable through standard electromagnetic observations, making its study of fundamental importance to understanding the evolution of the Universe. We carry out a search for the stochastic background with the latest data from the LIGO and Virgo detectors. Consistent with predictions from most stochastic gravitational-wave background models, the data display no evidence of a stochastic gravitational-wave signal. Assuming a gravitational-wave spectrum of ΩGW(f )=Ωα(f/fref ) α , we place 95% confidence level upper limits on the energy density of the background in each of four frequency bands spanning 41.5-1726 Hz. In the frequency band of 41.5-169.25 Hz for a spectral index of α =0 , we constrain the energy density of the stochastic background to be ΩGW(f )<5.6 ×1 0-6 . For the 600-1000 Hz band, ΩGW(f )<0.14 (f /900 Hz )3 , a factor of 2.5 lower than the best previously reported upper limits. We find ΩGW(f )<1.8 ×1 0-4 using a spectral index of zero for 170-600 Hz and ΩGW(f )<1.0 (f /1300 Hz )3 for 1000-1726 Hz, bands in which no previous direct limits have been placed. The limits in these four bands are the lowest direct measurements to date on the stochastic background. We discuss the implications of these results in light of the recent claim by the BICEP2 experiment of the possible evidence for inflationary gravitational waves.

Improved upper limits on the stochastic gravitational-wave background from 2009-2010 LIGO and Virgo data.

PubMed

Aasi, J; Abbott, B P; Abbott, R; Abbott, T; Abernathy, M R; Accadia, T; Acernese, F; Ackley, K; Adams, C; Adams, T; Addesso, P; Adhikari, R X; Affeldt, C; Agathos, M; Aggarwal, N; Aguiar, O D; Ain, A; Ajith, P; Alemic, A; Allen, B; Allocca, A; Amariutei, D; Andersen, M; Anderson, R; Anderson, S B; Anderson, W G; Arai, K; Araya, M C; Arceneaux, C; Areeda, J; Aston, S M; Astone, P; Aufmuth, P; Aulbert, C; Austin, L; Aylott, B E; Babak, S; Baker, P T; Ballardin, G; Ballmer, S W; Barayoga, J C; Barbet, M; Barish, B C; Barker, D; Barone, F; Barr, B; Barsotti, L; Barsuglia, M; Barton, M A; Bartos, I; Bassiri, R; Basti, A; Batch, J C; Bauchrowitz, J; Bauer, Th S; Behnke, B; Bejger, M; Beker, M G; Belczynski, C; Bell, A S; Bell, C; Bergmann, G; Bersanetti, D; Bertolini, A; Betzwieser, J; Beyersdorf, P T; Bilenko, I A; Billingsley, G; Birch, J; Biscans, S; Bitossi, M; Bizouard, M A; Black, E; Blackburn, J K; Blackburn, L; Blair, D; Bloemen, S; Blom, M; Bock, O; Bodiya, T P; Boer, M; Bogaert, G; Bogan, C; Bond, C; Bondu, F; Bonelli, L; Bonnand, R; Bork, R; Born, M; Boschi, V; Bose, Sukanta; Bosi, L; Bradaschia, C; Brady, P R; Braginsky, V B; Branchesi, M; Brau, J E; Briant, T; Bridges, D O; Brillet, A; Brinkmann, M; Brisson, V; Brooks, A F; Brown, D A; Brown, D D; Brückner, F; Buchman, S; Bulik, T; Bulten, H J; Buonanno, A; Burman, R; Buskulic, D; Buy, C; Cadonati, L; Cagnoli, G; Bustillo, J Calderón; Calloni, E; Camp, J B; Campsie, P; Cannon, K C; Canuel, B; Cao, J; Capano, C D; Carbognani, F; Carbone, L; Caride, S; Castiglia, A; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Celerier, C; Cella, G; Cepeda, C; Cesarini, E; Chakraborty, R; Chalermsongsak, T; Chamberlin, S J; Chao, S; Charlton, P; Chassande-Mottin, E; Chen, X; Chen, Y; Chincarini, A; Chiummo, A; Cho, H S; Chow, J; Christensen, N; Chu, Q; Chua, S S Y; Chung, S; Ciani, G; Clara, F; Clark, J A; Cleva, F; Coccia, E; Cohadon, P-F; Colla, A; Collette, C; Colombini, M; Cominsky, L; Constancio, M; Conte, A; Cook, D; Corbitt, T R; Cordier, M; Cornish, N; Corpuz, A; Corsi, A; Costa, C A; Coughlin, M W; Coughlin, S; Coulon, J-P; Countryman, S; Couvares, P; Coward, D M; Cowart, M; Coyne, D C; Coyne, R; Craig, K; Creighton, J D E; Crowder, S G; Cumming, A; Cunningham, L; Cuoco, E; Dahl, K; Canton, T Dal; Damjanic, M; Danilishin, S L; D'Antonio, S; Danzmann, K; Dattilo, V; Daveloza, H; Davier, M; Davies, G S; Daw, E J; Day, R; Dayanga, T; Debreczeni, G; Degallaix, J; Deléglise, S; Del Pozzo, W; Denker, T; Dent, T; Dereli, H; Dergachev, V; De Rosa, R; DeRosa, R T; DeSalvo, R; Dhurandhar, S; Díaz, M; Di Fiore, L; Di Lieto, A; Di Palma, I; Di Virgilio, A; Donath, A; Donovan, F; Dooley, K L; Doravari, S; Dossa, S; Douglas, R; Downes, T P; Drago, M; Drever, R W P; Driggers, J C; Du, Z; Dwyer, S; Eberle, T; Edo, T; Edwards, M; Effler, A; Eggenstein, H; Ehrens, P; Eichholz, J; Eikenberry, S S; Endrőczi, G; Essick, R; Etzel, T; Evans, M; Evans, T; Factourovich, M; Fafone, V; Fairhurst, S; Fang, Q; Farinon, S; Farr, B; Farr, W M; Favata, M; Fehrmann, H; Fejer, M M; Feldbaum, D; Feroz, F; Ferrante, I; Ferrini, F; Fidecaro, F; Finn, L S; Fiori, I; Fisher, R P; Flaminio, R; Fournier, J-D; Franco, S; Frasca, S; Frasconi, F; Frede, M; Frei, Z; Freise, A; Frey, R; Fricke, T T; Fritschel, P; Frolov, V V; Fulda, P; Fyffe, M; Gair, J; Gammaitoni, L; Gaonkar, S; Garufi, F; Gehrels, N; Gemme, G; Genin, E; Gennai, A; Ghosh, S; Giaime, J A; Giardina, K D; Giazotto, A; Gill, C; Gleason, J; Goetz, E; Goetz, R; Gondan, L; González, G; Gordon, N; Gorodetsky, M L; Gossan, S; Gossler, S; Gouaty, R; Gräf, C; Graff, P B; Granata, M; Grant, A; Gras, S; Gray, C; Greenhalgh, R J S; Gretarsson, A M; Groot, P; Grote, H; Grover, K; Grunewald, S; Guidi, G M; Guido, C; Gushwa, K; Gustafson, E K; Gustafson, R; Hammer, D; Hammond, G; Hanke, M; Hanks, J; Hanna, C; Hanson, J; Harms, J; Harry, G M; Harry, I W; Harstad, E D; Hart, M; Hartman, M T; Haster, C-J; Haughian, K; Heidmann, A; Heintze, M; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Heptonstall, A W; Heurs, M; Hewitson, M; Hild, S; Hoak, D; Hodge, K A; Holt, K; Hooper, S; Hopkins, P; Hosken, D J; Hough, J; Howell, E J; Hu, Y; Huerta, E; Hughey, B; Husa, S; Huttner, S H; Huynh, M; Huynh-Dinh, T; Ingram, D R; Inta, R; Isogai, T; Ivanov, A; Iyer, B R; Izumi, K; Jacobson, M; James, E; Jang, H; Jaranowski, P; Ji, Y; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; K, Haris; Kalmus, P; Kalogera, V; Kandhasamy, S; Kang, G; Kanner, J B; Karlen, J; Kasprzack, M; Katsavounidis, E; Katzman, W; Kaufer, H; Kawabe, K; Kawazoe, F; Kéfélian, F; Keiser, G M; Keitel, D; Kelley, D B; Kells, W; Khalaidovski, A; Khalili, F Y; Khazanov, E A; Kim, C; Kim, K; Kim, N; Kim, N G; Kim, Y-M; King, E J; King, P J; Kinzel, D L; Kissel, J S; Klimenko, S; Kline, J; Koehlenbeck, S; Kokeyama, K; Kondrashov, V; Koranda, S; Korth, W Z; Kowalska, I; Kozak, D B; Kremin, A; Kringel, V; Królak, A; Kuehn, G; Kumar, A; Kumar, P; Kumar, R; Kuo, L; Kutynia, A; Kwee, P; 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2014-12-05

Gravitational waves from a variety of sources are predicted to superpose to create a stochastic background. This background is expected to contain unique information from throughout the history of the Universe that is unavailable through standard electromagnetic observations, making its study of fundamental importance to understanding the evolution of the Universe. We carry out a search for the stochastic background with the latest data from the LIGO and Virgo detectors. Consistent with predictions from most stochastic gravitational-wave background models, the data display no evidence of a stochastic gravitational-wave signal. Assuming a gravitational-wave spectrum of Ω_{GW}(f)=Ω_{α}(f/f_{ref})^{α}, we place 95% confidence level upper limits on the energy density of the background in each of four frequency bands spanning 41.5-1726 Hz. In the frequency band of 41.5-169.25 Hz for a spectral index of α=0, we constrain the energy density of the stochastic background to be Ω_{GW}(f)<5.6×10^{-6}. For the 600-1000 Hz band, Ω_{GW}(f)<0.14(f/900  Hz)^{3}, a factor of 2.5 lower than the best previously reported upper limits. We find Ω_{GW}(f)<1.8×10^{-4} using a spectral index of zero for 170-600 Hz and Ω_{GW}(f)<1.0(f/1300  Hz)^{3} for 1000-1726 Hz, bands in which no previous direct limits have been placed. The limits in these four bands are the lowest direct measurements to date on the stochastic background. We discuss the implications of these results in light of the recent claim by the BICEP2 experiment of the possible evidence for inflationary gravitational waves.

An analysis of intrinsic variations of low-frequency shear wave speed in a stochastic tissue model: the first application for staging liver fibrosis

NASA Astrophysics Data System (ADS)

Wang, Yu; Wang, Min; Jiang, Jingfeng

2017-02-01

Shear wave elastography is increasingly being used to non-invasively stage liver fibrosis by measuring shear wave speed (SWS). This study quantitatively investigates intrinsic variations among SWS measurements obtained from heterogeneous media such as fibrotic livers. More specifically, it aims to demonstrate that intrinsic variations in SWS measurements, in general, follow a non-Gaussian distribution and are related to the heterogeneous nature of the medium being measured. Using the principle of maximum entropy (ME), our primary objective is to derive a probability density function (PDF) of the SWS distribution in conjunction with a lossless stochastic tissue model. Our secondary objective is to evaluate the performance of the proposed PDF using Monte Carlo (MC)-simulated shear wave (SW) data against three other commonly used PDFs. Based on statistical evaluation criteria, initial results showed that the derived PDF fits better to MC-simulated SWS data than the other three PDFs. It was also found that SW fronts stabilized after a short (compared with the SW wavelength) travel distance in lossless media. Furthermore, in lossless media, the distance required to stabilize the SW propagation was not correlated to the SW wavelength at the low frequencies investigated (i.e. 50, 100 and 150 Hz). Examination of the MC simulation data suggests that elastic (shear) wave scattering became more pronounced when the volume fraction of hard inclusions increased from 10 to 30%. In conclusion, using the principle of ME, we theoretically demonstrated for the first time that SWS measurements in this model follow a non-Gaussian distribution. Preliminary data indicated that the proposed PDF can quantitatively represent intrinsic variations in SWS measurements simulated using a two-phase random medium model. The advantages of the proposed PDF are its physically meaningful parameters and solid theoretical basis.

Wave failure at strong coupling in intracellular C a2 + signaling system with clustered channels

NASA Astrophysics Data System (ADS)

Li, Xiang; Wu, Yuning; Gao, Xuejuan; Cai, Meichun; Shuai, Jianwei

2018-01-01

As an important intracellular signal, C a2 + ions control diverse cellular functions. In this paper, we discuss the C a2 + signaling with a two-dimensional model in which the inositol 1,4,5-trisphosphate (I P3 ) receptor channels are distributed in clusters on the endoplasmic reticulum membrane. The wave failure at large C a2 + diffusion coupling is discussed in detail in the model. We show that with varying model parameters the wave failure is a robust behavior with either deterministic or stochastic channel dynamics. We suggest that the wave failure should be a general behavior in inhomogeneous diffusing systems with clustered excitable regions and may occur in biological C a2 + signaling systems.

The propagator of stochastic electrodynamics

NASA Astrophysics Data System (ADS)

Cavalleri, G.

1981-01-01

The "elementary propagator" for the position of a free charged particle subject to the zero-point electromagnetic field with Lorentz-invariant spectral density ~ω3 is obtained. The nonstationary process for the position is solved by the stationary process for the acceleration. The dispersion of the position elementary propagator is compared with that of quantum electrodynamics. Finally, the evolution of the probability density is obtained starting from an initial distribution confined in a small volume and with a Gaussian distribution in the velocities. The resulting probability density for the position turns out to be equal, to within radiative corrections, to ψψ* where ψ is the Kennard wave packet. If the radiative corrections are retained, the present result is new since the corresponding expression in quantum electrodynamics has not yet been found. Besides preceding quantum electrodynamics for this problem, no renormalization is required in stochastic electrodynamics.

Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background.

PubMed

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Grunewald, S; Gruning, P; Guidi, G M; Guo, X; Gupta, A; Gupta, M K; Gushwa, K E; Gustafson, E K; Gustafson, R; Halim, O; Hall, B R; Hall, E D; Hamilton, E Z; Hammond, G; Haney, M; Hanke, M M; Hanks, J; Hanna, C; Hannam, M D; Hannuksela, O A; Hanson, J; Hardwick, T; Harms, J; Harry, G M; Harry, I W; Hart, M J; Haster, C-J; Haughian, K; Healy, J; Heidmann, A; Heintze, M C; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Hennig, J; Heptonstall, A W; Heurs, M; Hild, S; Hinderer, T; Hoak, D; Hofman, D; Holt, K; Holz, D E; Hopkins, P; Horst, C; Hough, J; Houston, E A; Howell, E J; Hreibi, A; Hu, Y M; Huerta, E A; Huet, D; Hughey, B; Husa, S; Huttner, S H; Huynh-Dinh, T; Indik, N; Inta, R; Intini, G; Isa, H N; Isac, J-M; Isi, M; Iyer, B R; Izumi, K; Jacqmin, T; Jani, K; Jaranowski, P; Jawahar, S; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; Junker, J; Kalaghatgi, C V; Kalogera, V; Kamai, B; Kandhasamy, S; Kang, G; Kanner, J B; Kapadia, S J; Karki, S; Karvinen, K S; Kasprzack, M; Katolik, M; Katsavounidis, E; Katzman, W; Kaufer, S; Kawabe, K; Kéfélian, F; Keitel, D; Kemball, A J; Kennedy, R; Kent, C; Key, J S; Khalili, F Y; Khan, I; Khan, S; Khan, Z; Khazanov, E A; Kijbunchoo, N; Kim, Chunglee; Kim, J C; Kim, K; Kim, W; Kim, W S; Kim, Y-M; Kimbrell, S J; King, E J; King, P J; Kinley-Hanlon, M; Kirchhoff, R; Kissel, J S; Kleybolte, L; Klimenko, S; Knowles, T D; Koch, P; Koehlenbeck, S M; Koley, S; Kondrashov, V; Kontos, A; Korobko, M; Korth, W Z; Kowalska, I; Kozak, D B; Krämer, C; Kringel, V; Królak, A; Kuehn, G; Kumar, P; Kumar, R; Kumar, S; Kuo, L; Kutynia, A; Kwang, S; Lackey, B D; Lai, K H; Landry, M; Lang, R N; Lange, J; Lantz, B; Lanza, R K; Lartaux-Vollard, A; Lasky, P D; Laxen, M; Lazzarini, A; Lazzaro, C; Leaci, P; Leavey, S; Lee, C H; Lee, H K; Lee, H M; Lee, H W; Lee, K; Lehmann, J; Lenon, A; Leonardi, M; Leroy, N; Letendre, N; Levin, Y; Li, T G F; Linker, S D; Littenberg, T B; Liu, J; Lo, R K L; Lockerbie, N A; London, L T; Lord, J E; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J D; Lousto, C O; Lovelace, G; Lück, H; Lumaca, D; Lundgren, A P; Lynch, R; Ma, Y; Macas, R; Macfoy, S; Machenschalk, B; MacInnis, M; Macleod, D M; Magaña Hernandez, I; Magaña-Sandoval, F; Magaña Zertuche, L; Magee, R M; Majorana, E; Maksimovic, I; Man, N; Mandic, V; Mangano, V; Mansell, G L; Manske, M; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markakis, C; Markosyan, A S; Markowitz, A; Maros, E; Marquina, A; Martelli, F; Martellini, L; Martin, I W; Martin, R M; Martynov, D V; Mason, K; Massera, E; Masserot, A; Massinger, T J; Masso-Reid, M; Mastrogiovanni, S; Matas, A; Matichard, F; Matone, L; Mavalvala, N; Mazumder, N; McCarthy, R; McClelland, D E; McCormick, S; McCuller, L; McGuire, S C; McIntyre, G; McIver, J; McManus, D J; McNeill, L; McRae, T; McWilliams, S T; Meacher, D; Meadors, G D; Mehmet, M; Meidam, J; Mejuto-Villa, E; Melatos, A; Mendell, G; Mercer, R A; Merilh, E L; Merzougui, M; Meshkov, S; Messenger, C; Messick, C; Metzdorff, R; Meyers, P M; Miao, H; Michel, C; Middleton, H; Mikhailov, E E; Milano, L; Miller, A L; Miller, B B; Miller, J; Millhouse, M; Milovich-Goff, M C; Minazzoli, O; Minenkov, Y; Ming, J; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moffa, D; Moggi, A; Mogushi, K; Mohan, M; Mohapatra, S R P; Montani, M; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mours, B; Mow-Lowry, C M; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Muñiz, E A; Muratore, M; Murray, P G; Napier, K; Nardecchia, I; Naticchioni, L; Nayak, R K; Neilson, J; Nelemans, G; Nelson, T J N; Nery, M; Neunzert, A; Nevin, L; Newport, J M; Newton, G; Ng, K K Y; Nguyen, T T; Nichols, D; Nielsen, A B; Nissanke, S; Nitz, A; Noack, A; Nocera, F; Nolting, D; North, C; Nuttall, L K; Oberling, J; O'Dea, G D; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Okada, M A; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; Ormiston, R; Ortega, L F; O'Shaughnessy, R; Ossokine, S; Ottaway, D J; Overmier, H; Owen, B J; Pace, A E; Page, J; Page, M A; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, Howard; Pan, Huang-Wei; Pang, B; Pang, P T H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Parida, A; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patil, M; Patricelli, B; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perez, C J; Perreca, A; Perri, L M; Pfeiffer, H P; Phelps, M; Piccinni, O J; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pirello, M; Pitkin, M; Poe, M; Poggiani, R; Popolizio, P; Porter, E K; Post, A; Powell, J; Prasad, J; Pratt, J W W; Pratten, G; Predoi, V; Prestegard, T; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L G; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rajan, C; Rajbhandari, B; Rakhmanov, M; Ramirez, K E; Ramos-Buades, A; Rapagnani, P; Raymond, V; Razzano, M; Read, J; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Ren, W; Reyes, S D; Ricci, F; Ricker, P M; Rieger, S; Riles, K; Rizzo, M; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romel, C L; Romie, J H; Rosińska, D; Ross, M P; Rowan, S; Rüdiger, A; Ruggi, P; Rutins, G; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Sakellariadou, M; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sampson, L M; Sanchez, E J; Sanchez, L E; Sanchis-Gual, N; Sandberg, V; Sanders, J R; Sassolas, B; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Scheel, M; Scheuer, J; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schulte, B W; Schutz, B F; Schwalbe, S G; Scott, J; Scott, S M; Seidel, E; Sellers, D; Sengupta, A S; Sentenac, D; Sequino, V; Sergeev, A; Shaddock, D A; Shaffer, T J; Shah, A A; Shahriar, M S; Shaner, M B; Shao, L; Shapiro, B; Shawhan, P; Sheperd, A; Shoemaker, D H; Shoemaker, D M; Siellez, K; Siemens, X; Sieniawska, M; Sigg, D; Silva, A D; Singer, L P; Singh, A; Singhal, A; Sintes, A M; Slagmolen, B J J; Smith, B; Smith, J R; Smith, R J E; Somala, S; Son, E J; Sonnenberg, J A; Sorazu, B; Sorrentino, F; Souradeep, T; Spencer, A P; Srivastava, A K; Staats, K; Staley, A; Steinke, M; Steinlechner, J; Steinlechner, S; Steinmeyer, D; Stevenson, S P; Stone, R; Stops, D J; Strain, K A; Stratta, G; Strigin, S E; Strunk, A; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, L; Sunil, S; Suresh, J; Sutton, P J; Swinkels, B L; Szczepańczyk, M J; Tacca, M; Tait, S C; Talbot, C; Talukder, D; Tanner, D B; Tao, D; Tápai, M; Taracchini, A; Tasson, J D; Taylor, J A; Taylor, R; Tewari, S V; Theeg, T; Thies, F; Thomas, E G; Thomas, M; Thomas, P; Thorne, K A; Thrane, E; Tiwari, S; Tiwari, V; Tokmakov, K V; Toland, K; Tonelli, M; Tornasi, Z; Torres-Forné, A; Torrie, C I; Töyrä, D; Travasso, F; Traylor, G; Trinastic, J; Tringali, M C; Trozzo, L; Tsang, K W; Tse, M; Tso, R; Tsukada, L; Tsuna, D; Tuyenbayev, D; Ueno, K; Ugolini, D; Unnikrishnan, C S; Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Varma, V; Vass, S; Vasúth, M; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Venugopalan, G; Verkindt, D; Vetrano, F; Viceré, A; Viets, A D; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walet, R; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, J Z; Wang, W H; Wang, Y F; Ward, R L; Warner, J; Was, M; Watchi, J; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Wessel, E K; Weßels, P; Westerweck, J; Westphal, T; Wette, K; Whelan, J T; Whiting, B F; Whittle, C; Wilken, D; Williams, D; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Woehler, J; Wofford, J; Wong, K W K; Worden, J; Wright, J L; Wu, D S; Wysocki, D M; Xiao, S; Yamamoto, H; Yancey, C C; Yang, L; Yap, M J; Yazback, M; Yu, Hang; Yu, Haocun; Yvert, M; Zadrożny, A; Zanolin, M; Zelenova, T; Zendri, J-P; Zevin, M; Zhang, L; Zhang, M; Zhang, T; Zhang, Y-H; Zhao, C; Zhou, M; Zhou, Z; Zhu, S J; Zhu, X J; Zucker, M E; Zweizig, J

2018-05-18

The detection of gravitational waves with Advanced LIGO and Advanced Virgo has enabled novel tests of general relativity, including direct study of the polarization of gravitational waves. While general relativity allows for only two tensor gravitational-wave polarizations, general metric theories can additionally predict two vector and two scalar polarizations. The polarization of gravitational waves is encoded in the spectral shape of the stochastic gravitational-wave background, formed by the superposition of cosmological and individually unresolved astrophysical sources. Using data recorded by Advanced LIGO during its first observing run, we search for a stochastic background of generically polarized gravitational waves. We find no evidence for a background of any polarization, and place the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background. Under log-uniform priors for the energy in each polarization, we limit the energy densities of tensor, vector, and scalar modes at 95% credibility to Ω_{0}^{T}<5.58×10^{-8}, Ω_{0}^{V}<6.35×10^{-8}, and Ω_{0}^{S}<1.08×10^{-7} at a reference frequency f_{0}=25  Hz.

Schrödinger problem, Lévy processes, and noise in relativistic quantum mechanics

NASA Astrophysics Data System (ADS)

Garbaczewski, Piotr; Klauder, John R.; Olkiewicz, Robert

1995-05-01

The main purpose of the paper is an essentially probabilistic analysis of relativistic quantum mechanics. It is based on the assumption that whenever probability distributions arise, there exists a stochastic process that is either responsible for the temporal evolution of a given measure or preserves the measure in the stationary case. Our departure point is the so-called Schrödinger problem of probabilistic evolution, which provides for a unique Markov stochastic interpolation between any given pair of boundary probability densities for a process covering a fixed, finite duration of time, provided we have decided a priori what kind of primordial dynamical semigroup transition mechanism is involved. In the nonrelativistic theory, including quantum mechanics, Feynman-Kac-like kernels are the building blocks for suitable transition probability densities of the process. In the standard ``free'' case (Feynman-Kac potential equal to zero) the familiar Wiener noise is recovered. In the framework of the Schrödinger problem, the ``free noise'' can also be extended to any infinitely divisible probability law, as covered by the Lévy-Khintchine formula. Since the relativistic Hamiltonians ||∇|| and √-Δ+m2 -m are known to generate such laws, we focus on them for the analysis of probabilistic phenomena, which are shown to be associated with the relativistic wave (D'Alembert) and matter-wave (Klein-Gordon) equations, respectively. We show that such stochastic processes exist and are spatial jump processes. In general, in the presence of external potentials, they do not share the Markov property, except for stationary situations. A concrete example of the pseudodifferential Cauchy-Schrödinger evolution is analyzed in detail. The relativistic covariance of related wave equations is exploited to demonstrate how the associated stochastic jump processes comply with the principles of special relativity.

Joint Stochastic Inversion of Pre-Stack 3D Seismic Data and Well Logs for High Resolution Hydrocarbon Reservoir Characterization

NASA Astrophysics Data System (ADS)

Torres-Verdin, C.

2007-05-01

This paper describes the successful implementation of a new 3D AVA stochastic inversion algorithm to quantitatively integrate pre-stack seismic amplitude data and well logs. The stochastic inversion algorithm is used to characterize flow units of a deepwater reservoir located in the central Gulf of Mexico. Conventional fluid/lithology sensitivity analysis indicates that the shale/sand interface represented by the top of the hydrocarbon-bearing turbidite deposits generates typical Class III AVA responses. On the other hand, layer- dependent Biot-Gassmann analysis shows significant sensitivity of the P-wave velocity and density to fluid substitution. Accordingly, AVA stochastic inversion, which combines the advantages of AVA analysis with those of geostatistical inversion, provided quantitative information about the lateral continuity of the turbidite reservoirs based on the interpretation of inverted acoustic properties (P-velocity, S-velocity, density), and lithotype (sand- shale) distributions. The quantitative use of rock/fluid information through AVA seismic amplitude data, coupled with the implementation of co-simulation via lithotype-dependent multidimensional joint probability distributions of acoustic/petrophysical properties, yields accurate 3D models of petrophysical properties such as porosity and permeability. Finally, by fully integrating pre-stack seismic amplitude data and well logs, the vertical resolution of inverted products is higher than that of deterministic inversions methods.

Rogue waves and entropy consumption

NASA Astrophysics Data System (ADS)

Hadjihoseini, Ali; Lind, Pedro G.; Mori, Nobuhito; Hoffmann, Norbert P.; Peinke, Joachim

2017-11-01

Based on data from the Sea of Japan and the North Sea the occurrence of rogue waves is analyzed by a scale-dependent stochastic approach, which interlinks fluctuations of waves for different spacings. With this approach we are able to determine a stochastic cascade process, which provides information of the general multipoint statistics. Furthermore the evolution of single trajectories in scale, which characterize wave height fluctuations in the surroundings of a chosen location, can be determined. The explicit knowledge of the stochastic process enables to assign entropy values to all wave events. We show that for these entropies the integral fluctuation theorem, a basic law of non-equilibrium thermodynamics, is valid. This implies that positive and negative entropy events must occur. Extreme events like rogue waves are characterized as negative entropy events. The statistics of these entropy fluctuations changes with the wave state, thus for the Sea of Japan the statistics of the entropies has a more pronounced tail for negative entropy values, indicating a higher probability of rogue waves.

Five-wave-packet quantum error correction based on continuous-variable cluster entanglement

PubMed Central

Hao, Shuhong; Su, Xiaolong; Tian, Caixing; Xie, Changde; Peng, Kunchi

2015-01-01

Quantum error correction protects the quantum state against noise and decoherence in quantum communication and quantum computation, which enables one to perform fault-torrent quantum information processing. We experimentally demonstrate a quantum error correction scheme with a five-wave-packet code against a single stochastic error, the original theoretical model of which was firstly proposed by S. L. Braunstein and T. A. Walker. Five submodes of a continuous variable cluster entangled state of light are used for five encoding channels. Especially, in our encoding scheme the information of the input state is only distributed on three of the five channels and thus any error appearing in the remained two channels never affects the output state, i.e. the output quantum state is immune from the error in the two channels. The stochastic error on a single channel is corrected for both vacuum and squeezed input states and the achieved fidelities of the output states are beyond the corresponding classical limit. PMID:26498395

Gene surfing in expanding populations.

PubMed

Hallatschek, Oskar; Nelson, David R

2008-02-01

Large scale genomic surveys are partly motivated by the idea that the neutral genetic variation of a population may be used to reconstruct its migration history. However, our ability to trace back the colonization pathways of a species from their genetic footprints is limited by our understanding of the genetic consequences of a range expansion. Here, we study, by means of simulations and analytical methods, the neutral dynamics of gene frequencies in an asexual population undergoing a continual range expansion in one dimension. During such a colonization period, lineages can fix at the wave front by means of a "surfing" mechanism [Edmonds, C.A., Lillie, A.S., Cavalli-Sforza, L.L., 2004. Mutations arising in the wave front of an expanding population. Proc. Natl. Acad. Sci. 101, 975-979]. We quantify this phenomenon in terms of (i) the spatial distribution of lineages that reach fixation and, closely related, (ii) the continual loss of genetic diversity (heterozygosity) at the wave front, characterizing the approach to fixation. Our stochastic simulations show that an effective population size can be assigned to the wave that controls the (observable) gradient in heterozygosity left behind the colonization process. This effective population size is markedly higher in the presence of cooperation between individuals ("pushed waves") than when individuals proliferate independently ("pulled waves"), and increases only sub-linearly with deme size. To explain these and other findings, we develop a versatile analytical approach, based on the physics of reaction-diffusion systems, that yields simple predictions for any deterministic population dynamics. Our analytical theory compares well with the simulation results for pushed waves, but is less accurate in the case of pulled waves when stochastic fluctuations in the tip of the wave are important.

Strong Evidence for Stochastic Growth of Langmuir-Like Waves in Earth's Foreshock

NASA Technical Reports Server (NTRS)

Cairns, Iver H.; Robinson, P. A.

1999-01-01

Bursty Langmuir-like waves driven by electron beams in Earth's foreshock have properties which are inconsistent with the standard plasma physics paradigm of uniform exponential growth saturated by nonlinear processes. Here it is demonstrated for a specific period that stochastic growth theory (SGT) quantitatively describes these waves throughout a large fraction of the foreshock. The statistical wave properties are inconsistent with nonlinear processes or self-organized criticality being important. SGT's success in explaining the foreshock waves and type III solar bursts suggests that SGT is widely applicable to wave growth in space, astrophysical, and laboratory plasmas.

Constraints on the Primordial Black Hole Abundance from the First Advanced LIGO Observation Run Using the Stochastic Gravitational-Wave Background

NASA Astrophysics Data System (ADS)

Wang, Sai; Wang, Yi-Fan; Huang, Qing-Guo; Li, Tjonnie G. F.

2018-05-01

Advanced LIGO's discovery of gravitational-wave events is stimulating extensive studies on the origin of binary black holes. Assuming that the gravitational-wave events can be explained by binary primordial black hole mergers, we utilize the upper limits on the stochastic gravitational-wave background given by Advanced LIGO as a new observational window to independently constrain the abundance of primordial black holes in dark matter. We show that Advanced LIGO's first observation run gives the best constraint on the primordial black hole abundance in the mass range 1 M⊙≲MPBH≲100 M⊙, pushing the previous microlensing and dwarf galaxy dynamics constraints tighter by 1 order of magnitude. Moreover, we discuss the possibility to detect the stochastic gravitational-wave background from primordial black holes, in particular from subsolar mass primordial black holes, by Advanced LIGO in the near future.

Constraints on the Primordial Black Hole Abundance from the First Advanced LIGO Observation Run Using the Stochastic Gravitational-Wave Background.

PubMed

Wang, Sai; Wang, Yi-Fan; Huang, Qing-Guo; Li, Tjonnie G F

2018-05-11

Advanced LIGO's discovery of gravitational-wave events is stimulating extensive studies on the origin of binary black holes. Assuming that the gravitational-wave events can be explained by binary primordial black hole mergers, we utilize the upper limits on the stochastic gravitational-wave background given by Advanced LIGO as a new observational window to independently constrain the abundance of primordial black holes in dark matter. We show that Advanced LIGO's first observation run gives the best constraint on the primordial black hole abundance in the mass range 1M_{⊙}≲M_{PBH}≲100M_{⊙}, pushing the previous microlensing and dwarf galaxy dynamics constraints tighter by 1 order of magnitude. Moreover, we discuss the possibility to detect the stochastic gravitational-wave background from primordial black holes, in particular from subsolar mass primordial black holes, by Advanced LIGO in the near future.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaston, C. C.; Bonnell, J. W.; Reeves, Geoffrey D.

We show how dispersive Alfvén waves observed in the inner magnetosphere during geomagnetic storms can extract O + ions from the topside ionosphere and accelerate these ions to energies exceeding 50 keV in the equatorial plane. This occurs through wave trapping, a variant of “shock” surfing, and stochastic ion acceleration. These processes in combination with the mirror force drive field-aligned beams of outflowing ionospheric ions into the equatorial plane that evolve to provide energetic O + distributions trapped near the equator. These waves also accelerate preexisting/injected ion populations on the same field lines. We show that the action of dispersivemore » Alfvén waves over several minutes may drive order of magnitude increases in O + ion pressure to make substantial contributions to magnetospheric ion energy density. These wave accelerated ions will enhance the ring current and play a role in the storm time evolution of the magnetosphere.« less

Newton's method for nonlinear stochastic wave equations driven by one-dimensional Brownian motion.

PubMed

Leszczynski, Henryk; Wrzosek, Monika

2017-02-01

We consider nonlinear stochastic wave equations driven by one-dimensional white noise with respect to time. The existence of solutions is proved by means of Picard iterations. Next we apply Newton's method. Moreover, a second-order convergence in a probabilistic sense is demonstrated.

Non-linear resonant coupling of tsunami edge waves using stochastic earthquake source models

USGS Publications Warehouse

Geist, Eric L.

2016-01-01

Non-linear resonant coupling of edge waves can occur with tsunamis generated by large-magnitude subduction zone earthquakes. Earthquake rupture zones that straddle beneath the coastline of continental margins are particularly efficient at generating tsunami edge waves. Using a stochastic model for earthquake slip, it is shown that a wide range of edge-wave modes and wavenumbers can be excited, depending on the variability of slip. If two modes are present that satisfy resonance conditions, then a third mode can gradually increase in amplitude over time, even if the earthquake did not originally excite that edge-wave mode. These three edge waves form a resonant triad that can cause unexpected variations in tsunami amplitude long after the first arrival. An M ∼ 9, 1100 km-long continental subduction zone earthquake is considered as a test case. For the least-variable slip examined involving a Gaussian random variable, the dominant resonant triad includes a high-amplitude fundamental mode wave with wavenumber associated with the along-strike dimension of rupture. The two other waves that make up this triad include subharmonic waves, one of fundamental mode and the other of mode 2 or 3. For the most variable slip examined involving a Cauchy-distributed random variable, the dominant triads involve higher wavenumbers and modes because subevents, rather than the overall rupture dimension, control the excitation of edge waves. Calculation of the resonant period for energy transfer determines which cases resonant coupling may be instrumentally observed. For low-mode triads, the maximum transfer of energy occurs approximately 20–30 wave periods after the first arrival and thus may be observed prior to the tsunami coda being completely attenuated. Therefore, under certain circumstances the necessary ingredients for resonant coupling of tsunami edge waves exist, indicating that resonant triads may be observable and implicated in late, large-amplitude tsunami arrivals.

Stochastic Growth of Ion Cyclotron And Mirror Waves In Earth's Magnetosheath

NASA Technical Reports Server (NTRS)

Cairns, Iver H.; Grubits, K. A.

2001-01-01

Electromagnetic ion cyclotron and mirror waves in Earth's magnetosheath are bursty, have widely variable fields, and are unexpectedly persistent, properties difficult to reconcile with uniform secular growth. Here it is shown for specific periods that stochastic growth theory (SGT) quantitatively accounts for the functional form of the wave statistics and qualitatively explains the wave properties. The wave statistics are inconsistent with uniform secular growth or self-organized criticality, but nonlinear processes sometimes play a role at high fields. The results show SGT's relevance near marginal stability and suggest that it is widely relevant to space and astrophysical plasmas.

Stochastic Gravitational-Wave Background due to Primordial Binary Black Hole Mergers.

PubMed

Mandic, Vuk; Bird, Simeon; Cholis, Ilias

2016-11-11

Recent Advanced LIGO detections of binary black hole mergers have prompted multiple studies investigating the possibility that the heavy GW150914 binary system was of primordial origin, and hence could be evidence for dark matter in the form of black holes. We compute the stochastic background arising from the incoherent superposition of such primordial binary black hole systems in the Universe and compare it to the similar background spectrum due to binary black hole systems of stellar origin. We investigate the possibility of detecting this background with future gravitational-wave detectors, and conclude that constraining the dark matter component in the form of black holes using stochastic gravitational-wave background measurements will be very challenging.

A Stochastic Seismic Model for the European Arctic

NASA Astrophysics Data System (ADS)

Hauser, J.; Dyer, K.; Pasyanos, M. E.; Bungum, H.; Faleide, J. I.; Clark, S. A.

2009-12-01

The development of three-dimensional seismic models for the crust and upper mantle has traditionally focused on finding one model that provides the best fit to the data, while observing some regularization constraints. Such deterministic models however ignore a fundamental property of many inverse problems in geophysics, non-uniqueness, that is, if a model can be found to satisfy given datasets an infinite number of alternative models will exist that satisfy the datasets equally well. The solution to the inverse problem presented here is therefore a stochastic model, an ensemble of models that satisfy all available data to the same degree, the posterior distribution. It is based on two sources of information, (1) the data, in this work surface-wave group velocities, regional body-wave travel times, gravity data, compiled 1D velocity models, and thickness relationships between sedimentary rocks and underlying crystalline rocks, and (2) prior information, which is independent from the data. A Monte Carlo Markov Chain (MCMC) algorithm allows us to sample models from the prior distribution and test them against the data to generate the posterior distribution. While being computationally much more expensive, such a stochastic inversion provides a more complete picture of solution space and allows to seamlessly combine various datasets. The resulting stochastic model gives an overview of the different structures that can explain the observed datasets while taking the uncertainties in the data into account. Stochastic models are important for improving seismic monitoring capabilities as they allow to not only predict new observables but also their uncertainties. The model introduced here for the crust and upper mantle structure of the European Arctic is parametrized by a series of 8 layers in an equidistant mesh. Within each layer the seismic parameters (Vp, Vs and density) can vary linearly with depth. This allows to model changes of seismic parameters within the sediments and the crystalline crust without introducing artificial discontinuities that would result from parametrizing the structure using layers with constant seismic parameters. The complex geology of the region, encompassing oceanic crust, continental shelf regions, rift basins and old cratonic crust, and the non-uniform coverage of the region by data with varying levels of uncertainty makes the European Arctic a challenging setting for any imaging technique and therefore an ideal environment for demonstrating the practical advantages of a stochastic model. Maps of sediment thickness and thickness of the crystalline crust derived from the posterior distribution are in good agreement with knowledge of the regional tectonic setting. The predicted uncertainties, which are more important than the absolute values, correlate well with the variation in data coverage and data quality in the region. This indicates that the technique behaves as expected, thus we are properly tuning the methodology by allowing the Markov Chain adequate time to fully sample the model space.

A climate-based multivariate extreme emulator of met-ocean-hydrological events for coastal flooding

NASA Astrophysics Data System (ADS)

Camus, Paula; Rueda, Ana; Mendez, Fernando J.; Tomas, Antonio; Del Jesus, Manuel; Losada, Iñigo J.

2015-04-01

Atmosphere-ocean general circulation models (AOGCMs) are useful to analyze large-scale climate variability (long-term historical periods, future climate projections). However, applications such as coastal flood modeling require climate information at finer scale. Besides, flooding events depend on multiple climate conditions: waves, surge levels from the open-ocean and river discharge caused by precipitation. Therefore, a multivariate statistical downscaling approach is adopted to reproduce relationships between variables and due to its low computational cost. The proposed method can be considered as a hybrid approach which combines a probabilistic weather type downscaling model with a stochastic weather generator component. Predictand distributions are reproduced modeling the relationship with AOGCM predictors based on a physical division in weather types (Camus et al., 2012). The multivariate dependence structure of the predictand (extreme events) is introduced linking the independent marginal distributions of the variables by a probabilistic copula regression (Ben Ayala et al., 2014). This hybrid approach is applied for the downscaling of AOGCM data to daily precipitation and maximum significant wave height and storm-surge in different locations along the Spanish coast. Reanalysis data is used to assess the proposed method. A commonly predictor for the three variables involved is classified using a regression-guided clustering algorithm. The most appropriate statistical model (general extreme value distribution, pareto distribution) for daily conditions is fitted. Stochastic simulation of the present climate is performed obtaining the set of hydraulic boundary conditions needed for high resolution coastal flood modeling. References: Camus, P., Menéndez, M., Méndez, F.J., Izaguirre, C., Espejo, A., Cánovas, V., Pérez, J., Rueda, A., Losada, I.J., Medina, R. (2014b). A weather-type statistical downscaling framework for ocean wave climate. Journal of Geophysical Research, doi: 10.1002/2014JC010141. Ben Ayala, M.A., Chebana, F., Ouarda, T.B.M.J. (2014). Probabilistic Gaussian Copula Regression Model for Multisite and Multivariable Downscaling, Journal of Climate, 27, 3331-3347.

Letter: Modeling reactive shock waves in heterogeneous solids at the continuum level with stochastic differential equations

NASA Astrophysics Data System (ADS)

Kittell, D. E.; Yarrington, C. D.; Lechman, J. B.; Baer, M. R.

2018-05-01

A new paradigm is introduced for modeling reactive shock waves in heterogeneous solids at the continuum level. Inspired by the probability density function methods from turbulent reactive flows, it is hypothesized that the unreacted material microstructures lead to a distribution of heat release rates from chemical reaction. Fluctuations in heat release, rather than velocity, are coupled to the reactive Euler equations which are then solved via the Riemann problem. A numerically efficient, one-dimensional hydrocode is used to demonstrate this new approach, and simulation results of a representative impact calculation (inert flyer into explosive target) are discussed.

Asymptotic problems for stochastic partial differential equations

NASA Astrophysics Data System (ADS)

Salins, Michael

Stochastic partial differential equations (SPDEs) can be used to model systems in a wide variety of fields including physics, chemistry, and engineering. The main SPDEs of interest in this dissertation are the semilinear stochastic wave equations which model the movement of a material with constant mass density that is exposed to both determinstic and random forcing. Cerrai and Freidlin have shown that on fixed time intervals, as the mass density of the material approaches zero, the solutions of the stochastic wave equation converge uniformly to the solutions of a stochastic heat equation, in probability. This is called the Smoluchowski-Kramers approximation. In Chapter 2, we investigate some of the multi-scale behaviors that these wave equations exhibit. In particular, we show that the Freidlin-Wentzell exit place and exit time asymptotics for the stochastic wave equation in the small noise regime can be approximated by the exit place and exit time asymptotics for the stochastic heat equation. We prove that the exit time and exit place asymptotics are characterized by quantities called quasipotentials and we prove that the quasipotentials converge. We then investigate the special case where the equation has a gradient structure and show that we can explicitly solve for the quasipotentials, and that the quasipotentials for the heat equation and wave equation are equal. In Chapter 3, we study the Smoluchowski-Kramers approximation in the case where the material is electrically charged and exposed to a magnetic field. Interestingly, if the system is frictionless, then the Smoluchowski-Kramers approximation does not hold. We prove that the Smoluchowski-Kramers approximation is valid for systems exposed to both a magnetic field and friction. Notably, we prove that the solutions to the second-order equations converge to the solutions of the first-order equation in an Lp sense. This strengthens previous results where convergence was proved in probability.

Investigation of the stochastic nature of wave processes for renewable resources management: a pilot application in a remote island in the Aegean sea

NASA Astrophysics Data System (ADS)

Moschos, Evangelos; Manou, Georgia; Georganta, Xristina; Dimitriadis, Panayiotis; Iliopoulou, Theano; Tyralis, Hristos; Koutsoyiannis, Demetris; Tsoukala, Vicky

2017-04-01

The large energy potential of ocean dynamics is not yet being efficiently harvested mostly due to several technological and financial drawbacks. Nevertheless, modern renewable energy systems include wave and tidal energy in cases of nearshore locations. Although the variability of tidal waves can be adequately predictable, wind-generated waves entail a much larger uncertainty due to their dependence to the wind process. Recent research has shown, through estimation of the wave energy potential in coastal areas of the Aegean Sea, that installation of wave energy converters in nearshore locations could be an applicable scenario, assisting the electrical network of Greek islands. In this context, we analyze numerous of observations and we investigate the long-term behaviour of wave height and wave period processes. Additionally, we examine the case of a remote island in the Aegean sea, by estimating the local wave climate through past analysis data and numerical methods, and subsequently applying a parsimonious stochastic model to a theoretical scenario of wave energy production. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Application of Effective Medium Theory to the Three-Dimensional Heterogeneity of Mantle Anisotropy

NASA Astrophysics Data System (ADS)

Song, X.; Jordan, T. H.

2015-12-01

A self-consistent theory for the effective elastic parameters of stochastic media with small-scale 3D heterogeneities has been developed using a 2nd-order Born approximation to the scattered wavefield (T. H. Jordan, GJI, in press). Here we apply the theory to assess how small-scale variations in the local anisotropy of the upper mantle affect seismic wave propagation. We formulate a anisotropic model in which the local elastic properties are specified by a constant stiffness tensor with hexagonal symmetry of arbitrary orientation. This orientation is guided by a Gaussian random vector field with transversely isotropic (TI) statistics. If the outer scale of the statistical variability is small compared to a wavelength, then the effective seismic velocities are TI and depend on two parameters, a horizontal-to-vertical orientation ratio ξ and a horizontal-to-vertical aspect ratio, η. If ξ = 1, the symmetry axis is isotropically distributed; if ξ < 1, it is vertical biased (bipolar distribution), and if ξ > 1, it is horizontally biased (girdle distribution). If η = 1, the heterogeneity is geometrically isotropic; as η à∞, the medium becomes a horizontal stochastic laminate; as η à0, the medium becomes a vertical stochastic bundle. Using stiffness tensors constrained by laboratory measurements of mantle xenoliths, we explore the dependence of the effective P and S velocities on ξ and η. The effective velocities are strongly controlled by the orientation ratio ξ; e.g., if the hexagonal symmetry axis of the local anisotropy is the fast direction of propagation, then vPH > vPV and vSH > vSV for ξ > 1. A more surprising result is the 2nd-order insensitivity of the velocities to the heterogeneity aspect ratio η. Consequently, the geometrical anisotropy of upper-mantle heterogeneity significantly enhances seismic-wave anisotropy only through local variations in the Voigt-averaged velocities, which depend primarily on rock composition and not deformation history.

Driving ionospheric outflows and magnetospheric O + energy density with Alfvén waves

DOE PAGES

Chaston, C. C.; Bonnell, J. W.; Reeves, Geoffrey D.; ...

2016-05-11

We show how dispersive Alfvén waves observed in the inner magnetosphere during geomagnetic storms can extract O + ions from the topside ionosphere and accelerate these ions to energies exceeding 50 keV in the equatorial plane. This occurs through wave trapping, a variant of “shock” surfing, and stochastic ion acceleration. These processes in combination with the mirror force drive field-aligned beams of outflowing ionospheric ions into the equatorial plane that evolve to provide energetic O + distributions trapped near the equator. These waves also accelerate preexisting/injected ion populations on the same field lines. We show that the action of dispersivemore » Alfvén waves over several minutes may drive order of magnitude increases in O + ion pressure to make substantial contributions to magnetospheric ion energy density. These wave accelerated ions will enhance the ring current and play a role in the storm time evolution of the magnetosphere.« less

Consistent nonlinear deterministic and stochastic evolution equations for deep to shallow water wave shoaling

NASA Astrophysics Data System (ADS)

Vrecica, Teodor; Toledo, Yaron

2015-04-01

One-dimensional deterministic and stochastic evolution equations are derived for the dispersive nonlinear waves while taking dissipation of energy into account. The deterministic nonlinear evolution equations are formulated using operational calculus by following the approach of Bredmose et al. (2005). Their formulation is extended to include the linear and nonlinear effects of wave dissipation due to friction and breaking. The resulting equation set describes the linear evolution of the velocity potential for each wave harmonic coupled by quadratic nonlinear terms. These terms describe the nonlinear interactions between triads of waves, which represent the leading-order nonlinear effects in the near-shore region. The equations are translated to the amplitudes of the surface elevation by using the approach of Agnon and Sheremet (1997) with the correction of Eldeberky and Madsen (1999). The only current possibility for calculating the surface gravity wave field over large domains is by using stochastic wave evolution models. Hence, the above deterministic model is formulated as a stochastic one using the method of Agnon and Sheremet (1997) with two types of stochastic closure relations (Benney and Saffman's, 1966, and Hollway's, 1980). These formulations cannot be applied to the common wave forecasting models without further manipulation, as they include a non-local wave shoaling coefficients (i.e., ones that require integration along the wave rays). Therefore, a localization method was applied (see Stiassnie and Drimer, 2006, and Toledo and Agnon, 2012). This process essentially extracts the local terms that constitute the mean nonlinear energy transfer while discarding the remaining oscillatory terms, which transfer energy back and forth. One of the main findings of this work is the understanding that the approximated non-local coefficients behave in two essentially different manners. In intermediate water depths these coefficients indeed consist of rapidly oscillating terms, but as the water depth becomes shallow they change to an exponential growth (or decay) behavior. Hence, the formerly used localization technique cannot be justified for the shallow water region. A new formulation is devised for the localization in shallow water, it approximates the nonlinear non-local shoaling coefficient in shallow water and matches it to the one fitting to the intermediate water region. This allows the model behavior to be consistent from deep water to intermediate depths and up to the shallow water regime. Various simulations of the model were performed for the cases of intermediate, and shallow water, overall the model was found to give good results in both shallow and intermediate water depths. The essential difference between the shallow and intermediate nonlinear shoaling physics is explained via the dominating class III Bragg resonances phenomenon. By inspecting the resonance conditions and the nature of the dispersion relation, it is shown that unlike in the intermediate water regime, in shallow water depths the formation of resonant interactions is possible without taking into account bottom components. References Agnon, Y. & Sheremet, A. 1997 Stochastic nonlinear shoaling of directional spectra. J. Fluid Mech. 345, 79-99. Benney, D. J. & Saffman, P. G. 1966 Nonlinear interactions of random waves. Proc. R. Soc. Lond. A 289, 301-321. Bredmose, H., Agnon, Y., Madsen, P.A. & Schaffer, H.A. 2005 Wave transformation models with exact second-order transfer. European J. of Mech. - B/Fluids 24 (6), 659-682. Eldeberky, Y. & Madsen, P. A. 1999 Deterministic and stochastic evolution equations for fully dispersive and weakly nonlinear waves. Coastal Engineering 38, 1-24. Kaihatu, J. M. & Kirby, J. T. 1995 Nonlinear transformation of waves in infinite water depth. Phys. Fluids 8, 175-188. Holloway, G. 1980 Oceanic internal waves are not weak waves. J. Phys. Oceanogr. 10, 906-914. Stiassnie, M. & Drimer, N. 2006 Prediction of long forcing waves for harbor agitation studies. J. of waterways, port, coastal and ocean engineering 132(3), 166-171. Toledo, Y. & Agnon, Y. 2012 Stochastic evolution equations with localized nonlinear shoaling coefficients. European J. of Mech. - B/Fluids 34, 13-18.

A generalized semikinetic (GSK) model for mesoscale auroral plasma transport

NASA Astrophysics Data System (ADS)

Brown, David Gillespie

1993-12-01

The auroral region of the Earth's ionosphere-magnetosphere system is a complex and active part of the Earth's environment. In order to study the transport of ionospheric plasma in this region, we have developed a generalized semikinetic (GSK) model which combines the tracking of ionospheric ion gyrocenters (between stochastic impulses from waves), with a generalized fluid treatment of ionospheric electrons and Liouville mapping of magnetospheric plasma components. This model has been used to simulate the effects of 'self-consistent' heating ('self consistent' in the sense that heating occurs only where the modelled plasma is unstable) due to the current-driven ion cyclotron instability in the return current regions. Our results include generation of 'conics' whose wings are drawn in towards the upsilon(parallel)-axis at higher energies (such distributions were subsequently found in recent studies of DE-1 data for this region) and an alternative formation mechanism for toroidal (or 'ring'-shaped) ion velocity-space distributions. We also present results illustrating the effects of combining large scale electric fields (generated by anisotropic magnetospheric plasma distributions) with wave heating by a presumed distribution of wave spectra. In the presence of an upwards electric field the addition of wave heating increases the density of the O(sup +) 'beam' ('ion feeder' effect), while a downwards hot plasma-induced electric field increases the time which ions spend within the heating region ('pressure cooker' effect), resulting in greater ion energization.

Gravitational-wave stochastic background from cosmic strings.

PubMed

Siemens, Xavier; Mandic, Vuk; Creighton, Jolien

2007-03-16

We consider the stochastic background of gravitational waves produced by a network of cosmic strings and assess their accessibility to current and planned gravitational wave detectors, as well as to big bang nucleosynthesis (BBN), cosmic microwave background (CMB), and pulsar timing constraints. We find that current data from interferometric gravitational wave detectors, such as Laser Interferometer Gravitational Wave Observatory (LIGO), are sensitive to areas of parameter space of cosmic string models complementary to those accessible to pulsar, BBN, and CMB bounds. Future more sensitive LIGO runs and interferometers such as Advanced LIGO and Laser Interferometer Space Antenna (LISA) will be able to explore substantial parts of the parameter space.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Stochastic fire-diffuse-fire model with realistic cluster dynamics.

PubMed

Calabrese, Ana; Fraiman, Daniel; Zysman, Daniel; Ponce Dawson, Silvina

2010-09-01

Living organisms use waves that propagate through excitable media to transport information. Ca2+ waves are a paradigmatic example of this type of processes. A large hierarchy of Ca2+ signals that range from localized release events to global waves has been observed in Xenopus laevis oocytes. In these cells, Ca2+ release occurs trough inositol 1,4,5-trisphosphate receptors (IP3Rs) which are organized in clusters of channels located on the membrane of the endoplasmic reticulum. In this article we construct a stochastic model for a cluster of IP3R 's that replicates the experimental observations reported in [D. Fraiman, Biophys. J. 90, 3897 (2006)]. We then couple this phenomenological cluster model with a reaction-diffusion equation, so as to have a discrete stochastic model for calcium dynamics. The model we propose describes the transition regimes between isolated release and steadily propagating waves as the IP3 concentration is increased.

Optimal Search for an Astrophysical Gravitational-Wave Background

NASA Astrophysics Data System (ADS)

Smith, Rory; Thrane, Eric

2018-04-01

Roughly every 2-10 min, a pair of stellar-mass black holes merge somewhere in the Universe. A small fraction of these mergers are detected as individually resolvable gravitational-wave events by advanced detectors such as LIGO and Virgo. The rest contribute to a stochastic background. We derive the statistically optimal search strategy (producing minimum credible intervals) for a background of unresolved binaries. Our method applies Bayesian parameter estimation to all available data. Using Monte Carlo simulations, we demonstrate that the search is both "safe" and effective: it is not fooled by instrumental artifacts such as glitches and it recovers simulated stochastic signals without bias. Given realistic assumptions, we estimate that the search can detect the binary black hole background with about 1 day of design sensitivity data versus ≈40 months using the traditional cross-correlation search. This framework independently constrains the merger rate and black hole mass distribution, breaking a degeneracy present in the cross-correlation approach. The search provides a unified framework for population studies of compact binaries, which is cast in terms of hyperparameter estimation. We discuss a number of extensions and generalizations, including application to other sources (such as binary neutron stars and continuous-wave sources), simultaneous estimation of a continuous Gaussian background, and applications to pulsar timing.

Observation of Electron Bernstein Wave Heating in the RFP

NASA Astrophysics Data System (ADS)

Seltzman, Andrew; Anderson, Jay; Goetz, John; Forest, Cary

2017-10-01

The first observation of RF heating in a reversed field pinch (RFP) using the electron Bernstein wave (EBW) has been demonstrated on MST. Efficient mode conversion of an outboard-launched X mode wave at 5.5 GHz leads to Doppler-shifted resonant absorption (ωrf = nωce-k||v||) for a broad range (n =1-7) of harmonics. The dynamics of EBW-heated electrons are measured using a spatial distribution of solid targets with diametrically opposed x-ray detectors. EBW heating produces a clear supra-thermal electron tail in MST. Radial deposition of the EBW is controlled with |B|and is measured using the HXR flux emitted from an insertable probe. In the thick-shelled MST RFP, the radial accessibility of EBW is limited to r/a >0.8 ( 10cm) by magnetic field error induced by the porthole necessary for the antenna. Experimental measurements show EBW propagation inward through a stochastic magnetic field. EBW-heated test electrons are used as a direct probe of edge (r/a >0.9) radial transport, showing a modest transition from `standard' to reduced-tearing RFP operation. Electron loss is too fast for collisional effects and implies a large non-collisional radial diffusivity. EBW heating has been demonstrated in reduced magnetic stochasticity plasmas with β = 15-20%. Work supported by USDOE.

Active stability augmentation of large space structures: A stochastic control problem

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1987-01-01

A problem in SCOLE is that of slewing an offset antenna on a long flexible beam-like truss attached to the space shuttle, with rather stringent pointing accuracy requirements. The relevant methodology aspects in robust feedback-control design for stability augmentation of the beam using on-board sensors is examined. It is framed as a stochastic control problem, boundary control of a distributed parameter system described by partial differential equations. While the framework is mathematical, the emphasis is still on an engineering solution. An abstract mathematical formulation is developed as a nonlinear wave equation in a Hilbert space. That the system is controllable is shown and a feedback control law that is robust in the sense that it does not require quantitative knowledge of system parameters is developed. The stochastic control problem that arises in instrumenting this law using appropriate sensors is treated. Using an engineering first approximation which is valid for small damping, formulas for optimal choice of the control gain are developed.

Rogue waves in terms of multi-point statistics and nonequilibrium thermodynamics

NASA Astrophysics Data System (ADS)

Hadjihosseini, Ali; Lind, Pedro; Mori, Nobuhito; Hoffmann, Norbert P.; Peinke, Joachim

2017-04-01

Ocean waves, which lead to rogue waves, are investigated on the background of complex systems. In contrast to deterministic approaches based on the nonlinear Schroedinger equation or focusing effects, we analyze this system in terms of a noisy stochastic system. In particular we present a statistical method that maps the complexity of multi-point data into the statistics of hierarchically ordered height increments for different time scales. We show that the stochastic cascade process with Markov properties is governed by a Fokker-Planck equation. Conditional probabilities as well as the Fokker-Planck equation itself can be estimated directly from the available observational data. This stochastic description enables us to show several new aspects of wave states. Surrogate data sets can in turn be generated allowing to work out different statistical features of the complex sea state in general and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics. As a new outlook the ocean wave states will be considered in terms of nonequilibrium thermodynamics, for which the entropy production of different wave heights will be considered. We show evidence that rogue waves are characterized by negative entropy production. The statistics of the entropy production can be used to distinguish different wave states.

Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A.

2017-01-01

To better represent organized convection in the Climate Forecast System version 2 (CFSv2), a stochastic multicloud model (SMCM) parameterization is adopted and a 15 year climate run is made. The last 10 years of simulations are analyzed here. While retaining an equally good mean state (if not better) as the parent model, the CFS-SMCM simulation shows significant improvement in the synoptic and intraseasonal variability. The CFS-SMCM provides a better account of convectively coupled equatorial waves and the Madden-Julian oscillation. The CFS-SMCM exhibits improvements in northward and eastward propagation of intraseasonal oscillation of convection including the MJO propagation beyond the maritime continent barrier, which is the Achilles Heel for coarse-resolution global climate models (GCMs). The distribution of precipitation events is better simulated in CFSsmcm and spreads naturally toward high-precipitation events. Deterministic GCMs tend to simulate a narrow distribution with too much drizzling precipitation and too little high-precipitation events.

Long-time Dynamics of Stochastic Wave Breaking

NASA Astrophysics Data System (ADS)

Restrepo, J. M.; Ramirez, J. M.; Deike, L.; Melville, K.

2017-12-01

A stochastic parametrization is proposed for the dynamics of wave breaking of progressive water waves. The model is shown to agree with transport estimates, derived from the Lagrangian path of fluid parcels. These trajectories are obtained numerically and are shown to agree well with theory in the non-breaking regime. Of special interest is the impact of wave breaking on transport, momentum exchanges and energy dissipation, as well as dispersion of trajectories. The proposed model, ensemble averaged to larger time scales, is compared to ensemble averages of the numerically generated parcel dynamics, and is then used to capture energy dissipation and path dispersion.

3D radiation belt diffusion model results using new empirical models of whistler chorus and hiss

NASA Astrophysics Data System (ADS)

Cunningham, G.; Chen, Y.; Henderson, M. G.; Reeves, G. D.; Tu, W.

2012-12-01

3D diffusion codes model the energization, radial transport, and pitch angle scattering due to wave-particle interactions. Diffusion codes are powerful but are limited by the lack of knowledge of the spatial & temporal distribution of waves that drive the interactions for a specific event. We present results from the 3D DREAM model using diffusion coefficients driven by new, activity-dependent, statistical models of chorus and hiss waves. Most 3D codes parameterize the diffusion coefficients or wave amplitudes as functions of magnetic activity indices like Kp, AE, or Dst. These functional representations produce the average value of the wave intensities for a given level of magnetic activity; however, the variability of the wave population at a given activity level is lost with such a representation. Our 3D code makes use of the full sample distributions contained in a set of empirical wave databases (one database for each wave type, including plasmaspheric hiss, lower and upper hand chorus) that were recently produced by our team using CRRES and THEMIS observations. The wave databases store the full probability distribution of observed wave intensity binned by AE, MLT, MLAT and L*. In this presentation, we show results that make use of the wave intensity sample probability distributions for lower-band and upper-band chorus by sampling the distributions stochastically during a representative CRRES-era storm. The sampling of the wave intensity probability distributions produces a collection of possible evolutions of the phase space density, which quantifies the uncertainty in the model predictions caused by the uncertainty of the chorus wave amplitudes for a specific event. A significant issue is the determination of an appropriate model for the spatio-temporal correlations of the wave intensities, since the diffusion coefficients are computed as spatio-temporal averages of the waves over MLT, MLAT and L*. The spatiotemporal correlations cannot be inferred from the wave databases. In this study we use a temporal correlation of ~1 hour for the sampled wave intensities that is informed by the observed autocorrelation in the AE index, a spatial correlation length of ~100 km in the two directions perpendicular to the magnetic field, and a spatial correlation length of 5000 km in the direction parallel to the magnetic field, according to the work of Santolik et al (2003), who used multi-spacecraft measurements from Cluster to quantify the correlation length scales for equatorial chorus . We find that, despite the small correlation length scale for chorus, there remains significant variability in the model outcomes driven by variability in the chorus wave intensities.

Stochastic Acceleration of Ions Driven by Pc1 Wave Packets

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Sibeck, D. G.; Tel'nikhin, A. A.; Kronberg, T. K.

2015-01-01

The stochastic motion of protons and He(sup +) ions driven by Pc1 wave packets is studied in the context of resonant particle heating. Resonant ion cyclotron heating typically occurs when wave powers exceed 10(exp -4) nT sq/Hz. Gyroresonance breaks the first adiabatic invariant and energizes keV ions. Cherenkov resonances with the electrostatic component of wave packets can also accelerate ions. The main effect of this interaction is to accelerate thermal protons to the local Alfven speed. The dependencies of observable quantities on the wave power and plasma parameters are determined, and estimates for the heating extent and rate of particle heating in these wave-particle interactions are shown to be in reasonable agreement with known empirical data.

Stochastic Convection Parameterizations

NASA Technical Reports Server (NTRS)

Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios

2012-01-01

computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts

Chang'e 3 lunar mission and upper limit on stochastic background of gravitational wave around the 0.01 Hz band

NASA Astrophysics Data System (ADS)

Tang, Wenlin; Xu, Peng; Hu, Songjie; Cao, Jianfeng; Dong, Peng; Bu, Yanlong; Chen, Lue; Han, Songtao; Gong, Xuefei; Li, Wenxiao; Ping, Jinsong; Lau, Yun-Kau; Tang, Geshi

2017-09-01

The Doppler tracking data of the Chang'e 3 lunar mission is used to constrain the stochastic background of gravitational wave in cosmology within the 1 mHz to 0.05 Hz frequency band. Our result improves on the upper bound on the energy density of the stochastic background of gravitational wave in the 0.02-0.05 Hz band obtained by the Apollo missions, with the improvement reaching almost one order of magnitude at around 0.05 Hz. Detailed noise analysis of the Doppler tracking data is also presented, with the prospect that these noise sources will be mitigated in future Chinese deep space missions. A feasibility study is also undertaken to understand the scientific capability of the Chang'e 4 mission, due to be launched in 2018, in relation to the stochastic gravitational wave background around 0.01 Hz. The study indicates that the upper bound on the energy density may be further improved by another order of magnitude from the Chang'e 3 mission, which will fill the gap in the frequency band from 0.02 Hz to 0.1 Hz in the foreseeable future.

Stochastic analysis and modeling of abnormally large waves

NASA Astrophysics Data System (ADS)

Kuznetsov, Konstantin; Shamin, Roman; Yudin, Aleksandr

2016-04-01

In this work stochastics of amplitude characteristics of waves during the freak waves formation was estimated. Also amplitude characteristics of freak wave was modeling with the help of the developed Markov model on the basis of in-situ and numerical experiments. Simulation using the Markov model showed a great similarity of results of in-situ wave measurements[1], results of directly calculating the Euler equations[2] and stochastic modeling data. This work is supported by grant of Russian Foundation for Basic Research (RFBR) n°16-35-00526. 1. K. I. Kuznetsov, A. A. Kurkin, E. N. Pelinovsky and P. D. Kovalev Features of Wind Waves at the Southeastern Coast of Sakhalin according to Bottom Pressure Measurements //Izvestiya, Atmospheric and Oceanic Physics, 2014, Vol. 50, No. 2, pp. 213-220. DOI: 10.1134/S0001433814020066. 2. R.V. Shamin, V.E. Zakharov, A.I. Dyachenko. How probability for freak wave formation can be found // THE EUROPEAN PHYSICAL JOURNAL - SPECIAL TOPICS Volume 185, Number 1, 113-124, DOI: 10.1140/epjst/e2010-01242-y 3.E. N. Pelinovsky, K. I. Kuznetsov, J. Touboul, A. A. Kurkin Bottom pressure caused by passage of a solitary wave within the strongly nonlinear Green-Naghdi model //Doklady Physics, April 2015, Volume 60, Issue 4, pp 171-174. DOI: 10.1134/S1028335815040035

Stochastic Particle Acceleration in Impulsive Solar Flares

NASA Technical Reports Server (NTRS)

Miller, James A.

2001-01-01

The acceleration of a huge number of electrons and ions to relativistic energies over timescales ranging from several seconds to several tens of seconds is the fundamental problem in high-energy solar physics. The cascading turbulence model we have developed has been shown previously (e.g., Miller 2000; Miller & Roberts 1995; Miner, LaRosa, & Moore 1996) to account for all the bulk features (such as acceleration timescales, fluxes, total number of energetic particles, and maximum energies) of electron and proton acceleration in impulsive solar flares. While the simulation of this acceleration process is involved, the essential idea of the model is quite simple, and consists of just a few parts: 1. During the primary flare energy release phase, we assume that low-amplitude MHD Alfven and fast mode waves are excited at long wavelengths, say comparable to the size of the event (although the results are actually insensitive to this initial wavelength). While an assumption, this appears reasonable in light of the likely highly turbulent nature of the flare. 2. These waves then cascade in a Kolmogorov-like fashion to smaller wavelengths (e.g., Verma et al. 1996), forming a power-law spectral density in wavenumber space through the inertial range. 3. When the mean wavenumber of the fast mode waves has increased sufficiently, the transit-time acceleration rate (Miller 1997) for superAlfvenic electrons can overcome Coulomb energy losses, and these electrons are accelerated out of the thermal distribution and to relativistic energies (Miller et al. 1996). As the Alfven waves cascade to higher wavenumbers, they can cyclotron resonate with progressively lower energy protons. Eventually, they will resonate with protons in the tail of the thermal distribution, which will then be accelerated to relativistic energies as well (Miller & Roberts 1995). Hence, both ions and electrons are stochastically accelerated, albeit by different mechanisms and different waves. 4. When the protons become superAlfvenic (above about 1 MeV/nucleon), they too can suffer transit-time acceleration by the fast mode waves and will receive an extra acceleration "kick." The basic overall objective of this 1 year effort was to construct a spatially-dependent version of this acceleration model and this has been realized.

Decoherence and surface hopping: When can averaging over initial conditions help capture the effects of wave packet separation?

NASA Astrophysics Data System (ADS)

Subotnik, Joseph E.; Shenvi, Neil

2011-06-01

Fewest-switches surface hopping (FSSH) is a popular nonadiabatic dynamics method which treats nuclei with classical mechanics and electrons with quantum mechanics. In order to simulate the motion of a wave packet as accurately as possible, standard FSSH requires a stochastic sampling of the trajectories over a distribution of initial conditions corresponding, e.g., to the Wigner distribution of the initial quantum wave packet. Although it is well-known that FSSH does not properly account for decoherence effects, there is some confusion in the literature about whether or not this averaging over a distribution of initial conditions can approximate some of the effects of decoherence. In this paper, we not only show that averaging over initial conditions does not generally account for decoherence, but also why it fails to do so. We also show how an apparent improvement in accuracy can be obtained for a fortuitous choice of model problems, even though this improvement is not possible, in general. For a basic set of one-dimensional and two-dimensional examples, we find significantly improved results using our recently introduced augmented FSSH algorithm.

Upper Limits on a Stochastic Gravitational-Wave Background Using LIGO and Virgo Interferometers at 600-1000 Hz

NASA Technical Reports Server (NTRS)

Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adhikari, R.; Affeldt, C.;

Upper limits on a stochastic gravitational-wave background using LIGO and Virgo interferometers at 600-1000 Hz

NASA Astrophysics Data System (ADS)

Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adhikari, R.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Ajith, P.; Allen, B.; Amador Ceron, E.; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Arain, M. A.; Araya, M. C.; Aston, S. M.; Astone, P.; Atkinson, D.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P.; Ballardin, G.; Ballmer, S.; Barayoga, J. C. B.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Beck, D.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Belletoile, A.; Belopolski, I.; Benacquista, M.; Berliner, J. M.; Bertolini, A.; Betzwieser, J.; Beveridge, N.; Beyersdorf, P. T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biswas, R.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bland, B.; Blom, M.; Bock, O.; Bodiya, T. P.; Bogan, C.; Bondarescu, R.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bouhou, B.; Braccini, S.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burguet–Castell, J.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannizzo, J.; Cannon, K.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chaibi, O.; Chalermsongsak, T.; Charlton, P.; Chassande-Mottin, E.; Chelkowski, S.; Chen, W.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chua, S. S. Y.; Chung, C. T. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J.; Clayton, J. H.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colacino, C. N.; Colas, J.; Colla, A.; Colombini, M.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M.; Coulon, J.-P.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, R. M.; Dahl, K.; Danilishin, S. L.; Dannenberg, R.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Daw, E. J.; Day, R.; Dayanga, T.; De Rosa, R.; DeBra, D.; Debreczeni, G.; Del Pozzo, W.; del Prete, M.; Dent, T.; Dergachev, V.; DeRosa, R.; DeSalvo, R.; Dhurandhar, S.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Paolo Emilio, M.; Di Virgilio, A.; Díaz, M.; Dietz, A.; Donovan, F.; Dooley, K. L.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edgar, M.; Edwards, M.; Effler, A.; Ehrens, P.; Endrőczi, G.; Engel, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fan, Y.; Farr, B. F.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Feroz, F.; Ferrante, I.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Flanigan, M.; Foley, S.; Forsi, E.; Forte, L. A.; Fotopoulos, N.; Fournier, J.-D.; Franc, J.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Friedrich, D.; Fritschel, P.; Frolov, V. V.; Fujimoto, M.-K.; Fulda, P. J.; Fyffe, M.; Gair, J.; Galimberti, M.; Gammaitoni, L.; Garcia, J.; Garufi, F.; Gáspár, M. E.; Gemme, G.; Geng, R.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gil-Casanova, S.; Gill, C.; Gleason, J.; Goetz, E.; Goggin, L. M.; González, G.; Gorodetsky, M. L.; Goßler, S.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Gray, N.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Greverie, C.; Grosso, R.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guido, C..; Gupta, R.; Gustafson, E. K.; Gustafson, R.; Ha, T.; Hallam, J. M.; Hammer, D.; Hammond, G.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haughian, K.; Hayama, K.; Hayau, J.-F.; Heefner, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hendry, M. A.; Heng, I. S.; Heptonstall, A. W.; Herrera, V.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Holtrop, M.; Hong, T.; Hooper, S.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Izumi, K.; Jacobson, M.; James, E.; Jang, Y. J.; Jaranowski, P.; Jesse, E.; Johnson, W. W.; Jones, D. I.; Jones, G.; Jones, R.; Ju, L.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasturi, R.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Kelley, D.; Kells, W.; Keppel, D. G.; Keresztes, Z.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B. K.; Kim, C.; Kim, H.; Kim, K.; Kim, N.; Kim, Y. M.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kranz, O.; Kringel, V.; Krishnamurthy, S.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, R.; Kwee, P.; Lam, P. K.; Landry, M.; Lantz, B.; Lastzka, N.; Lawrie, C.; Lazzarini, A.; Leaci, P.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Leong, J. R.; Leonor, I.; Leroy, N.; Letendre, N.; Li, J.; Li, T. G. F.; Liguori, N.; Lindquist, P. E.; Liu, Y.; Liu, Z.; Lockerbie, N. A.; Lodhia, D.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Luan, J.; Lubinski, M.; Lück, H.; Lundgren, A. P.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Man, N.; Mandel, I.; Mandic, V.; Mantovani, M.; Marandi, A.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Marx, J. N.; Mason, K.; Masserot, A.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; McKechan, D. J. A.; McWilliams, S.; Meadors, G. D.; Mehmet, M.; Meier, T.; Melatos, A.; Melissinos, A. C.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Milano, L.; Miller, J.; Minenkov, Y.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Miyakawa, O.; Moe, B.; Mohan, M.; Mohanty, S. D.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morgia, A.; Mori, T.; Morriss, S. R.; Mosca, S.; Mossavi, K.; Mours, B.; Mow–Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Müller-Ebhardt, H.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nash, T.; Naticchioni, L.; Necula, V.; Nelson, J.; Neri, I.; Newton, G.; Nguyen, T.; Nishizawa, A.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Page, A.; Pagliaroli, G.; Palladino, L.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Papa, M. A.; Parisi, M.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patel, P.; Pedraza, M.; Peiris, P.; Pekowsky, L.; Penn, S.; Perreca, A.; Persichetti, G.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pietka, M.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Plissi, M. V.; Poggiani, R.; Pöld, J.; Postiglione, F.; Prato, M.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Rakhmanov, M.; Rankins, B.; Rapagnani, P.; Raymond, V.; Re, V.; Redwine, K.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Robertson, N. A.; Robinet, F.; Robinson, C.; Robinson, E. L.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Rolland, L.; Rollins, J. G.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Röver, C.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sainathan, P.; Salemi, F.; Sammut, L.; Sandberg, V.; Sannibale, V.; Santamaría, L.; Santiago-Prieto, I.; Santostasi, G.; Sassolas, B.; Sathyaprakash, B. S.; Sato, S.; Saulson, P. R.; Savage, R. L.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Seifert, F.; Sellers, D.; Sentenac, D.; Sergeev, A.; Shaddock, D. A.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sibley, A.; Siemens, X.; Sigg, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G. R.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Somiya, K.; Sorazu, B.; Soto, J.; Speirits, F. C.; Sperandio, L.; Stefszky, M.; Stein, A. J.; Stein, L. C.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S. E.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sung, M.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Tacca, M.; Taffarello, L.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, J. R.; Taylor, R.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Thüring, A.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C.; Torrie, C. I.; Tournefier, E.; Travasso, F.; Traylor, G.; Tseng, K.; Ugolini, D.; Vahlbruch, H.; Vajente, G.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van Veggel, A. A.; Vass, S.; Vasuth, M.; Vaulin, R.; Vavoulidis, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Veltkamp, C.; Verkindt, D.; Vetrano, F.; Viceré, A.; Villar, A. E.; Vinet, J.-Y.; Vitale, S.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Waldman, S. J.; Wallace, L.; Wan, Y.; Wang, M.; Wang, X.; Wang, Z.; Wanner, A.; Ward, R. L.; Was, M.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Wilkinson, C.; Willems, P. A.; Williams, L.; Williams, R.; Willke, B.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Wooley, R.; Worden, J.; Yakushin, I.; Yamamoto, H.; Yamamoto, K.; Yancey, C. C.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yu, P.; Yvert, M.; Zadroźny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhang, W.; Zhao, C.; Zotov, N.; Zucker, M. E.; Zweizig, J.

2012-06-01

A stochastic background of gravitational waves is expected to arise from a superposition of many incoherent sources of gravitational waves, of either cosmological or astrophysical origin. This background is a target for the current generation of ground-based detectors. In this article we present the first joint search for a stochastic background using data from the LIGO and Virgo interferometers. In a frequency band of 600-1000 Hz, we obtained a 95% upper limit on the amplitude of ΩGW(f)=Ω3(f/900Hz)3, of Ω3<0.32, assuming a value of the Hubble parameter of h100=0.71. These new limits are a factor of seven better than the previous best in this frequency band.

Super-stable Poissonian structures

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2012-10-01

In this paper we characterize classes of Poisson processes whose statistical structures are super-stable. We consider a flow generated by a one-dimensional ordinary differential equation, and an ensemble of particles ‘surfing’ the flow. The particles start from random initial positions, and are propagated along the flow by stochastic ‘wave processes’ with general statistics and general cross correlations. Setting the initial positions to be Poisson processes, we characterize the classes of Poisson processes that render the particles’ positions—at all times, and invariantly with respect to the wave processes—statistically identical to their initial positions. These Poisson processes are termed ‘super-stable’ and facilitate the generalization of the notion of stationary distributions far beyond the realm of Markov dynamics.

Optimizing signal recycling for detecting a stochastic gravitational-wave background

NASA Astrophysics Data System (ADS)

Tao, Duo; Christensen, Nelson

2018-06-01

Signal recycling is applied in laser interferometers such as the Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO) to increase their sensitivity to gravitational waves. In this study, signal recycling configurations for detecting a stochastic gravitational wave background are optimized based on aLIGO parameters. Optimal transmission of the signal recycling mirror (SRM) and detuning phase of the signal recycling cavity under a fixed laser power and low-frequency cutoff are calculated. Based on the optimal configurations, the compatibility with a binary neutron star (BNS) search is discussed. Then, different laser powers and low-frequency cutoffs are considered. Two models for the dimensionless energy density of gravitational waves , the flat model and the model, are studied. For a stochastic background search, it is found that an interferometer using signal recycling has a better sensitivity than an interferometer not using it. The optimal stochastic search configurations are typically found when both the SRM transmission and the signal recycling detuning phase are low. In this region, the BNS range mostly lies between 160 and 180 Mpc. When a lower laser power is used the optimal signal recycling detuning phase increases, the optimal SRM transmission increases and the optimal sensitivity improves. A reduced low-frequency cutoff gives a better sensitivity limit. For both models of , a typical optimal sensitivity limit on the order of 10‑10 is achieved at a reference frequency of Hz.

Spatiotemporal Stochastic Resonance:Theory and Experiment

NASA Astrophysics Data System (ADS)

Peter, Jung

1996-03-01

The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3] A. Cornell-Bell, Steven M. Finkbeiner, Mark.S. Cooper and Stephen J. Smith, SCIENCE, 247, 373 (1990).

Geological, Geophysical, and Stochastic Factors in Nepal's Gorkha Earthquake-Triggered Landslide Distribution

NASA Astrophysics Data System (ADS)

Kargel, J. S.; Shugar, D. H.; Haritashya, U. K.; Leonard, G. J.; Fielding, E. J.; Hudnut, K. W.; Jibson, R.; Collins, B. D.

2015-12-01

On 25 April 2015, a magnitude 7.8 earthquake struck Nepal. Subsequently many large aftershocks shook the region, including one of magnitude 7.3. Much damage and over 4300 landslides were triggered. The landslides were mapped by a volunteer group who self organized to undertake an emergency response to the earthquake disaster. The number of landslides is fewer than expected based on total released seismic energy. This may be because of lack of a surface rupture and possibly also because of high surface-wave attenuation due to rugged surface topography or to the geological and geophysical characteristics of the upper crust. The observed landslides were primarily in the southern half of the Himalaya in areas where the steepest slopes occur and where peak ground accelerations were relatively high. The landslides are also concentrated on the tectonically downdropped block. However, the distribution is complex and varies dramatically from valley to valley. Furthermore, different types of landslides are concentrated in different geologic materials, which suggests local factors control the valley-scale attenuation or amplification of seismic waves or the way wave disturbances couple to the local geologic materials. Across the earthquake-affected zone on the regional scale, wave attenuation and also net downdrop and uplift may also explain as much about the distribution of landslides as slopes and distance from large slips on the fault. We will offer the regional distribution results and some specific case studies to illustrate a set of possible controlling factors.

Stochastic generation of MAC waves and implications for convection in Earth's core

NASA Astrophysics Data System (ADS)

Buffett, Bruce; Knezek, Nicholas

2018-03-01

Convection in Earth's core can sustain magnetic-Archemedes-Coriolis (MAC) waves through a variety of mechanisms. Buoyancy and Lorentz forces are viable sources for wave motion, together with the effects of magnetic induction. We develop a quantitative description for zonal MAC waves and assess the source mechanisms using a numerical dynamo model. The largest sources at conditions accessible to the dynamo model are due to buoyancy forces and magnetic induction. However, when these sources are extrapolated to conditions expected in Earth's core, the Lorentz force emerges as the dominant generation mechanism. This source is expected to produce wave velocities of roughly 2 km yr-1 when the internal magnetic field is characterized by a dimensionless Elsasser number of roughly Λ ≈ 10 and the root-mean-square convective velocity defines a magnetic Reynolds number of Rm ≈ 103. Our preferred model has a radially varying stratification and a constant (radial) background magnetic field. It predicts a broad power spectrum for the wave velocity with most power distributed across periods from 30 to 100 yr.

On the contribution of a stochastic background of gravitational radiation to the timing noise of pulsars

NASA Technical Reports Server (NTRS)

Mashhoon, B.

1982-01-01

The influence of a stochastic and isotropic background of gravitational radiation on timing measurements of pulsars is investigated, and it is shown that pulsar timing noise may be used to establish a significant upper limit of about 10 to the -10th on the total energy density of very long-wavelength stochastic gravitational waves. This places restriction on the strength of very long wavelength gravitational waves in the Friedmann model, and such a background is expected to have no significant effect on the approximately 3 K electromagnetic background radiation or on the dynamics of a cluster of galaxies.

q-Gaussian distributions and multiplicative stochastic processes for analysis of multiple financial time series

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2010-12-01

This study considers q-Gaussian distributions and stochastic differential equations with both multiplicative and additive noises. In the M-dimensional case a q-Gaussian distribution can be theoretically derived as a stationary probability distribution of the multiplicative stochastic differential equation with both mutually independent multiplicative and additive noises. By using the proposed stochastic differential equation a method to evaluate a default probability under a given risk buffer is proposed.

REVIEWS OF TOPICAL PROBLEMS: Gravitational-wave astronomy

NASA Astrophysics Data System (ADS)

Grishchuk, Leonid P.

1988-10-01

CONTENTS 1. Introduction. Gravitational-wave astronomy in action 940 2. Astronomical manifestations of gravitational waves 941 2.1. The binary radio pulsar PSR 1913 + 16. 2.2. Cataclysmic variables. 2.3. Type I supernovas. 3. Theory and some new results 942 3.1. Mathematical description of gravitational waves. 3.2. Relativistic celestial mechanics. 4. Sources of gravitational waves and modern experimental limits 943 4.1. Pulsed sources. 4.2. Periodic sources. 5. Stochastic background of gravitational waves and the early universe 946 5.1. Quantum production of gravitons. 5.2. Observational bounds on the intensity of the stochastic background and physics of the early universe. 6. Detection of gravitational waves 950 6.1. Brief description of detectors. 6.2. Noise and sensitivity. 7. New ideas and prospects 951 7.1. Kinematic resonance and the memory effect. 7.2. Possibilities of detection of high-frequency relic gravitons. References 953

Development of spiral wave in a regular network of excitatory neurons due to stochastic poisoning of ion channels

NASA Astrophysics Data System (ADS)

Wu, Xinyi; Ma, Jun; Li, Fan; Jia, Ya

2013-12-01

Some experimental evidences show that spiral wave could be observed in the cortex of brain, and the propagation of this spiral wave plays an important role in signal communication as a pacemaker. The profile of spiral wave generated in a numerical way is often perfect while the observed profile in experiments is not perfect and smooth. In this paper, formation and development of spiral wave in a regular network of Morris-Lecar neurons, which neurons are placed on nodes uniformly in a two-dimensional array and each node is coupled with nearest-neighbor type, are investigated by considering the effect of stochastic ion channels poisoning and channel noise. The formation and selection of spiral wave could be detected as follows. (1) External forcing currents with diversity are imposed on neurons in the network of excitatory neurons with nearest-neighbor connection, a target-like wave emerges and its potential mechanism is discussed; (2) artificial defects and local poisoned area are selected in the network to induce new wave to interact with the target wave; (3) spiral wave can be induced to occupy the network when the target wave is blocked by the artificial defects or poisoned area with regular border lines; (4) the stochastic poisoning effect is introduced by randomly modifying the border lines (areas) of specific regions in the network. It is found that spiral wave can be also developed to occupy the network under appropriate poisoning ratio. The process of growth for the poisoned area of ion channels poisoning is measured, the effect of channels noise is also investigated. It is confirmed that perfect spiral wave emerges in the network under gradient poisoning even if the channel noise is considered.

Search for optimal 3D wave launching configurations for the acceleration of charged particles in a magnetized plasma: Resonant Moments Method

NASA Astrophysics Data System (ADS)

Ponomarjov, Maxim; Carati, Daniele

2004-11-01

Three-dimensional electromagnetic wave configurations are proposed for accelerating charged particles in an external magnetic field. A primary wave responsible for the acceleration is coupled to a secondary wave generating the chaotic motion of the particles. The wave vectors and the magnetic field are not supposed to be co-planar and create a fully three dimensional system. This configuration produces faster acceleration with low amplitude. The idea considered here is similar to Refs. [1-2] although no constraint is imposed on the refraction indices. The theoretical analysis of the acceleration mechanism is based on the Resonance Moments Method (RMM) in which the velocity distribution and its moments are approximated by using an average over the resonant layers (RL)i only instead of a complete phase-space averages. The quantities obtained using this approach, referred to as Resonant Moments (RM), suggest the existence of optimal angles of propagation for the primary and secondary waves as long as the maximization of the parallel flux of charged particles is considered The secondary wave tends to maintain a pseudo-equilibrium velocity distribution by continuously re-filling the RL. Our suggestions are confirmed by direct numerical simulations of particle trajectories. The parameters for these simulations are relevant to magnetic plasma fusion experiments in electron cyclotron resonance heating and electron acceleration in planetary magnetospheres. Although measures of the distributions clearly show a departure from thermal equilibrium, the stochastization effect of the secondary wave yields a clear increase (up to one order of magnitude) of the average parallel velocity of the particles. It is a quite promising result since the amplitude of the secondary wave is ten times lower the one of the first wave. 1 H. Karimabadi and V. Angelopoulos, Phys. Rev. Lett., 62, 2342 (1989). 2 B. I. Cohen, R. H Cohen, W. M. Nevins, and T. D. Rognlien, Rev. Mod. Phys., 63, 949 (1991).

Stochastic control of inertial sea wave energy converter.

PubMed

Raffero, Mattia; Martini, Michele; Passione, Biagio; Mattiazzo, Giuliana; Giorcelli, Ermanno; Bracco, Giovanni

2015-01-01

The ISWEC (inertial sea wave energy converter) is presented, its control problems are stated, and an optimal control strategy is introduced. As the aim of the device is energy conversion, the mean absorbed power by ISWEC is calculated for a plane 2D irregular sea state. The response of the WEC (wave energy converter) is driven by the sea-surface elevation, which is modeled by a stationary and homogeneous zero mean Gaussian stochastic process. System equations are linearized thus simplifying the numerical model of the device. The resulting response is obtained as the output of the coupled mechanic-hydrodynamic model of the device. A stochastic suboptimal controller, derived from optimal control theory, is defined and applied to ISWEC. Results of this approach have been compared with the ones obtained with a linear spring-damper controller, highlighting the capability to obtain a higher value of mean extracted power despite higher power peaks.

Stochastic Control of Inertial Sea Wave Energy Converter

PubMed Central

Mattiazzo, Giuliana; Giorcelli, Ermanno

2015-01-01

The ISWEC (inertial sea wave energy converter) is presented, its control problems are stated, and an optimal control strategy is introduced. As the aim of the device is energy conversion, the mean absorbed power by ISWEC is calculated for a plane 2D irregular sea state. The response of the WEC (wave energy converter) is driven by the sea-surface elevation, which is modeled by a stationary and homogeneous zero mean Gaussian stochastic process. System equations are linearized thus simplifying the numerical model of the device. The resulting response is obtained as the output of the coupled mechanic-hydrodynamic model of the device. A stochastic suboptimal controller, derived from optimal control theory, is defined and applied to ISWEC. Results of this approach have been compared with the ones obtained with a linear spring-damper controller, highlighting the capability to obtain a higher value of mean extracted power despite higher power peaks. PMID:25874267

Stochastic mechanics of reciprocal diffusions

NASA Astrophysics Data System (ADS)

Levy, Bernard C.; Krener, Arthur J.

1996-02-01

The dynamics and kinematics of reciprocal diffusions were examined in a previous paper [J. Math. Phys. 34, 1846 (1993)], where it was shown that reciprocal diffusions admit a chain of conservation laws, which close after the first two laws for two disjoint subclasses of reciprocal diffusions, the Markov and quantum diffusions. For the case of quantum diffusions, the conservation laws are equivalent to Schrödinger's equation. The Markov diffusions were employed by Schrödinger [Sitzungsber. Preuss. Akad. Wiss. Phys. Math Kl. 144 (1931); Ann. Inst. H. Poincaré 2, 269 (1932)], Nelson [Dynamical Theories of Brownian Motion (Princeton University, Princeton, NJ, 1967); Quantum Fluctuations (Princeton University, Princeton, NJ, 1985)], and other researchers to develop stochastic formulations of quantum mechanics, called stochastic mechanics. We propose here an alternative version of stochastic mechanics based on quantum diffusions. A procedure is presented for constructing the quantum diffusion associated to a given wave function. It is shown that quantum diffusions satisfy the uncertainty principle, and have a locality property, whereby given two dynamically uncoupled but statistically correlated particles, the marginal statistics of each particle depend only on the local fields to which the particle is subjected. However, like Wigner's joint probability distribution for the position and momentum of a particle, the finite joint probability densities of quantum diffusions may take negative values.

Spatial delineation, fluid-lithology characterization, and petrophysical modeling of deepwater Gulf of Mexico reservoirs though joint AVA deterministic and stochastic inversion of three-dimensional partially-stacked seismic amplitude data and well logs

NASA Astrophysics Data System (ADS)

Contreras, Arturo Javier

This dissertation describes a novel Amplitude-versus-Angle (AVA) inversion methodology to quantitatively integrate pre-stack seismic data, well logs, geologic data, and geostatistical information. Deterministic and stochastic inversion algorithms are used to characterize flow units of deepwater reservoirs located in the central Gulf of Mexico. A detailed fluid/lithology sensitivity analysis was conducted to assess the nature of AVA effects in the study area. Standard AVA analysis indicates that the shale/sand interface represented by the top of the hydrocarbon-bearing turbidite deposits generate typical Class III AVA responses. Layer-dependent Biot-Gassmann analysis shows significant sensitivity of the P-wave velocity and density to fluid substitution, indicating that presence of light saturating fluids clearly affects the elastic response of sands. Accordingly, AVA deterministic and stochastic inversions, which combine the advantages of AVA analysis with those of inversion, have provided quantitative information about the lateral continuity of the turbidite reservoirs based on the interpretation of inverted acoustic properties and fluid-sensitive modulus attributes (P-Impedance, S-Impedance, density, and LambdaRho, in the case of deterministic inversion; and P-velocity, S-velocity, density, and lithotype (sand-shale) distributions, in the case of stochastic inversion). The quantitative use of rock/fluid information through AVA seismic data, coupled with the implementation of co-simulation via lithotype-dependent multidimensional joint probability distributions of acoustic/petrophysical properties, provides accurate 3D models of petrophysical properties such as porosity, permeability, and water saturation. Pre-stack stochastic inversion provides more realistic and higher-resolution results than those obtained from analogous deterministic techniques. Furthermore, 3D petrophysical models can be more accurately co-simulated from AVA stochastic inversion results. By combining AVA sensitivity analysis techniques with pre-stack stochastic inversion, geologic data, and awareness of inversion pitfalls, it is possible to substantially reduce the risk in exploration and development of conventional and non-conventional reservoirs. From the final integration of deterministic and stochastic inversion results with depositional models and analogous examples, the M-series reservoirs have been interpreted as stacked terminal turbidite lobes within an overall fan complex (the Miocene MCAVLU Submarine Fan System); this interpretation is consistent with previous core data interpretations and regional stratigraphic/depositional studies.

Regionally dependent summer heat wave response to increased surface temperature in the US

NASA Astrophysics Data System (ADS)

Lopez, H.; Dong, S.; Kirtman, B. P.; Goni, G. J.; Lee, S. K.; Atlas, R. M.; West, R.

2017-12-01

Climate projections for the 21st Century suggest an increase in the occurrence of heat waves. However, the time it takes for the externally forced signal of climate change to emerge against the background of natural variability (i.e., Time of Emergence, ToE) particularly on the regional scale makes reliable future projection of heat waves challenging. Here, we combine observations and model simulations under present and future climate forcing to assess internal variability versus external forcing in modulating US heat waves. We characterized the most common heat wave patterns over the US by the use of clustering of extreme events by their spatial distribution. For each heat wave cluster, we assess changes in the probability density function (PDF) of summer temperature extremes by modeling the PDF as a stochastically generated skewed (SGS) distribution. The probability of necessary causation for each heat wave cluster was also quantified, allowing to make assessments of heat extreme attribution to anthropogenic climate change. The results suggest that internal variability will dominate heat wave occurrence over the Great Plains with ToE occurring in the 2050s (2070s) and of occurrence of ratio of warm-to-cold extremes of 1.7 (1.7) for the Northern (Southern) Plains. In contrast, external forcing will dominate over the Western (Great Lakes) region with ToE occurring as early as in the 2020s (2030s) and warm-to-cold extremes ratio of 6.4 (10.2), suggesting caution in attributing heat extremes to external forcing due to their regional dependence.

The oceanic boundary layer driven by wave breaking with stochastic variability. Part 1. Direct numerical simulations

NASA Astrophysics Data System (ADS)

Sullivan, Peter P.; McWilliams, James C.; Melville, W. Kendall

2004-05-01

We devise a stochastic model for the effects of breaking waves and fit its distribution functions to laboratory and field data. This is used to represent the space time structure of momentum and energy forcing of the oceanic boundary layer in turbulence-resolving simulations. The aptness of this breaker model is evaluated in a direct numerical simulation (DNS) of an otherwise quiescent fluid driven by an isolated breaking wave, and the results are in good agreement with laboratory measurements. The breaker model faithfully reproduces the bulk features of a breaking event: the mean kinetic energy decays at a rate approaching t(-1) , and a long-lived vortex (eddy) is generated close to the water surface. The long lifetime of this vortex (more than 50 wave periods) makes it effective in energizing the surface region of oceanic boundary layers. Next, a comparison of several different DNS of idealized oceanic boundary layers driven by different surface forcing (i.e. constant current (as in Couette flow), constant stress, or a mixture of constant stress plus stochastic breakers) elucidates the importance of intermittent stress transmission to the underlying currents. A small amount of active breaking, about 1.6% of the total water surface area at any instant in time, significantly alters the instantaneous flow patterns as well as the ensemble statistics. Near the water surface a vigorous downwelling upwelling pattern develops at the head and tail of each three-dimensional breaker. This enhances the vertical velocity variance and generates both negative- and positive-signed vertical momentum flux. Analysis of the mean velocity and scalar profiles shows that breaking effectively increases the surface roughness z_o by more than a factor of 30; for our simulations z_o/lambda {≈} 0.04 to 0.06, where lambda is the wavelength of the breaking wave. Compared to a flow driven by a constant current, the extra mixing from breakers increases the mean eddy viscosity by more than a factor of 10 near the water surface. Breaking waves alter the usual balance of production and dissipation in the turbulent kinetic energy (TKE) budget; turbulent and pressure transports and breaker work are important sources and sinks in the budget. We also show that turbulent boundary layers driven by constant current and constant stress (i.e. with no breaking) differ in fundamental ways. The additional freedom provided by a constant-stress boundary condition permits finite velocity variances at the water surface, so that flows driven by constant stress mimic flows with weakly and statistically homogeneous breaking waves.

Wave-optics modeling of the optical-transport line for passive optical stochastic cooling

NASA Astrophysics Data System (ADS)

Andorf, M. B.; Lebedev, V. A.; Piot, P.; Ruan, J.

2018-03-01

Optical stochastic cooling (OSC) is expected to enable fast cooling of dense particle beams. Transition from microwave to optical frequencies enables an achievement of stochastic cooling rates which are orders of magnitude higher than ones achievable with the classical microwave based stochastic cooling systems. A subsystemcritical to the OSC scheme is the focusing optics used to image radiation from the upstream "pickup" undulator to the downstream "kicker" undulator. In this paper, we present simulation results using wave-optics calculation carried out with the SYNCHROTRON RADIATION WORKSHOP (SRW). Our simulations are performed in support to a proof-of-principle experiment planned at the Integrable Optics Test Accelerator (IOTA) at Fermilab. The calculations provide an estimate of the energy kick received by a 100-MeV electron as it propagates in the kicker undulator and interacts with the electromagnetic pulse it radiated at an earlier time while traveling through the pickup undulator.

Science with the space-based interferometer eLISA. II: gravitational waves from cosmological phase transitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caprini, Chiara, E-mail: chiara.caprini@cea.fr; Hindmarsh, Mark; Huber, Stephan

We investigate the potential for the eLISA space-based interferometer to detect the stochastic gravitational wave background produced by strong first-order cosmological phase transitions. We discuss the resulting contributions from bubble collisions, magnetohydrodynamic turbulence, and sound waves to the stochastic background, and estimate the total corresponding signal predicted in gravitational waves. The projected sensitivity of eLISA to cosmological phase transitions is computed in a model-independent way for various detector designs and configurations. By applying these results to several specific models, we demonstrate that eLISA is able to probe many well-motivated scenarios beyond the Standard Model of particle physics predicting strong first-ordermore » cosmological phase transitions in the early Universe.« less

Turbulence hierarchy in a random fibre laser

PubMed Central

González, Iván R. Roa; Lima, Bismarck C.; Pincheira, Pablo I. R.; Brum, Arthur A.; Macêdo, Antônio M. S.; Vasconcelos, Giovani L.; de S. Menezes, Leonardo; Raposo, Ernesto P.; Gomes, Anderson S. L.; Kashyap, Raman

2017-01-01

Turbulence is a challenging feature common to a wide range of complex phenomena. Random fibre lasers are a special class of lasers in which the feedback arises from multiple scattering in a one-dimensional disordered cavity-less medium. Here we report on statistical signatures of turbulence in the distribution of intensity fluctuations in a continuous-wave-pumped erbium-based random fibre laser, with random Bragg grating scatterers. The distribution of intensity fluctuations in an extensive data set exhibits three qualitatively distinct behaviours: a Gaussian regime below threshold, a mixture of two distributions with exponentially decaying tails near the threshold and a mixture of distributions with stretched-exponential tails above threshold. All distributions are well described by a hierarchical stochastic model that incorporates Kolmogorov’s theory of turbulence, which includes energy cascade and the intermittence phenomenon. Our findings have implications for explaining the remarkably challenging turbulent behaviour in photonics, using a random fibre laser as the experimental platform. PMID:28561064

Kinetic Monte Carlo simulations of travelling pulses and spiral waves in the lattice Lotka-Volterra model.

PubMed

Makeev, Alexei G; Kurkina, Elena S; Kevrekidis, Ioannis G

2012-06-01

Kinetic Monte Carlo simulations are used to study the stochastic two-species Lotka-Volterra model on a square lattice. For certain values of the model parameters, the system constitutes an excitable medium: travelling pulses and rotating spiral waves can be excited. Stable solitary pulses travel with constant (modulo stochastic fluctuations) shape and speed along a periodic lattice. The spiral waves observed persist sometimes for hundreds of rotations, but they are ultimately unstable and break-up (because of fluctuations and interactions between neighboring fronts) giving rise to complex dynamic behavior in which numerous small spiral waves rotate and interact with each other. It is interesting that travelling pulses and spiral waves can be exhibited by the model even for completely immobile species, due to the non-local reaction kinetics.

Stochastic Modeling and Generation of Partially Polarized or Partially Coherent Electromagnetic Waves

NASA Technical Reports Server (NTRS)

Davis, Brynmor; Kim, Edward; Piepmeier, Jeffrey; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.

Detecting the Stochastic Gravitational-Wave Background

NASA Astrophysics Data System (ADS)

Colacino, Carlo Nicola

2017-12-01

The stochastic gravitational-wave background (SGWB) is by far the most difficult source of gravitational radiation detect. At the same time, it is the most interesting and intriguing one. This book describes the initial detection of the SGWB and describes the underlying mathematics behind one of the most amazing discoveries of the 21st century. On the experimental side it would mean that interferometric gravitational wave detectors work even better than expected. On the observational side, such a detection could give us information about the very early Universe, information that could not be obtained otherwise. Even negative results and improved upper bounds could put constraints on many cosmological and particle physics models.

Surface plasmon enhanced cell microscopy with blocked random spatial activation

NASA Astrophysics Data System (ADS)

Son, Taehwang; Oh, Youngjin; Lee, Wonju; Yang, Heejin; Kim, Donghyun

2016-03-01

We present surface plasmon enhanced fluorescence microscopy with random spatial sampling using patterned block of silver nanoislands. Rigorous coupled wave analysis was performed to confirm near-field localization on nanoislands. Random nanoislands were fabricated in silver by temperature annealing. By analyzing random near-field distribution, average size of localized fields was found to be on the order of 135 nm. Randomly localized near-fields were used to spatially sample F-actin of J774 cells (mouse macrophage cell-line). Image deconvolution algorithm based on linear imaging theory was established for stochastic estimation of fluorescent molecular distribution. The alignment between near-field distribution and raw image was performed by the patterned block. The achieved resolution is dependent upon factors including the size of localized fields and estimated to be 100-150 nm.

Inner Core Anisotropy: Can Seismic Observations be Reconciled with Ab Initio Calculations of Elasticity?

NASA Astrophysics Data System (ADS)

Song, X.; Jordan, T. H.

2016-12-01

Body-wave and normal-mode observations have revealed an inner-core structure that is radially layered, axially anisotropic, and hemispherically asymmetric. Previous theoretical studies have examined the consistency of these features with the elasticity of iron crystals thought to dominate inner-core composition, but a fully consistent model has been elusive. Here we compare the seismic observation with effective-medium models derived from ab initio calculations of the elasticity tensors for hcp-Fe and bcc-Fe. Our estimates are based on Jordan's (GJI, 2015) effective medium theory, which is derived from a self-consistent, second-order Born approximation. The theory provides closed-form expressions for the effective elastic parameters of 3D anisotropic, heterogeneous media in which the local anisotropy is a constant hexagonal stiffness tensor C stochastically oriented about a constant symmetry axis \\hat{s} and the statistics of the small-scale heterogeneities are transversely isotropic in the plane perpendicular to \\hat{s}. The stochastic model is then described by a dimensionless "aspect ratio of the heterogeneity", 0 ≤ η < ∞, and a dimensionless "orientation ratio of the anisotropy", 0 ≤ ξ < ∞. The latter determines the degree to which the axis of C is aligned with \\hat{s}. We compute the loci of models with \\hat{s} oriented along the Earth's rotational axis ( \\hat{s} = north) by varying ξ and η for various ab initio estimates of C. We show that a lot of widely used estimates of C are inconsistent with most published normal-mode models of inner-core anisotropy. In particular, if the P-wave fast axis aligns with the rotational axis, which is required to satisfy the body-wave observations, then these hcp-Fe models predict that the fast polarization of the S waves is in the plane perpendicular to \\hat{s}, which disagrees with most normal-mode models. We have attempted to resolve this discrepancy by examining alternative hcp-Fe models, including radially anisotropic distributions of stochastic anisotropy and heterogeneity (i.e., where \\hat{s} = \\hat{r}), as well as bcc-Fe models. Our calculations constrain the form of C needed to satisfy the seismological inferences.

MmWave Vehicle-to-Infrastructure Communication :Analysis of Urban Microcellular Networks

DOT National Transportation Integrated Search

2017-05-01

Vehicle-to-infrastructure (V2I) communication may provide high data rates to vehicles via millimeterwave (mmWave) microcellular networks. This report uses stochastic geometry to analyze the coverage of urban mmWave microcellular networks. Prior work ...

Electron acceleration and radiation signatures in loop coronal transients

NASA Technical Reports Server (NTRS)

Vlahos, L.; Gergely, T. E.; Papadopoulos, K.

1982-01-01

It is proposed that in loop coronal transients an erupting loop moves away from the solar surface, with a velocity exceeding the local Alfven speed, pushing against the overlying magnetic fields and driving a shock in the front of the moving part of the loop. Lower hybrid waves are excited at the shock front and propagate radially toward the center of the loop with phase velocity along the magnetic field that exceeds the thermal velocity. The lower hybrid waves stochastically accelerate the tail of the electron distribution inside the loop. The manner in which the accelerated electrons are trapped in the moving loop are discussed, and their radiation signature is estimated. It is suggested that plasma radiation can explain the power observed in stationary and moving type IV bursts.

Ten reasons why a thermalized system cannot be described by a many-particle wave function

NASA Astrophysics Data System (ADS)

Drossel, Barbara

2017-05-01

It is widely believed that the underlying reality behind statistical mechanics is a deterministic and unitary time evolution of a many-particle wave function, even though this is in conflict with the irreversible, stochastic nature of statistical mechanics. The usual attempts to resolve this conflict for instance by appealing to decoherence or eigenstate thermalization are riddled with problems. This paper considers theoretical physics of thermalized systems as it is done in practice and shows that all approaches to thermalized systems presuppose in some form limits to linear superposition and deterministic time evolution. These considerations include, among others, the classical limit, extensivity, the concepts of entropy and equilibrium, and symmetry breaking in phase transitions and quantum measurement. As a conclusion, the paper suggests that the irreversibility and stochasticity of statistical mechanics should be taken as a real property of nature. It follows that a gas of a macroscopic number N of atoms in thermal equilibrium is best represented by a collection of N wave packets of a size of the order of the thermal de Broglie wave length, which behave quantum mechanically below this scale but classically sufficiently far beyond this scale. In particular, these wave packets must localize again after scattering events, which requires stochasticity and indicates a connection to the measurement process.

Near Source Structural Effects on Seismic Waves: Implication for Shear Motion Generation During SPE-4Prime

NASA Astrophysics Data System (ADS)

Pitarka, A.

2015-12-01

Arben Pitarka, Souheil M. Ezzedine, Oleg Y. Vorobiev, Tarabay H. Antoun, Lew A. Glenn, William R. Walter, Robert J. Mellors, and Evan Hirakawa. We have analyzed effects of wave scattering due to near-source structural complexity and sliding joint motion on generation of shear waves from SPE-4Pprime, a shallow chemical explosion conducted at the Nevada National Security Site. In addition to analyzing far-field ground motion recorded on three-component geophones, we performed high-frequency simulations of the explosion using a finite difference method and heterogeneous media with stochastic variability. The stochastic variations of seismic velocity were modeled using Gaussian correlation functions. Using simulations and recorded waveforms we demonstrate the implication of wave scattering on generation of shear motion, and show the gradual increase of shear motion energy as the waves propagate through media with variable scattering. The amplitude and duration of shear waves resulting from wave scattering are found to be dependent on the model complexity and to a lesser extent to source distance. Analysis of shear-motion generation due to joint motion were conducted using numerical simulations performed with GEODYN-L, a parallelized Lagrangian hydrocode, while a stochastic approach was used in depicting the properties of joints. Separated effects of source and wave scattering on shear motion generation will be shown through simulated motion. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 Release Number: LLNL-ABS-675570

Stochastic Optimization for Unit Commitment-A Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Qipeng P.; Wang, Jianhui; Liu, Andrew L.

2015-07-01

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC's birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and modeling approaches for deterministic UC, such as priority list, dynamic programming, and Lagrangian relaxation. With the high penetration of renewable energy, increasing deregulation of the electricity industry, and growing demands on system reliability, the next wave ismore » focused on transitioning from traditional deterministic approaches to stochastic optimization for unit commitment. Since the literature has grown rapidly in the past several years, this paper is to review the works that have contributed to the modeling and computational aspects of stochastic optimization (SO) based UC. Relevant lines of future research are also discussed to help transform research advances into real-world applications.« less

Two Optical Atmospheric Remote Sensing Techniques and AN Associated Analytic Solution to a Class of Integral Equations

NASA Astrophysics Data System (ADS)

Manning, Robert Michael

This work concerns itself with the analysis of two optical remote sensing methods to be used to obtain parameters of the turbulent atmosphere pertinent to stochastic electromagnetic wave propagation studies, and the well -posed solution to a class of integral equations that are central to the development of these remote sensing methods. A remote sensing technique is theoretically developed whereby the temporal frequency spectrum of the scintillations of a stellar source or a point source within the atmosphere, observed through a variable radius aperture, is related to the space-time spectrum of atmospheric scintillation. The key to this spectral remote sensing method is the spatial filtering performed by a finite aperture. The entire method is developed without resorting to a priori information such as results from stochastic wave propagation theory. Once the space-time spectrum of the scintillations is obtained, an application of known results of atmospheric wave propagation theory and simple geometric considerations are shown to yield such important information such as the spectrum of atmospheric turbulence, the cross-wind velocity, and the path profile of the atmospheric refractive index structure parameter. A method is also developed to independently verify the Taylor frozen flow hypothesis. The success of the spectral remote sensing method relies on the solution to a Fredholm integral equation of the first kind. An entire class of such equations, that are peculiar to inverse diffraction problems, is studied and a well-posed solution (in the sense of Hadamard) is obtained and probed. Conditions of applicability are derived and shown not to limit the useful operating range of the spectral remote sensing method. The general integral equation solution obtained is then applied to another remote sensing problem having to do with the characterization of the particle size distribution to atmospheric aerosols and hydrometeors. By measuring the diffraction pattern in the focal plane of a lens created by the passage of a laser beam through a distribution of particles, it is shown that the particle-size distribution of the particles can be obtained. An intermediate result of the analysis also gives the total volume concentration of the particles.

Constraining Modified Theories of Gravity with Gravitational-Wave Stochastic Backgrounds

NASA Astrophysics Data System (ADS)

Maselli, Andrea; Marassi, Stefania; Ferrari, Valeria; Kokkotas, Kostas; Schneider, Raffaella

2016-08-01

The direct discovery of gravitational waves has finally opened a new observational window on our Universe, suggesting that the population of coalescing binary black holes is larger than previously expected. These sources produce an unresolved background of gravitational waves, potentially observable by ground-based interferometers. In this Letter we investigate how modified theories of gravity, modeled using the parametrized post-Einsteinian formalism, affect the expected signal, and analyze the detectability of the resulting stochastic background by current and future ground-based interferometers. We find the constraints that Advanced LIGO would be able to set on modified theories, showing that they may significantly improve the current bounds obtained from astrophysical observations of binary pulsars.

Wave-Optics Modeling of the Optical-Transport Line for Passive Optical Stochastic Cooling

DOE PAGES

Andorf, M. B.; Lebedev, V. A.; Piot, P.; ...

2018-03-01

Optical stochastic cooling (OSC) is expected to enable fast cooling of dense particle beams. Transition from microwave to optical frequencies enables an achievement of stochastic cooling rates which are orders of magnitude higher than ones achievable with the classical microwave based stochastic cooling systems. A subsystemcritical to the OSC scheme is the focusing optics used to image radiation from the upstream “pickup” undulator to the downstream “kicker” undulator. In this paper, we present simulation results using wave-optics calculation carried out with the Synchrotron Radiation Workshop (SRW). Our simulations are performed in support to a proof-of-principle experiment planned at the Integrablemore » Optics Test Accelerator (IOTA) at Fermilab. The calculations provide an estimate of the energy kick received by a 100-MeV electron as it propagates in the kicker undulator and interacts with the electromagnetic pulse it radiated at an earlier time while traveling through the pickup undulator.« less

Perpendicular and Parallel Ion Stochastic Heating by Kinetic Alfvén Wave Turbulence in the Solar Wind

NASA Astrophysics Data System (ADS)

Hoppock, I. W.; Chandran, B. D. G.

2017-12-01

The dissipation of turbulence is a prime candidate to explain the heating of collisionless plasmas like the solar wind. We consider the heating of protons and alpha particles using test particle simulations with a broad spectrum of randomly phased kinetic Alfvén waves (KAWs). Previous research extensively simulated and analytically considered stochastic heating at low plasma beta for conditions similar to coronal holes and the near-sun solar wind. We verify the analytical models of proton and alpha particle heating rates, and extend these simulations to plasmas with beta of order unity like in the solar wind at 1 au. Furthermore, we consider cases with very large beta of order 100, relevant to other astrophysical plasmas. We explore the parameter dependency of the critical KAW amplitude that breaks the gyro-center approximation and leads to stochastic gyro-orbits of the particles. Our results suggest that stochastic heating by KAW turbulence is an efficient heating mechanisms for moderate to high beta plasmas.

Probing gravitational parity violation with gravitational waves from stellar-mass black hole binaries

NASA Astrophysics Data System (ADS)

Yagi, Kent; Yang, Huan

2018-05-01

The recent discovery of gravitational-wave events has offered us unique test beds of gravity in the strong and dynamical field regime. One possible modification to General Relativity is the gravitational parity violation that arises naturally from quantum gravity. Such parity violation gives rise to the so-called amplitude birefringence in gravitational waves, in which one of the circularly polarized modes is amplified while the other one is suppressed during their propagation. In this paper, we study how well one can measure gravitational parity violation via the amplitude birefringence effect of gravitational waves sourced by stellar-mass black hole binaries. We choose Chern-Simons gravity as an example and work within an effective field theory formalism to ensure that the approximate theory is well posed. We consider gravitational waves from both individual sources and stochastic gravitational-wave backgrounds. Regarding bounds from individual sources, we estimate such bounds using a Fisher analysis and carry out Monte Carlo simulations by randomly distributing sources over their sky location and binary orientation. We find that the bounds on the scalar field evolution in Chern-Simons gravity from the recently discovered gravitational-wave events are too weak to satisfy the weak Chern-Simons approximation, while aLIGO with its design sensitivity can place meaningful bounds. Regarding bounds from stochastic gravitational-wave backgrounds, we set the threshold signal-to-noise ratio for detection of the parity-violation mode as 5 and estimate projected bounds with future detectors assuming that signals are consistent with no parity violation. In an ideal situation in which all the source parameters and binary black hole merger-rate history are known a priori, we find that a network of two third-generation detectors is able to place bounds that are comparable to or slightly stronger than binary pulsar bounds. In a more realistic situation in which one does not have such information beforehand, approximate bounds can be derived if the regular parity-insensitive mode is detected and the peak redshift of the merger-rate history is known theoretically. Since gravitational-wave observations probe either the difference in parity violation between the source and the detector (with individual sources) or the line-of-sight cosmological integration of the scalar field (with gravitational-wave backgrounds), such bounds are complementary to local measurements from solar system experiments and binary pulsar observations.

Comparison of a Classical and Quantum Based Restricted Boltzmann Machine (RBM) for Application to Non-linear Multivariate Regression.

NASA Astrophysics Data System (ADS)

Dorband, J. E.; Tilak, N.; Radov, A.

2016-12-01

In this paper, a classical computer implementation of RBM is compared to a quantum annealing based RBM running on a D-Wave 2X (an adiabatic quantum computer). The codes for both are essentially identical. Only a flag is set to change the activation function from a classically computed logistic function to the D-Wave. To obtain greater understanding of the behavior of the D-Wave, a study of the stochastic properties of a virtual qubit (a 12 qubit chain) and a cell of qubits (an 8 qubit cell) was performed. We will present the results of comparing the D-Wave implementation with a theoretically errorless adiabatic quantum computer. The main purpose of this study is to develop a generic RBM regression tool in order to infer CO2 fluxes from the NASA satellite OCO-2 observed CO2 concentrations and predicted atmospheric states using regression models. The carbon fluxes will then be assimilated into a land surface model to predict the Net Ecosystem Exchange at globally distributed regional sites.

Detecting stochastic backgrounds of gravitational waves with pulsar timing arrays

NASA Astrophysics Data System (ADS)

Siemens, Xavier

2016-03-01

For the past decade the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has been using the Green Bank Telescope and the Arecibo Observatory to monitor millisecond pulsars. NANOGrav, along with two other international collaborations, the European Pulsar Timing Array and the Parkes Pulsar Timing Array in Australia, form a consortium of consortia: the International Pulsar Timing Array (IPTA). The goal of the IPTA is to directly detect low-frequency gravitational waves which cause small changes to the times of arrival of radio pulses from millisecond pulsars. In this talk I will discuss the work of NANOGrav and the IPTA, as well as our sensitivity to stochastic backgrounds of gravitational waves. I will show that a detection of the background produced by supermassive black hole binaries is possible by the end of the decade. Supported by the NANOGrav Physics Frontiers Center.

Two-Dimensional Vlasov Simulations of Fast Stochastic Electron Heating in Ionospheric Modification Experiments

NASA Astrophysics Data System (ADS)

Speirs, David Carruthers; Eliasson, Bengt; Daldorff, Lars K. S.

2017-10-01

Ionospheric heating experiments using high-frequency ordinary (O)-mode electromagnetic waves have shown the induced formation of magnetic field-aligned density striations in the ionospheric F region, in association with lower hybrid (LH) and upper hybrid (UH) turbulence. In recent experiments using high-power transmitters, the creation of new plasma regions and the formation of descending artificial ionospheric layers (DAILs) have been observed. These are attributed to suprathermal electrons ionizing the neutral gas, so that the O-mode reflection point and associated turbulence is moving to a progressively lower altitude. We present the results of two-dimensional (2-D) Vlasov simulations used to study the mode conversion of an O-mode pump wave to trapped UH waves in a small-scale density striation of circular cross section. Subsequent multiwave parametric decays lead to UH and LH turbulence and to the excitation of electron Bernstein (EB) waves. Large-amplitude EB waves result in rapid stochastic electron heating when the wave amplitude exceeds a threshold value. For typical experimental parameters, the electron temperature is observed to rise from 1,500 K to about 8,000 K in a fraction of a millisecond, much faster than Ohmic heating due to collisions which occurs on a timescale of an order of a second. This initial heating could then lead to further acceleration due to Langmuir turbulence near the critical layer. Stochastic electron heating therefore represents an important potential mechanism for the formation of DAILs.

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hong; Aziz, H M Abdul; Young, Stan

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less

Distributed parallel computing in stochastic modeling of groundwater systems.

PubMed

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

Capturing rogue waves by multi-point statistics

NASA Astrophysics Data System (ADS)

Hadjihosseini, A.; Wächter, Matthias; Hoffmann, N. P.; Peinke, J.

2016-01-01

As an example of a complex system with extreme events, we investigate ocean wave states exhibiting rogue waves. We present a statistical method of data analysis based on multi-point statistics which for the first time allows the grasping of extreme rogue wave events in a highly satisfactory statistical manner. The key to the success of the approach is mapping the complexity of multi-point data onto the statistics of hierarchically ordered height increments for different time scales, for which we can show that a stochastic cascade process with Markov properties is governed by a Fokker-Planck equation. Conditional probabilities as well as the Fokker-Planck equation itself can be estimated directly from the available observational data. With this stochastic description surrogate data sets can in turn be generated, which makes it possible to work out arbitrary statistical features of the complex sea state in general, and extreme rogue wave events in particular. The results also open up new perspectives for forecasting the occurrence probability of extreme rogue wave events, and even for forecasting the occurrence of individual rogue waves based on precursory dynamics.

Stochastic Geomorphology: A Framework for Creating General Principles on Erosion and Sedimentation in River Basins (Invited)

NASA Astrophysics Data System (ADS)

Benda, L. E.

2009-12-01

Stochastic geomorphology refers to the interaction of the stochastic field of sediment supply with hierarchically branching river networks where erosion, sediment flux and sediment storage are described by their probability densities. There are a number of general principles (hypotheses) that stem from this conceptual and numerical framework that may inform the science of erosion and sedimentation in river basins. Rainstorms and other perturbations, characterized by probability distributions of event frequency and magnitude, stochastically drive sediment influx to channel networks. The frequency-magnitude distribution of sediment supply that is typically skewed reflects strong interactions among climate, topography, vegetation, and geotechnical controls that vary between regions; the distribution varies systematically with basin area and the spatial pattern of erosion sources. Probability densities of sediment flux and storage evolve from more to less skewed forms downstream in river networks due to the convolution of the population of sediment sources in a watershed that should vary with climate, network patterns, topography, spatial scale, and degree of erosion asynchrony. The sediment flux and storage distributions are also transformed downstream due to diffusion, storage, interference, and attrition. In stochastic systems, the characteristically pulsed sediment supply and transport can create translational or stationary-diffusive valley and channel depositional landforms, the geometries of which are governed by sediment flux-network interactions. Episodic releases of sediment to the network can also drive a system memory reflected in a Hurst Effect in sediment yields and thus in sedimentological records. Similarly, discreet events of punctuated erosion on hillslopes can lead to altered surface and subsurface properties of a population of erosion source areas that can echo through time and affect subsequent erosion and sediment flux rates. Spatial patterns of probability densities have implications for the frequency and magnitude of sediment transport and storage and thus for the formation of alluvial and colluvial landforms throughout watersheds. For instance, the combination and interference of probability densities of sediment flux at confluences creates patterns of riverine heterogeneity, including standing waves of sediment with associated age distributions of deposits that can vary from younger to older depending on network geometry and position. Although the watershed world of probability densities is rarified and typically confined to research endeavors, it has real world implications for the day-to-day work on hillslopes and in fluvial systems, including measuring erosion, sediment transport, mapping channel morphology and aquatic habitats, interpreting deposit stratigraphy, conducting channel restoration, and applying environmental regulations. A question for the geomorphology community is whether the stochastic framework is useful for advancing our understanding of erosion and sedimentation and whether it should stimulate research to further develop, refine and test these and other principles. For example, a changing climate should lead to shifts in probability densities of erosion, sediment flux, storage, and associated habitats and thus provide a useful index of climate change in earth science forecast models.

A developmental basis for stochasticity in floral organ numbers

PubMed Central

Kitazawa, Miho S.; Fujimoto, Koichi

2014-01-01

Stochasticity ubiquitously inevitably appears at all levels from molecular traits to multicellular, morphological traits. Intrinsic stochasticity in biochemical reactions underlies the typical intercellular distributions of chemical concentrations, e.g., morphogen gradients, which can give rise to stochastic morphogenesis. While the universal statistics and mechanisms underlying the stochasticity at the biochemical level have been widely analyzed, those at the morphological level have not. Such morphological stochasticity is found in foral organ numbers. Although the floral organ number is a hallmark of floral species, it can distribute stochastically even within an individual plant. The probability distribution of the floral organ number within a population is usually asymmetric, i.e., it is more likely to increase rather than decrease from the modal value, or vice versa. We combined field observations, statistical analysis, and mathematical modeling to study the developmental basis of the variation in floral organ numbers among 50 species mainly from Ranunculaceae and several other families from core eudicots. We compared six hypothetical mechanisms and found that a modified error function reproduced much of the asymmetric variation found in eudicot floral organ numbers. The error function is derived from mathematical modeling of floral organ positioning, and its parameters represent measurable distances in the floral bud morphologies. The model predicts two developmental sources of the organ-number distributions: stochastic shifts in the expression boundaries of homeotic genes and a semi-concentric (whorled-type) organ arrangement. Other models species- or organ-specifically reproduced different types of distributions that reflect different developmental processes. The organ-number variation could be an indicator of stochasticity in organ fate determination and organ positioning. PMID:25404932

Disordered cellular automaton traffic flow model: phase separated state, density waves and self organized criticality

NASA Astrophysics Data System (ADS)

Fourrate, K.; Loulidi, M.

2006-01-01

We suggest a disordered traffic flow model that captures many features of traffic flow. It is an extension of the Nagel-Schreckenberg (NaSch) stochastic cellular automata for single line vehicular traffic model. It incorporates random acceleration and deceleration terms that may be greater than one unit. Our model leads under its intrinsic dynamics, for high values of braking probability pr, to a constant flow at intermediate densities without introducing any spatial inhomogeneities. For a system of fast drivers pr→0, the model exhibits a density wave behavior that was observed in car following models with optimal velocity. The gap of the disordered model we present exhibits, for high values of pr and random deceleration, at a critical density, a power law distribution which is a hall mark of a self organized criticality phenomena.

Complex earthquake rupture and local tsunamis

USGS Publications Warehouse

Geist, E.L.

2002-01-01

In contrast to far-field tsunami amplitudes that are fairly well predicted by the seismic moment of subduction zone earthquakes, there exists significant variation in the scaling of local tsunami amplitude with respect to seismic moment. From a global catalog of tsunami runup observations this variability is greatest for the most frequently occuring tsunamigenic subduction zone earthquakes in the magnitude range of 7 < Mw < 8.5. Variability in local tsunami runup scaling can be ascribed to tsunami source parameters that are independent of seismic moment: variations in the water depth in the source region, the combination of higher slip and lower shear modulus at shallow depth, and rupture complexity in the form of heterogeneous slip distribution patterns. The focus of this study is on the effect that rupture complexity has on the local tsunami wave field. A wide range of slip distribution patterns are generated using a stochastic, self-affine source model that is consistent with the falloff of far-field seismic displacement spectra at high frequencies. The synthetic slip distributions generated by the stochastic source model are discretized and the vertical displacement fields from point source elastic dislocation expressions are superimposed to compute the coseismic vertical displacement field. For shallow subduction zone earthquakes it is demonstrated that self-affine irregularities of the slip distribution result in significant variations in local tsunami amplitude. The effects of rupture complexity are less pronounced for earthquakes at greater depth or along faults with steep dip angles. For a test region along the Pacific coast of central Mexico, peak nearshore tsunami amplitude is calculated for a large number (N = 100) of synthetic slip distribution patterns, all with identical seismic moment (Mw = 8.1). Analysis of the results indicates that for earthquakes of a fixed location, geometry, and seismic moment, peak nearshore tsunami amplitude can vary by a factor of 3 or more. These results indicate that there is substantially more variation in the local tsunami wave field derived from the inherent complexity subduction zone earthquakes than predicted by a simple elastic dislocation model. Probabilistic methods that take into account variability in earthquake rupture processes are likely to yield more accurate assessments of tsunami hazards.

Delay-distribution-dependent H∞ state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.

PubMed

Sheng, Li; Wang, Zidong; Tian, Engang; Alsaadi, Fuad E

2016-12-01

This paper deals with the H ∞ state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying stochastic delay takes values on certain intervals with known probability distributions. The system measurement is transmitted through fading channels described by the Rice fading model. The aim of the addressed problem is to design a state estimator such that the estimation performance is guaranteed in the mean-square sense against admissible stochastic time-delays, stochastic noises as well as stochastic fading signals. By employing the stochastic analysis approach combined with the Kronecker product, several delay-distribution-dependent conditions are derived to ensure that the error dynamics of the neuron states is stochastically stable with prescribed H ∞ performance. Finally, a numerical example is provided to illustrate the effectiveness of the obtained results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic Theory of Relativistic Electrons Stochastic Heating by Whistler Mode Waves with Application to the Earth Magnetosphere

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Tel'nikhin, A. A.; Kronberg, T. K.

2007-01-01

In the Hamiltonian approach an electron motion in a coherent packet of the whistler mode waves propagating along the direction of an ambient magnetic field is studied. The physical processes by which these particles are accelerated to high energy are established. Equations governing a particle motion were transformed in to a closed pair of nonlinear difference equations. The solutions of these equations have shown there exists the energetic threshold below that the electron motion is regular, and when the initial energy is above the threshold an electron moves stochastically. Particle energy spectra and pitch angle electron scattering are described by the Fokker-Planck-Kolmogorov equations. Calculating the stochastic diffusion of electrons due to a spectrum of whistler modes is presented. The parametric dependence of the diffusion coefficients on the plasma particle density, magnitude of wave field, and the strength of magnetic field is studies. It is shown that significant pitch angle diffusion occurs for the Earth radiation belt electrons with energies from a few keV up to a few MeV.

GW170817: Implications for the Stochastic Gravitational-Wave Background from Compact Binary Coalescences

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Afrough, M.; Agarwal, B.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allen, G.; Allocca, A.; Altin, P. A.; Amato, A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Angelova, S. V.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Atallah, D. V.; Aufmuth, P.; Aulbert, C.; AultONeal, K.; Austin, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Bae, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Banagiri, S.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barkett, K.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bawaj, M.; Bayley, J. C.; Bazzan, M.; Bécsy, B.; Beer, C.; Bejger, M.; Belahcene, I.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Bero, J. J.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bode, N.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonilla, E.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bossie, K.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Bustillo, J. Calderón; Callister, T. A.; Calloni, E.; Camp, J. B.; Canepa, M.; Canizares, P.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Carney, M. F.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerdá-Durán, P.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chase, E.; Chassande-Mottin, E.; Chatterjee, D.; Cheeseboro, B. D.; Chen, H. Y.; Chen, X.; Chen, Y.; Cheng, H.-P.; Chia, H.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, A. K. W.; Chung, S.; Ciani, G.; Ciolfi, R.; Cirelli, C. E.; Cirone, A.; Clara, F.; Clark, J. A.; Clearwater, P.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Cohen, D.; Colla, A.; Collette, C. G.; Cominsky, L. R.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-Carrión, I.; Corley, K. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Dálya, G.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davis, D.; Daw, E. J.; Day, B.; De, S.; DeBra, D.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Demos, N.; Denker, T.; Dent, T.; De Pietri, R.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; De Rossi, C.; DeSalvo, R.; de Varona, O.; Devenson, J.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Dreissigacker, C.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dupej, P.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Estevez, D.; Etienne, Z. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fee, C.; Fehrmann, H.; Feicht, J.; Fejer, M. M.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Finstad, D.; Fiori, I.; Fiorucci, D.; Fishbach, M.; Fisher, R. P.; Fitz-Axen, M.; Flaminio, R.; Fletcher, M.; Fong, H.; Font, J. A.; Forsyth, P. W. F.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Ganija, M. R.; Gaonkar, S. G.; Garcia-Quiros, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, D.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; Goncharov, B.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Gretarsson, E. M.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Halim, O.; Hall, B. R.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hinderer, T.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hreibi, A.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kapadia, S. J.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. 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F.; Whittle, C.; Wilken, D.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wysocki, D. M.; Xiao, S.; Yamamoto, H.; Yancey, C. C.; Yang, L.; Yap, M. J.; Yazback, M.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2018-03-01

The LIGO Scientific and Virgo Collaborations have announced the event GW170817, the first detection of gravitational waves from the coalescence of two neutron stars. The merger rate of binary neutron stars estimated from this event suggests that distant, unresolvable binary neutron stars create a significant astrophysical stochastic gravitational-wave background. The binary neutron star component will add to the contribution from binary black holes, increasing the amplitude of the total astrophysical background relative to previous expectations. In the Advanced LIGO-Virgo frequency band most sensitive to stochastic backgrounds (near 25 Hz), we predict a total astrophysical background with amplitude ΩGW(f =25 Hz )=1. 8-1.3+2.7×10-9 with 90% confidence, compared with ΩGW(f =25 Hz )=1. 1-0.7+1.2×10-9 from binary black holes alone. Assuming the most probable rate for compact binary mergers, we find that the total background may be detectable with a signal-to-noise-ratio of 3 after 40 months of total observation time, based on the expected timeline for Advanced LIGO and Virgo to reach their design sensitivity.

GW150914: Implications for the Stochastic Gravitational-Wave Background from Binary Black Holes

NASA Astrophysics Data System (ADS)

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B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. 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I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J. L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2016-04-01

The LIGO detection of the gravitational wave transient GW150914, from the inspiral and merger of two black holes with masses ≳30 M⊙, suggests a population of binary black holes with relatively high mass. This observation implies that the stochastic gravitational-wave background from binary black holes, created from the incoherent superposition of all the merging binaries in the Universe, could be higher than previously expected. Using the properties of GW150914, we estimate the energy density of such a background from binary black holes. In the most sensitive part of the Advanced LIGO and Advanced Virgo band for stochastic backgrounds (near 25 Hz), we predict ΩGW(f =25 Hz )=1. 1-0.9+2.7×10-9 with 90% confidence. This prediction is robustly demonstrated for a variety of formation scenarios with different parameters. The differences between models are small compared to the statistical uncertainty arising from the currently poorly constrained local coalescence rate. We conclude that this background is potentially measurable by the Advanced LIGO and Advanced Virgo detectors operating at their projected final sensitivity.

GW150914: Implications for the Stochastic Gravitational-Wave Background from Binary Black Holes.

PubMed

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Miller, J; Millhouse, M; Minenkov, Y; Ming, J; Mirshekari, S; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moggi, A; Mohan, M; Mohapatra, S R P; Montani, M; Moore, B C; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mossavi, K; Mours, B; Mow-Lowry, C M; Mueller, C L; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Murphy, D J; Murray, P G; Mytidis, A; Nardecchia, I; Naticchioni, L; Nayak, R K; Necula, V; Nedkova, K; Nelemans, G; Neri, M; Neunzert, A; Newton, G; Nguyen, T T; Nielsen, A B; Nissanke, S; Nitz, A; Nocera, F; Nolting, D; Normandin, M E N; Nuttall, L K; Oberling, J; Ochsner, E; O'Dell, J; Oelker, E; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; O'Shaughnessy, R; Ottaway, D J; Ottens, R S; Overmier, H; Owen, B J; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Paris, H R; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patricelli, B; Patrick, Z; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perreca, A; Phelps, M; Piccinni, O; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pitkin, M; Poggiani, R; Popolizio, P; Post, A; Powell, J; Prasad, J; Predoi, V; Premachandra, S S; Prestegard, T; Price, L R; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Qin, J; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rakhmanov, M; Rapagnani, P; Raymond, V; Razzano, M; Re, V; Read, J; Reed, C M; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Rew, H; Reyes, S D; Ricci, F; Riles, K; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romanov, G; Romie, J H; Rosińska, D; Rowan, S; Rüdiger, A; Ruggi, P; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sanchez, E J; Sandberg, V; Sandeen, B; Sanders, J R; Sassolas, B; Sathyaprakash, B S; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Schilling, R; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schutz, B F; Scott, J; Scott, S M; Sellers, D; Sentenac, D; Sequino, V; Sergeev, A; Serna, G; Setyawati, Y; Sevigny, A; Shaddock, D A; Shah, S; Shahriar, M S; Shaltev, M; Shao, Z; Shapiro, B; Shawhan, P; Sheperd, A; Shoemaker, D H; Shoemaker, D M; Siellez, K; Siemens, X; Sigg, D; Silva, A D; Simakov, D; Singer, A; Singer, L P; Singh, A; Singh, R; Singhal, A; Sintes, A M; Slagmolen, B J J; Smith, J R; Smith, N D; Smith, R J E; Son, E J; Sorazu, B; Sorrentino, F; Souradeep, T; Srivastava, A K; Staley, A; Steinke, M; Steinlechner, J; Steinlechner, S; Steinmeyer, D; Stephens, B C; Stone, R; Strain, K A; Straniero, N; Stratta, G; Strauss, N A; Strigin, S; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, L; Sutton, P J; Swinkels, B L; Szczepańczyk, M J; Tacca, M; Talukder, D; Tanner, D B; Tápai, M; Tarabrin, S P; Taracchini, A; Taylor, R; Theeg, T; Thirugnanasambandam, M P; Thomas, E G; Thomas, M; Thomas, P; Thorne, K A; Thorne, K S; Thrane, E; Tiwari, S; Tiwari, V; Tokmakov, K V; Tomlinson, C; Tonelli, M; Torres, C V; Torrie, C I; Töyrä, D; Travasso, F; Traylor, G; Trifirò, D; Tringali, M C; Trozzo, L; Tse, M; Turconi, M; Tuyenbayev, D; Ugolini, D; Unnikrishnan, C S; Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Vass, S; Vasúth, M; Vaulin, R; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Verkindt, D; Vetrano, F; Viceré, A; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Voss, D; Vousden, W D; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, M; Wang, X; Wang, Y; Ward, R L; Warner, J; Was, M; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Welborn, T; Wen, L; Weßels, P; Westphal, T; Wette, K; Whelan, J T; White, D J; Whiting, B F; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Worden, J; Wright, J L; Wu, G; Yablon, J; Yam, W; Yamamoto, H; Yancey, C C; Yap, M J; Yu, H; Yvert, M; Zadrożny, A; Zangrando, L; Zanolin, M; Zendri, J-P; Zevin, M; Zhang, F; Zhang, L; Zhang, M; Zhang, Y; Zhao, C; Zhou, M; Zhou, Z; Zhu, X J; Zucker, M E; Zuraw, S E; Zweizig, J

2016-04-01

The LIGO detection of the gravitational wave transient GW150914, from the inspiral and merger of two black holes with masses ≳30M_{⊙}, suggests a population of binary black holes with relatively high mass. This observation implies that the stochastic gravitational-wave background from binary black holes, created from the incoherent superposition of all the merging binaries in the Universe, could be higher than previously expected. Using the properties of GW150914, we estimate the energy density of such a background from binary black holes. In the most sensitive part of the Advanced LIGO and Advanced Virgo band for stochastic backgrounds (near 25 Hz), we predict Ω_{GW}(f=25  Hz)=1.1_{-0.9}^{+2.7}×10^{-9} with 90% confidence. This prediction is robustly demonstrated for a variety of formation scenarios with different parameters. The differences between models are small compared to the statistical uncertainty arising from the currently poorly constrained local coalescence rate. We conclude that this background is potentially measurable by the Advanced LIGO and Advanced Virgo detectors operating at their projected final sensitivity.

A Stochastic Diffusion Process for the Dirichlet Distribution

DOE PAGES

Bakosi, J.; Ristorcelli, J. R.

2013-03-01

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability ofNcoupled stochastic variables with the Dirichlet distribution as its asymptotic solution. To ensure a bounded sample space, a coupled nonlinear diffusion process is required: the Wiener processes in the equivalent system of stochastic differential equations are multiplicative with coefficients dependent on all the stochastic variables. Individual samples of a discrete ensemble, obtained from the stochastic process, satisfy a unit-sum constraint at all times. The process may be used to represent realizations of a fluctuating ensemble ofNvariables subject to a conservation principle.more » Similar to the multivariate Wright-Fisher process, whose invariant is also Dirichlet, the univariate case yields a process whose invariant is the beta distribution. As a test of the results, Monte Carlo simulations are used to evolve numerical ensembles toward the invariant Dirichlet distribution.« less

Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes.

PubMed

Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V

2013-04-01

Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes

NASA Astrophysics Data System (ADS)

Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V.

2013-04-01

Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

Stochastic volatility models and Kelvin waves

NASA Astrophysics Data System (ADS)

Lipton, Alex; Sepp, Artur

2008-08-01

We use stochastic volatility models to describe the evolution of an asset price, its instantaneous volatility and its realized volatility. In particular, we concentrate on the Stein and Stein model (SSM) (1991) for the stochastic asset volatility and the Heston model (HM) (1993) for the stochastic asset variance. By construction, the volatility is not sign definite in SSM and is non-negative in HM. It is well known that both models produce closed-form expressions for the prices of vanilla option via the Lewis-Lipton formula. However, the numerical pricing of exotic options by means of the finite difference and Monte Carlo methods is much more complex for HM than for SSM. Until now, this complexity was considered to be an acceptable price to pay for ensuring that the asset volatility is non-negative. We argue that having negative stochastic volatility is a psychological rather than financial or mathematical problem, and advocate using SSM rather than HM in most applications. We extend SSM by adding volatility jumps and obtain a closed-form expression for the density of the asset price and its realized volatility. We also show that the current method of choice for solving pricing problems with stochastic volatility (via the affine ansatz for the Fourier-transformed density function) can be traced back to the Kelvin method designed in the 19th century for studying wave motion problems arising in fluid dynamics.

Identification and mitigation of narrow spectral artifacts that degrade searches for persistent gravitational waves in the first two observing runs of Advanced LIGO

NASA Astrophysics Data System (ADS)

Covas, P. B.; Effler, A.; Goetz, E.; Meyers, P. M.; Neunzert, A.; Oliver, M.; Pearlstone, B. L.; Roma, V. J.; Schofield, R. M. S.; Adya, V. B.; Astone, P.; Biscoveanu, S.; Callister, T. A.; Christensen, N.; Colla, A.; Coughlin, E.; Coughlin, M. W.; Crowder, S. G.; Dwyer, S. E.; Eggenstein, H.-B.; Hourihane, S.; Kandhasamy, S.; Liu, W.; Lundgren, A. P.; Matas, A.; McCarthy, R.; McIver, J.; Mendell, G.; Ormiston, R.; Palomba, C.; Papa, M. A.; Piccinni, O. J.; Rao, K.; Riles, K.; Sammut, L.; Schlassa, S.; Sigg, D.; Strauss, N.; Tao, D.; Thorne, K. A.; Thrane, E.; Trembath-Reichert, S.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Adams, C.; Adhikari, R. X.; Ananyeva, A.; Appert, S.; Arai, K.; Aston, S. M.; Austin, C.; Ballmer, S. W.; Barker, D.; Barr, B.; Barsotti, L.; Bartlett, J.; Bartos, I.; Batch, J. C.; Bejger, M.; Bell, A. S.; Betzwieser, J.; Billingsley, G.; Birch, J.; Biscans, S.; Biwer, C.; Blair, C. D.; Blair, R. M.; Bork, R.; Brooks, A. F.; Cao, H.; Ciani, G.; Clara, F.; Clearwater, P.; Cooper, S. J.; Corban, P.; Countryman, S. T.; Cowart, M. J.; Coyne, D. C.; Cumming, A.; Cunningham, L.; Danzmann, K.; Costa, C. F. Da Silva; Daw, E. J.; DeBra, D.; DeRosa, R. T.; DeSalvo, R.; Dooley, K. L.; Doravari, S.; Driggers, J. C.; Edo, T. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fair, H.; Galiana, A. Fernández; Ferreira, E. C.; Fisher, R. P.; Fong, H.; Frey, R.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gateley, B.; Giaime, J. A.; Giardina, K. D.; Goetz, R.; Goncharov, B.; Gras, S.; Gray, C.; Grote, H.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, E. D.; Hammond, G.; Hanks, J.; Hanson, J.; Hardwick, T.; Harry, G. M.; Heintze, M. C.; Heptonstall, A. W.; Hough, J.; Inta, R.; Izumi, K.; Jones, R.; Karki, S.; Kasprzack, M.; Kaufer, S.; Kawabe, K.; Kennedy, R.; Kijbunchoo, N.; Kim, W.; King, E. J.; King, P. J.; Kissel, J. S.; Korth, W. Z.; Kuehn, G.; Landry, M.; Lantz, B.; Laxen, M.; Liu, J.; Lockerbie, N. A.; Lormand, M.; MacInnis, M.; Macleod, D. M.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Marsh, P.; Martin, I. W.; Martynov, D. V.; Mason, K.; Massinger, T. J.; Matichard, F.; Mavalvala, N.; McClelland, D. E.; McCormick, S.; McCuller, L.; McIntyre, G.; McRae, T.; Merilh, E. L.; Miller, J.; Mittleman, R.; Mo, G.; Mogushi, K.; Moraru, D.; Moreno, G.; Mueller, G.; Mukund, N.; Mullavey, A.; Munch, J.; Nelson, T. J. N.; Nguyen, P.; Nuttall, L. K.; Oberling, J.; Oktavia, O.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ottaway, D. J.; Overmier, H.; Palamos, J. R.; Parker, W.; Pele, A.; Penn, S.; Perez, C. J.; Phelps, M.; Pierro, V.; Pinto, I.; Principe, M.; Prokhorov, L. G.; Puncken, O.; Quetschke, V.; Quintero, E. A.; Radkins, H.; Raffai, P.; Ramirez, K. E.; Reid, S.; Reitze, D. H.; Robertson, N. A.; Rollins, J. G.; Romel, C. L.; Romie, J. H.; Ross, M. P.; Rowan, S.; Ryan, K.; Sadecki, T.; Sanchez, E. J.; Sanchez, L. E.; Sandberg, V.; Savage, R. L.; Sellers, D.; Shaddock, D. A.; Shaffer, T. J.; Shapiro, B.; Shoemaker, D. H.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Sorazu, B.; Spencer, A. P.; Staley, A.; Strain, K. A.; Sun, L.; Tanner, D. B.; Tasson, J. D.; Taylor, R.; Thomas, M.; Thomas, P.; Toland, K.; Torrie, C. I.; Traylor, G.; Tse, M.; Tuyenbayev, D.; Vajente, G.; Valdes, G.; van Veggel, A. A.; Vecchio, A.; Veitch, P. J.; Venkateswara, K.; Vo, T.; Vorvick, C.; Wade, M.; Walker, M.; Ward, R. L.; Warner, J.; Weaver, B.; Weiss, R.; Weßels, P.; Willke, B.; Wipf, C. C.; Wofford, J.; Worden, J.; Yamamoto, H.; Yancey, C. C.; Yu, Hang; Yu, Haocun; Zhang, L.; Zhu, S.; Zucker, M. E.; Zweizig, J.; LSC Instrument Authors

2018-04-01

Searches are under way in Advanced LIGO and Virgo data for persistent gravitational waves from continuous sources, e.g. rapidly rotating galactic neutron stars, and stochastic sources, e.g. relic gravitational waves from the Big Bang or superposition of distant astrophysical events such as mergers of black holes or neutron stars. These searches can be degraded by the presence of narrow spectral artifacts (lines) due to instrumental or environmental disturbances. We describe a variety of methods used for finding, identifying and mitigating these artifacts, illustrated with particular examples. Results are provided in the form of lists of line artifacts that can safely be treated as non-astrophysical. Such lists are used to improve the efficiencies and sensitivities of continuous and stochastic gravitational wave searches by allowing vetoes of false outliers and permitting data cleaning.

Shallow velocity structure of Stromboli Volcano, Italy, derived from small-aperture array measurements of Strombolian tremor

USGS Publications Warehouse

Chouet, B.; De Luca, G.; Milana, G.; Dawson, P.; Martini, M.; Scarpa, R.

1998-01-01

The properties of the tremor wave field at Stromboli are analyzed using data from small-aperture arrays of short-period seismometers deployed on the north flank of the volcano. The seismometers are configued in two semi-circular arrays with radii of 60 and 150 m and a linear array with length of 600 m. The data are analyzed using a spatiotemporal correlation technique specifically designed for the study of the stationary stochastic wave field of Rayleigh and Love waves generated by volcanic activity and by scattering sources distributed within the island. The correlation coefficients derived as a function of frequency for the three components of motion clearly define the dispersion characteristics for both Rayleigh and Love waves. Love and Rayleigh waves contribute 70% and 30%, respectively, of the surface-wave power. The phase velocities of Rayleigh waves range from 1000 m/sec at 2 Hz to 350 m/sec at 9 Hz, and those for Love waves range from 700 to 400 m/sec over the same frequency band. These velocities are similar to those measured near Puu Oo on the east rift of Kilauea Volcano, Hawaii, although the dispersion characteristics of Rayleigh waves at Stromboli show a stronger dependence on frequency. Such low velocities are consistent with values expected for densely cracked solidified basalt. The dispersion curves are inverted for a velocity model beneath the arrays, assuming those dispersions represent the fundamental modes of Rayleigh and Love waves.

Surface drift prediction in the Adriatic Sea using hyper-ensemble statistics on atmospheric, ocean and wave models: Uncertainties and probability distribution areas

USGS Publications Warehouse

Rixen, M.; Ferreira-Coelho, E.; Signell, R.

2008-01-01

Despite numerous and regular improvements in underlying models, surface drift prediction in the ocean remains a challenging task because of our yet limited understanding of all processes involved. Hence, deterministic approaches to the problem are often limited by empirical assumptions on underlying physics. Multi-model hyper-ensemble forecasts, which exploit the power of an optimal local combination of available information including ocean, atmospheric and wave models, may show superior forecasting skills when compared to individual models because they allow for local correction and/or bias removal. In this work, we explore in greater detail the potential and limitations of the hyper-ensemble method in the Adriatic Sea, using a comprehensive surface drifter database. The performance of the hyper-ensembles and the individual models are discussed by analyzing associated uncertainties and probability distribution maps. Results suggest that the stochastic method may reduce position errors significantly for 12 to 72??h forecasts and hence compete with pure deterministic approaches. ?? 2007 NATO Undersea Research Centre (NURC).

Identification and chemical characterization of particulate matter from wave soldering processes at a printed circuit board manufacturing company.

PubMed

Szoboszlai, Z; Kertész, Zs; Szikszai, Z; Angyal, A; Furu, E; Török, Zs; Daróczi, L; Kiss, A Z

2012-02-15

In this case study, the elemental composition and mass size distribution of indoor aerosol particles were determined in a working environment where soldering of printed circuit boards (PCB) took place. Single particle analysis using ion and electron microscopy was carried out to obtain more detailed and reliable data about the origin of these particles. As a result, outdoor and indoor aerosol sources such as wave soldering, fluxing processes, workers' activity, mineral dust, biomass burning, fertilizing and other anthropogenic sources could be separated. With the help of scanning electron microscopy, characteristic particle types were identified. On the basis of the mass size distribution data, a stochastic lung deposition model was used to calculate the total and regional deposition efficiencies of the different types of particles within the human respiratory system. The information presented in this study aims to give insights into the detailed characteristics and the health impact of aerosol particles in a working environment where different kinds of soldering activity take place. Copyright © 2011 Elsevier B.V. All rights reserved.

Detection methods for stochastic gravitational-wave backgrounds: a unified treatment

NASA Astrophysics Data System (ADS)

Romano, Joseph D.; Cornish, Neil. J.

2017-04-01

We review detection methods that are currently in use or have been proposed to search for a stochastic background of gravitational radiation. We consider both Bayesian and frequentist searches using ground-based and space-based laser interferometers, spacecraft Doppler tracking, and pulsar timing arrays; and we allow for anisotropy, non-Gaussianity, and non-standard polarization states. Our focus is on relevant data analysis issues, and not on the particular astrophysical or early Universe sources that might give rise to such backgrounds. We provide a unified treatment of these searches at the level of detector response functions, detection sensitivity curves, and, more generally, at the level of the likelihood function, since the choice of signal and noise models and prior probability distributions are actually what define the search. Pedagogical examples are given whenever possible to compare and contrast different approaches. We have tried to make the article as self-contained and comprehensive as possible, targeting graduate students and new researchers looking to enter this field.

Interplanetary ions during an energetic storm particle event - The distribution function from solar wind thermal energies to 1.6 MeV

NASA Technical Reports Server (NTRS)

Gosling, J. T.; Asbridge, J. R.; Bame, S. J.; Feldman, W. C.; Zwickl, R. D.; Paschmann, G.; Sckopke, N.; Hynds, R. J.

1981-01-01

An ion velocity distribution function of the postshock phase of an energetic storm particle (ESP) event is obtained from data from the ISEE 2 and ISEE 3 experiments. The distribution function is roughly isotropic in the solar wind frame from solar wind thermal energies to 1.6 MeV. The ESP event studied (8/27/78) is superposed upon a more energetic particle event which was predominantly field-aligned and which was probably of solar origin. The observations suggest that the ESP population is accelerated directly out of the solar wind thermal population or its quiescent suprathermal tail by a stochastic process associated with shock wave disturbance. The acceleration mechanism is sufficiently efficient so that approximately 1% of the solar wind population is accelerated to suprathermal energies. These suprathermal particles have an energy density of approximately 290 eV cubic centimeters.

An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harlim, John, E-mail: jharlim@psu.edu; Mahdi, Adam, E-mail: amahdi@ncsu.edu; Majda, Andrew J., E-mail: jonjon@cims.nyu.edu

2014-01-15

A central issue in contemporary science is the development of nonlinear data driven statistical–dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partialmore » noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east–west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.« less

Quantal diffusion description of multinucleon transfers in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Ayik, S.; Yilmaz, B.; Yilmaz, O.; Umar, A. S.

2018-05-01

Employing the stochastic mean-field (SMF) approach, we develop a quantal diffusion description of the multi-nucleon transfer in heavy-ion collisions at finite impact parameters. The quantal transport coefficients are determined by the occupied single-particle wave functions of the time-dependent Hartree-Fock equations. As a result, the primary fragment mass and charge distribution functions are determined entirely in terms of the mean-field properties. This powerful description does not involve any adjustable parameter, includes the effects of shell structure, and is consistent with the fluctuation-dissipation theorem of the nonequilibrium statistical mechanics. As a first application of the approach, we analyze the fragment mass distribution in 48Ca+ 238U collisions at the center-of-mass energy Ec.m.=193 MeV and compare the calculations with the experimental data.

Dynamics of a stochastic cell-to-cell HIV-1 model with distributed delay

NASA Astrophysics Data System (ADS)

Ji, Chunyan; Liu, Qun; Jiang, Daqing

2018-02-01

In this paper, we consider a stochastic cell-to-cell HIV-1 model with distributed delay. Firstly, we show that there is a global positive solution of this model before exploring its long-time behavior. Then sufficient conditions for extinction of the disease are established. Moreover, we obtain sufficient conditions for the existence of an ergodic stationary distribution of the model by constructing a suitable stochastic Lyapunov function. The stationary distribution implies that the disease is persistent in the mean. Finally, we provide some numerical examples to illustrate theoretical results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krasnobaeva, L. A., E-mail: kla1983@mail.ru; Siberian State Medical University Moscowski Trakt 2, Tomsk, 634050; Shapovalov, A. V.

Within the formalism of the Fokker–Planck equation, the influence of nonstationary external force, random force, and dissipation effects on dynamics local conformational perturbations (kink) propagating along the DNA molecule is investigated. Such waves have an important role in the regulation of important biological processes in living systems at the molecular level. As a dynamic model of DNA was used a modified sine-Gordon equation, simulating the rotational oscillations of bases in one of the chains DNA. The equation of evolution of the kink momentum is obtained in the form of the stochastic differential equation in the Stratonovich sense within the frameworkmore » of the well-known McLaughlin and Scott energy approach. The corresponding Fokker–Planck equation for the momentum distribution function coincides with the equation describing the Ornstein–Uhlenbek process with a regular nonstationary external force. The influence of the nonlinear stochastic effects on the kink dynamics is considered with the help of the Fokker– Planck nonlinear equation with the shift coefficient dependent on the first moment of the kink momentum distribution function. Expressions are derived for average value and variance of the momentum. Examples are considered which demonstrate the influence of the external regular and random forces on the evolution of the average value and variance of the kink momentum. Within the formalism of the Fokker–Planck equation, the influence of nonstationary external force, random force, and dissipation effects on the kink dynamics is investigated in the sine–Gordon model. The equation of evolution of the kink momentum is obtained in the form of the stochastic differential equation in the Stratonovich sense within the framework of the well-known McLaughlin and Scott energy approach. The corresponding Fokker–Planck equation for the momentum distribution function coincides with the equation describing the Ornstein–Uhlenbek process with a regular nonstationary external force. The influence of the nonlinear stochastic effects on the kink dynamics is considered with the help of the Fokker–Planck nonlinear equation with the shift coefficient dependent on the first moment of the kink momentum distribution function. Expressions are derived for average value and variance of the momentum. Examples are considered which demonstrate the influence of the external regular and random forces on the evolution of the average value and variance of the kink momentum.« less

A theory of bimodal acceleration of pick up ions by compression solar wind turbulence under pressure balance

DOE PAGES

Zhang, Ming; Schlickeiser, Reinhard

2012-08-22

Recently, it was demonstrated that stochastic acceleration of particles going through a series of compressive plasma waves can be efficient and fast. It could be too fast so that the pressure built up by the accelerated particles may in turn modify the amplitude of waves to prevent the particles from having an exploding pressure. We call this condition pressure balance. In this paper, we take into account the fact that active acceleration of particles only occupies a limited volume of space due to a possible intermittent nature of plasma waves or turbulence. We also develop a bimodal acceleration theory thatmore » treats the populations of particles in the active and inactive acceleration regions separately and allows the two populations to exchange particles efficiently. We show that the system automatically produces a solution of v -5 steady state distribution for the accelerated particles, under the requirement of the pressure balance condition. It is found that the v -5 distribution is more robust and easier to achieve with a small volume of intense particle acceleration. These properties explain why the v -5 distribution is commonly observed in space. We apply our model to pickup ion propagation and acceleration throughout the entire heliosphere. These results can reproduce various observations in some great detail. We also found that this mechanism could be responsible for producing anomalous cosmic rays deep in the heliosheath.« less

Diversity waves in collapse-driven population dynamics

DOE PAGES

Maslov, Sergei; Sneppen, Kim

2015-09-14

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g.more » by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less

Diversity waves in collapse-driven population dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maslov, Sergei; Sneppen, Kim

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g.more » by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less

Acoustic receptivity and transition modeling of Tollmien-Schlichting disturbances induced by distributed surface roughness

NASA Astrophysics Data System (ADS)

Raposo, Henrique; Mughal, Shahid; Ashworth, Richard

2018-04-01

Acoustic receptivity to Tollmien-Schlichting waves in the presence of surface roughness is investigated for a flat plate boundary layer using the time-harmonic incompressible linearized Navier-Stokes equations. It is shown to be an accurate and efficient means of predicting receptivity amplitudes and, therefore, to be more suitable for parametric investigations than other approaches with direct-numerical-simulation-like accuracy. Comparison with the literature provides strong evidence of the correctness of the approach, including the ability to quantify non-parallel flow effects. These effects are found to be small for the efficiency function over a wide range of frequencies and local Reynolds numbers. In the presence of a two-dimensional wavy-wall, non-parallel flow effects are quite significant, producing both wavenumber detuning and an increase in maximum amplitude. However, a smaller influence is observed when considering an oblique Tollmien-Schlichting wave. This is explained by considering the non-parallel effects on receptivity and on linear growth which may, under certain conditions, cancel each other out. Ultimately, we undertake a Monte Carlo type uncertainty quantification analysis with two-dimensional distributed random roughness. Its power spectral density (PSD) is assumed to follow a power law with an associated uncertainty following a probabilistic Gaussian distribution. The effects of the acoustic frequency over the mean amplitude of the generated two-dimensional Tollmien-Schlichting waves are studied. A strong dependence on the mean PSD shape is observed and discussed according to the basic resonance mechanisms leading to receptivity. The growth of Tollmien-Schlichting waves is predicted with non-linear parabolized stability equations computations to assess the effects of stochasticity in transition location.

Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamadameen, Abdulqader Othman; Zainuddin, Zaitul Marlizawati

This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.

Stochastic particle instability for electron motion in combined helical wiggler, radiation, and longitudinal wave fields

NASA Astrophysics Data System (ADS)

Davidson, Ronald C.; McMullin, Wayne A.

1982-07-01

The relativistic motion of an electron is calculated in the combined fields of a transverse helical wiggler field (axial wavelength is λ0=2πk0) and the constant-amplitude, circularly polarized primary electromagnetic wave (δBT,ω,k) propagating in the z direction. For particle velocity near the beat-wave phase velocity ω(k+k0) of the primary wave, it is shown that the presence of a second, moderate-amplitude longitudinal wave (δÊL,ω,k) or transverse electromagnetic wave (δB2,ω2,k2) can lead to stochastic particle instability in which particles trapped near the separatrix of the primary wave undergo a systematic departure from the potential well. The condition for onset of instability is calculated, and the importance of these results for free-electron-laser (FEL) application is discussed. For development of long-pulse or steady-state free-electron lasers, the maintenance of beam integrity for an extended period of time will be of considerable practical importance. The fact that the presence of secondary, moderate-amplitude longitudinal or transverse electromagnetic waves can destroy coherent motion for certain classes of beam particles moving with velocity near ω(k+k0) may lead to a degradation of beam quality and concomitant modification of FEL emission properties.

New Astrometric Limits on the Stochastic Gravitational Wave Background

NASA Astrophysics Data System (ADS)

Darling, Jeremiah K.; Truebenbach, Alexandra; Paine, Jennie

2018-06-01

We present new limits on the low frequency (f < 10-8 Hz) stochastic gravitational wave background using correlated extragalactic proper motions. The familiar methods for gravitational wave detection are ground- and space-based laser interferometry, pulsar timing, and polarization of the cosmic microwave background. Astrometry offers an additional path to gravitational wave detection because gravitational waves deflect the light rays of extragalactic objects, creating apparent proper motions in a quadrupolar (and higher order modes) pattern. Astrometry is sensitive to gravitational waves with frequencies between roughly 10-18 Hz and 10-8 Hz (between H0 and 1/3 yr-1), which overlaps and bridges the pulsar timing and CMB polarization regimes. We present the methods and results of two complementary approaches to astrometric gravitational wave detection: (1) a small ~500-object radio interferometric sample with low per-source proper motion uncertainty but large intrinsic proper motions caused by radio jets, and (2) a thousand-fold larger sample with large per-source uncertainties that has small intrinsic proper motions (Gaia active galactic nuclei). Both approaches produce limits on ΩGW, the energy density of gravitational waves as a fraction of the cosmological critical energy density.The authors acknowledge support from the NSF grant AST-1411605 and the NASA grant 14-ATP14-0086.

Gravitational Waves Propagation through the Stochastic Background of Gravitational Waves

NASA Astrophysics Data System (ADS)

Frajuca, C.; Bortoli, F. S.; Nakamoto, F. Y.; Santos, G. A.

2018-02-01

With the recent claim that gravitational waves were finally detected and with other efforts around the world for GWs detection, its is reasonable to imagine that the relic gravitational wave background could be detected in some time in the future and with such information gather some hints about the origin of the universe. But, it’s also be considered that gravity has self-interaction, with such assumption it’s reasonable to expect that these gravitational wave will interact with the relic or nonrelic GW background by scattering, for example. Such interaction should decrease the distance which such propagating waves could be detected The propagation of gravitational waves (GWs) is analyzed in an asymptotically de Sitter space by the perturbation expansion around Minkowski space using a scalar component. Using the case of de Sitter inflationary phase scenario, the perturbation propagates through a FRW background. The GW, using the actual value for the Hubble scale (Ho), has a damping factor with a very small valor for the size of the observational universe; the stochastic relic GW background is given by a dimensionless function of the frequency. In this work we analyze this same damping including the gravitational wave background due to astrophysical sources such background is 3 orders of magnitude bigger in some frequencies and produces a higher damping factor.

Shocks, Rarefaction Waves, and Current Fluctuations for Anharmonic Chains

DOE PAGES

Mendl, Christian B.; Spohn, Herbert

2016-10-04

The nonequilibrium dynamics of anharmonic chains is studied by imposing an initial domain-wall state, in which the two half lattices are prepared in equilibrium with distinct parameters. Here, we analyse the Riemann problem for the corresponding Euler equations and, in specific cases, compare with molecular dynamics. Additionally, the fluctuations of time-integrated currents are investigated. In analogy with the KPZ equation, their typical fluctuations should be of size t 1/3 and have a Tracy–Widom GUE distributed amplitude. The proper extension to anharmonic chains is explained and tested through molecular dynamics. Our results are calibrated against the stochastic LeRoux lattice gas.

Matter-wave dark solitons: stochastic versus analytical results.

PubMed

Cockburn, S P; Nistazakis, H E; Horikis, T P; Kevrekidis, P G; Proukakis, N P; Frantzeskakis, D J

2010-04-30

The dynamics of dark matter-wave solitons in elongated atomic condensates are discussed at finite temperatures. Simulations with the stochastic Gross-Pitaevskii equation reveal a noticeable, experimentally observable spread in individual soliton trajectories, attributed to inherent fluctuations in both phase and density of the underlying medium. Averaging over a number of such trajectories (as done in experiments) washes out such background fluctuations, revealing a well-defined temperature-dependent temporal growth in the oscillation amplitude. The average soliton dynamics is well captured by the simpler dissipative Gross-Pitaevskii equation, both numerically and via an analytically derived equation for the soliton center based on perturbation theory for dark solitons.

Interaction of electromagnetic and acoustic waves in a stochastic atmosphere

NASA Technical Reports Server (NTRS)

Bhatnagar, N.; Frankel, M. S.; Peterson, A. M.

1977-01-01

This paper considers the interaction of electromagnetic and acoustic waves where a Radio Acoustic Sounding System (RASS) is operated in a stochastic environment characterized by turbulence, winds and mean-temperature gradients. It has been shown that for a RASS operating at acoustic frequencies below a few kilohertz propagating under typical atmospheric conditions, turbulence has little effect on the strength of the received radio signal scattered from the pulse at heights up to a few kilometers. This result implies that the received RF signal level (power) is primarily a function of sound intensity which decreases as x exp minus 2 where x is the altitude.

Digging Deeper: Observing Primordial Gravitational Waves below the Binary-Black-Hole-Produced Stochastic Background.

PubMed

Regimbau, T; Evans, M; Christensen, N; Katsavounidis, E; Sathyaprakash, B; Vitale, S

2017-04-14

The merger rate of black hole binaries inferred from the detections in the first Advanced LIGO science run implies that a stochastic background produced by a cosmological population of mergers will likely mask the primordial gravitational wave background. Here we demonstrate that the next generation of ground-based detectors, such as the Einstein Telescope and Cosmic Explorer, will be able to observe binary black hole mergers throughout the Universe with sufficient efficiency that the confusion background can potentially be subtracted to observe the primordial background at the level of Ω_{GW}≃10^{-13} after 5 years of observation.

What can we learn from the stochastic gravitational wave background produced by oscillons?

NASA Astrophysics Data System (ADS)

Antusch, Stefan; Cefalà, Francesco; Orani, Stefano

2018-03-01

The stochastic gravitational wave (GW) background provides a fascinating window to the physics of the very early universe. Beyond the nearly scale-invariant primordial GW spectrum produced during inflation, a spectrum with a much richer structure is typically generated during the preheating phase after inflation (or after some other phase transition at lower energies). This raises the question of what one can learn from a future observation of the stochastic gravitational wave background spectrum about the underlying physics during preheating. Recently, it has been shown that during preheating non-perturbative quasi-stable objects like oscillons can act as strong sources for GW, leading to characteristic features such as distinct peaks in the spectrum. In this paper, we study the GW production from oscillons using semi-analytical techniques. In particular, we discuss how the GW spectrum is affected by the parameters that characterise a given oscillon system, e.g. by the background cosmology, the asymmetry of the oscillons and the evolution of the number density of the oscillons. We compare our semi-analytic results with numerical lattice simulations for a hilltop inflation model and a KKLT scenario, which differ strongly in some of these characteristics, and find very good agreement.

GW170817: Implications for the Stochastic Gravitational-Wave Background from Compact Binary Coalescences.

PubMed

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Cavalier, F; Cavalieri, R; Cella, G; Cepeda, C B; Cerdá-Durán, P; Cerretani, G; Cesarini, E; Chamberlin, S J; Chan, M; Chao, S; Charlton, P; Chase, E; Chassande-Mottin, E; Chatterjee, D; Cheeseboro, B D; Chen, H Y; Chen, X; Chen, Y; Cheng, H-P; Chia, H; Chincarini, A; Chiummo, A; Chmiel, T; Cho, H S; Cho, M; Chow, J H; Christensen, N; Chu, Q; Chua, A J K; Chua, S; Chung, A K W; Chung, S; Ciani, G; Ciolfi, R; Cirelli, C E; Cirone, A; Clara, F; Clark, J A; Clearwater, P; Cleva, F; Cocchieri, C; Coccia, E; Cohadon, P-F; Cohen, D; Colla, A; Collette, C G; Cominsky, L R; Constancio, M; Conti, L; Cooper, S J; Corban, P; Corbitt, T R; Cordero-Carrión, I; Corley, K R; Cornish, N; Corsi, A; Cortese, S; Costa, C A; Coughlin, M W; Coughlin, S B; Coulon, J-P; Countryman, S T; Couvares, P; Covas, P B; Cowan, E E; Coward, D M; Cowart, M J; Coyne, D C; Coyne, R; Creighton, J D E; Creighton, T D; Cripe, J; Crowder, S G; Cullen, T J; Cumming, A; Cunningham, L; Cuoco, E; Dal Canton, T; Dálya, G; Danilishin, S L; 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London, L T; Lord, J E; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J D; Lousto, C O; Lovelace, G; Lück, H; Lumaca, D; Lundgren, A P; Lynch, R; Ma, Y; Macas, R; Macfoy, S; Machenschalk, B; MacInnis, M; Macleod, D M; Magaña Hernandez, I; Magaña-Sandoval, F; Magaña Zertuche, L; Magee, R M; Majorana, E; Maksimovic, I; Man, N; Mandic, V; Mangano, V; Mansell, G L; Manske, M; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markakis, C; Markosyan, A S; Markowitz, A; Maros, E; Marquina, A; Martelli, F; Martellini, L; Martin, I W; Martin, R M; Martynov, D V; Mason, K; Massera, E; Masserot, A; Massinger, T J; Masso-Reid, M; Mastrogiovanni, S; Matas, A; Matichard, F; Matone, L; Mavalvala, N; Mazumder, N; McCarthy, R; McClelland, D E; McCormick, S; McCuller, L; McGuire, S C; McIntyre, G; McIver, J; McManus, D J; McNeill, L; McRae, T; McWilliams, S T; Meacher, D; Meadors, G D; Mehmet, M; Meidam, J; Mejuto-Villa, E; Melatos, A; Mendell, G; Mercer, R A; Merilh, E L; Merzougui, M; Meshkov, S; Messenger, C; Messick, C; Metzdorff, R; Meyers, P M; Miao, H; Michel, C; Middleton, H; Mikhailov, E E; Milano, L; Miller, A L; Miller, B B; Miller, J; Millhouse, M; Milovich-Goff, M C; Minazzoli, O; Minenkov, Y; Ming, J; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moffa, D; Moggi, A; Mogushi, K; Mohan, M; Mohapatra, S R P; Montani, M; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mours, B; Mow-Lowry, C M; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Muñiz, E A; Muratore, M; Murray, P G; Napier, K; Nardecchia, I; Naticchioni, L; Nayak, R K; Neilson, J; Nelemans, G; Nelson, T J N; Nery, M; Neunzert, A; Nevin, L; Newport, J M; Newton, G; Ng, K K Y; Nguyen, T T; Nichols, D; Nielsen, A B; Nissanke, S; Nitz, A; Noack, A; Nocera, F; Nolting, D; North, C; Nuttall, L K; Oberling, J; O'Dea, G D; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Okada, M A; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; Ormiston, R; Ortega, L F; O'Shaughnessy, R; Ossokine, S; Ottaway, D J; Overmier, H; Owen, B J; Pace, A E; Page, J; Page, M A; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, Howard; Pan, Huang-Wei; Pang, B; Pang, P T H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Parida, A; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patil, M; Patricelli, B; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perez, C J; Perreca, A; Perri, L M; Pfeiffer, H P; Phelps, M; Piccinni, O J; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pirello, M; Pitkin, M; Poe, M; Poggiani, R; Popolizio, P; Porter, E K; Post, A; Powell, J; Prasad, J; Pratt, J W W; Pratten, G; Predoi, V; Prestegard, T; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L G; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rajan, C; Rajbhandari, B; Rakhmanov, M; Ramirez, K E; Ramos-Buades, A; Rapagnani, P; Raymond, V; Razzano, M; Read, J; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Ren, W; Reyes, S D; Ricci, F; Ricker, P M; Rieger, S; Riles, K; Rizzo, M; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romel, C L; Romie, J H; Rosińska, D; Ross, M P; Rowan, S; Rüdiger, A; Ruggi, P; Rutins, G; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Sakellariadou, M; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sampson, L M; Sanchez, E J; Sanchez, L E; Sanchis-Gual, N; Sandberg, V; Sanders, J R; Sassolas, B; Sathyaprakash, B S; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Scheel, M; Scheuer, J; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schulte, B W; Schutz, B F; Schwalbe, S G; Scott, J; Scott, S M; Seidel, E; Sellers, D; Sengupta, A S; Sentenac, D; Sequino, V; Sergeev, A; Shaddock, D A; Shaffer, T J; Shah, A A; Shahriar, M S; Shaner, M B; Shao, L; Shapiro, B; Shawhan, P; Sheperd, A; Shoemaker, D H; Shoemaker, D M; Siellez, K; Siemens, X; Sieniawska, M; Sigg, D; Silva, A D; Singer, L P; Singh, A; Singhal, A; Sintes, A M; Slagmolen, B J J; Smith, B; Smith, J R; Smith, R J E; Somala, S; Son, E J; Sonnenberg, J A; Sorazu, B; Sorrentino, F; Souradeep, T; Spencer, A P; Srivastava, A K; Staats, K; Staley, A; Steinke, M; Steinlechner, J; Steinlechner, S; Steinmeyer, D; Stevenson, S P; Stone, R; Stops, D J; Strain, K A; Stratta, G; Strigin, S E; Strunk, A; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, L; Sunil, S; Suresh, J; Sutton, P J; Swinkels, B L; Szczepańczyk, M J; Tacca, M; Tait, S C; Talbot, C; Talukder, D; Tanner, D B; Tápai, M; Taracchini, A; Tasson, J D; Taylor, J A; Taylor, R; Tewari, S V; Theeg, T; Thies, F; Thomas, E G; Thomas, M; Thomas, P; Thorne, K A; Thrane, E; Tiwari, S; Tiwari, V; Tokmakov, K V; Toland, K; Tonelli, M; Tornasi, Z; Torres-Forné, A; Torrie, C I; Töyrä, D; Travasso, F; Traylor, G; Trinastic, J; Tringali, M C; Trozzo, L; Tsang, K W; Tse, M; Tso, R; Tsukada, L; Tsuna, D; Tuyenbayev, D; Ueno, K; Ugolini, D; Unnikrishnan, C S; Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Varma, V; Vass, S; Vasúth, M; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Venugopalan, G; Verkindt, D; Vetrano, F; Viceré, A; Viets, A D; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walet, R; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, J Z; Wang, W H; Wang, Y F; Ward, R L; Warner, J; Was, M; Watchi, J; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Wessel, E K; Weßels, P; Westerweck, J; Westphal, T; Wette, K; Whelan, J T; Whiting, B F; Whittle, C; Wilken, D; Williams, D; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Woehler, J; Wofford, J; Wong, K W K; Worden, J; Wright, J L; Wu, D S; Wysocki, D M; Xiao, S; Yamamoto, H; Yancey, C C; Yang, L; Yap, M J; Yazback, M; Yu, Hang; Yu, Haocun; Yvert, M; Zadrożny, A; Zanolin, M; Zelenova, T; Zendri, J-P; Zevin, M; Zhang, L; Zhang, M; Zhang, T; Zhang, Y-H; Zhao, C; Zhou, M; Zhou, Z; Zhu, S J; Zhu, X J; Zucker, M E; Zweizig, J

2018-03-02

The LIGO Scientific and Virgo Collaborations have announced the event GW170817, the first detection of gravitational waves from the coalescence of two neutron stars. The merger rate of binary neutron stars estimated from this event suggests that distant, unresolvable binary neutron stars create a significant astrophysical stochastic gravitational-wave background. The binary neutron star component will add to the contribution from binary black holes, increasing the amplitude of the total astrophysical background relative to previous expectations. In the Advanced LIGO-Virgo frequency band most sensitive to stochastic backgrounds (near 25 Hz), we predict a total astrophysical background with amplitude Ω_{GW}(f=25  Hz)=1.8_{-1.3}^{+2.7}×10^{-9} with 90% confidence, compared with Ω_{GW}(f=25  Hz)=1.1_{-0.7}^{+1.2}×10^{-9} from binary black holes alone. Assuming the most probable rate for compact binary mergers, we find that the total background may be detectable with a signal-to-noise-ratio of 3 after 40 months of total observation time, based on the expected timeline for Advanced LIGO and Virgo to reach their design sensitivity.

Stochastic characteristics of different duration annual maximum rainfall and its spatial difference in China based on information entropy

NASA Astrophysics Data System (ADS)

Li, X.; Sang, Y. F.

2017-12-01

Mountain torrents, urban floods and other disasters caused by extreme precipitation bring great losses to the ecological environment, social and economic development, people's lives and property security. So there is of great significance to floods prevention and control by the study of its spatial distribution. Based on the annual maximum rainfall data of 60min, 6h and 24h, the paper generate long sequences following Pearson-III distribution, and then use the information entropy index to study the spatial distribution and difference of different duration. The results show that the information entropy value of annual maximum rainfall in the south region is greater than that in the north region, indicating more obvious stochastic characteristics of annual maximum rainfall in the latter. However, the spatial distribution of stochastic characteristics is different in different duration. For example, stochastic characteristics of 60min annual maximum rainfall in the Eastern Tibet is smaller than surrounding, but 6h and 24h annual maximum rainfall is larger than surrounding area. In the Haihe River Basin and the Huaihe River Basin, the stochastic characteristics of the 60min annual maximum rainfall was not significantly different from that in the surrounding area, and stochastic characteristics of 6h and 24h was smaller than that in the surrounding area. We conclude that the spatial distribution of information entropy values of annual maximum rainfall in different duration can reflect the spatial distribution of its stochastic characteristics, thus the results can be an importantly scientific basis for the flood prevention and control, agriculture, economic-social developments and urban flood control and waterlogging.

Turbulent mixing noise from supersonic jets

NASA Technical Reports Server (NTRS)

Tam, Christopher K. W.; Chen, Ping

1994-01-01

There is now a substantial body of theoretical and experimental evidence that the dominant part of the turbulent noise of supersonic jets is generated directly by the large turbulence structures/instability waves of the jet flow. Earlier, Tam and Burton provided a description of the physical mechanism by which supersonically traveling instability waves can generate sound efficiently. They used the method of matched asymptotic expansions to construct an instability wave solution which is valid in the far field. The present work is an extension of the theory of Tam and Burton. It is argued that the instability wave spectrum of the jet may be regarded as generated by stochastic white noise excitation at the nozzle lip region. The reason why the excitation has white noise characteristics is that near the nozzle lip region the flow in the jet mixing layer has no intrinsic length and time scales. The present stochastic wave model theory of supersonic jet noise contains a single unknown multiplicative constant. Comparisons between the calculated noise directivities at selected Strouhal numbers and experimental measurements of a Mach 2 jet at different jet temperatures have been carried out. Favorable agreements are found.

Waves of actin and microtubule polymerization drive microtubule-based transport and neurite growth before single axon formation

PubMed Central

Winans, Amy M; Collins, Sean R; Meyer, Tobias

2016-01-01

Many developing neurons transition through a multi-polar state with many competing neurites before assuming a unipolar state with one axon and multiple dendrites. Hallmarks of the multi-polar state are large fluctuations in microtubule-based transport into and outgrowth of different neurites, although what drives these fluctuations remains elusive. We show that actin waves, which stochastically migrate from the cell body towards neurite tips, direct microtubule-based transport during the multi-polar state. Our data argue for a mechanical control system whereby actin waves transiently widen the neurite shaft to allow increased microtubule polymerization to direct Kinesin-based transport and create bursts of neurite extension. Actin waves also require microtubule polymerization, arguing that positive feedback links these two components. We propose that actin waves create large stochastic fluctuations in microtubule-based transport and neurite outgrowth, promoting competition between neurites as they explore the environment until sufficient external cues can direct one to become the axon. DOI: http://dx.doi.org/10.7554/eLife.12387.001 PMID:26836307

Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

PubMed

Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

2016-08-01

In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

The NANOGrav Nine-Year Data Set: Limits on the Isotropic Stochastic Gravitational Wave Background

NASA Technical Reports Server (NTRS)

Arzoumanian, Z.; Brazier, A.; Burke-Spolaor, S.; Chamberlin, S. J.; Chatterjee, S.; Christy, B.; Cordes, J. M.; Cornish, N. J.; Crowter, K.; Demorest, P. B.;

Variation of Time Domain Failure Probabilities of Jack-up with Wave Return Periods

NASA Astrophysics Data System (ADS)

Idris, Ahmad; Harahap, Indra S. H.; Ali, Montassir Osman Ahmed

2018-04-01

This study evaluated failure probabilities of jack up units on the framework of time dependent reliability analysis using uncertainty from different sea states representing different return period of the design wave. Surface elevation for each sea state was represented by Karhunen-Loeve expansion method using the eigenfunctions of prolate spheroidal wave functions in order to obtain the wave load. The stochastic wave load was propagated on a simplified jack up model developed in commercial software to obtain the structural response due to the wave loading. Analysis of the stochastic response to determine the failure probability in excessive deck displacement in the framework of time dependent reliability analysis was performed by developing Matlab codes in a personal computer. Results from the study indicated that the failure probability increases with increase in the severity of the sea state representing a longer return period. Although the results obtained are in agreement with the results of a study of similar jack up model using time independent method at higher values of maximum allowable deck displacement, it is in contrast at lower values of the criteria where the study reported that failure probability decreases with increase in the severity of the sea state.

New window into stochastic gravitational wave background.

PubMed

Rotti, Aditya; Souradeep, Tarun

2012-11-30

A stochastic gravitational wave background (SGWB) would gravitationally lens the cosmic microwave background (CMB) photons. We correct the results provided in existing literature for modifications to the CMB polarization power spectra due to lensing by gravitational waves. Weak lensing by gravitational waves distorts all four CMB power spectra; however, its effect is most striking in the mixing of power between the E mode and B mode of CMB polarization. This suggests the possibility of using measurements of the CMB angular power spectra to constrain the energy density (Ω(GW)) of the SGWB. Using current data sets (QUAD, WMAP, and ACT), we find that the most stringent constraints on the present Ω(GW) come from measurements of the angular power spectra of CMB temperature anisotropies. In the near future, more stringent bounds on Ω(GW) can be expected with improved upper limits on the B modes of CMB polarization. Any detection of B modes of CMB polarization above the expected signal from large scale structure lensing could be a signal for a SGWB.

Measurement and subtraction of Schumann resonances at gravitational-wave interferometers

NASA Astrophysics Data System (ADS)

Coughlin, Michael W.; Cirone, Alessio; Meyers, Patrick; Atsuta, Sho; Boschi, Valerio; Chincarini, Andrea; Christensen, Nelson L.; De Rosa, Rosario; Effler, Anamaria; Fiori, Irene; Gołkowski, Mark; Guidry, Melissa; Harms, Jan; Hayama, Kazuhiro; Kataoka, Yuu; Kubisz, Jerzy; Kulak, Andrzej; Laxen, Michael; Matas, Andrew; Mlynarczyk, Janusz; Ogawa, Tsutomu; Paoletti, Federico; Salvador, Jacobo; Schofield, Robert; Somiya, Kentaro; Thrane, Eric

2018-05-01

Correlated magnetic noise from Schumann resonances threatens to contaminate the observation of a stochastic gravitational-wave background in interferometric detectors. In previous work, we reported on the first effort to eliminate global correlated noise from the Schumann resonances using Wiener filtering, demonstrating as much as a factor of two reduction in the coherence between magnetometers on different continents. In this work, we present results from dedicated magnetometer measurements at the Virgo and KAGRA sites, which are the first results for subtraction using data from gravitational-wave detector sites. We compare these measurements to a growing network of permanent magnetometer stations, including at the LIGO sites. We show the effect of mutual magnetometer attraction, arguing that magnetometers should be placed at least one meter from one another. In addition, for the first time, we show how dedicated measurements by magnetometers near to the interferometers can reduce coherence to a level consistent with uncorrelated noise, making a potential detection of a stochastic gravitational-wave background possible.

Dynamics of a stochastic HIV-1 infection model with logistic growth

NASA Astrophysics Data System (ADS)

Jiang, Daqing; Liu, Qun; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed; Xia, Peiyan

2017-03-01

This paper is concerned with a stochastic HIV-1 infection model with logistic growth. Firstly, by constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of ergodic stationary distribution of the solution to the HIV-1 infection model. Then we obtain sufficient conditions for extinction of the infection. The stationary distribution shows that the infection can become persistent in vivo.

Hydrodynamics of the Polyakov line in SU(N c) Yang-Mills

DOE PAGES

Liu, Yizhuang; Warchoł, Piotr; Zahed, Ismail

2015-12-08

We discuss a hydrodynamical description of the eigenvalues of the Polyakov line at large but finite N c for Yang-Mills theory in even and odd space-time dimensions. The hydro-static solutions for the eigenvalue densities are shown to interpolate between a uniform distribution in the confined phase and a localized distribution in the de-confined phase. The resulting critical temperatures are in overall agreement with those measured on the lattice over a broad range of N c, and are consistent with the string model results at N c = ∞. The stochastic relaxation of the eigenvalues of the Polyakov line out ofmore » equilibrium is captured by a hydrodynamical instanton. An estimate of the probability of formation of a Z(N c)bubble using a piece-wise sound wave is suggested.« less

Stochastic simulation for the propagation of high-frequency acoustic waves through a random velocity field

NASA Astrophysics Data System (ADS)

Lu, B.; Darmon, M.; Leymarie, N.; Chatillon, S.; Potel, C.

2012-05-01

In-service inspection of Sodium-Cooled Fast Reactors (SFR) requires the development of non-destructive techniques adapted to the harsh environment conditions and the examination complexity. From past experiences, ultrasonic techniques are considered as suitable candidates. The ultrasonic telemetry is a technique used to constantly insure the safe functioning of reactor inner components by determining their exact position: it consists in measuring the time of flight of the ultrasonic response obtained after propagation of a pulse emitted by a transducer and its interaction with the targets. While in-service the sodium flow creates turbulences that lead to temperature inhomogeneities, which translates into ultrasonic velocity inhomogeneities. These velocity variations could directly impact the accuracy of the target locating by introducing time of flight variations. A stochastic simulation model has been developed to calculate the propagation of ultrasonic waves in such an inhomogeneous medium. Using this approach, the travel time is randomly generated by a stochastic process whose inputs are the statistical moments of travel times known analytically. The stochastic model predicts beam deviations due to velocity inhomogeneities, which are similar to those provided by a determinist method, such as the ray method.

On the generation of log-Lévy distributions and extreme randomness

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Klafter, Joseph

2011-10-01

The log-normal distribution is prevalent across the sciences, as it emerges from the combination of multiplicative processes and the central limit theorem (CLT). The CLT, beyond yielding the normal distribution, also yields the class of Lévy distributions. The log-Lévy distributions are the Lévy counterparts of the log-normal distribution, they appear in the context of ultraslow diffusion processes, and they are categorized by Mandelbrot as belonging to the class of extreme randomness. In this paper, we present a natural stochastic growth model from which both the log-normal distribution and the log-Lévy distributions emerge universally—the former in the case of deterministic underlying setting, and the latter in the case of stochastic underlying setting. In particular, we establish a stochastic growth model which universally generates Mandelbrot’s extreme randomness.

Periodic Solution and Stationary Distribution of Stochastic Predator-Prey Models with Higher-Order Perturbation

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing

2018-04-01

In this paper, two stochastic predator-prey models with general functional response and higher-order perturbation are proposed and investigated. For the nonautonomous periodic case of the system, by using Khasminskii's theory of periodic solution, we show that the system admits a nontrivial positive T-periodic solution. For the system disturbed by both white and telegraph noises, sufficient conditions for positive recurrence and the existence of an ergodic stationary distribution to the solutions are established. The existence of stationary distribution implies stochastic weak stability to some extent.

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

NASA Technical Reports Server (NTRS)

Carter, M. C.; Madison, M. W.

1973-01-01

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

Constraints on cosmic strings using data from the first Advanced LIGO observing run

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Afrough, M.; Agarwal, B.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allen, G.; Allocca, A.; Altin, P. A.; Amato, A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; AultONeal, K.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Bae, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Banagiri, S.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bawaj, M.; Bazzan, M.; Bécsy, B.; Beer, C.; Bejger, M.; Belahcene, I.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bode, N.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Canepa, M.; Canizares, P.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Carney, M. F.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chatterjee, D.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, H.-P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, A. K. W.; Chung, S.; Ciani, G.; Ciolfi, R.; Cirelli, C. E.; Cirone, A.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L. R.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Corley, K. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davis, D.; Daw, E. J.; Day, B.; De, S.; DeBra, D.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Duncan, J.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Etienne, Z. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Feicht, J.; Fejer, M. M.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Fitz-Axen, M.; Flaminio, R.; Fletcher, M.; Fong, H.; Forsyth, P. W. F.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gabel, M.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Ganija, M. R.; Gaonkar, S. G.; Garufi, F.; Gaudio, S.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, D.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, W.; Kim, W. S.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kumar, S.; Kuo, L.; Kutynia, A.; Kwang, S.; Lackey, B. D.; Lai, K. H.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, H. W.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lo, R. K. L.; Lockerbie, N. A.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña Hernandez, I.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McCuller, L.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Mejuto-Villa, E.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minazzoli, O.; Minenkov, Y.; Ming, J.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Ng, K. K. Y.; Nguyen, T. T.; Nichols, D.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ormiston, R.; Ortega, L. F.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Page, M. A.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pang, B.; Pang, P. T. H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Ramirez, K. E.; Rapagnani, P.; Raymond, V.; Razzano, M.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Ricker, P. M.; Rieger, S.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romel, C. L.; Romie, J. H.; Rosińska, D.; Ross, M. P.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schulte, B. W.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Seidel, E.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D. A.; Shaffer, T. J.; Shah, A. A.; Shahriar, M. S.; Shao, L.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Son, E. J.; Sonnenberg, J. A.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steer, D. A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Taracchini, A.; Taylor, J. A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tsang, K. W.; Tse, M.; Tso, R.; Tuyenbayev, D.; Ueno, K.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Vallisneri, M.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walet, R.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, J. Z.; Wang, M.; Wang, Y.-F.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessel, E. K.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2018-05-01

Cosmic strings are topological defects which can be formed in grand unified theory scale phase transitions in the early universe. They are also predicted to form in the context of string theory. The main mechanism for a network of Nambu-Goto cosmic strings to lose energy is through the production of loops and the subsequent emission of gravitational waves, thus offering an experimental signature for the existence of cosmic strings. Here we report on the analysis conducted to specifically search for gravitational-wave bursts from cosmic string loops in the data of Advanced LIGO 2015-2016 observing run (O1). No evidence of such signals was found in the data, and as a result we set upper limits on the cosmic string parameters for three recent loop distribution models. In this paper, we initially derive constraints on the string tension G μ and the intercommutation probability, using not only the burst analysis performed on the O1 data set but also results from the previously published LIGO stochastic O1 analysis, pulsar timing arrays, cosmic microwave background and big-bang nucleosynthesis experiments. We show that these data sets are complementary in that they probe gravitational waves produced by cosmic string loops during very different epochs. Finally, we show that the data sets exclude large parts of the parameter space of the three loop distribution models we consider.

Radial-Poloidal Mapping of the Energy Distribution of Electrons Accelerated by Lower Hybrid Waves in the Scrape-Off Layer

NASA Astrophysics Data System (ADS)

Gunn, J. P.; Petržílka, V.; Fuchs, V.; Ekedahl, A.; Goniche, M.; Hillaret, J.; Kočan, M.; Saint-Laurent, F.

2009-11-01

According to theory, Landau damping transfers the power carried by the high n//>50 components of the lower hybrid (LH) wave to thermal SOL electrons and stochastically accelerates them up to a few keV [1]. What amounts to a few percent of the injected LH power is thus transported along field lines and strikes plasma facing components, leading to the formation of well known "LH hot spots." We report on the first measurements of both the energy from 0 to 1 keV and the radial-poloidal distributions of the accelerated electrons using a retarding field analyzer. Two distinct electron populations are present : a cold, thermal population with temperatures between 10 and 30 eV, and a suprathermal component. Only partial attenuation of the electron flux was achieved at maximum applied voltage, indicating energies greater than 1 keV. Detailed 2D mapping of the hot spots was obtained by varying the safety factor stepwise during a single discharge. The radial width of the suprathermal electron beam at full power is rather large, at least about 5-6 cm, in contrast to Landau damping theory of the launched wave that predicts the radial width of the hot spots should not exceed a few millimetres [2]. The electron flux far from the grill is intermittent, with a typical burst rate of the order of 10 kHz.

Price sensitive demand with random sales price - a newsboy problem

NASA Astrophysics Data System (ADS)

Sankar Sana, Shib

2012-03-01

Up to now, many newsboy problems have been considered in the stochastic inventory literature. Some assume that stochastic demand is independent of selling price (p) and others consider the demand as a function of stochastic shock factor and deterministic sales price. This article introduces a price-dependent demand with stochastic selling price into the classical Newsboy problem. The proposed model analyses the expected average profit for a general distribution function of p and obtains an optimal order size. Finally, the model is discussed for various appropriate distribution functions of p and illustrated with numerical examples.

On Alfvenic Waves and Stochastic Ion Heating with 1Re Observations of Strong Field-aligned Currents, Electric Fields, and O+ ions

NASA Technical Reports Server (NTRS)

Coffey, Victoria; Chandler, Michael; Singh, Nagendra

2008-01-01

The role that the cleft/cusp has in ionosphere/magnetosphere coupling makes it a very dynamic region having similar fundamental processes to those within the auroral regions. With Polar passing through the cusp at 1 Re in the Spring of 1996, we observe a strong correlation between ion heating and broadband ELF (BBELF) emissions. This commonly observed relationship led to the study of the coupling of large field-aligned currents, burst electric fields, and the thermal O+ ions. We demonstrate the role of these measurements to Alfvenic waves and stochastic ion heating. Finally we will show the properties of the resulting density cavities.

Reducing the number of templates for aligned-spin compact binary coalescence gravitational wave searches using metric-agnostic template nudging

NASA Astrophysics Data System (ADS)

Indik, Nathaniel; Fehrmann, Henning; Harke, Franz; Krishnan, Badri; Nielsen, Alex B.

2018-06-01

Efficient multidimensional template placement is crucial in computationally intensive matched-filtering searches for gravitational waves (GWs). Here, we implement the neighboring cell algorithm (NCA) to improve the detection volume of an existing compact binary coalescence (CBC) template bank. This algorithm has already been successfully applied for a binary millisecond pulsar search in data from the Fermi satellite. It repositions templates from overdense regions to underdense regions and reduces the number of templates that would have been required by a stochastic method to achieve the same detection volume. Our method is readily generalizable to other CBC parameter spaces. Here we apply this method to the aligned-single-spin neutron star-black hole binary coalescence inspiral-merger-ringdown gravitational wave parameter space. We show that the template nudging algorithm can attain the equivalent effectualness of the stochastic method with 12% fewer templates.

Predator-prey model for the self-organization of stochastic oscillators in dual populations

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan; Gürcan, Ozgür D.

2015-12-01

A predator-prey model of dual populations with stochastic oscillators is presented. A linear cross-coupling between the two populations is introduced following the coupling between the motions of a Wilberforce pendulum in two dimensions: one in the longitudinal and the other in torsional plain. Within each population a Kuramoto-type competition between the phases is assumed. Thus, the synchronization state of the whole system is controlled by these two types of competitions. The results of the numerical simulations show that by adding the linear cross-coupling interactions predator-prey oscillations between the two populations appear, which results in self-regulation of the system by a transfer of synchrony between the two populations. The model represents several important features of the dynamical interplay between the drift wave and zonal flow turbulence in magnetically confined plasmas, and a novel interpretation of the coupled dynamics of drift wave-zonal flow turbulence using synchronization of stochastic oscillator is discussed.

Ion pickup, scattering, and stochastic acceleration in the cometary environment of P/Giacobini-Zinner

NASA Technical Reports Server (NTRS)

Barbosa, D. D.

1991-01-01

Observations and theory related to the scattering and acceleration of cometary pickup ions are reviewed with emphasis on Comet P/Giacobini-Zinner. A comparison of the regions upstream and downstream of the bow shock is made to assess the relative merits of each as a site for stochastic acceleration of ions above the pickup energy through interaction with low-frequency MHD waves. In the far upstream region the data are most consistent with a model where pickup ions generate a low level of MHD waves but remain relatively scatter-free. In the downstream region intense magnetic fluctuations gives rise to rapid isotropization of the ions and a second-order stochastic acceleration. The properties of the MHD power spectrum are related to the energetic ion spectrum in the framework of a leaky box model where the bulk of the acceleration occurs downstream of the shock throughout the cometosheath. Good agreement of the observations with theory is evident for both P/Giacobini-Zinner and P/Halley.

Structural factoring approach for analyzing stochastic networks

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.; Shier, Douglas R.

1991-01-01

The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

Critical Gradient Behavior of Alfvén Eigenmode Induced Fast-Ion Transport in Phase Space

NASA Astrophysics Data System (ADS)

Collins, C. S.; Pace, D. C.; van Zeeland, M. A.; Heidbrink, W. W.; Stagner, L.; Zhu, Y. B.; Kramer, G. J.; Podesta, M.; White, R. B.

2016-10-01

Experiments on DIII-D have shown that energetic particle (EP) transport suddenly increases when multiple Alfvén eigenmodes (AEs) cause particle orbits to become stochastic. Several key features have been observed; (1) the transport threshold is phase-space dependent and occurs above the AE linear stability threshold, (2) EP losses become intermittent above threshold and appear to depend on the types of AEs present, and (3) stiff transport causes the EP density profile to remain unchanged even if the source increases. Theoretical analysis using the NOVA and ORBIT codes shows that the threshold corresponds to when particle orbits become stochastic due to wave-particle resonances with AEs in the region of phase space measured by the diagnostics. The kick model in NUBEAM (TRANSP) is used to evolve the EP distribution function to study which modes cause the most transport and further characterize intermittent bursts of EP losses, which are associated with large scale redistribution through the domino effect. Work supported by the US DOE under DE-FC02-04ER54698.

Occupational activity and cognitive reserve: implications in terms of prevention of cognitive aging and Alzheimer’s disease

PubMed Central

Adam, Stéphane; Bonsang, Eric; Grotz, Catherine; Perelman, Sergio

2013-01-01

This paper investigates the relationship between the concept of activity (including both professional and nonprofessional) and cognitive functioning among older European individuals. In this research, we used data collected during the first wave of SHARE (Survey on Health, Ageing and Retirement in Europe), and a measurement approach known as stochastic frontier analysis, derived from the economic literature. SHARE includes a large population (n > 25,000) geographically distributed across Europe, and analyzes several dimensions simultaneously, including physical and mental health activity. The main advantages of stochastic frontier analysis are that it allows estimation of parametric function relating cognitive scores and driving factors at the boundary and disentangles frontier noise and distance to frontier components, as well as testing the effect of potential factors on these distances simultaneously. The analysis reveals that all activities are positively related to cognitive functioning in elderly people. Our results are discussed in terms of prevention of cognitive aging and Alzheimer’s disease, and regarding the potential impact that some retirement programs might have on cognitive functioning in individuals across Europe. PMID:23671387

Waveform inversion with source encoding for breast sound speed reconstruction in ultrasound computed tomography.

PubMed

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the sound speed distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Both computer simulation and experimental phantom studies are conducted to demonstrate the use of the WISE method. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

The effect of stochastic re-acceleration on the energy spectrum of shock-accelerated protons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Afanasiev, Alexandr; Vainio, Rami; Kocharov, Leon

2014-07-20

The energy spectra of particles in gradual solar energetic particle (SEP) events do not always have a power-law form attributed to the diffusive shock acceleration mechanism. In particular, the observed spectra in major SEP events can take the form of a broken (double) power law. In this paper, we study the effect of a process that can modify the power-law spectral form produced by the diffusive shock acceleration: the stochastic re-acceleration of energetic protons by enhanced Alfvénic turbulence in the downstream region of a shock wave. There are arguments suggesting that this process can be important when the shock propagatesmore » in the corona. We consider a coronal magnetic loop traversed by a shock and perform Monte Carlo simulations of interactions of shock-accelerated protons with Alfvén waves in the loop. The wave-particle interactions are treated self-consistently, so the finiteness of the available turbulent energy is taken into account. The initial energy spectrum of particles is taken to be a power law. The simulations reveal that the stochastic re-acceleration leads either to the formation of a spectrum that is described in a wide energy range by a power law (although the resulting power-law index is different from the initial one) or to a broken power-law spectrum. The resulting spectral form is determined by the ratio of the energy density of shock-accelerated protons to the wave energy density in the shock's downstream region.« less

Detecting a Non-Gaussian Stochastic Background of Gravitational Radiation

NASA Astrophysics Data System (ADS)

Drasco, Steve; Flanagan, Éanna É.

2002-12-01

We derive a detection method for a stochastic background of gravitational waves produced by events where the ratio of the average time between events to the average duration of an event is large. Such a signal would sound something like popcorn popping. Our derivation is based on the somewhat unrealistic assumption that the duration of an event is smaller than the detector time resolution.

Kelvin Absolute Temperature Scale Identified as Length Scale and Related to de Broglie Thermal Wavelength

NASA Astrophysics Data System (ADS)

Sohrab, Siavash

Thermodynamic equilibrium between matter and radiation leads to de Broglie wavelength λdβ = h /mβvrβ and frequency νdβ = k /mβvrβ of matter waves and stochastic definitions of Planck h =hk =mk <λrk > c and Boltzmann k =kk =mk <νrk > c constants, λrkνrk = c , that respectively relate to spatial (λ) and temporal (ν) aspects of vacuum fluctuations. Photon massmk =√{ hk /c3 } , amu =√{ hkc } = 1 /No , and universal gas constant Ro =No k =√{ k / hc } result in internal Uk = Nhνrk = Nmkc2 = 3 Nmkvmpk2 = 3 NkT and potential pV = uN\\vcirc / 3 = N\\ucirc / 3 = NkT energy of photon gas in Casimir vacuum such that H = TS = 4 NkT . Therefore, Kelvin absolute thermodynamic temperature scale [degree K] is identified as length scale [meter] and related to most probable wavelength and de Broglie thermal wavelength as Tβ =λmpβ =λdβ / 3 . Parallel to Wien displacement law obtained from Planck distribution, the displacement law λwS T =c2 /√{ 3} is obtained from Maxwell -Boltzmann distribution of speed of ``photon clusters''. The propagation speeds of sound waves in ideal gas versus light waves in photon gas are described in terms of vrβ in harmony with perceptions of Huygens. Newton formula for speed of long waves in canals √{ p / ρ } is modified to √{ gh } =√{ γp / ρ } in accordance with adiabatic theory of Laplace.

Stochastic simulation of human pulmonary blood flow and transit time frequency distribution based on anatomic and elasticity data.

PubMed

Huang, Wei; Shi, Jun; Yen, R T

2012-12-01

The objective of our study was to develop a computing program for computing the transit time frequency distributions of red blood cell in human pulmonary circulation, based on our anatomic and elasticity data of blood vessels in human lung. A stochastic simulation model was introduced to simulate blood flow in human pulmonary circulation. In the stochastic simulation model, the connectivity data of pulmonary blood vessels in human lung was converted into a probability matrix. Based on this model, the transit time of red blood cell in human pulmonary circulation and the output blood pressure were studied. Additionally, the stochastic simulation model can be used to predict the changes of blood flow in human pulmonary circulation with the advantage of the lower computing cost and the higher flexibility. In conclusion, a stochastic simulation approach was introduced to simulate the blood flow in the hierarchical structure of a pulmonary circulation system, and to calculate the transit time distributions and the blood pressure outputs.

The complexity of divisibility.

PubMed

Bausch, Johannes; Cubitt, Toby

2016-09-01

We address two sets of long-standing open questions in linear algebra and probability theory, from a computational complexity perspective: stochastic matrix divisibility, and divisibility and decomposability of probability distributions. We prove that finite divisibility of stochastic matrices is an NP-complete problem, and extend this result to nonnegative matrices, and completely-positive trace-preserving maps, i.e. the quantum analogue of stochastic matrices. We further prove a complexity hierarchy for the divisibility and decomposability of probability distributions, showing that finite distribution divisibility is in P, but decomposability is NP-hard. For the former, we give an explicit polynomial-time algorithm. All results on distributions extend to weak-membership formulations, proving that the complexity of these problems is robust to perturbations.

p-adic stochastic hidden variable model

NASA Astrophysics Data System (ADS)

Khrennikov, Andrew

1998-03-01

We propose stochastic hidden variables model in which hidden variables have a p-adic probability distribution ρ(λ) and at the same time conditional probabilistic distributions P(U,λ), U=A,A',B,B', are ordinary probabilities defined on the basis of the Kolmogorov measure-theoretical axiomatics. A frequency definition of p-adic probability is quite similar to the ordinary frequency definition of probability. p-adic frequency probability is defined as the limit of relative frequencies νn but in the p-adic metric. We study a model with p-adic stochastics on the level of the hidden variables description. But, of course, responses of macroapparatuses have to be described by ordinary stochastics. Thus our model describes a mixture of p-adic stochastics of the microworld and ordinary stochastics of macroapparatuses. In this model probabilities for physical observables are the ordinary probabilities. At the same time Bell's inequality is violated.

How the Slip Distribution Complexities Control the Tsunami Scenarios: a Sensitivity Analysis for the Hellenic and Calabrian Subduction Interfaces.

NASA Astrophysics Data System (ADS)

Scala, A.; Murphy, S.; Herrero, A.; Maesano, F. E.; Lorito, S.; Romano, F.; Tiberti, M. M.; Tonini, R.; Volpe, M.; Basili, R.

2017-12-01

Recent giant tsunamigenic earthquakes (Sumatra 2004, Chile 2010, Tohoku 2011) have confirmed that the complexity of seismic slip distributions may play a fundamental role in the generation and the amplitude of the tsunami waves. In particular, big patches of large slip on the shallower part of the subduction zones, as well as slow rupture propagation within low rigidity areas, can contribute to increase the tsunamigenic potential thus generating devastating coastal inundation. In the Mediterranean Sea, some subduction structures can be identified, such as the Hellenic Arc at the boundary between the African and Aegean plates, and the Calabrian Arc between the European and African plates. We have modelled these areas using discretized high-resolution 3D fault geometries with realistic variability of the strike and dip angles. In particular, the latter geometries have been constrained from the analysis of a dense network of seismic reflection profiles and the seismicity of the areas. To study the influence of different rigidity conditions, we compare the tsunami scenarios deriving from homogeneous slip to those obtained from depth-dependent slip distributions at different magnitudes. These depth-dependent slip distributions are obtained by imposing a variability with depth of both shear modulus and seismic rate, and the conservation of the dislocation over the whole subduction zone. Furthermore, we generate along the Hellenic and Calabrian arc subduction interfaces an ensemble of stochastic slip distributions using a composite source model technique. To mimic either single or multiple asperity source models, the distribution of sub-events whose sum produces the stochastic slip, are distributed based on a PDF, defined as the combination of either one or more Gaussian functions. Tsunami scenarios are then generated from this ensemble in order to address how the position of the main patch of slip can affect the tsunami amplitude along the coast.

Stochastic Ion Heating by the Lower-Hybrid Waves

NASA Technical Reports Server (NTRS)

Khazanov, G.; Tel'nikhin, A.; Krotov, A.

2011-01-01

The resonance lower-hybrid wave-ion interaction is described by a group (differentiable map) of transformations of phase space of the system. All solutions to the map belong to a strange attractor, and chaotic motion of the attractor manifests itself in a number of macroscopic effects, such as the energy spectrum and particle heating. The applicability of the model to the problem of ion heating by waves at the front of collisionless shock as well as ion acceleration by a spectrum of waves is discussed. Keywords: plasma; ion-cyclotron heating; shocks; beat-wave accelerator.

Dark Matter in the Universe and in the Galaxy

NASA Technical Reports Server (NTRS)

Kamionkowski, Marc

1999-01-01

During the past four years, Prof. Kamionkowski and collaborators have made progress in research on the nature and distribution of dark-matter in the Universe and in the Galaxy, and on related topics in astrophysics and cosmology. We have made progress on research on the cosmic microwave background, large-scale structure, issues related to particle dark matter, and the gamma-ray-burst enigma. A significant fraction of the research supported by this ATP has been on the cosmic microwave background (CMB). Prof. Kamionkowski and collaborators showed how the polarization of the CMB could be used to detect long-wavelength gravitational waves, such as those produced by inflation. With Kosowsky, Prof. Kamionkowski calculated the amplitude of a stochastic gravitational-wave background that could be detected for a satellite experiment of a given sensitivity and angular resolution. They showed that polarization should improve the sensitivity oa MAP to these gravity waves, and that the Planck Surveyor should do even better. Prof. Kamionkowski, Caldwell, and a student calculated and illustrated the CMB temperature/polarization pattern produced by a single plane-wave gravitational wave. They calculated the amplitude of such a wave that would be detectable with MAP and Planck, and compared that with the sensitivity of traditional gravitational-wave detectors like LIGO and LISA. With Lue and Wang, the PI showed how parity violation from new high-energy physics could conceivably give rise to an observable signature in the CMB polarization. With Loeb, Prof. Kamionkowski showed how measurement of the polarization of CMB photons scattered by hot gas in a cluster could be used to determine the quadrupole moment of the CMB incident on that cluster. Prof. Kamionkowski and Jaffe calculated the amplitude of secondary anisotropies produced by scattering of CMB photons from reionized regions. Research has also been carried out on probing the large-scale distribution of mass in the Universe today, and on structure-formation theories. They investigated the possibility of determining the large-scale distribution of mass in the Universe via measurement of ellipticity-ellipticity correlations in the FIRST radio survey induced by weak gravitational lensing due to mass inhomogeneities along the line of sight. Dr. Summers, Prof. Kamionkowski, and a student investigated the distribution of protogalactic masses and angular momenta in an effort to understand how the luminosity function and angular-momentum distribution of disk galaxies arises from an initial power spectrum of density perturbations. Several projects related to the distribution and possible detection of dark matter in our Galactic halo were studied. The PI was involved in several projects involving the calculation of nuclear-reaction rates needed for stellar evolution and for predictions of solar-neutrino fluxes.

The contribution of statistical physics to evolutionary biology.

PubMed

de Vladar, Harold P; Barton, Nicholas H

2011-08-01

Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. Here, we discuss aspects of population genetics that have embraced methods from physics: non-equilibrium statistical mechanics, travelling waves and Monte-Carlo methods, among others, have been used to study polygenic evolution, rates of adaptation and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics; for example, by following the distribution of paths taken by a population through time. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spin-squeezing and Dicke-state preparation by heterodyne measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanderbruggen, T.; Bernon, S.; Bertoldi, A.

2011-01-15

We investigate the quantum nondemolition (QND) measurement of an atomic population based on a heterodyne detection and show that the induced back-action allows for the preparation of both spin-squeezed and Dicke states. We use a wave-vector formalism to describe the stochastic process of the measurement and the associated atomic evolution. Analytical formulas of the atomic distribution momenta are derived in the weak-coupling regime both for short- and long-time behavior, and they are in good agreement with those obtained by a Monte Carlo simulation. The experimental implementation of the proposed heterodyne detection scheme is discussed. The role played in the squeezingmore » process by the spontaneous emission is considered.« less

Searching for stochastic gravitational waves using data from the two colocated LIGO Hanford detectors

NASA Astrophysics Data System (ADS)

Aasi, J.; Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Accadia, T.; Acernese, F.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Affeldt, C.; Agathos, M.; Aggarwal, N.; Aguiar, O. D.; Ajith, P.; Allen, B.; Allocca, A.; Amador Ceron, E.; Amariutei, D.; Anderson, R. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C.; Areeda, J.; Ast, S.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Austin, L.; Aylott, B. E.; Babak, S.; Baker, P. T.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barker, D.; Barnum, S. H.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Bell, C.; Belopolski, I.; Bergmann, G.; Berliner, J. M.; Bersanetti, D.; Bertolini, A.; Bessis, D.; Betzwieser, J.; Beyersdorf, P. T.; Bhadbhade, T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biscans, S.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Blom, M.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogan, C.; Bond, C.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bowers, J.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brannen, C. A.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brückner, F.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calderón Bustillo, J.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K. C.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Castiglia, A.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chu, Q.; Chua, S. S. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Colombini, M.; Constancio, M.; Conte, A.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Craig, K.; Creighton, J. D. E.; Creighton, T. D.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dahl, K.; Dal Canton, T.; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Dayanga, T.; Debreczeni, G.; Degallaix, J.; Deleeuw, E.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R. T.; De Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Díaz, M.; Dietz, A.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Dmitry, K.; Donovan, F.; Dooley, K. L.; Doravari, S.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edwards, M.; Effler, A.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Endrőczi, G.; Essick, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fang, Q.; Farr, B.; Farr, W.; Favata, M.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Ferrante, I.; Ferrini, F.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R.; Flaminio, R.; Foley, E.; Foley, S.; Forsi, E.; Fotopoulos, N.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fujimoto, M.-K.; Fulda, P.; Fyffe, M.; Gair, J.; Gammaitoni, L.; Garcia, J.; Garufi, F.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; Gergely, L.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gil-Casanova, S.; Gill, C.; Gleason, J.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gordon, N.; Gorodetsky, M. L.; Gossan, S.; Goßler, S.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Griffo, C.; Grote, H.; Grover, K.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, B.; Hall, E.; Hammer, D.; Hammond, G.; Hanke, M.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haughian, K.; Hayama, K.; Heefner, J.; Heidmann, A.; Heintze, M.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Hong, T.; Hooper, S.; Horrom, T.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hu, Y.; Hua, Z.; Huang, V.; Huerta, E. A.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh, M.; Huynh-Dinh, T.; Iafrate, J.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Iyer, B. R.; Izumi, K.; Jacobson, M.; James, E.; Jang, H.; Jang, Y. J.; Jaranowski, P.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, D.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasprzack, M.; Kasturi, R.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kaufman, K.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kells, W.; Keppel, D. G.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B. K.; Kim, C.; Kim, K.; Kim, N.; Kim, W.; Kim, Y.-M.; King, E.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Koehlenbeck, S.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kremin, A.; Kringel, V.; Krishnan, B.; Królak, A.; Kucharczyk, C.; Kudla, S.; Kuehn, G.; Kumar, A.; Kumar, D. Nanda; Kumar, P.; Kumar, R.; Kurdyumov, R.; Kwee, P.; Landry, M.; Lantz, B.; Larson, S.; Lasky, P. D.; Lawrie, C.; Lazzarini, A.; Leaci, P.; Lebigot, E. O.; Lee, C.-H.; Lee, H. K.; Lee, H. M.; Lee, J. J.; Lee, J.; Leonardi, M.; Leong, J. R.; Le Roux, A.; Leroy, N.; Letendre, N.; Levine, B.; Lewis, J. B.; Lhuillier, V.; Li, T. G. F.; Lin, A. C.; Littenberg, T. B.; Litvine, V.; Liu, F.; Liu, H.; Liu, Y.; Liu, Z.; Lloyd, D.; Lockerbie, N. A.; Lockett, V.; Lodhia, D.; Loew, K.; Logue, J.; Lombardi, A. L.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Luan, J.; Lubinski, M. J.; Lück, H.; Lundgren, A. P.; Macarthur, J.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Manca, G. M.; Mandel, I.; Mandic, V.; Mangano, V.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martini, G.; Martynov, D.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; May, G.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Meier, T.; Melatos, A.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Mikhailov, E.; Milano, L.; Miller, J.; Minenkov, Y.; Mingarelli, C. M. F.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Mohan, M.; Mohapatra, S. R. P.; Mokler, F.; Moraru, D.; Moreno, G.; Morgado, N.; Mori, T.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nagy, M. F.; Nardecchia, I.; Nash, T.; Naticchioni, L.; Nayak, R.; Necula, V.; Neri, I.; Neri, M.; Newton, G.; Nguyen, T.; Nishida, E.; Nishizawa, A.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L. K.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oppermann, P.; O'Reilly, B.; Ortega Larcher, W.; O'Shaughnessy, R.; Osthelder, C.; Ottaway, D. J.; Ottens, R. S.; Ou, J.; Overmier, H.; Owen, B. J.; Padilla, C.; Pai, A.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Paoletti, R.; Paris, H.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Pedraza, M.; Peiris, P.; Penn, S.; Perreca, A.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pierro, V.; Pinard, L.; Pindor, B.; Pinto, I. M.; Pitkin, M.; Poeld, J.; Poggiani, R.; Poole, V.; Postiglione, F.; Poux, C.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Quintero, E.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Raja, S.; Rajalakshmi, G.; Rakhmanov, M.; Ramet, C.; Rapagnani, P.; Raymond, V.; Re, V.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Robertson, N. A.; Robinet, F.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Roever, C.; Rolland, L.; Rollins, J. G.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Salemi, F.; Sammut, L.; Sandberg, V.; Sanders, J.; Sannibale, V.; Santiago-Prieto, I.; Saracco, E.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schuette, D.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Seifert, F.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siellez, K.; Siemens, X.; Sigg, D.; Simakov, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G. R.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Soden, K.; Son, E. J.; Sorazu, B.; Souradeep, T.; Sperandio, L.; Staley, A.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stevens, D.; Stochino, A.; Stone, R.; Strain, K. A.; Straniero, N.; Strigin, S.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Szeifert, G.; Tacca, M.; Talukder, D.; Tang, L.; Tanner, D. B.; Tarabrin, S. P.; Taylor, R.; ter Braack, A. P. M.; Thirugnanasambandam, M. P.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C. V.; Torrie, C. I.; Travasso, F.; Traylor, G.; Tse, M.; Ugolini, D.; Unnikrishnan, C. S.; Vahlbruch, H.; Vajente, G.; Vallisneri, M.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van der Sluys, M. V.; van Heijningen, J.; van Veggel, A. A.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, P. J.; Veitch, J.; Venkateswara, K.; Verkindt, D.; Verma, S.; Vetrano, F.; Viceré, A.; Vincent-Finley, R.; Vinet, J.-Y.; Vitale, S.; Vitale, S.; Vlcek, B.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vrinceanu, D.; Vyachanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Waldman, S. J.; Walker, M.; Wallace, L.; Wan, Y.; Wang, J.; Wang, M.; Wang, X.; Wanner, A.; Ward, R. L.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Wibowo, S.; Wiesner, K.; Wilkinson, C.; Williams, L.; Williams, R.; Williams, T.; Willis, J. L.; Willke, B.; Wimmer, M.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yancey, C. C.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yum, H.; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhao, C.; Zhu, H.; Zhu, X. J.; Zotov, N.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2015-01-01

Searches for a stochastic gravitational-wave background (SGWB) using terrestrial detectors typically involve cross-correlating data from pairs of detectors. The sensitivity of such cross-correlation analyses depends, among other things, on the separation between the two detectors: the smaller the separation, the better the sensitivity. Hence, a colocated detector pair is more sensitive to a gravitational-wave background than a noncolocated detector pair. However, colocated detectors are also expected to suffer from correlated noise from instrumental and environmental effects that could contaminate the measurement of the background. Hence, methods to identify and mitigate the effects of correlated noise are necessary to achieve the potential increase in sensitivity of colocated detectors. Here we report on the first SGWB analysis using the two LIGO Hanford detectors and address the complications arising from correlated environmental noise. We apply correlated noise identification and mitigation techniques to data taken by the two LIGO Hanford detectors, H1 and H2, during LIGO's fifth science run. At low frequencies, 40-460 Hz, we are unable to sufficiently mitigate the correlated noise to a level where we may confidently measure or bound the stochastic gravitational-wave signal. However, at high frequencies, 460-1000 Hz, these techniques are sufficient to set a 95% confidence level upper limit on the gravitational-wave energy density of Ω (f )<7.7 ×1 0-4(f /900 Hz )3 , which improves on the previous upper limit by a factor of ˜180 . In doing so, we demonstrate techniques that will be useful for future searches using advanced detectors, where correlated noise (e.g., from global magnetic fields) may affect even widely separated detectors.

The nightmare scenario: measuring the stochastic gravitational wave background from stalling massive black hole binaries with pulsar timing arrays

NASA Astrophysics Data System (ADS)

Dvorkin, Irina; Barausse, Enrico

2017-10-01

Massive black hole binaries, formed when galaxies merge, are among the primary sources of gravitational waves targeted by ongoing pulsar timing array (PTA) experiments and the upcoming space-based Laser Interferometer Space Antenna (LISA) interferometer. However, their formation and merger rates are still highly uncertain. Recent upper limits on the stochastic gravitational wave background obtained by PTAs are starting to be in marginal tension with theoretical models for the pairing and orbital evolution of these systems. This tension can be resolved by assuming that these binaries are more eccentric or interact more strongly with the environment (gas and stars) than expected, or by accounting for possible selection biases in the construction of the theoretical models. However, another (pessimistic) possibility is that these binaries do not merge at all, but stall at large (˜pc) separations. We explore this extreme scenario by using a semi-analytic galaxy formation model including massive black holes (isolated and in binaries), and show that future generations of PTAs will detect the stochastic gravitational wave background from the massive black hole binary population within 10-15 yr of observations, even in the `nightmare scenario' in which all binaries stall at the hardening radius. Moreover, we argue that this scenario is too pessimistic, because our model predicts the existence of a subpopulation of binaries with small mass ratios (q ≲ 10-3) that should merge within a Hubble time simply as a result of gravitational wave emission. This subpopulation will be observable with large signal-to-noise ratios by future PTAs thanks to next-generation radio telescopes such as Square Kilometre Array or Five-hundred-meter Aperture Spherical Telescope, and possibly by LISA.

Searching for Stochastic Gravitational Waves Using Data from the Two Co-Located LIGO Hanford Detectors

NASA Technical Reports Server (NTRS)

Aasi, J.; Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Accadia, T.; Acernese, F.; Adams, C.; Adams, T.;

Spectra of KeV Protons Related to Ion-Cyclotron Wave Packets

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Sibeck, D. G.; Tel'Nikhin, A. A.; Kronberg, T. K.

2017-01-01

We use the Fokker-Planck-Kolmogorov equation to study the statistical aspects of stochastic dynamics of the radiation belt (RB) protons driven by nonlinear electromagnetic ion-cyclotron (EMIC) wave packets. We obtain the spectra of keV protons scattered by these waves that showsteeping near the gyroresonance, the signature of resonant wave-particle interaction that cannot be described by a simple power law. The most likely mechanism for proton precipitation events in RBs is shown to be nonlinear wave-particle interaction, namely, the scattering of RB protons into the loss cone by EMIC waves.

Discussion of a ``coherent artifact'' in four-wave mixing experiments

NASA Astrophysics Data System (ADS)

Ferwerda, Hedzer A.; Terpstra, Jacob; Wiersma, Douwe A.

1989-09-01

In this paper, we discuss the nonlinear optical effects that arise when stochastic light waves, with different correlation times, interfere in an absorbing medium. It is shown that four-wave mixing signals are generated in several directions that spectrally track the incoming light fields. This effect is particularly relevant to transient hole-burning experiments, where one of these signals could easily be misinterpreted as a genuine hole-burning feature.

Stochastic maps, continuous approximation, and stable distribution

NASA Astrophysics Data System (ADS)

Kessler, David A.; Burov, Stanislav

2017-10-01

A continuous approximation framework for general nonlinear stochastic as well as deterministic discrete maps is developed. For the stochastic map with uncorelated Gaussian noise, by successively applying the Itô lemma, we obtain a Langevin type of equation. Specifically, we show how nonlinear maps give rise to a Langevin description that involves multiplicative noise. The multiplicative nature of the noise induces an additional effective force, not present in the absence of noise. We further exploit the continuum description and provide an explicit formula for the stable distribution of the stochastic map and conditions for its existence. Our results are in good agreement with numerical simulations of several maps.

Impact of correlated magnetic noise on the detection of stochastic gravitational waves: Estimation based on a simple analytical model

NASA Astrophysics Data System (ADS)

Himemoto, Yoshiaki; Taruya, Atsushi

2017-07-01

After the first direct detection of gravitational waves (GW), detection of the stochastic background of GWs is an important next step, and the first GW event suggests that it is within the reach of the second-generation ground-based GW detectors. Such a GW signal is typically tiny and can be detected by cross-correlating the data from two spatially separated detectors if the detector noise is uncorrelated. It has been advocated, however, that the global magnetic fields in the Earth-ionosphere cavity produce the environmental disturbances at low-frequency bands, known as Schumann resonances, which potentially couple with GW detectors. In this paper, we present a simple analytical model to estimate its impact on the detection of stochastic GWs. The model crucially depends on the geometry of the detector pair through the directional coupling, and we investigate the basic properties of the correlated magnetic noise based on the analytic expressions. The model reproduces the major trend of the recently measured global correlation between the GW detectors via magnetometer. The estimated values of the impact of correlated noise also match those obtained from the measurement. Finally, we give an implication to the detection of stochastic GWs including upcoming detectors, KAGRA and LIGO India. The model suggests that LIGO Hanford-Virgo and Virgo-KAGRA pairs are possibly less sensitive to the correlated noise and can achieve a better sensitivity to the stochastic GW signal in the most pessimistic case.

Time-dependent Electron Acceleration in Blazar Transients: X-Ray Time Lags and Spectral Formation

NASA Astrophysics Data System (ADS)

Lewis, Tiffany R.; Becker, Peter A.; Finke, Justin D.

2016-06-01

Electromagnetic radiation from blazar jets often displays strong variability, extending from radio to γ-ray frequencies. In a few cases, this variability has been characterized using Fourier time lags, such as those detected in the X-rays from Mrk 421 using BeppoSAX. The lack of a theoretical framework to interpret the data has motivated us to develop a new model for the formation of the X-ray spectrum and the time lags in blazar jets based on a transport equation including terms describing stochastic Fermi acceleration, synchrotron losses, shock acceleration, adiabatic expansion, and spatial diffusion. We derive the exact solution for the Fourier transform of the electron distribution and use it to compute the Fourier transform of the synchrotron radiation spectrum and the associated X-ray time lags. The same theoretical framework is also used to compute the peak flare X-ray spectrum, assuming that a steady-state electron distribution is achieved during the peak of the flare. The model parameters are constrained by comparing the theoretical predictions with the observational data for Mrk 421. The resulting integrated model yields, for the first time, a complete first-principles physical explanation for both the formation of the observed time lags and the shape of the peak flare X-ray spectrum. It also yields direct estimates of the strength of the shock and the stochastic magnetohydrodynamical wave acceleration components in the Mrk 421 jet.

Dynamics of a stochastic tuberculosis model with constant recruitment and varying total population size

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed

2017-03-01

In this paper, we develop a mathematical model for a tuberculosis model with constant recruitment and varying total population size by incorporating stochastic perturbations. By constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of an ergodic stationary distribution as well as extinction of the disease to the stochastic system.

Considering inventory distributions in a stochastic periodic inventory routing system

NASA Astrophysics Data System (ADS)

Yadollahi, Ehsan; Aghezzaf, El-Houssaine

2017-07-01

Dealing with the stochasticity of parameters is one of the critical issues in business and industry nowadays. Supply chain planners have difficulties in forecasting stochastic parameters of a distribution system. Demand rates of customers during their lead time are one of these parameters. In addition, holding a huge level of inventory at the retailers is costly and inefficient. To cover the uncertainty of forecasting demand rates, researchers have proposed the usage of safety stock to avoid stock-out. However, finding the precise level of safety stock depends on forecasting the statistical distribution of demand rates and their variations in different settings among the planning horizon. In this paper the demand rate distributions and its parameters are taken into account for each time period in a stochastic periodic IRP. An analysis of the achieved statistical distribution of the inventory and safety stock level is provided to measure the effects of input parameters on the output indicators. Different values for coefficient of variation are applied to the customers' demand rate in the optimization model. The outcome of the deterministic equivalent model of SPIRP is simulated in form of an illustrative case.

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

PubMed

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

Stochastic parameter estimation in nonlinear time-delayed vibratory systems with distributed delay

NASA Astrophysics Data System (ADS)

Torkamani, Shahab; Butcher, Eric A.

2013-07-01

The stochastic estimation of parameters and states in linear and nonlinear time-delayed vibratory systems with distributed delay is explored. The approach consists of first employing a continuous time approximation to approximate the delayed integro-differential system with a large set of ordinary differential equations having stochastic excitations. Then the problem of state and parameter estimation in the resulting stochastic ordinary differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the augmented filtering problem, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states. Similarly, the upper bound of the distributed delay can also be estimated by the proposed technique. As an illustrative example to a practical problem in vibrations, the parameter, delay upper bound, and state estimation from noise-corrupted measurements in a distributed force model widely used for modeling machine tool vibrations in the turning operation is investigated.

Transverse eV Ion Heating by Random Electric Field Fluctuations in the Plasmasphere

NASA Technical Reports Server (NTRS)

Artemyev, A. V.; Mourenas, D.; Agapitov, O. V.; Blum, L.

2017-01-01

Charged particle acceleration in the Earth inner magnetosphere is believed to be mainly due to the local resonant wave-particle interaction or particle transport processes. However, the Van Allen Probes have recently provided interesting evidence of a relatively slow transverse heating of eV ions at distances about 2-3 Earth radii during quiet times. Waves that are able to resonantly interact with such very cold ions are generally rare in this region of space, called the plasmasphere. Thus, non-resonant wave-particle interactions are expected to play an important role in the observed ion heating. We demonstrate that stochastic heating by random transverse electric field fluctuations of whistler (and possibly electromagnetic ion cyclotron) waves could explain this weak and slow transverse heating of H+ and O+ ions in the inner magnetosphere. The essential element of the proposed model of ion heating is the presence of trains of random whistler (hiss) wave packets, with significant amplitude modulations produced by strong wave damping, rapid wave growth, or a superposition of wave packets of different frequencies, phases, and amplitudes. Such characteristics correspond to measured characteristics of hiss waves in this region. Using test particle simulations with typical wave and plasma parameters, we demonstrate that the corresponding stochastic transverse ion heating reaches 0.07-0.2 eV/h for protons and 0.007-0.015 eV/h for O+ ions. This global temperature increase of the Maxwellian ion population from an initial Ti approx. 0.3 eV could potentially explain the observations.

Extended quantum jump description of vibronic two-dimensional spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albert, Julian; Falge, Mirjam; Keß, Martin

2015-06-07

We calculate two-dimensional (2D) vibronic spectra for a model system involving two electronic molecular states. The influence of a bath is simulated using a quantum-jump approach. We use a method introduced by Makarov and Metiu [J. Chem. Phys. 111, 10126 (1999)] which includes an explicit treatment of dephasing. In this way it is possible to characterize the influence of dissipation and dephasing on the 2D-spectra, using a wave function based method. The latter scales with the number of stochastic runs and the number of system eigenstates included in the expansion of the wave-packets to be propagated with the stochastic methodmore » and provides an efficient method for the calculation of the 2D-spectra.« less

Uncertainties in the 2004 Sumatra–Andaman source through nonlinear stochastic inversion of tsunami waves

PubMed Central

Venugopal, M.; Roy, D.; Rajendran, K.; Guillas, S.; Dias, F.

2017-01-01

Numerical inversions for earthquake source parameters from tsunami wave data usually incorporate subjective elements to stabilize the search. In addition, noisy and possibly insufficient data result in instability and non-uniqueness in most deterministic inversions, which are barely acknowledged. Here, we employ the satellite altimetry data for the 2004 Sumatra–Andaman tsunami event to invert the source parameters. We also include kinematic parameters that improve the description of tsunami generation and propagation, especially near the source. Using a finite fault model that represents the extent of rupture and the geometry of the trench, we perform a new type of nonlinear joint inversion of the slips, rupture velocities and rise times with minimal a priori constraints. Despite persistently good waveform fits, large uncertainties in the joint parameter distribution constitute a remarkable feature of the inversion. These uncertainties suggest that objective inversion strategies should incorporate more sophisticated physical models of seabed deformation in order to significantly improve the performance of early warning systems. PMID:28989311

Uncertainties in the 2004 Sumatra-Andaman source through nonlinear stochastic inversion of tsunami waves.

PubMed

Gopinathan, D; Venugopal, M; Roy, D; Rajendran, K; Guillas, S; Dias, F

2017-09-01

Numerical inversions for earthquake source parameters from tsunami wave data usually incorporate subjective elements to stabilize the search. In addition, noisy and possibly insufficient data result in instability and non-uniqueness in most deterministic inversions, which are barely acknowledged. Here, we employ the satellite altimetry data for the 2004 Sumatra-Andaman tsunami event to invert the source parameters. We also include kinematic parameters that improve the description of tsunami generation and propagation, especially near the source. Using a finite fault model that represents the extent of rupture and the geometry of the trench, we perform a new type of nonlinear joint inversion of the slips, rupture velocities and rise times with minimal a priori constraints. Despite persistently good waveform fits, large uncertainties in the joint parameter distribution constitute a remarkable feature of the inversion. These uncertainties suggest that objective inversion strategies should incorporate more sophisticated physical models of seabed deformation in order to significantly improve the performance of early warning systems.

Mixed Poisson distributions in exact solutions of stochastic autoregulation models.

PubMed

Iyer-Biswas, Srividya; Jayaprakash, C

2014-11-01

In this paper we study the interplay between stochastic gene expression and system design using simple stochastic models of autoactivation and autoinhibition. Using the Poisson representation, a technique whose particular usefulness in the context of nonlinear gene regulation models we elucidate, we find exact results for these feedback models in the steady state. Further, we exploit this representation to analyze the parameter spaces of each model, determine which dimensionless combinations of rates are the shape determinants for each distribution, and thus demarcate where in the parameter space qualitatively different behaviors arise. These behaviors include power-law-tailed distributions, bimodal distributions, and sub-Poisson distributions. We also show how these distribution shapes change when the strength of the feedback is tuned. Using our results, we reexamine how well the autoinhibition and autoactivation models serve their conventionally assumed roles as paradigms for noise suppression and noise exploitation, respectively.

On two mathematical problems of canonical quantization. IV

NASA Astrophysics Data System (ADS)

Kirillov, A. I.

1992-11-01

A method for solving the problem of reconstructing a measure beginning with its logarithmic derivative is presented. The method completes that of solving the stochastic differential equation via Dirichlet forms proposed by S. Albeverio and M. Rockner. As a result one obtains the mathematical apparatus for the stochastic quantization. The apparatus is applied to prove the existence of the Feynman-Kac measure of the sine-Gordon and λφ2n/(1 + K2φ2n)-models. A synthesis of both mathematical problems of canonical quantization is obtained in the form of a second-order martingale problem for vacuum noise. It is shown that in stochastic mechanics the martingale problem is an analog of Newton's second law and enables us to find the Nelson's stochastic trajectories without determining the wave functions.

Phenomenology of stochastic exponential growth

NASA Astrophysics Data System (ADS)

Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya

2017-06-01

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.

A stochastic diffusion process for Lochner's generalized Dirichlet distribution

DOE PAGES

Bakosi, J.; Ristorcelli, J. R.

2013-10-01

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner’s generalized Dirichlet distribution as its asymptotic solution. Individual samples of a discrete ensemble, obtained from the system of stochastic differential equations, equivalent to the Fokker-Planck equation developed here, satisfy a unit-sum constraint at all times and ensure a bounded sample space, similarly to the process developed in for the Dirichlet distribution. Consequently, the generalized Dirichlet diffusion process may be used to represent realizations of a fluctuating ensemble of N variables subject to a conservation principle.more » Compared to the Dirichlet distribution and process, the additional parameters of the generalized Dirichlet distribution allow a more general class of physical processes to be modeled with a more general covariance matrix.« less

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

NASA Astrophysics Data System (ADS)

Kim, Changho; Nonaka, Andy; Bell, John B.; Garcia, Alejandro L.; Donev, Aleksandar

2017-03-01

We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules, to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. By comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

DOE PAGES

Kim, Changho; Nonaka, Andy; Bell, John B.; ...

2017-03-24

Here, we develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules,more » to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. Furthermore, by comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.« less

Importance of vesicle release stochasticity in neuro-spike communication.

PubMed

Ramezani, Hamideh; Akan, Ozgur B

2017-07-01

Aim of this paper is proposing a stochastic model for vesicle release process, a part of neuro-spike communication. Hence, we study biological events occurring in this process and use microphysiological simulations to observe functionality of these events. Since the most important source of variability in vesicle release probability is opening of voltage dependent calcium channels (VDCCs) followed by influx of calcium ions through these channels, we propose a stochastic model for this event, while using a deterministic model for other variability sources. To capture the stochasticity of calcium influx to pre-synaptic neuron in our model, we study its statistics and find that it can be modeled by a distribution defined based on Normal and Logistic distributions.

Stochastic resonance based on modulation instability in spatiotemporal chaos.

PubMed

Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu

2017-04-03

A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

The Impact of an Instructional Intervention Designed to Support Development of Stochastic Understanding of Probability Distribution

ERIC Educational Resources Information Center

Conant, Darcy Lynn

2013-01-01

Stochastic understanding of probability distribution undergirds development of conceptual connections between probability and statistics and supports development of a principled understanding of statistical inference. This study investigated the impact of an instructional course intervention designed to support development of stochastic…

Noise-Induced Entrainment and Stochastic Resonance in Human Brain Waves

NASA Astrophysics Data System (ADS)

Mori, Toshio; Kai, Shoichi

2002-05-01

We present the first observation of stochastic resonance (SR) in the human brain's visual processing area. The novel experimental protocol is to stimulate the right eye with a subthreshold periodic optical signal and the left eye with a noisy one. The stimuli bypass sensory organs and are mixed in the visual cortex. With many noise sources present in the brain, higher brain functions, e.g., perception and cognition, may exploit SR.

Directional Limits on Persistent Gravitational Waves from Advanced LIGO's First Observing Run

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Beer, C.; Bejger, M.; Belahcene, I.; Belgin, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, A. S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Campbell, W.; Canepa, M.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, H.-P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conti, L.; Cooper, S. J.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, E.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Daw, E. J.; Day, B.; Day, R.; De, S.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Essick, R. C.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fernández Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fong, H.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kennedy, R.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, Whansun; Kim, W.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGrath, C.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Mytidis, A.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Rhoades, E.; Ricci, F.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schlassa, S.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T. J.; Shahriar, M. S.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson, S. P.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tao, D.; Tápai, M.; Taracchini, A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tippens, T.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tse, M.; Tso, R.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2017-03-01

We employ gravitational-wave radiometry to map the stochastic gravitational wave background expected from a variety of contributing mechanisms and test the assumption of isotropy using data from the Advanced Laser Interferometer Gravitational Wave Observatory's (aLIGO) first observing run. We also search for persistent gravitational waves from point sources with only minimal assumptions over the 20-1726 Hz frequency band. Finding no evidence of gravitational waves from either point sources or a stochastic background, we set limits at 90% confidence. For broadband point sources, we report upper limits on the gravitational wave energy flux per unit frequency in the range Fα ,Θ(f )<(0.1 - 56 )×10-8 erg cm-2 s-1 Hz-1(f /25 Hz )α -1 depending on the sky location Θ and the spectral power index α . For extended sources, we report upper limits on the fractional gravitational wave energy density required to close the Universe of Ω (f ,Θ )<(0.39 - 7.6 )×10-8 sr-1(f /25 Hz )α depending on Θ and α . Directed searches for narrowband gravitational waves from astrophysically interesting objects (Scorpius X-1, Supernova 1987 A, and the Galactic Center) yield median frequency-dependent limits on strain amplitude of h0<(6.7 ,5.5 , and 7.0 )×10-25 , respectively, at the most sensitive detector frequencies between 130-175 Hz. This represents a mean improvement of a factor of 2 across the band compared to previous searches of this kind for these sky locations, considering the different quantities of strain constrained in each case.

[Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy].

PubMed

Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming

2018-04-01

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

Finite-Difference Modeling of Seismic Wave Scattering in 3D Heterogeneous Media: Generation of Tangential Motion from an Explosion Source

NASA Astrophysics Data System (ADS)

Hirakawa, E. T.; Pitarka, A.; Mellors, R. J.

2015-12-01

Evan Hirakawa, Arben Pitarka, and Robert Mellors One challenging task in explosion seismology is development of physical models for explaining the generation of S-waves during underground explosions. Pitarka et al. (2015) used finite difference simulations of SPE-3 (part of Source Physics Experiment, SPE, an ongoing series of underground chemical explosions at the Nevada National Security Site) and found that while a large component of shear motion was generated directly at the source, additional scattering from heterogeneous velocity structure and topography are necessary to better match the data. Large-scale features in the velocity model used in the SPE simulations are well constrained, however, small-scale heterogeneity is poorly constrained. In our study we used a stochastic representation of small-scale variability in order to produce additional high-frequency scattering. Two methods for generating the distributions of random scatterers are tested. The first is done in the spatial domain by essentially smoothing a set of random numbers over an ellipsoidal volume using a Gaussian weighting function. The second method consists of filtering a set of random numbers in the wavenumber domain to obtain a set of heterogeneities with a desired statistical distribution (Frankel and Clayton, 1986). This method is capable of generating distributions with either Gaussian or von Karman autocorrelation functions. The key parameters that affect scattering are the correlation length, the standard deviation of velocity for the heterogeneities, and the Hurst exponent, which is only present in the von Karman media. Overall, we find that shorter correlation lengths as well as higher standard deviations result in increased tangential motion in the frequency band of interest (0 - 10 Hz). This occurs partially through S-wave refraction, but mostly by P-S and Rg-S waves conversions. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344

Stochastic Lagrangian dynamics for charged flows in the E-F regions of ionosphere

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang Wenbo; Mahalov, Alex

2013-03-15

We develop a three-dimensional numerical model for the E-F region ionosphere and study the Lagrangian dynamics for plasma flows in this region. Our interest rests on the charge-neutral interactions and the statistics associated with stochastic Lagrangian motion. In particular, we examine the organizing mixing patterns for plasma flows due to polarized gravity wave excitations in the neutral field, using Lagrangian coherent structures (LCS). LCS objectively depict the flow topology-the extracted attractors indicate generation of ionospheric density gradients, due to accumulation of plasma. Using Lagrangian measures such as the finite-time Lyapunov exponents, we locate the Lagrangian skeletons for mixing in plasma,more » hence where charged fronts are expected to appear. With polarized neutral wind, we find that the corresponding plasma velocity is also polarized. Moreover, the polarized velocity alone, coupled with stochastic Lagrangian motion, may give rise to polarized density fronts in plasma. Statistics of these trajectories indicate high level of non-Gaussianity. This includes clear signatures of variance, skewness, and kurtosis of displacements taking polarized structures aligned with the gravity waves, and being anisotropic.« less

Stochastic Template Bank for Gravitational Wave Searches for Precessing Neutron Star-Black Hole Coalescence Events

NASA Technical Reports Server (NTRS)

Indik, Nathaniel; Haris, K.; Dal Canton, Tito; Fehrmann, Henning; Krishnan, Badri; Lundgren, Andrew; Nielsen, Alex B.; Pai, Archana

2017-01-01

Gravitational wave searches to date have largely focused on non-precessing systems. Including precession effects greatly increases the number of templates to be searched over. This leads to a corresponding increase in the computational cost and can increase the false alarm rate of a realistic search. On the other hand, there might be astrophysical systems that are entirely missed by non-precessing searches. In this paper we consider the problem of constructing a template bank using stochastic methods for neutron star-black hole binaries allowing for precession, but with the restrictions that the total angular momentum of the binary is pointing toward the detector and that the neutron star spin is negligible relative to that of the black hole. We quantify the number of templates required for the search, and we explicitly construct the template bank. We show that despite the large number of templates, stochastic methods can be adapted to solve the problem. We quantify the parameter space region over which the non-precessing search might miss signals.

Deterministic alternatives to the full configuration interaction quantum Monte Carlo method for strongly correlated systems

NASA Astrophysics Data System (ADS)

Tubman, Norm; Whaley, Birgitta

The development of exponential scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, allows exact diagonalization through stochastically sampling of determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, together with a stochastic projected wave function, which are used to explore the important parts of Hilbert space. However, a stochastic representation of the wave function is not required to search Hilbert space efficiently and new deterministic approaches have recently been shown to efficiently find the important parts of determinant space. We shall discuss the technique of Adaptive Sampling Configuration Interaction (ASCI) and the related heat-bath Configuration Interaction approach for ground state and excited state simulations. We will present several applications for strongly correlated Hamiltonians. This work was supported through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences.

Capture of fixation by rotational flow; a deterministic hypothesis regarding scaling and stochasticity in fixational eye movements

PubMed Central

Wilkinson, Nicholas M.; Metta, Giorgio

2014-01-01

Visual scan paths exhibit complex, stochastic dynamics. Even during visual fixation, the eye is in constant motion. Fixational drift and tremor are thought to reflect fluctuations in the persistent neural activity of neural integrators in the oculomotor brainstem, which integrate sequences of transient saccadic velocity signals into a short term memory of eye position. Despite intensive research and much progress, the precise mechanisms by which oculomotor posture is maintained remain elusive. Drift exhibits a stochastic statistical profile which has been modeled using random walk formalisms. Tremor is widely dismissed as noise. Here we focus on the dynamical profile of fixational tremor, and argue that tremor may be a signal which usefully reflects the workings of oculomotor postural control. We identify signatures reminiscent of a certain flavor of transient neurodynamics; toric traveling waves which rotate around a central phase singularity. Spiral waves play an organizational role in dynamical systems at many scales throughout nature, though their potential functional role in brain activity remains a matter of educated speculation. Spiral waves have a repertoire of functionally interesting dynamical properties, including persistence, which suggest that they could in theory contribute to persistent neural activity in the oculomotor postural control system. Whilst speculative, the singularity hypothesis of oculomotor postural control implies testable predictions, and could provide the beginnings of an integrated dynamical framework for eye movements across scales. PMID:24616670

Hybrid geometric-random template-placement algorithm for gravitational wave searches from compact binary coalescences

NASA Astrophysics Data System (ADS)

Roy, Soumen; Sengupta, Anand S.; Thakor, Nilay

2017-05-01

Astrophysical compact binary systems consisting of neutron stars and black holes are an important class of gravitational wave (GW) sources for advanced LIGO detectors. Accurate theoretical waveform models from the inspiral, merger, and ringdown phases of such systems are used to filter detector data under the template-based matched-filtering paradigm. An efficient grid over the parameter space at a fixed minimal match has a direct impact on the overall time taken by these searches. We present a new hybrid geometric-random template placement algorithm for signals described by parameters of two masses and one spin magnitude. Such template banks could potentially be used in GW searches from binary neutron stars and neutron star-black hole systems. The template placement is robust and is able to automatically accommodate curvature and boundary effects with no fine-tuning. We also compare these banks against vanilla stochastic template banks and show that while both are equally efficient in the fitting-factor sense, the bank sizes are ˜25 % larger in the stochastic method. Further, we show that the generation of the proposed hybrid banks can be sped up by nearly an order of magnitude over the stochastic bank. Generic issues related to optimal implementation are discussed in detail. These improvements are expected to directly reduce the computational cost of gravitational wave searches.

Low-complexity stochastic modeling of wall-bounded shear flows

NASA Astrophysics Data System (ADS)

Zare, Armin

Turbulent flows are ubiquitous in nature and they appear in many engineering applications. Transition to turbulence, in general, increases skin-friction drag in air/water vehicles compromising their fuel-efficiency and reduces the efficiency and longevity of wind turbines. While traditional flow control techniques combine physical intuition with costly experiments, their effectiveness can be significantly enhanced by control design based on low-complexity models and optimization. In this dissertation, we develop a theoretical and computational framework for the low-complexity stochastic modeling of wall-bounded shear flows. Part I of the dissertation is devoted to the development of a modeling framework which incorporates data-driven techniques to refine physics-based models. We consider the problem of completing partially known sample statistics in a way that is consistent with underlying stochastically driven linear dynamics. Neither the statistics nor the dynamics are precisely known. Thus, our objective is to reconcile the two in a parsimonious manner. To this end, we formulate optimization problems to identify the dynamics and directionality of input excitation in order to explain and complete available covariance data. For problem sizes that general-purpose solvers cannot handle, we develop customized optimization algorithms based on alternating direction methods. The solution to the optimization problem provides information about critical directions that have maximal effect in bringing model and statistics in agreement. In Part II, we employ our modeling framework to account for statistical signatures of turbulent channel flow using low-complexity stochastic dynamical models. We demonstrate that white-in-time stochastic forcing is not sufficient to explain turbulent flow statistics and develop models for colored-in-time forcing of the linearized Navier-Stokes equations. We also examine the efficacy of stochastically forced linearized NS equations and their parabolized equivalents in the receptivity analysis of velocity fluctuations to external sources of excitation as well as capturing the effect of the slowly-varying base flow on streamwise streaks and Tollmien-Schlichting waves. In Part III, we develop a model-based approach to design surface actuation of turbulent channel flow in the form of streamwise traveling waves. This approach is capable of identifying the drag reducing trends of traveling waves in a simulation-free manner. We also use the stochastically forced linearized NS equations to examine the Reynolds number independent effects of spanwise wall oscillations on drag reduction in turbulent channel flows. This allows us to extend the predictive capability of our simulation-free approach to high Reynolds numbers.

An efficient distribution method for nonlinear transport problems in highly heterogeneous stochastic porous media

NASA Astrophysics Data System (ADS)

Ibrahima, Fayadhoi; Meyer, Daniel; Tchelepi, Hamdi

2016-04-01

Because geophysical data are inexorably sparse and incomplete, stochastic treatments of simulated responses are crucial to explore possible scenarios and assess risks in subsurface problems. In particular, nonlinear two-phase flows in porous media are essential, yet challenging, in reservoir simulation and hydrology. Adding highly heterogeneous and uncertain input, such as the permeability and porosity fields, transforms the estimation of the flow response into a tough stochastic problem for which computationally expensive Monte Carlo (MC) simulations remain the preferred option.We propose an alternative approach to evaluate the probability distribution of the (water) saturation for the stochastic Buckley-Leverett problem when the probability distributions of the permeability and porosity fields are available. We give a computationally efficient and numerically accurate method to estimate the one-point probability density (PDF) and cumulative distribution functions (CDF) of the (water) saturation. The distribution method draws inspiration from a Lagrangian approach of the stochastic transport problem and expresses the saturation PDF and CDF essentially in terms of a deterministic mapping and the distribution and statistics of scalar random fields. In a large class of applications these random fields can be estimated at low computational costs (few MC runs), thus making the distribution method attractive. Even though the method relies on a key assumption of fixed streamlines, we show that it performs well for high input variances, which is the case of interest. Once the saturation distribution is determined, any one-point statistics thereof can be obtained, especially the saturation average and standard deviation. Moreover, the probability of rare events and saturation quantiles (e.g. P10, P50 and P90) can be efficiently derived from the distribution method. These statistics can then be used for risk assessment, as well as data assimilation and uncertainty reduction in the prior knowledge of input distributions. We provide various examples and comparisons with MC simulations to illustrate the performance of the method.

SOLAR INTERACTING PROTONS VERSUS INTERPLANETARY PROTONS IN THE CORE PLUS HALO MODEL OF DIFFUSIVE SHOCK ACCELERATION AND STOCHASTIC RE-ACCELERATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kocharov, L.; Laitinen, T.; Vainio, R.

2015-06-10

With the first observations of solar γ-rays from the decay of pions, the relationship of protons producing ground level enhancements (GLEs) on the Earth to those of similar energies producing the γ-rays on the Sun has been debated. These two populations may be either independent and simply coincident in large flares, or they may be, in fact, the same population stemming from a single accelerating agent and jointly distributed at the Sun and also in space. Assuming the latter, we model a scenario in which particles are accelerated near the Sun in a shock wave with a fraction transported backmore » to the solar surface to radiate, while the remainder is detected at Earth in the form of a GLE. Interplanetary ions versus ions interacting at the Sun are studied for a spherical shock wave propagating in a radial magnetic field through a highly turbulent radial ray (the acceleration core) and surrounding weakly turbulent sector in which the accelerated particles can propagate toward or away from the Sun. The model presented here accounts for both the first-order Fermi acceleration at the shock front and the second-order, stochastic re-acceleration by the turbulence enhanced behind the shock. We find that the re-acceleration is important in generating the γ-radiation and we also find that up to 10% of the particle population can find its way to the Sun as compared to particles escaping to the interplanetary space.« less

Dynamics of a Stochastic Predator-Prey Model with Stage Structure for Predator and Holling Type II Functional Response

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing; Hayat, Tasawar; Alsaedi, Ahmed

2018-01-01

In this paper, we develop and study a stochastic predator-prey model with stage structure for predator and Holling type II functional response. First of all, by constructing a suitable stochastic Lyapunov function, we establish sufficient conditions for the existence and uniqueness of an ergodic stationary distribution of the positive solutions to the model. Then, we obtain sufficient conditions for extinction of the predator populations in two cases, that is, the first case is that the prey population survival and the predator populations extinction; the second case is that all the prey and predator populations extinction. The existence of a stationary distribution implies stochastic weak stability. Numerical simulations are carried out to demonstrate the analytical results.

Dynamics of a Stochastic Predator-Prey Model with Stage Structure for Predator and Holling Type II Functional Response

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing; Hayat, Tasawar; Alsaedi, Ahmed

2018-06-01

In this paper, we develop and study a stochastic predator-prey model with stage structure for predator and Holling type II functional response. First of all, by constructing a suitable stochastic Lyapunov function, we establish sufficient conditions for the existence and uniqueness of an ergodic stationary distribution of the positive solutions to the model. Then, we obtain sufficient conditions for extinction of the predator populations in two cases, that is, the first case is that the prey population survival and the predator populations extinction; the second case is that all the prey and predator populations extinction. The existence of a stationary distribution implies stochastic weak stability. Numerical simulations are carried out to demonstrate the analytical results.

Charge and energy migration in molecular clusters: A stochastic Schrödinger equation approach.

PubMed

Plehn, Thomas; May, Volkhard

2017-01-21

The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented. It starts with the finite temperature reduced density operator expanded in coherent reservoir states and ends up with two linear stochastic Schrödinger equations. Both equations are valid in the weak and intermediate coupling limit and can be properly related to two existing approaches in literature. In the second part, we focus on the numerical solution of these equations. The main issue is the missing norm conservation of the wave function propagation which may lead to numerical discrepancies. To illustrate this, we simulate the exciton dynamics in the Fenna-Matthews-Olson complex in direct comparison with the data from literature. Subsequently a strategy for the proper computational handling of the linear stochastic Schrödinger equation is exposed particularly with regard to large systems. Here, we study charge carrier transfer kinetics in realistic hybrid organic/inorganic para-sexiphenyl/ZnO systems of different extension.

Proper orthogonal decomposition-based spectral higher-order stochastic estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baars, Woutijn J., E-mail: wbaars@unimelb.edu.au; Tinney, Charles E.

A unique routine, capable of identifying both linear and higher-order coherence in multiple-input/output systems, is presented. The technique combines two well-established methods: Proper Orthogonal Decomposition (POD) and Higher-Order Spectra Analysis. The latter of these is based on known methods for characterizing nonlinear systems by way of Volterra series. In that, both linear and higher-order kernels are formed to quantify the spectral (nonlinear) transfer of energy between the system's input and output. This reduces essentially to spectral Linear Stochastic Estimation when only first-order terms are considered, and is therefore presented in the context of stochastic estimation as spectral Higher-Order Stochastic Estimationmore » (HOSE). The trade-off to seeking higher-order transfer kernels is that the increased complexity restricts the analysis to single-input/output systems. Low-dimensional (POD-based) analysis techniques are inserted to alleviate this void as POD coefficients represent the dynamics of the spatial structures (modes) of a multi-degree-of-freedom system. The mathematical framework behind this POD-based HOSE method is first described. The method is then tested in the context of jet aeroacoustics by modeling acoustically efficient large-scale instabilities as combinations of wave packets. The growth, saturation, and decay of these spatially convecting wave packets are shown to couple both linearly and nonlinearly in the near-field to produce waveforms that propagate acoustically to the far-field for different frequency combinations.« less

Charge and energy migration in molecular clusters: A stochastic Schrödinger equation approach

NASA Astrophysics Data System (ADS)

Plehn, Thomas; May, Volkhard

2017-01-01

The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented. It starts with the finite temperature reduced density operator expanded in coherent reservoir states and ends up with two linear stochastic Schrödinger equations. Both equations are valid in the weak and intermediate coupling limit and can be properly related to two existing approaches in literature. In the second part, we focus on the numerical solution of these equations. The main issue is the missing norm conservation of the wave function propagation which may lead to numerical discrepancies. To illustrate this, we simulate the exciton dynamics in the Fenna-Matthews-Olson complex in direct comparison with the data from literature. Subsequently a strategy for the proper computational handling of the linear stochastic Schrödinger equation is exposed particularly with regard to large systems. Here, we study charge carrier transfer kinetics in realistic hybrid organic/inorganic para-sexiphenyl/ZnO systems of different extension.

Optimal Operation of Energy Storage in Power Transmission and Distribution

NASA Astrophysics Data System (ADS)

Akhavan Hejazi, Seyed Hossein

In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider uncertainty from various elements, such as solar photovoltaic , electric vehicle chargers, and residential baseloads, in the form of discrete probability functions. In the last part of this thesis we address some other resources and concepts for enhancing the operation of power distribution and transmission systems. In particular, we proposed a new framework to determine the best sites, sizes, and optimal payment incentives under special contracts for committed-type DG projects to offset distribution network investment costs. In this framework, the aim is to allocate DGs such that the profit gained by the distribution company is maximized while each DG unit's individual profit is also taken into account to assure that private DG investment remains economical.

Breast ultrasound computed tomography using waveform inversion with source encoding

NASA Astrophysics Data System (ADS)

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A.

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm2 reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

Emergence of traveling waves in the spreading of dengue fever

NASA Astrophysics Data System (ADS)

Bianco, Simone; Faatz, Andrea; Cummings, Derek; Shaw, Leah

2010-03-01

Dengue fever is a multistrain mosquito-borne subtropical disease that exhibits complex oscillatory outbreaks. Epidemiological data from Thailand displays traveling waves of infection originating in Bangkok, the largest population center (Cummings et al., Nature 427: 344, 2004). We present a multistrain metapopulation model in which traveling wave like behavior results from migration coupling between heterogeneous regions. The region with the highest effective person-to-person contact rate leads the dynamics. A stochastic version of the model will also be presented.

Unidirectional random growth with resetting

NASA Astrophysics Data System (ADS)

Biró, T. S.; Néda, Z.

2018-06-01

We review stochastic processes without detailed balance condition and derive their H-theorem. We obtain stationary distributions and investigate their stability in terms of generalized entropic distances beyond the Kullback-Leibler formula. A simple stochastic model with local growth rates and direct resetting to the ground state is investigated and applied to various networks, scientific citations and Facebook popularity, hadronic yields in high energy particle reactions, income and wealth distributions, biodiversity and settlement size distributions.

THE DISTRIBUTION OF ROUNDS FIRED IN STOCHASTIC DUELS

DTIC Science & Technology

This paper continues the development of the theory of Stochastic Duels to include the distribution of the number of rounds fired. Most generally...the duel between two contestants who fire at each other with constant kill probabilities per round is considered. The time between rounds fired may be...at the beginning of the duel may be limited and is a discrete random variable. Besides the distribution of rounds fired, its first two moments and

Topological supersymmetry breaking: The definition and stochastic generalization of chaos and the limit of applicability of statistics

NASA Astrophysics Data System (ADS)

Ovchinnikov, Igor V.; Schwartz, Robert N.; Wang, Kang L.

2016-03-01

The concept of deterministic dynamical chaos has a long history and is well established by now. Nevertheless, its field theoretic essence and its stochastic generalization have been revealed only very recently. Within the newly found supersymmetric theory of stochastics (STS), all stochastic differential equations (SDEs) possess topological or de Rahm supersymmetry and stochastic chaos is the phenomenon of its spontaneous breakdown. Even though the STS is free of approximations and thus is technically solid, it is still missing a firm interpretational basis in order to be physically sound. Here, we make a few important steps toward the construction of the interpretational foundation for the STS. In particular, we discuss that one way to understand why the ground states of chaotic SDEs are conditional (not total) probability distributions, is that some of the variables have infinite memory of initial conditions and thus are not “thermalized”, i.e., cannot be described by the initial-conditions-independent probability distributions. As a result, the definitive assumption of physical statistics that the ground state is a steady-state total probability distribution is not valid for chaotic SDEs.

Sea ice floe size distribution in the marginal ice zone: Theory and numerical experiments

NASA Astrophysics Data System (ADS)

Zhang, Jinlun; Schweiger, Axel; Steele, Michael; Stern, Harry

2015-05-01

To better describe the state of sea ice in the marginal ice zone (MIZ) with floes of varying thicknesses and sizes, both an ice thickness distribution (ITD) and a floe size distribution (FSD) are needed. In this work, we have developed a FSD theory that is coupled to the ITD theory of Thorndike et al. (1975) in order to explicitly simulate the evolution of FSD and ITD jointly. The FSD theory includes a FSD function and a FSD conservation equation in parallel with the ITD equation. The FSD equation takes into account changes in FSD due to ice advection, thermodynamic growth, and lateral melting. It also includes changes in FSD because of mechanical redistribution of floe size due to ice ridging and, particularly, ice fragmentation induced by stochastic ocean surface waves. The floe size redistribution due to ice fragmentation is based on the assumption that wave-induced breakup is a random process such that when an ice floe is broken, floes of any smaller sizes have an equal opportunity to form, without being either favored or excluded. To focus only on the properties of mechanical floe size redistribution, the FSD theory is implemented in a simplified ITD and FSD sea ice model for idealized numerical experiments. Model results show that the simulated cumulative floe number distribution (CFND) follows a power law as observed by satellites and airborne surveys. The simulated values of the exponent of the power law, with varying levels of ice breakups, are also in the range of the observations. It is found that floe size redistribution and the resulting FSD and mean floe size do not depend on how floe size categories are partitioned over a given floe size range. The ability to explicitly simulate multicategory FSD and ITD together may help to incorporate additional model physics, such as FSD-dependent ice mechanics, surface exchange of heat, mass, and momentum, and wave-ice interactions.

Combining deterministic and stochastic velocity fields in the analysis of deep crustal seismic data

NASA Astrophysics Data System (ADS)

Larkin, Steven Paul

Standard crustal seismic modeling obtains deterministic velocity models which ignore the effects of wavelength-scale heterogeneity, known to exist within the Earth's crust. Stochastic velocity models are a means to include wavelength-scale heterogeneity in the modeling. These models are defined by statistical parameters obtained from geologic maps of exposed crystalline rock, and are thus tied to actual geologic structures. Combining both deterministic and stochastic velocity models into a single model allows a realistic full wavefield (2-D) to be computed. By comparing these simulations to recorded seismic data, the effects of wavelength-scale heterogeneity can be investigated. Combined deterministic and stochastic velocity models are created for two datasets, the 1992 RISC seismic experiment in southeastern California and the 1986 PASSCAL seismic experiment in northern Nevada. The RISC experiment was located in the transition zone between the Salton Trough and the southern Basin and Range province. A high-velocity body previously identified beneath the Salton Trough is constrained to pinch out beneath the Chocolate Mountains to the northeast. The lateral extent of this body is evidence for the ephemeral nature of rifting loci as a continent is initially rifted. Stochastic modeling of wavelength-scale structures above this body indicate that little more than 5% mafic intrusion into a more felsic continental crust is responsible for the observed reflectivity. Modeling of the wide-angle RISC data indicates that coda waves following PmP are initially dominated by diffusion of energy out of the near-surface basin as the wavefield reverberates within this low-velocity layer. At later times, this coda consists of scattered body waves and P to S conversions. Surface waves do not play a significant role in this coda. Modeling of the PASSCAL dataset indicates that a high-gradient crust-mantle transition zone or a rough Moho interface is necessary to reduce precritical PmP energy. Possibly related, inconsistencies in published velocity models are rectified by hypothesizing the existence of large, elongate, high-velocity bodies at the base of the crust oriented to and of similar scale as the basins and ranges at the surface. This structure would result in an anisotropic lower crust.

Measuring the Binary Black Hole Mass Spectrum with an Astrophysically Motivated Parameterization

NASA Astrophysics Data System (ADS)

Talbot, Colm; Thrane, Eric

2018-04-01

Gravitational-wave detections have revealed a previously unknown population of stellar mass black holes with masses above 20 M ⊙. These observations provide a new way to test models of stellar evolution for massive stars. By considering the astrophysical processes likely to determine the shape of the binary black hole mass spectrum, we construct a parameterized model to capture key spectral features that relate gravitational-wave data to theoretical stellar astrophysics. In particular, we model the signature of pulsational pair-instability supernovae, which are expected to cause all stars with initial mass 100 M ⊙ ≲ M ≲ 150 M ⊙ to form ∼40 M ⊙ black holes. This would cause a cutoff in the black hole mass spectrum along with an excess of black holes near 40 M ⊙. We carry out a simulated data study to illustrate some of the stellar physics that can be inferred using gravitational-wave measurements of binary black holes and demonstrate several such inferences that might be made in the near future. First, we measure the minimum and maximum stellar black hole mass. Second, we infer the presence of a peak due to pair-instability supernovae. Third, we measure the distribution of black hole mass ratios. Finally, we show how inadequate models of the black hole mass spectrum lead to biased estimates of the merger rate and the amplitude of the stochastic gravitational-wave background.

Directional Limits on Persistent Gravitational Waves from Advanced LIGO's First Observing Run.

PubMed

Abbott, B P; Abbott, R; Abbott, T D; Abernathy, M R; Acernese, F; Ackley, K; Adams, C; Adams, T; Addesso, P; Adhikari, R X; Adya, V B; Affeldt, C; Agathos, M; Agatsuma, K; Aggarwal, N; Aguiar, O D; Aiello, L; Ain, A; Ajith, P; Allen, B; Allocca, A; Altin, P A; Ananyeva, A; Anderson, S B; Anderson, W G; Appert, S; Arai, K; Araya, M C; Areeda, J S; Arnaud, N; Arun, K G; Ascenzi, S; Ashton, G; Ast, M; Aston, S M; Astone, P; Aufmuth, P; Aulbert, C; Avila-Alvarez, A; Babak, S; Bacon, P; Bader, M K M; Baker, P T; Baldaccini, F; Ballardin, G; Ballmer, S W; Barayoga, J C; Barclay, S E; Barish, B C; Barker, D; Barone, F; Barr, B; Barsotti, L; Barsuglia, M; Barta, D; Bartlett, J; Bartos, I; Bassiri, R; Basti, A; Batch, J C; Baune, C; Bavigadda, V; Bazzan, M; Beer, C; Bejger, M; Belahcene, I; Belgin, M; Bell, A S; Berger, B K; Bergmann, G; Berry, C P L; Bersanetti, D; Bertolini, A; Betzwieser, J; Bhagwat, S; Bhandare, R; Bilenko, I A; Billingsley, G; Billman, C R; Birch, J; Birney, R; Birnholtz, O; Biscans, S; Biscoveanu, A S; Bisht, A; Bitossi, M; Biwer, C; Bizouard, M A; Blackburn, J K; Blackman, J; Blair, C D; Blair, D G; Blair, R M; Bloemen, S; Bock, O; Boer, M; Bogaert, G; Bohe, A; Bondu, F; Bonnand, R; Boom, B A; Bork, R; Boschi, V; Bose, S; Bouffanais, Y; Bozzi, A; Bradaschia, C; Brady, P R; Braginsky, V B; Branchesi, M; Brau, J E; Briant, T; Brillet, A; Brinkmann, M; Brisson, V; Brockill, P; Broida, J E; Brooks, A F; Brown, D A; Brown, D D; Brown, N M; Brunett, S; Buchanan, C C; Buikema, A; Bulik, T; Bulten, H J; Buonanno, A; Buskulic, D; Buy, C; Byer, R L; Cabero, M; Cadonati, L; Cagnoli, G; Cahillane, C; Calderón Bustillo, J; Callister, T A; Calloni, E; Camp, J B; Campbell, W; Canepa, M; Cannon, K C; Cao, H; Cao, J; Capano, C D; Capocasa, E; Carbognani, F; Caride, S; Casanueva Diaz, J; Casentini, C; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Cella, G; Cepeda, C B; Cerboni Baiardi, L; Cerretani, G; Cesarini, E; Chamberlin, S J; Chan, M; Chao, S; Charlton, P; Chassande-Mottin, E; Cheeseboro, B D; Chen, H Y; Chen, Y; Cheng, H-P; Chincarini, A; Chiummo, A; Chmiel, T; Cho, H S; Cho, M; Chow, J H; Christensen, N; Chu, Q; Chua, A J K; Chua, S; Chung, S; Ciani, G; Clara, F; Clark, J A; Cleva, F; Cocchieri, C; Coccia, E; Cohadon, P-F; Colla, A; Collette, C G; Cominsky, L; Constancio, M; Conti, L; Cooper, S J; Corbitt, T R; Cornish, N; Corsi, A; Cortese, S; Costa, C A; Coughlin, E; Coughlin, M W; Coughlin, S B; Coulon, J-P; Countryman, S T; Couvares, P; Covas, P B; Cowan, E E; Coward, D M; Cowart, M J; Coyne, D C; Coyne, R; Creighton, J D E; Creighton, T D; Cripe, J; Crowder, S G; Cullen, T J; Cumming, A; Cunningham, L; Cuoco, E; Dal Canton, T; Danilishin, S L; D'Antonio, S; Danzmann, K; Dasgupta, A; Da Silva Costa, C F; Dattilo, V; Dave, I; Davier, M; Davies, G S; Davis, D; Daw, E J; Day, B; Day, R; De, S; DeBra, D; Debreczeni, G; Degallaix, J; De Laurentis, M; Deléglise, S; Del Pozzo, W; Denker, T; Dent, T; Dergachev, V; De Rosa, R; DeRosa, R T; DeSalvo, R; Devenson, J; Devine, R C; Dhurandhar, S; Díaz, M C; Di Fiore, L; Di Giovanni, M; Di Girolamo, T; Di Lieto, A; Di Pace, S; Di Palma, I; Di Virgilio, A; Doctor, Z; Dolique, V; Donovan, F; Dooley, K L; Doravari, S; Dorrington, I; Douglas, R; Dovale Álvarez, M; Downes, T P; Drago, M; Drever, R W P; Driggers, J C; Du, Z; Ducrot, M; Dwyer, S E; Edo, T B; Edwards, M C; Effler, A; Eggenstein, H-B; Ehrens, P; Eichholz, J; Eikenberry, S S; Essick, R C; Etienne, Z; Etzel, T; Evans, M; Evans, T M; Everett, R; Factourovich, M; Fafone, V; Fair, H; Fairhurst, S; Fan, X; Farinon, S; Farr, B; Farr, W M; Fauchon-Jones, E J; Favata, M; Fays, M; Fehrmann, H; Fejer, M M; Fernández Galiana, A; Ferrante, I; Ferreira, E C; Ferrini, F; Fidecaro, F; Fiori, I; Fiorucci, D; Fisher, R P; Flaminio, R; Fletcher, M; Fong, H; Forsyth, S S; Fournier, J-D; Frasca, S; Frasconi, F; Frei, Z; Freise, A; Frey, R; Frey, V; Fries, E M; Fritschel, P; Frolov, V V; Fulda, P; Fyffe, M; Gabbard, H; Gadre, B U; Gaebel, S M; Gair, J R; Gammaitoni, L; Gaonkar, S G; Garufi, F; Gaur, G; Gayathri, V; Gehrels, N; Gemme, G; Genin, E; Gennai, A; George, J; Gergely, L; Germain, V; Ghonge, S; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S; Giaime, J A; Giardina, K D; Giazotto, A; Gill, K; Glaefke, A; Goetz, E; Goetz, R; Gondan, L; González, G; Gonzalez Castro, J M; Gopakumar, A; Gorodetsky, M L; Gossan, S E; Gosselin, M; Gouaty, R; Grado, A; Graef, C; Granata, M; Grant, A; Gras, S; Gray, C; Greco, G; Green, A C; Groot, P; Grote, H; Grunewald, S; Guidi, G M; Guo, X; Gupta, A; Gupta, M K; Gushwa, K E; Gustafson, E K; Gustafson, R; Hacker, J J; Hall, B R; Hall, E D; Hammond, G; Haney, M; Hanke, M M; Hanks, J; Hanna, C; Hannam, M D; Hanson, J; Hardwick, T; Harms, J; Harry, G M; Harry, I W; Hart, M J; Hartman, M T; Haster, C-J; Haughian, K; Healy, J; Heidmann, A; Heintze, M C; Heitmann, H; Hello, P; Hemming, G; Hendry, M; Heng, I S; Hennig, J; Henry, J; Heptonstall, A W; Heurs, M; Hild, S; Hoak, D; Hofman, D; Holt, K; Holz, D E; Hopkins, P; Hough, J; Houston, E A; Howell, E J; Hu, Y M; Huerta, E A; Huet, D; Hughey, B; Husa, S; Huttner, S H; Huynh-Dinh, T; Indik, N; Ingram, D R; Inta, R; Isa, H N; Isac, J-M; Isi, M; Isogai, T; Iyer, B R; Izumi, K; Jacqmin, T; Jani, K; Jaranowski, P; Jawahar, S; Jiménez-Forteza, F; Johnson, W W; Jones, D I; Jones, R; Jonker, R J G; Ju, L; Junker, J; Kalaghatgi, C V; Kalogera, V; Kandhasamy, S; Kang, G; Kanner, J B; Karki, S; Karvinen, K S; Kasprzack, M; Katsavounidis, E; Katzman, W; Kaufer, S; Kaur, T; Kawabe, K; Kéfélian, F; Keitel, D; Kelley, D B; Kennedy, R; Key, J S; Khalili, F Y; Khan, I; Khan, S; Khan, Z; Khazanov, E A; Kijbunchoo, N; Kim, Chunglee; Kim, J C; Kim, Whansun; Kim, W; Kim, Y-M; Kimbrell, S J; King, E J; King, P J; Kirchhoff, R; Kissel, J S; Klein, B; Kleybolte, L; Klimenko, S; Koch, P; Koehlenbeck, S M; Koley, S; Kondrashov, V; Kontos, A; Korobko, M; Korth, W Z; Kowalska, I; Kozak, D B; Krämer, C; Kringel, V; Królak, A; Kuehn, G; Kumar, P; Kumar, R; Kuo, L; Kutynia, A; Lackey, B D; Landry, M; Lang, R N; Lange, J; Lantz, B; Lanza, R K; Lartaux-Vollard, A; Lasky, P D; Laxen, M; Lazzarini, A; Lazzaro, C; Leaci, P; Leavey, S; Lebigot, E O; Lee, C H; Lee, H K; Lee, H M; Lee, K; Lehmann, J; Lenon, A; Leonardi, M; Leong, J R; Leroy, N; Letendre, N; Levin, Y; Li, T G F; Libson, A; Littenberg, T B; Liu, J; Lockerbie, N A; Lombardi, A L; London, L T; Lord, J E; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lough, J D; Lousto, C O; Lovelace, G; Lück, H; Lundgren, A P; Lynch, R; Ma, Y; Macfoy, S; Machenschalk, B; MacInnis, M; Macleod, D M; Magaña-Sandoval, F; Majorana, E; Maksimovic, I; Malvezzi, V; Man, N; Mandic, V; Mangano, V; Mansell, G L; Manske, M; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markosyan, A S; Maros, E; Martelli, F; Martellini, L; Martin, I W; Martynov, D V; Mason, K; Masserot, A; Massinger, T J; Masso-Reid, M; Mastrogiovanni, S; Matas, A; Matichard, F; Matone, L; Mavalvala, N; Mazumder, N; McCarthy, R; McClelland, D E; McCormick, S; McGrath, C; McGuire, S C; McIntyre, G; McIver, J; McManus, D J; McRae, T; McWilliams, S T; Meacher, D; Meadors, G D; Meidam, J; Melatos, A; Mendell, G; Mendoza-Gandara, D; Mercer, R A; Merilh, E L; Merzougui, M; Meshkov, S; Messenger, C; Messick, C; Metzdorff, R; Meyers, P M; Mezzani, F; Miao, H; Michel, C; Middleton, H; Mikhailov, E E; Milano, L; Miller, A L; Miller, A; Miller, B B; Miller, J; Millhouse, M; Minenkov, Y; Ming, J; Mirshekari, S; Mishra, C; Mitra, S; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Moggi, A; Mohan, M; Mohapatra, S R P; Montani, M; Moore, B C; Moore, C J; Moraru, D; Moreno, G; Morriss, S R; Mours, B; Mow-Lowry, C M; Mueller, G; Muir, A W; Mukherjee, Arunava; Mukherjee, D; Mukherjee, S; Mukund, N; Mullavey, A; Munch, J; Muniz, E A M; Murray, P G; Mytidis, A; Napier, K; Nardecchia, I; Naticchioni, L; Nelemans, G; Nelson, T J N; Neri, M; Nery, M; Neunzert, A; Newport, J M; Newton, G; Nguyen, T T; Nielsen, A B; Nissanke, S; Nitz, A; Noack, A; Nocera, F; Nolting, D; Normandin, M E N; Nuttall, L K; Oberling, J; Ochsner, E; Oelker, E; Ogin, G H; Oh, J J; Oh, S H; Ohme, F; Oliver, M; Oppermann, P; Oram, Richard J; O'Reilly, B; O'Shaughnessy, R; Ottaway, D J; Overmier, H; Owen, B J; Pace, A E; Page, J; Pai, A; Pai, S A; Palamos, J R; Palashov, O; Palomba, C; Pal-Singh, A; Pan, H; Pankow, C; Pannarale, F; Pant, B C; Paoletti, F; Paoli, A; Papa, M A; Paris, H R; Parker, W; Pascucci, D; Pasqualetti, A; Passaquieti, R; Passuello, D; Patricelli, B; Pearlstone, B L; Pedraza, M; Pedurand, R; Pekowsky, L; Pele, A; Penn, S; Perez, C J; Perreca, A; Perri, L M; Pfeiffer, H P; Phelps, M; Piccinni, O J; Pichot, M; Piergiovanni, F; Pierro, V; Pillant, G; Pinard, L; Pinto, I M; Pitkin, M; Poe, M; Poggiani, R; Popolizio, P; Post, A; Powell, J; Prasad, J; Pratt, J W W; Predoi, V; Prestegard, T; Prijatelj, M; Principe, M; Privitera, S; Prodi, G A; Prokhorov, L G; Puncken, O; Punturo, M; Puppo, P; Pürrer, M; Qi, H; Qin, J; Qiu, S; Quetschke, V; Quintero, E A; Quitzow-James, R; Raab, F J; Rabeling, D S; Radkins, H; Raffai, P; Raja, S; Rajan, C; Rakhmanov, M; Rapagnani, P; Raymond, V; Razzano, M; Re, V; Read, J; Regimbau, T; Rei, L; Reid, S; Reitze, D H; Rew, H; Reyes, S D; Rhoades, E; Ricci, F; Riles, K; Rizzo, M; Robertson, N A; Robie, R; Robinet, F; Rocchi, A; Rolland, L; Rollins, J G; Roma, V J; Romano, J D; Romano, R; Romie, J H; Rosińska, D; Rowan, S; Rüdiger, A; Ruggi, P; Ryan, K; Sachdev, S; Sadecki, T; Sadeghian, L; Sakellariadou, M; Salconi, L; Saleem, M; Salemi, F; Samajdar, A; Sammut, L; Sampson, L M; Sanchez, E J; Sandberg, V; Sanders, J R; Sassolas, B; Sathyaprakash, B S; Saulson, P R; Sauter, O; Savage, R L; Sawadsky, A; Schale, P; Scheuer, J; Schlassa, S; Schmidt, E; Schmidt, J; Schmidt, P; Schnabel, R; Schofield, R M S; Schönbeck, A; Schreiber, E; Schuette, D; Schutz, B F; Schwalbe, S G; Scott, J; Scott, S M; Sellers, D; Sengupta, A S; Sentenac, D; Sequino, V; Sergeev, A; Setyawati, Y; Shaddock, D A; Shaffer, T J; Shahriar, M S; Shapiro, B; Shawhan, P; 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Urban, A L; Usman, S A; Vahlbruch, H; Vajente, G; Valdes, G; van Bakel, N; van Beuzekom, M; van den Brand, J F J; Van Den Broeck, C; Vander-Hyde, D C; van der Schaaf, L; van Heijningen, J V; van Veggel, A A; Vardaro, M; Varma, V; Vass, S; Vasúth, M; Vecchio, A; Vedovato, G; Veitch, J; Veitch, P J; Venkateswara, K; Venugopalan, G; Verkindt, D; Vetrano, F; Viceré, A; Viets, A D; Vinciguerra, S; Vine, D J; Vinet, J-Y; Vitale, S; Vo, T; Vocca, H; Vorvick, C; Voss, D V; Vousden, W D; Vyatchanin, S P; Wade, A R; Wade, L E; Wade, M; Walker, M; Wallace, L; Walsh, S; Wang, G; Wang, H; Wang, M; Wang, Y; Ward, R L; Warner, J; Was, M; Watchi, J; Weaver, B; Wei, L-W; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Weßels, P; Westphal, T; Wette, K; Whelan, J T; Whiting, B F; Whittle, C; Williams, D; Williams, R D; Williamson, A R; Willis, J L; Willke, B; Wimmer, M H; Winkler, W; Wipf, C C; Wittel, H; Woan, G; Woehler, J; Worden, J; Wright, J L; Wu, D S; Wu, G; Yam, W; Yamamoto, H; Yancey, C C; Yap, M J; Yu, Hang; Yu, Haocun; Yvert, M; Zadrożny, A; Zangrando, L; Zanolin, M; Zendri, J-P; Zevin, M; Zhang, L; Zhang, M; Zhang, T; Zhang, Y; Zhao, C; Zhou, M; Zhou, Z; Zhu, S J; Zhu, X J; Zucker, M E; Zweizig, J

2017-03-24

We employ gravitational-wave radiometry to map the stochastic gravitational wave background expected from a variety of contributing mechanisms and test the assumption of isotropy using data from the Advanced Laser Interferometer Gravitational Wave Observatory's (aLIGO) first observing run. We also search for persistent gravitational waves from point sources with only minimal assumptions over the 20-1726 Hz frequency band. Finding no evidence of gravitational waves from either point sources or a stochastic background, we set limits at 90% confidence. For broadband point sources, we report upper limits on the gravitational wave energy flux per unit frequency in the range F_{α,Θ}(f)<(0.1-56)×10^{-8}    erg cm^{-2} s^{-1} Hz^{-1}(f/25  Hz)^{α-1} depending on the sky location Θ and the spectral power index α. For extended sources, we report upper limits on the fractional gravitational wave energy density required to close the Universe of Ω(f,Θ)<(0.39-7.6)×10^{-8}  sr^{-1}(f/25  Hz)^{α} depending on Θ and α. Directed searches for narrowband gravitational waves from astrophysically interesting objects (Scorpius X-1, Supernova 1987 A, and the Galactic Center) yield median frequency-dependent limits on strain amplitude of h_{0}<(6.7,5.5,  and  7.0)×10^{-25}, respectively, at the most sensitive detector frequencies between 130-175 Hz. This represents a mean improvement of a factor of 2 across the band compared to previous searches of this kind for these sky locations, considering the different quantities of strain constrained in each case.

Stochastic Seismic Response of an Algiers Site with Random Depth to Bedrock

NASA Astrophysics Data System (ADS)

Badaoui, M.; Berrah, M. K.; Mébarki, A.

2010-05-01

Among the important effects of the Boumerdes earthquake (Algeria, May 21st 2003) was that, within the same zone, the destructions in certain parts were more important than in others. This phenomenon is due to site effects which alter the characteristics of seismic motions and cause concentration of damage during earthquakes. Local site effects such as thickness and mechanical properties of soil layers have important effects on the surface ground motions. This paper deals with the effect of the randomness aspect of the depth to bedrock (soil layers heights) which is assumed to be a random variable with lognormal distribution. This distribution is suitable for strictly non-negative random variables with large values of the coefficient of variation. In this case, Monte Carlo simulations are combined with the stiffness matrix method, used herein as a deterministic method, for evaluating the effect of the depth to bedrock uncertainty on the seismic response of a multilayered soil. This study considers a P and SV wave propagation pattern using input accelerations collected at Keddara station, located at 20 km from the epicenter, as it is located directly on the bedrock. A parametric study is conducted do derive the stochastic behavior of the peak ground acceleration and its response spectrum, the transfer function and the amplification factors. It is found that the soil height heterogeneity causes a widening of the frequency content and an increase in the fundamental frequency of the soil profile, indicating that the resonance phenomenon concerns a larger number of structures.

TIME-DEPENDENT ELECTRON ACCELERATION IN BLAZAR TRANSIENTS: X-RAY TIME LAGS AND SPECTRAL FORMATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Tiffany R.; Becker, Peter A.; Finke, Justin D., E-mail: pbecker@gmu.edu, E-mail: tlewis13@gmu.edu, E-mail: justin.finke@nrl.navy.mil

2016-06-20

Electromagnetic radiation from blazar jets often displays strong variability, extending from radio to γ -ray frequencies. In a few cases, this variability has been characterized using Fourier time lags, such as those detected in the X-rays from Mrk 421 using Beppo SAX. The lack of a theoretical framework to interpret the data has motivated us to develop a new model for the formation of the X-ray spectrum and the time lags in blazar jets based on a transport equation including terms describing stochastic Fermi acceleration, synchrotron losses, shock acceleration, adiabatic expansion, and spatial diffusion. We derive the exact solution formore » the Fourier transform of the electron distribution and use it to compute the Fourier transform of the synchrotron radiation spectrum and the associated X-ray time lags. The same theoretical framework is also used to compute the peak flare X-ray spectrum, assuming that a steady-state electron distribution is achieved during the peak of the flare. The model parameters are constrained by comparing the theoretical predictions with the observational data for Mrk 421. The resulting integrated model yields, for the first time, a complete first-principles physical explanation for both the formation of the observed time lags and the shape of the peak flare X-ray spectrum. It also yields direct estimates of the strength of the shock and the stochastic magnetohydrodynamical wave acceleration components in the Mrk 421 jet.« less

Self-organized behavior of modeled shoreline shapes

NASA Astrophysics Data System (ADS)

Ashton, A.; Murray, A. B.

2003-04-01

Whenever waves approach a coast and break at oblique angles, they drive a current along the shore. This current, along with wave-induced sediment suspension, transports relatively large amounts of sediment, affecting the shape and evolution of a coastline. Traditionally, researchers have assumed that alongshore sediment transport will diffuse, or smooth, bumps along a shoreline. Recent research, however, shows that when the angle between wave crests in deep water and the shoreline is sufficiently high (greater than approximately 45 degrees), a shoreline is unstable. Linear stability analysis does not predict that this instability will cause a preferred wavelength of shoreline perturbation growth or that organized patterns will emerge. However, a simple numerical model of shoreline change shows those when there is a predominance of high angle waves approaching a shoreline, finite-amplitude features will develop that interact with each other and increase in wavelength over time, translating in the direction of net alongshore sediment transport. Some of these simulated features resemble naturally occurring shoreline features, such as 'alongshore sandwaves', 'ords', 'cuspate spits', and 'cuspate forelands'. By varying two wave climate parameters, one describing the relative dominance of waves approaching at high angles and the other controlling the signs of the approach angle of incoming waves (i.e., the asymmetry of waves approaching from the right vs. the left), we investigate how the attributes of the input wave climate determine the aspect ratio and characteristic form of the simulated features. Varying these two parameters also affects the wavelength of the initially fastest growing perturbation. By tracking the average wavelength of simulated features, which increases over time for all simulations, we show that more complicated phenomena, such as rapid period doubling, can dominate simulated shoreline evolution. These rich behaviors result from large-scale emergent interactions. Although the wave distribution determines the character of shoreline features, their specific configuration and evolution is sensitively dependant on both initial conditions and the stochastic sequencing of wave approach angles.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

Evolution of a hybrid micro-macro entangled state of the qubit-oscillator system via the generalized rotating wave approximation

NASA Astrophysics Data System (ADS)

Chakrabarti, R.; Yogesh, V.

2016-04-01

We study the evolution of the hybrid entangled states in a bipartite (ultra) strongly coupled qubit-oscillator system. Using the generalized rotating wave approximation the reduced density matrices of the qubit and the oscillator are obtained. The reduced density matrix of the oscillator yields the phase space quasi probability distributions such as the diagonal P-representation, the Wigner W-distribution and the Husimi Q-function. In the strong coupling regime the Q-function evolves to uniformly separated macroscopically distinct Gaussian peaks representing ‘kitten’ states at certain specified times that depend on multiple time scales present in the interacting system. The ultrastrong coupling strength of the interaction triggers appearance of a large number of modes that quickly develop a randomization of their phase relationships. A stochastic averaging of the dynamical quantities sets in, and leads to the decoherence of the system. The delocalization in the phase space of the oscillator is studied by using the Wehrl entropy. The negativity of the W-distribution reflects the departure of the oscillator from the classical states, and allows us to study the underlying differences between various information-theoretic measures such as the Wehrl entropy and the Wigner entropy. Other features of nonclassicality such as the existence of the squeezed states and appearance of negative values of the Mandel parameter are realized during the course of evolution of the bipartite system. In the parametric regime studied here these properties do not survive in the time-averaged limit.

Energy dissipation of Alfven wave packets deformed by irregular magnetic fields in solar-coronal arches

NASA Technical Reports Server (NTRS)

Similon, Philippe L.; Sudan, R. N.

1989-01-01

The importance of field line geometry for shear Alfven wave dissipation in coronal arches is demonstrated. An eikonal formulation makes it possible to account for the complicated magnetic geometry typical in coronal loops. An interpretation of Alfven wave resonance is given in terms of gradient steepening, and dissipation efficiencies are studied for two configurations: the well-known slab model with a straight magnetic field, and a new model with stochastic field lines. It is shown that a large fraction of the Alfven wave energy flux can be effectively dissipated in the corona.

A Family of Poisson Processes for Use in Stochastic Models of Precipitation

NASA Astrophysics Data System (ADS)

Penland, C.

2013-12-01

Both modified Poisson processes and compound Poisson processes can be relevant to stochastic parameterization of precipitation. This presentation compares the dynamical properties of these systems and discusses the physical situations in which each might be appropriate. If the parameters describing either class of systems originate in hydrodynamics, then proper consideration of stochastic calculus is required during numerical implementation of the parameterization. It is shown here that an improper numerical treatment can have severe implications for estimating rainfall distributions, particularly in the tails of the distributions and, thus, on the frequency of extreme events.

Role of demographic stochasticity in a speciation model with sexual reproduction

NASA Astrophysics Data System (ADS)

Lafuerza, Luis F.; McKane, Alan J.

2016-03-01

Recent theoretical studies have shown that demographic stochasticity can greatly increase the tendency of asexually reproducing phenotypically diverse organisms to spontaneously evolve into localized clusters, suggesting a simple mechanism for sympatric speciation. Here we study the role of demographic stochasticity in a model of competing organisms subject to assortative mating. We find that in models with sexual reproduction, noise can also lead to the formation of phenotypic clusters in parameter ranges where deterministic models would lead to a homogeneous distribution. In some cases, noise can have a sizable effect, rendering the deterministic modeling insufficient to understand the phenotypic distribution.

Exact solution for a non-Markovian dissipative quantum dynamics.

PubMed

Ferialdi, Luca; Bassi, Angelo

2012-04-27

We provide the exact analytic solution of the stochastic Schrödinger equation describing a harmonic oscillator interacting with a non-Markovian and dissipative environment. This result represents an arrival point in the study of non-Markovian dynamics via stochastic differential equations. It is also one of the few exactly solvable models for infinite-dimensional systems. We compute the Green's function; in the case of a free particle and with an exponentially correlated noise, we discuss the evolution of Gaussian wave functions.

Probabilistic analysis and fatigue damage assessment of offshore mooring system due to non-Gaussian bimodal tension processes

NASA Astrophysics Data System (ADS)

Chang, Anteng; Li, Huajun; Wang, Shuqing; Du, Junfeng

2017-08-01

Both wave-frequency (WF) and low-frequency (LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system. This paper conducts a comprehensive investigation of applicable probability density functions (PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method. Short-term statistical characteristics of mooring-line tension responses are firstly investigated, in which the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients. Several distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes. Results indicate that the Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components. A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses. Using time domain simulation as a benchmark, its accuracy is further validated using a numerical case study of a moored semi-submersible platform.

Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Lermusiaux, Pierre F. J.

2016-04-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

Incorporating prior knowledge induced from stochastic differential equations in the classification of stochastic observations.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2016-12-01

In classification, prior knowledge is incorporated in a Bayesian framework by assuming that the feature-label distribution belongs to an uncertainty class of feature-label distributions governed by a prior distribution. A posterior distribution is then derived from the prior and the sample data. An optimal Bayesian classifier (OBC) minimizes the expected misclassification error relative to the posterior distribution. From an application perspective, prior construction is critical. The prior distribution is formed by mapping a set of mathematical relations among the features and labels, the prior knowledge, into a distribution governing the probability mass across the uncertainty class. In this paper, we consider prior knowledge in the form of stochastic differential equations (SDEs). We consider a vector SDE in integral form involving a drift vector and dispersion matrix. Having constructed the prior, we develop the optimal Bayesian classifier between two models and examine, via synthetic experiments, the effects of uncertainty in the drift vector and dispersion matrix. We apply the theory to a set of SDEs for the purpose of differentiating the evolutionary history between two species.

A stochastic differential equations approach for the description of helium bubble size distributions in irradiated metals

NASA Astrophysics Data System (ADS)

Seif, Dariush; Ghoniem, Nasr M.

2014-12-01

A rate theory model based on the theory of nonlinear stochastic differential equations (SDEs) is developed to estimate the time-dependent size distribution of helium bubbles in metals under irradiation. Using approaches derived from Itô's calculus, rate equations for the first five moments of the size distribution in helium-vacancy space are derived, accounting for the stochastic nature of the atomic processes involved. In the first iteration of the model, the distribution is represented as a bivariate Gaussian distribution. The spread of the distribution about the mean is obtained by white-noise terms in the second-order moments, driven by fluctuations in the general absorption and emission of point defects by bubbles, and fluctuations stemming from collision cascades. This statistical model for the reconstruction of the distribution by its moments is coupled to a previously developed reduced-set, mean-field, rate theory model. As an illustrative case study, the model is applied to a tungsten plasma facing component under irradiation. Our findings highlight the important role of stochastic atomic fluctuations on the evolution of helium-vacancy cluster size distributions. It is found that when the average bubble size is small (at low dpa levels), the relative spread of the distribution is large and average bubble pressures may be very large. As bubbles begin to grow in size, average bubble pressures decrease, and stochastic fluctuations have a lessened effect. The distribution becomes tighter as it evolves in time, corresponding to a more uniform bubble population. The model is formulated in a general way, capable of including point defect drift due to internal temperature and/or stress gradients. These arise during pulsed irradiation, and also during steady irradiation as a result of externally applied or internally generated non-homogeneous stress fields. Discussion is given into how the model can be extended to include full spatial resolution and how the implementation of a path-integral approach may proceed if the distribution is known experimentally to significantly stray from a Gaussian description.

Stochastic model simulation using Kronecker product analysis and Zassenhaus formula approximation.

PubMed

Caglar, Mehmet Umut; Pal, Ranadip

2013-01-01

Probabilistic Models are regularly applied in Genetic Regulatory Network modeling to capture the stochastic behavior observed in the generation of biological entities such as mRNA or proteins. Several approaches including Stochastic Master Equations and Probabilistic Boolean Networks have been proposed to model the stochastic behavior in genetic regulatory networks. It is generally accepted that Stochastic Master Equation is a fundamental model that can describe the system being investigated in fine detail, but the application of this model is computationally enormously expensive. On the other hand, Probabilistic Boolean Network captures only the coarse-scale stochastic properties of the system without modeling the detailed interactions. We propose a new approximation of the stochastic master equation model that is able to capture the finer details of the modeled system including bistabilities and oscillatory behavior, and yet has a significantly lower computational complexity. In this new method, we represent the system using tensors and derive an identity to exploit the sparse connectivity of regulatory targets for complexity reduction. The algorithm involves an approximation based on Zassenhaus formula to represent the exponential of a sum of matrices as product of matrices. We derive upper bounds on the expected error of the proposed model distribution as compared to the stochastic master equation model distribution. Simulation results of the application of the model to four different biological benchmark systems illustrate performance comparable to detailed stochastic master equation models but with considerably lower computational complexity. The results also demonstrate the reduced complexity of the new approach as compared to commonly used Stochastic Simulation Algorithm for equivalent accuracy.

Stochastic strong ground motion simulations for the intermediate-depth earthquakes of the south Aegean subduction zone

NASA Astrophysics Data System (ADS)

Kkallas, Harris; Papazachos, Konstantinos; Boore, David; Margaris, Vasilis

2015-04-01

We have employed the stochastic finite-fault modelling approach of Motazedian and Atkinson (2005), as described by Boore (2009), for the simulation of Fourier spectra of the Intermediate-depth earthquakes of the south Aegean subduction zone. The stochastic finite-fault method is a practical tool for simulating ground motions of future earthquakes which requires region-specific source, path and site characterizations as input model parameters. For this reason we have used data from both acceleration-sensor and broadband velocity-sensor instruments from intermediate-depth earthquakes with magnitude of M 4.5-6.7 that occurred in the south Aegean subduction zone. Source mechanisms for intermediate-depth events of north Aegean subduction zone are either collected from published information or are constrained using the main faulting types from Kkallas et al. (2013). The attenuation parameters for simulations were adopted from Skarladoudis et al. (2013) and are based on regression analysis of a response spectra database. The site amplification functions for each soil class were adopted from Klimis et al., (1999), while the kappa values were constrained from the analysis of the EGELADOS network data from Ventouzi et al., (2013). The investigation of stress-drop values was based on simulations performed with the EXSIM code for several ranges of stress drop values and by comparing the results with the available Fourier spectra of intermediate-depth earthquakes. Significant differences regarding the strong-motion duration, which is determined from Husid plots (Husid, 1969), have been identified between the for-arc and along-arc stations due to the effect of the low-velocity/low-Q mantle wedge on the seismic wave propagation. In order to estimate appropriate values for the duration of P-waves, we have automatically picked P-S durations on the available seismograms. For the S-wave durations we have used the part of the seismograms starting from the S-arrivals and ending at the 95%-energy limit of the Husid plots. After appropriate calibration of all parameters involved in the simulations we generated separate stochastic waveforms for both P- and S-waves, and produce the final synthetics by appropriate merging of the two stochastic waveforms. This work has been partly supported by the 3D-SEGMENTS project #1337 funded by EC European Social Fund and the Operational Programme "Education and Lifelong Learning" of the ARISTEIA-I call of the Greek Secretariat of Research and Technology.

The chaotic interaction of two walkers

NASA Astrophysics Data System (ADS)

Tadrist, Loic; Samara, Naresh; Schlagheck, Peter; Gilet, Tristan

2016-11-01

A droplet bouncing on a vertically vibrated bath may be propelled horizontally by the Faraday waves that it generates at each rebound. This association of a wave and a particle is called a walker. Ten years ago, Yves Couder and co-workers noted that the dynamical encounter of two walkers may lead to either scattered trajectories or orbital motion. In this work, we investigate the interaction of two walkers more systematically. The walkers are launched towards each other with finely controlled initial conditions. Output trajectories are classified in four types: scattering, orbiting, wandering and complex. The interaction appears stochastic: the same set of initial parameters (to the measurement accuracy) can produce different outputs. Our analysis of the underlying chaos provides new insights on the stochastic nature of this experiment. This work is supported by the ARC Quandrops of the Wallonia-Brussels Federation.

Conservative Diffusions: a Constructive Approach to Nelson's Stochastic Mechanics.

NASA Astrophysics Data System (ADS)

Carlen, Eric Anders

In Nelson's stochastic mechanics, quantum phenomena are described in terms of diffusions instead of wave functions; this thesis is a study of that description. We emphasize that we are concerned here with the possibility of describing, as opposed to explaining, quantum phenomena in terms of diffusions. In this direction, the following questions arise: "Do the diffusions of stochastic mechanics--which are formally given by stochastic differential equations with extremely singular coefficients--really exist?" Given that they exist, one can ask, "Do these diffusions have physically reasonable sample path behavior, and can we use information about sample paths to study the behavior of physical systems?" These are the questions we treat in this thesis. In Chapter I we review stochastic mechanics and diffusion theory, using the Guerra-Morato variational principle to establish the connection with the Schroedinger equation. This chapter is largely expository; however, there are some novel features and proofs. In Chapter II we settle the first of the questions raised above. Using PDE methods, we construct the diffusions of stochastic mechanics. Our result is sufficiently general to be of independent mathematical interest. In Chapter III we treat potential scattering in stochastic mechanics and discuss direct probabilistic methods of studying quantum scattering problems. Our results provide a solid "Yes" in answer to the second question raised above.

A deterministic model predicts the properties of stochastic calcium oscillations in airway smooth muscle cells.

PubMed

Cao, Pengxing; Tan, Xiahui; Donovan, Graham; Sanderson, Michael J; Sneyd, James

2014-08-01

The inositol trisphosphate receptor ([Formula: see text]) is one of the most important cellular components responsible for oscillations in the cytoplasmic calcium concentration. Over the past decade, two major questions about the [Formula: see text] have arisen. Firstly, how best should the [Formula: see text] be modeled? In other words, what fundamental properties of the [Formula: see text] allow it to perform its function, and what are their quantitative properties? Secondly, although calcium oscillations are caused by the stochastic opening and closing of small numbers of [Formula: see text], is it possible for a deterministic model to be a reliable predictor of calcium behavior? Here, we answer these two questions, using airway smooth muscle cells (ASMC) as a specific example. Firstly, we show that periodic calcium waves in ASMC, as well as the statistics of calcium puffs in other cell types, can be quantitatively reproduced by a two-state model of the [Formula: see text], and thus the behavior of the [Formula: see text] is essentially determined by its modal structure. The structure within each mode is irrelevant for function. Secondly, we show that, although calcium waves in ASMC are generated by a stochastic mechanism, [Formula: see text] stochasticity is not essential for a qualitative prediction of how oscillation frequency depends on model parameters, and thus deterministic [Formula: see text] models demonstrate the same level of predictive capability as do stochastic models. We conclude that, firstly, calcium dynamics can be accurately modeled using simplified [Formula: see text] models, and, secondly, to obtain qualitative predictions of how oscillation frequency depends on parameters it is sufficient to use a deterministic model.

On the probabilistic structure of water age

NASA Astrophysics Data System (ADS)

Porporato, Amilcare; Calabrese, Salvatore

2015-05-01

The age distribution of water in hydrologic systems has received renewed interest recently, especially in relation to watershed response to rainfall inputs. The purpose of this contribution is first to draw attention to existing theories of age distributions in population dynamics, fluid mechanics and stochastic groundwater, and in particular to the McKendrick-von Foerster equation and its generalizations and solutions. A second and more important goal is to clarify that, when hydrologic fluxes are modeled by means of time-varying stochastic processes, the age distributions must themselves be treated as random functions. Once their probabilistic structure is obtained, it can be used to characterize the variability of age distributions in real systems and thus help quantify the inherent uncertainty in the field determination of water age. We illustrate these concepts with reference to a stochastic storage model, which has been used as a minimalist model of soil moisture and streamflow dynamics.

The stochastic spectator

NASA Astrophysics Data System (ADS)

Hardwick, Robert J.; Vennin, Vincent; Byrnes, Christian T.; Torrado, Jesús; Wands, David

2017-10-01

We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.

Rupture Propagation for Stochastic Fault Models

NASA Astrophysics Data System (ADS)

Favreau, P.; Lavallee, D.; Archuleta, R.

2003-12-01

The inversion of strong motion data of large earhquakes give the spatial distribution of pre-stress on the ruptured faults and it can be partially reproduced by stochastic models, but a fundamental question remains: how rupture propagates, constrained by the presence of spatial heterogeneity? For this purpose we investigate how the underlying random variables, that control the pre-stress spatial variability, condition the propagation of the rupture. Two stochastic models of prestress distributions are considered, respectively based on Cauchy and Gaussian random variables. The parameters of the two stochastic models have values corresponding to the slip distribution of the 1979 Imperial Valley earthquake. We use a finite difference code to simulate the spontaneous propagation of shear rupture on a flat fault in a 3D continuum elastic body. The friction law is the slip dependent friction law. The simulations show that the propagation of the rupture front is more complex, incoherent or snake-like for a prestress distribution based on Cauchy random variables. This may be related to the presence of a higher number of asperities in this case. These simulations suggest that directivity is stronger in the Cauchy scenario, compared to the smoother rupture of the Gauss scenario.

Generation of Langmuir wave supercontinuum by phase-preserving equilibration of plasmons with irreversible wave-particle interaction

NASA Astrophysics Data System (ADS)

Eiichirou, Kawamori

2018-04-01

We report the observation of supercontinuum of Langmuir plasma waves, that exhibits broad power spectrum having significant spatio-temporal coherence grown from a monochromatic seed-wave, in one-dimensional particle-in-cell simulations. The Langmuir wave supercontinuum (LWSC) is formed when the seed wave excites side-band fields efficiently by the modulational instabilities. Its identification is achieved by the use of the tricoherence analysis, which detects four wave mixings (FWMs) of plasmons (plasma wave quanta), and evaluation of the first order coherence, which is a measure of temporal coherence, of the wave electric fields. The irreversible evolution to the coherent LWSC from the seed wave is realized by the wave-particle interactions causing stochastic electron motions in the phase space and the coherence of LWSC is maintained by the phase-preserving FWMs of plasmons. The LWSC corresponds to a quasi Bernstein-Greene-Kruskal mode.

Methods of Stochastic Analysis of Complex Regimes in the 3D Hindmarsh-Rose Neuron Model

NASA Astrophysics Data System (ADS)

Bashkirtseva, Irina; Ryashko, Lev; Slepukhina, Evdokia

A problem of the stochastic nonlinear analysis of neuronal activity is studied by the example of the Hindmarsh-Rose (HR) model. For the parametric region of tonic spiking oscillations, it is shown that random noise transforms the spiking dynamic regime into the bursting one. This stochastic phenomenon is specified by qualitative changes in distributions of random trajectories and interspike intervals (ISIs). For a quantitative analysis of the noise-induced bursting, we suggest a constructive semi-analytical approach based on the stochastic sensitivity function (SSF) technique and the method of confidence domains that allows us to describe geometrically a distribution of random states around the deterministic attractors. Using this approach, we develop a new algorithm for estimation of critical values for the noise intensity corresponding to the qualitative changes in stochastic dynamics. We show that the obtained estimations are in good agreement with the numerical results. An interplay between noise-induced bursting and transitions from order to chaos is discussed.

Predator-prey model for the self-organization of stochastic oscillators in dual populations

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan; Gürcan, Ozgur D.

A predator-prey model of dual populations with stochastic oscillators is presented. A linear cross-coupling between the two populations is introduced that follows the coupling between the motions of a Wilberforce pendulum in two dimensions: one in the longitudinal and the other in torsional plain. Within each population a Kuramoto type competition between the phases is assumed. Thus, the synchronization state of the whole system is controlled by these two types of competitions. The results of the numerical simulations show that by adding the linear cross-coupling interactions predator-prey oscillations between the two populations appear which results in self-regulation of the system by a transfer of synchrony between the two populations. The model represents several important features of the dynamical interplay between the drift wave and zonal flow turbulence in magnetically confined plasmas, and a novel interpretation of the coupled dynamics of drift wave-zonal flow turbulence using synchronization of stochastic oscillator is discussed. Sara Moradi has benefited from a mobility grant funded by the Belgian Federal Science Policy Office and the MSCA of the European Commission (FP7-PEOPLE-COFUND-2008 nº 246540).

Optimization of contrast resolution by genetic algorithm in ultrasound tissue harmonic imaging.

PubMed

Ménigot, Sébastien; Girault, Jean-Marc

2016-09-01

The development of ultrasound imaging techniques such as pulse inversion has improved tissue harmonic imaging. Nevertheless, no recommendation has been made to date for the design of the waveform transmitted through the medium being explored. Our aim was therefore to find automatically the optimal "imaging" wave which maximized the contrast resolution without a priori information. To overcome assumption regarding the waveform, a genetic algorithm investigated the medium thanks to the transmission of stochastic "explorer" waves. Moreover, these stochastic signals could be constrained by the type of generator available (bipolar or arbitrary). To implement it, we changed the current pulse inversion imaging system by including feedback. Thus the method optimized the contrast resolution by adaptively selecting the samples of the excitation. In simulation, we benchmarked the contrast effectiveness of the best found transmitted stochastic commands and the usual fixed-frequency command. The optimization method converged quickly after around 300 iterations in the same optimal area. These results were confirmed experimentally. In the experimental case, the contrast resolution measured on a radiofrequency line could be improved by 6% with a bipolar generator and it could still increase by 15% with an arbitrary waveform generator. Copyright © 2016 Elsevier B.V. All rights reserved.

Stochastic and Resolvable Gravitational Waves from Ultralight Bosons

NASA Astrophysics Data System (ADS)

Brito, Richard; Ghosh, Shrobana; Barausse, Enrico; Berti, Emanuele; Cardoso, Vitor; Dvorkin, Irina; Klein, Antoine; Pani, Paolo

2017-09-01

Ultralight scalar fields around spinning black holes can trigger superradiant instabilities, forming a long-lived bosonic condensate outside the horizon. We use numerical solutions of the perturbed field equations and astrophysical models of massive and stellar-mass black hole populations to compute, for the first time, the stochastic gravitational-wave background from these sources. In optimistic scenarios the background is observable by Advanced LIGO and LISA for field masses ms in the range ˜[2 ×10-13,10-12] and ˜5 ×[10-19,10-16] eV , respectively, and it can affect the detectability of resolvable sources. Our estimates suggest that an analysis of the stochastic background limits from LIGO O1 might already be used to marginally exclude axions with mass ˜10-12.5 eV . Semicoherent searches with Advanced LIGO (LISA) should detect ˜15 (5 ) to 200(40) resolvable sources for scalar field masses 3 ×10-13 (10-17) eV . LISA measurements of massive BH spins could either rule out bosons in the range ˜[10-18,2 ×10-13] eV , or measure ms with 10% accuracy in the range ˜[10-17,10-13] eV .

Generating synthetic wave climates for coastal modelling: a linear mixed modelling approach

NASA Astrophysics Data System (ADS)

Thomas, C.; Lark, R. M.

2013-12-01

Numerical coastline morphological evolution models require wave climate properties to drive morphological change through time. Wave climate properties (typically wave height, period and direction) may be temporally fixed, culled from real wave buoy data, or allowed to vary in some way defined by a Gaussian or other pdf. However, to examine sensitivity of coastline morphologies to wave climate change, it seems desirable to be able to modify wave climate time series from a current to some new state along a trajectory, but in a way consistent with, or initially conditioned by, the properties of existing data, or to generate fully synthetic data sets with realistic time series properties. For example, mean or significant wave height time series may have underlying periodicities, as revealed in numerous analyses of wave data. Our motivation is to develop a simple methodology to generate synthetic wave climate time series that can change in some stochastic way through time. We wish to use such time series in a coastline evolution model to test sensitivities of coastal landforms to changes in wave climate over decadal and centennial scales. We have worked initially on time series of significant wave height, based on data from a Waverider III buoy located off the coast of Yorkshire, England. The statistical framework for the simulation is the linear mixed model. The target variable, perhaps after transformation (Box-Cox), is modelled as a multivariate Gaussian, the mean modelled as a function of a fixed effect, and two random components, one of which is independently and identically distributed (iid) and the second of which is temporally correlated. The model was fitted to the data by likelihood methods. We considered the option of a periodic mean, the period either fixed (e.g. at 12 months) or estimated from the data. We considered two possible correlation structures for the second random effect. In one the correlation decays exponentially with time. In the second (spherical) model, it cuts off at a temporal range. Having fitted the model, multiple realisations were generated; the random effects were simulated by specifying a covariance matrix for the simulated values, with the estimated parameters. The Cholesky factorisation of the covariance matrix was computed and realizations of the random component of the model generated by pre-multiplying a vector of iid standard Gaussian variables by the lower triangular factor. The resulting random variate was added to the mean value computed from the fixed effects, and the result back-transformed to the original scale of the measurement. Realistic simulations result from approach described above. Background exploratory data analysis was undertaken on 20-day sets of 30-minute buoy data, selected from days 5-24 of months January, April, July, October, 2011, to elucidate daily to weekly variations, and to keep numerical analysis tractable computationally. Work remains to be undertaken to develop suitable models for synthetic directional data. We suggest that the general principles of the method will have applications in other geomorphological modelling endeavours requiring time series of stochastically variable environmental parameters.

Exploring Empirical Rank-Frequency Distributions Longitudinally through a Simple Stochastic Process

PubMed Central

Finley, Benjamin J.; Kilkki, Kalevi

2014-01-01

The frequent appearance of empirical rank-frequency laws, such as Zipf’s law, in a wide range of domains reinforces the importance of understanding and modeling these laws and rank-frequency distributions in general. In this spirit, we utilize a simple stochastic cascade process to simulate several empirical rank-frequency distributions longitudinally. We focus especially on limiting the process’s complexity to increase accessibility for non-experts in mathematics. The process provides a good fit for many empirical distributions because the stochastic multiplicative nature of the process leads to an often observed concave rank-frequency distribution (on a log-log scale) and the finiteness of the cascade replicates real-world finite size effects. Furthermore, we show that repeated trials of the process can roughly simulate the longitudinal variation of empirical ranks. However, we find that the empirical variation is often less that the average simulated process variation, likely due to longitudinal dependencies in the empirical datasets. Finally, we discuss the process limitations and practical applications. PMID:24755621

Exploring empirical rank-frequency distributions longitudinally through a simple stochastic process.

PubMed

Finley, Benjamin J; Kilkki, Kalevi

2014-01-01

The frequent appearance of empirical rank-frequency laws, such as Zipf's law, in a wide range of domains reinforces the importance of understanding and modeling these laws and rank-frequency distributions in general. In this spirit, we utilize a simple stochastic cascade process to simulate several empirical rank-frequency distributions longitudinally. We focus especially on limiting the process's complexity to increase accessibility for non-experts in mathematics. The process provides a good fit for many empirical distributions because the stochastic multiplicative nature of the process leads to an often observed concave rank-frequency distribution (on a log-log scale) and the finiteness of the cascade replicates real-world finite size effects. Furthermore, we show that repeated trials of the process can roughly simulate the longitudinal variation of empirical ranks. However, we find that the empirical variation is often less that the average simulated process variation, likely due to longitudinal dependencies in the empirical datasets. Finally, we discuss the process limitations and practical applications.

The effect of stochiastic technique on estimates of population viability from transition matrix models

USGS Publications Warehouse

Kaye, T.N.; Pyke, David A.

2003-01-01

Population viability analysis is an important tool for conservation biologists, and matrix models that incorporate stochasticity are commonly used for this purpose. However, stochastic simulations may require assumptions about the distribution of matrix parameters, and modelers often select a statistical distribution that seems reasonable without sufficient data to test its fit. We used data from long-term (5a??10 year) studies with 27 populations of five perennial plant species to compare seven methods of incorporating environmental stochasticity. We estimated stochastic population growth rate (a measure of viability) using a matrix-selection method, in which whole observed matrices were selected at random at each time step of the model. In addition, we drew matrix elements (transition probabilities) at random using various statistical distributions: beta, truncated-gamma, truncated-normal, triangular, uniform, or discontinuous/observed. Recruitment rates were held constant at their observed mean values. Two methods of constraining stage-specific survival to a??100% were also compared. Different methods of incorporating stochasticity and constraining matrix column sums interacted in their effects and resulted in different estimates of stochastic growth rate (differing by up to 16%). Modelers should be aware that when constraining stage-specific survival to 100%, different methods may introduce different levels of bias in transition element means, and when this happens, different distributions for generating random transition elements may result in different viability estimates. There was no species effect on the results and the growth rates derived from all methods were highly correlated with one another. We conclude that the absolute value of population viability estimates is sensitive to model assumptions, but the relative ranking of populations (and management treatments) is robust. Furthermore, these results are applicable to a range of perennial plants and possibly other life histories.

Bidirectional Classical Stochastic Processes with Measurements and Feedback

NASA Technical Reports Server (NTRS)

Hahne, G. E.

2005-01-01

A measurement on a quantum system is said to cause the "collapse" of the quantum state vector or density matrix. An analogous collapse occurs with measurements on a classical stochastic process. This paper addresses the question of describing the response of a classical stochastic process when there is feedback from the output of a measurement to the input, and is intended to give a model for quantum-mechanical processes that occur along a space-like reaction coordinate. The classical system can be thought of in physical terms as two counterflowing probability streams, which stochastically exchange probability currents in a way that the net probability current, and hence the overall probability, suitably interpreted, is conserved. The proposed formalism extends the . mathematics of those stochastic processes describable with linear, single-step, unidirectional transition probabilities, known as Markov chains and stochastic matrices. It is shown that a certain rearrangement and combination of the input and output of two stochastic matrices of the same order yields another matrix of the same type. Each measurement causes the partial collapse of the probability current distribution in the midst of such a process, giving rise to calculable, but non-Markov, values for the ensuing modification of the system's output probability distribution. The paper concludes with an analysis of a classical probabilistic version of the so-called grandfather paradox.

Stochastic transformation of points in polygons according to the Voronoi tessellation: microstructural description.

PubMed

Di Vito, Alessia; Fanfoni, Massimo; Tomellini, Massimo

2010-12-01

Starting from a stochastic two-dimensional process we studied the transformation of points in disks and squares following a protocol according to which at any step the island size increases proportionally to the corresponding Voronoi tessera. Two interaction mechanisms among islands have been dealt with: coalescence and impingement. We studied the evolution of the island density and of the island size distribution functions, in dependence on island collision mechanisms for both Poissonian and correlated spatial distributions of points. The island size distribution functions have been found to be invariant with the fraction of transformed phase for a given stochastic process. The n(Θ) curve describing the island decay has been found to be independent of the shape (apart from high correlation degrees) and interaction mechanism.

Plasma and wave properties downstream of Martian bow shock: Hybrid simulations and MAVEN observations

NASA Astrophysics Data System (ADS)

Dong, Chuanfei; Winske, Dan; Cowee, Misa; Bougher, Stephen W.; Andersson, Laila; Connerney, Jack; Epley, Jared; Ergun, Robert; McFadden, James P.; Ma, Yingjuan; Toth, Gabor; Curry, Shannon; Nagy, Andrew; Jakosky, Bruce

2015-04-01

Two-dimensional hybrid simulation codes are employed to investigate the kinetic properties of plasmas and waves downstream of the Martian bow shock. The simulations are two-dimensional in space but three dimensional in field and velocity components. Simulations show that ion cyclotron waves are generated by temperature anisotropy resulting from the reflected protons around the Martian bow shock. These proton cyclotron waves could propagate downward into the Martian ionosphere and are expected to heat the O+ layer peaked from 250 to 300 km due to the wave-particle interaction. The proton cyclotron wave heating is anticipated to be a significant source of energy into the thermosphere, which impacts atmospheric escape rates. The simulation results show that the specific dayside heating altitude depends on the Martian crustal field orientations, solar cycles and seasonal variations since both the cyclotron resonance condition and the non/sub-resonant stochastic heating threshold depend on the ambient magnetic field strength. The dayside magnetic field profiles for different crustal field orientation, solar cycle and seasonal variations are adopted from the BATS-R-US Mars multi-fluid MHD model. The simulation results, however, show that the heating of O+ via proton cyclotron wave resonant interaction is not likely in the relatively weak crustal field region, based on our simplified model. This indicates that either the drift motion resulted from the transport of ionospheric O+, or the non/sub-resonant stochastic heating mechanism are important to explain the heating of Martian O+ layer. We will investigate this further by comparing the simulation results with the available MAVEN data. These simulated ion cyclotron waves are important to explain the heating of Martian O+ layer and have significant implications for future observations.

New primordial-magnetic-field limit from the latest LIGO S5 data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, S.

Since the energy momentum tensor of a magnetic field always contains a spin-2 component in its anisotropic stress, stochastic primordial magnetic field (PMF) in the early universe must generate stochastic gravitational-wave (GW) background. This process will greatly affect the relic gravitational wave (RGW), which is one of the major scientific goals of the laser interferometer GW detections. Recently, the fifth science (S5) run of laser interferometer gravitational-wave observatory (LIGO) gave a latest upper limit {Omega}{sub GW}<6.9x10{sup -6} on the RGW background. Utilizing this upper limit, we derive new PMF limits: for a scale of galactic cluster {lambda}=1 Mpc, the amplitudemore » of PMF, that produced by the electroweak phase transition, has to be weaker than B{sub {lambda}{<=}4}x10{sup -7} G; for a scale of supercluster {lambda}=100 Mpc, the amplitude of PMF has to be weaker than B{sub {lambda}{<=}9}x10{sup -11} G. In this manner, GW observation has potential to make interesting contributions to the study of primordial magnetic field.« less

I = 1 and I = 2 π-π scattering phase shifts from Nf = 2 + 1 lattice QCD

NASA Astrophysics Data System (ADS)

Bulava, John; Fahy, Brendan; Hörz, Ben; Juge, Keisuke J.; Morningstar, Colin; Wong, Chik Him

2016-09-01

The I = 1 p-wave and I = 2 s-wave elastic π-π scattering amplitudes are calculated from a first-principles lattice QCD simulation using a single ensemble of gauge field configurations with Nf = 2 + 1 dynamical flavors of anisotropic clover-improved Wilson fermions. This ensemble has a large spatial volume V =(3.7 fm)3, pion mass mπ = 230 MeV, and spatial lattice spacing as = 0.11 fm. Calculation of the necessary temporal correlation matrices is efficiently performed using the stochastic LapH method, while the large volume enables an improved energy resolution compared to previous work. For this single ensemble we obtain mρ /mπ = 3.350 (24), gρππ = 5.99 (26), and a clear signal for the I = 2 s-wave. The success of the stochastic LapH method in this proof-of-principle large-volume calculation paves the way for quantitative study of the lattice spacing effects and quark mass dependence of scattering amplitudes using state-of-the-art ensembles.

Degree Distribution of Position-Dependent Ball-Passing Networks in Football Games

NASA Astrophysics Data System (ADS)

Narizuka, Takuma; Yamamoto, Ken; Yamazaki, Yoshihiro

2015-08-01

We propose a simple stochastic model describing the position-dependent ball-passing network in football (soccer) games. In this network, a player in a certain area in a divided field is a node, and a pass between two nodes corresponds to an edge. Our stochastic process model is characterized by the consecutive choice of a node depending on its intrinsic fitness. We derive an explicit expression for the degree distribution and find that the derived distribution reproduces that for actual data reasonably well.

Gravitational waves at interferometer scales and primordial black holes in axion inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

García-Bellido, Juan; Peloso, Marco; Unal, Caner, E-mail: juan.garciabellido@uam.es, E-mail: peloso@physics.umn.edu, E-mail: unal@physics.umn.edu

We study the prospects of detection at terrestrial and space interferometers, as well as at pulsar timing array experiments, of a stochastic gravitational wave background which can be produced in models of axion inflation. This potential signal, and the development of these experiments, open a new window on inflation on scales much smaller than those currently probed with Cosmic Microwave Background and Large Scale Structure measurements. The sourced signal generated in axion inflation is an ideal candidate for such searches, since it naturally grows at small scales, and it has specific properties (chirality and non-gaussianity) that can distinguish it frommore » an astrophysical background. We study under which conditions such a signal can be produced at an observable level, without the simultaneous overproduction of scalar perturbations in excess of what is allowed by the primordial black hole limits. We also explore the possibility that scalar perturbations generated in a modified version of this model may provide a distribution of primordial black holes compatible with the current bounds, that can act as a seeds of the present black holes in the universe.« less

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

Adaptive two-regime method: Application to front propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Martin, E-mail: martin.robinson@maths.ox.ac.uk; Erban, Radek, E-mail: erban@maths.ox.ac.uk; Flegg, Mark, E-mail: mark.flegg@monash.edu

2014-03-28

The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in termsmore » of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.« less

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

2016-11-14

In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

Stochastic inversion of cross-borehole radar data from metalliferous vein detection

NASA Astrophysics Data System (ADS)

Zeng, Zhaofa; Huai, Nan; Li, Jing; Zhao, Xueyu; Liu, Cai; Hu, Yingsa; Zhang, Ling; Hu, Zuzhi; Yang, Hui

2017-12-01

In the exploration and evaluation of the metalliferous veins with a cross-borehole radar system, traditional linear inversion methods (least squares inversion, LSQR) only get indirect parameters (permittivity, resistivity, or velocity) to estimate the target structure. They cannot accurately reflect the geological parameters of the metalliferous veins’ media properties. In order to get the intrinsic geological parameters and internal distribution, in this paper, we build a metalliferous veins model based on the stochastic effective medium theory, and carry out stochastic inversion and parameter estimation based on the Monte Carlo sampling algorithm. Compared with conventional LSQR, the stochastic inversion can get higher resolution inversion permittivity and velocity of the target body. We can estimate more accurately the distribution characteristics of abnormality and target internal parameters. It provides a new research idea to evaluate the properties of complex target media.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Modeling of Outer Radiation Belt Electron Scattering due to Spatial and Spectral Properties of ULF Waves

NASA Astrophysics Data System (ADS)

Tornquist, Mattias

The research presented in this thesis covers wave-particle interactions for relativistic (0.5-10 MeV) electrons in Earth's outer radiation belt (r = 3-7 RE, or L-shells: L = 3-7) interacting with magnetospheric Pc-5 (ULF) waves. This dissertation focuses on ideal models for short and long term electron energy and radial position scattering caused by interactions with ULF waves. We use test particle simulations to investigate these wave-particle interactions with ideal wave and magnetic dipole fields. We demonstrate that the wave-particle phase can cause various patterns in phase space trajectories, i.e. local acceleration, and that for a global electron population, for all initial conditions accounted for, has a negligible net energy scattering. Working with GSM polar coordinates, the relevant wave field components are EL, Ephi and Bz, where we find that the maximum energy scattering is 3-10 times more effective for Ephi compared to EL in a magnetic dipole field with a realistic dayside compression amplitude. We also evaluate electron interactions with two coexisting waves for a set of small frequency separations and phases, where it is confirmed that multi-resonant transport is possible for overlapping resonances in phase space when the Chirikov criterion is met (stochasticity parameter K = 1). The electron energy scattering enhances with decreasing frequency separation, i.e. increasing K, and is also dependent on the phases of the waves. The global acceleration is non-zero, can be onset in about 1 hour and last for > 4 hours. The adiabatic wave-particle interaction discussed up to this point can be regarded as short-term scattering ( tau ˜ hours ). When the physical problem extends to longer time scales (tau ˜ days ) the process ceases to be adiabatic due to the introduction of stochastic element in the system and becomes a diffusive process. We show that any mode in a broadband spectrum can contribute to the total diffusion rate for a particular drift frequency within the spectral band via dynamic phases. Each mode contributes maximally at a phase reset frequency fr = 2.63fk, where fk is the mode frequency. We experiment with electron diffusion due to interaction with wave broadband spectra in MLT sectors and find the phase reset effect being strongest when there is no azimuthal wave vector (msec = 0) within the sector. DLL rapidly coheres to the local PSD as the wave number increases and, for example, at msec = 1.00+/-0.25 the effect of phase resets is only 10-30% as strong as for msec = 0. Since phase resets depend on particle drift frequencies when MLT sectors are involved, a consequence is that DLL must adjust as a function of L-shell as well. For example, from the local PSD as the sole contributor to diffusion Schulz and Lanzerotte (1979) has shown that DLL ˜ L6 , but we prove that the function becomes DLL ˜ L5 with some variations due to fd and MLT sector width. The final part of this dissertation evaluates a pre storm commencement event on November 7, 2004, when Earth's magnetopause was struck by a high-speed solar wind with a mostly northward component of interplanetary magnetic field. We obtained a global MHD field simulated by the OpenGGC model for the interval 17:00-18:40 in universal time from NASA's Community Coordinated Modeling Center. Global distribution plots of the electric and magnetic field PSD reveal strong ULF waves spanning the whole dayside sector. There are distinct electric field modes at approximately 0.9, 2.3 and 3.7-6.3 mHz within the dayside sector, which we then used in test-particle simulations and the variance calculations in order to evaluate the diffusion coefficients. To ensure diffusion by sufficient stochasticity, we run the event by repeating the interval 10 times in series for a total duration of 12 hours. For the wave electric fields, the predicted diffusion coefficient due to local PSD matches the outcome from simulated electron scattering at 0.9 and 2.3 mHz. The diffusion due to the wider frequency band at 3.7-6.3 mHz does not fit the PSD profile alone, and requires phase resets in non-resonant modes within the spectrum to yield an agreement between the calculations and the simulations. Furthermore, only msec = 1 provides the correct solution. We have thus demonstrated the importance in including both the MLT sector width and wave number as additional significant factors apart from the local PSD in determining the diffusion coefficient for a realistic wave field. (Abstract shortened by UMI.).

Recursively constructing analytic expressions for equilibrium distributions of stochastic biochemical reaction networks.

PubMed

Meng, X Flora; Baetica, Ania-Ariadna; Singhal, Vipul; Murray, Richard M

2017-05-01

Noise is often indispensable to key cellular activities, such as gene expression, necessitating the use of stochastic models to capture its dynamics. The chemical master equation (CME) is a commonly used stochastic model of Kolmogorov forward equations that describe how the probability distribution of a chemically reacting system varies with time. Finding analytic solutions to the CME can have benefits, such as expediting simulations of multiscale biochemical reaction networks and aiding the design of distributional responses. However, analytic solutions are rarely known. A recent method of computing analytic stationary solutions relies on gluing simple state spaces together recursively at one or two states. We explore the capabilities of this method and introduce algorithms to derive analytic stationary solutions to the CME. We first formally characterize state spaces that can be constructed by performing single-state gluing of paths, cycles or both sequentially. We then study stochastic biochemical reaction networks that consist of reversible, elementary reactions with two-dimensional state spaces. We also discuss extending the method to infinite state spaces and designing the stationary behaviour of stochastic biochemical reaction networks. Finally, we illustrate the aforementioned ideas using examples that include two interconnected transcriptional components and biochemical reactions with two-dimensional state spaces. © 2017 The Author(s).

Recursively constructing analytic expressions for equilibrium distributions of stochastic biochemical reaction networks

PubMed Central

Baetica, Ania-Ariadna; Singhal, Vipul; Murray, Richard M.

2017-01-01

Noise is often indispensable to key cellular activities, such as gene expression, necessitating the use of stochastic models to capture its dynamics. The chemical master equation (CME) is a commonly used stochastic model of Kolmogorov forward equations that describe how the probability distribution of a chemically reacting system varies with time. Finding analytic solutions to the CME can have benefits, such as expediting simulations of multiscale biochemical reaction networks and aiding the design of distributional responses. However, analytic solutions are rarely known. A recent method of computing analytic stationary solutions relies on gluing simple state spaces together recursively at one or two states. We explore the capabilities of this method and introduce algorithms to derive analytic stationary solutions to the CME. We first formally characterize state spaces that can be constructed by performing single-state gluing of paths, cycles or both sequentially. We then study stochastic biochemical reaction networks that consist of reversible, elementary reactions with two-dimensional state spaces. We also discuss extending the method to infinite state spaces and designing the stationary behaviour of stochastic biochemical reaction networks. Finally, we illustrate the aforementioned ideas using examples that include two interconnected transcriptional components and biochemical reactions with two-dimensional state spaces. PMID:28566513

Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects

PubMed Central

Baumann, Hendrik; Sandmann, Werner

2016-01-01

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity. PMID:27010993

Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects.

PubMed

Baumann, Hendrik; Sandmann, Werner

2016-01-01

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity.

Stochastic Acceleration of Galactic Cosmic Rays by Compressible Plasma Fluctuations in Supernova Shells

NASA Astrophysics Data System (ADS)

Zhang, Ming

2015-10-01

A theory of 2-stage acceleration of Galactic cosmic rays in supernova remnants is proposed. The first stage is accomplished by the supernova shock front, where a power-law spectrum is established up to a certain cutoff energy. It is followed by stochastic acceleration with compressible waves/turbulence in the downstream medium. With a broad \\propto {k}-2 spectrum for the compressible plasma fluctuations, the rate of stochastic acceleration is constant over a wide range of particle momentum. In this case, the stochastic acceleration process extends the power-law spectrum cutoff energy of Galactic cosmic rays to the knee without changing the spectral slope. This situation happens as long as the rate of stochastic acceleration is faster than 1/5 of the adiabatic cooling rate. A steeper spectrum of compressible plasma fluctuations that concentrate their power in long wavelengths will accelerate cosmic rays to the knee with a small bump before its cutoff in the comic-ray energy spectrum. This theory does not require a strong amplification of the magnetic field in the upstream interstellar medium in order to accelerate cosmic rays to the knee energy.

Ion precipitation from the inner plasma sheet due to stochastic diffusion

NASA Technical Reports Server (NTRS)

Zelenyi, L.; Galeev, A.; Kennel, C. F.

1990-01-01

Plasma sheet ions do not conserve their first adiabatic invariant when the magnetic field is appreciably tail-like. They do conserve a different adiabatic invariant but only to linear, rather than exponential, accuracy in the appropriate small parameter. Thus significant stochastic diffusion can occur for particles crossing the separatrix dividing the segments of orbits on which the particles cross and do not cross the tail midplane. Such ions can escape the plasma sheet and precipitate into the atmosphere. Stochastic scattering is strongest from those field lines where the ion's Larmor period in the normal component of the neutral sheet magnetic field approximately equals its bounce period. By comparing the rates of stochastic ion loss and convection in the tail, it is possible to estimate the location and thickness of the inner edge of the ion plasma sheet created by stochastic ion loss. Ions of different masses precipitate into the atmosphere at slightly different locations. Since wave particle interactions are not needed, this precipitation will always occur and should be particularly evident during quiet geomagnetic conditions, when it is less likely to be masked by other precipitation mechanisms.

Numerical simulations in stochastic mechanics

NASA Astrophysics Data System (ADS)

McClendon, Marvin; Rabitz, Herschel

1988-05-01

The stochastic differential equation of Nelson's stochastic mechanics is integrated numerically for several simple quantum systems. The calculations are performed with use of Helfand and Greenside's method and pseudorandom numbers. The resulting trajectories are analyzed both individually and collectively to yield insight into momentum, uncertainty principles, interference, tunneling, quantum chaos, and common models of diatomic molecules from the stochastic quantization point of view. In addition to confirming Shucker's momentum theorem, these simulations illustrate, within the context of stochastic mechanics, the position-momentum and time-energy uncertainty relations, the two-slit diffraction pattern, exponential decay of an unstable system, and the greater degree of anticorrelation in a valence-bond model as compared with a molecular-orbital model of H2. The attempt to find exponential divergence of initially nearby trajectories, potentially useful as a criterion for quantum chaos, in a periodically forced oscillator is inconclusive. A way of computing excited energies from the ground-state motion is presented. In all of these studies the use of particle trajectories allows a more insightful interpretation of physical phenomena than is possible within traditional wave mechanics.

Explicit mathematical construction of relativistic nonlinear de Broglie waves described by three-dimensional (wave and electromagnetic) solitons ``piloted'' (controlled) by corresponding solutions of associated linear Klein-Gordon and Schrödinger equations

NASA Astrophysics Data System (ADS)

Vigier, Jean-Pierre

1991-02-01

Starting from a nonlinear relativistic Klein-Gordon equation derived from the stochastic interpretation of quantum mechanics (proposed by Bohm-Vigier, (1) Nelson, (2) de Broglie, (3) Guerra et al. (4) ), one can construct joint wave and particle, soliton-like solutions, which follow the average de Broglie-Bohm (5) real trajectories associated with linear solutions of the usual Schrödinger and Klein-Gordon equations.

Stochastic Evolution Equations Driven by Fractional Noises

DTIC Science & Technology

2016-11-28

rate of convergence to zero or the error and the limit in distribution of the error fluctuations. We have studied time discrete numerical schemes...error fluctuations. We have studied time discrete numerical schemes based on Taylor expansions for rough differential equations and for stochastic...variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian

Fault detection and diagnosis for non-Gaussian stochastic distribution systems with time delays via RBF neural networks.

PubMed

Yi, Qu; Zhan-ming, Li; Er-chao, Li

2012-11-01

A new fault detection and diagnosis (FDD) problem via the output probability density functions (PDFs) for non-gausian stochastic distribution systems (SDSs) is investigated. The PDFs can be approximated by radial basis functions (RBFs) neural networks. Different from conventional FDD problems, the measured information for FDD is the output stochastic distributions and the stochastic variables involved are not confined to Gaussian ones. A (RBFs) neural network technique is proposed so that the output PDFs can be formulated in terms of the dynamic weighings of the RBFs neural network. In this work, a nonlinear adaptive observer-based fault detection and diagnosis algorithm is presented by introducing the tuning parameter so that the residual is as sensitive as possible to the fault. Stability and Convergency analysis is performed in fault detection and fault diagnosis analysis for the error dynamic system. At last, an illustrated example is given to demonstrate the efficiency of the proposed algorithm, and satisfactory results have been obtained. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

ULTRASONIC STUDIES OF THE FUNDAMENTAL MECHANISMS OF RECRYSTALLIZATION AND SINTERING OF METALS

DOE Office of Scientific and Technical Information (OSTI.GOV)

TURNER, JOSEPH A.

2005-11-30

The purpose of this project was to develop a fundamental understanding of the interaction of an ultrasonic wave with complex media, with specific emphases on recrystallization and sintering of metals. A combined analytical, numerical, and experimental research program was implemented. Theoretical models of elastic wave propagation through these complex materials were developed using stochastic wave field techniques. The numerical simulations focused on finite element wave propagation solutions through complex media. The experimental efforts were focused on corroboration of the models developed and on the development of new experimental techniques. The analytical and numerical research allows the experimental results to bemore » interpreted quantitatively.« less

Learning stochastic reward distributions in a speeded pointing task.

PubMed

Seydell, Anna; McCann, Brian C; Trommershäuser, Julia; Knill, David C

2008-04-23

Recent studies have shown that humans effectively take into account task variance caused by intrinsic motor noise when planning fast hand movements. However, previous evidence suggests that humans have greater difficulty accounting for arbitrary forms of stochasticity in their environment, both in economic decision making and sensorimotor tasks. We hypothesized that humans can learn to optimize movement strategies when environmental randomness can be experienced and thus implicitly learned over several trials, especially if it mimics the kinds of randomness for which subjects might have generative models. We tested the hypothesis using a task in which subjects had to rapidly point at a target region partly covered by three stochastic penalty regions introduced as "defenders." At movement completion, each defender jumped to a new position drawn randomly from fixed probability distributions. Subjects earned points when they hit the target, unblocked by a defender, and lost points otherwise. Results indicate that after approximately 600 trials, subjects approached optimal behavior. We further tested whether subjects simply learned a set of stimulus-contingent motor plans or the statistics of defenders' movements by training subjects with one penalty distribution and then testing them on a new penalty distribution. Subjects immediately changed their strategy to achieve the same average reward as subjects who had trained with the second penalty distribution. These results indicate that subjects learned the parameters of the defenders' jump distributions and used this knowledge to optimally plan their hand movements under conditions involving stochastic rewards and penalties.

Discrete Deterministic and Stochastic Petri Nets

NASA Technical Reports Server (NTRS)

Zijal, Robert; Ciardo, Gianfranco

1996-01-01

Petri nets augmented with timing specifications gained a wide acceptance in the area of performance and reliability evaluation of complex systems exhibiting concurrency, synchronization, and conflicts. The state space of time-extended Petri nets is mapped onto its basic underlying stochastic process, which can be shown to be Markovian under the assumption of exponentially distributed firing times. The integration of exponentially and non-exponentially distributed timing is still one of the major problems for the analysis and was first attacked for continuous time Petri nets at the cost of structural or analytical restrictions. We propose a discrete deterministic and stochastic Petri net (DDSPN) formalism with no imposed structural or analytical restrictions where transitions can fire either in zero time or according to arbitrary firing times that can be represented as the time to absorption in a finite absorbing discrete time Markov chain (DTMC). Exponentially distributed firing times are then approximated arbitrarily well by geometric distributions. Deterministic firing times are a special case of the geometric distribution. The underlying stochastic process of a DDSPN is then also a DTMC, from which the transient and stationary solution can be obtained by standard techniques. A comprehensive algorithm and some state space reduction techniques for the analysis of DDSPNs are presented comprising the automatic detection of conflicts and confusions, which removes a major obstacle for the analysis of discrete time models.

Getting Astrophysical Information from LISA Data

NASA Technical Reports Server (NTRS)

Stebbins, R. T.; Bender, P. L.; Folkner, W. M.

1997-01-01

Gravitational wave signals from a large number of astrophysical sources will be present in the LISA data. Information about as many sources as possible must be estimated from time series of strain measurements. Several types of signals are expected to be present: simple periodic signals from relatively stable binary systems, chirped signals from coalescing binary systems, complex waveforms from highly relativistic binary systems, stochastic backgrounds from galactic and extragalactic binary systems and possibly stochastic backgrounds from the early Universe. The orbital motion of the LISA antenna will modulate the phase and amplitude of all these signals, except the isotropic backgrounds and thereby give information on the directions of sources. Here we describe a candidate process for disentangling the gravitational wave signals and estimating the relevant astrophysical parameters from one year of LISA data. Nearly all of the sources will be identified by searching with templates based on source parameters and directions.

Langevin approach to a chemical wave front: Selection of the propagation velocity in the presence of internal noise

NASA Astrophysics Data System (ADS)

Lemarchand, A.; Lesne, A.; Mareschal, M.

1995-05-01

The reaction-diffusion equation associated with the Fisher chemical model A+B-->2A admits wave-front solutions by replacing an unstable stationary state with a stable one. The deterministic analysis concludes that their propagation velocity is not prescribed by the dynamics. For a large class of initial conditions the velocity which is spontaneously selected is equal to the minimum allowed velocity vmin, as predicted by the marginal stability criterion. In order to test the relevance of this deterministic description we investigate the macroscopic consequences, on the velocity and the width of the front, of the intrinsic stochasticity due to the underlying microscopic dynamics. We solve numerically the Langevin equations, deduced analytically from the master equation within a system size expansion procedure. We show that the mean profile associated with the stochastic solution propagates faster than the deterministic solution at a velocity up to 25% greater than vmin.

Sensitivity curves for searches for gravitational-wave backgrounds

NASA Astrophysics Data System (ADS)

Thrane, Eric; Romano, Joseph D.

2013-12-01

We propose a graphical representation of detector sensitivity curves for stochastic gravitational-wave backgrounds that takes into account the increase in sensitivity that comes from integrating over frequency in addition to integrating over time. This method is valid for backgrounds that have a power-law spectrum in the analysis band. We call these graphs “power-law integrated curves.” For simplicity, we consider cross-correlation searches for unpolarized and isotropic stochastic backgrounds using two or more detectors. We apply our method to construct power-law integrated sensitivity curves for second-generation ground-based detectors such as Advanced LIGO, space-based detectors such as LISA and the Big Bang Observer, and timing residuals from a pulsar timing array. The code used to produce these plots is available at https://dcc.ligo.org/LIGO-P1300115/public for researchers interested in constructing similar sensitivity curves.

Stochastic process of pragmatic information for 2D spiral wave turbulence in globally and locally coupled Alief-Panfilov oscillators

NASA Astrophysics Data System (ADS)

Kuwahara, Jun; Miyata, Hajime; Konno, Hidetoshi

2017-09-01

Recently, complex dynamics of globally coupled oscillators have been attracting many researcher's attentions. In spite of their numerous studies, their features of nonlinear oscillator systems with global and local couplings in two-dimension (2D) are not understood fully. The paper focuses on 2D states of coherent, clustered and chaotic oscillation especially under the effect of negative global coupling (NGC) in 2D Alief-Panfilov model. It is found that the tuning NGC can cause various new coupling-parameter dependency on the features of oscillations. Then quantitative characterization of various states of oscillations (so called spiral wave turbulence) is examined by using the pragmatic information (PI) which have been utilized in analyzing multimode laser, solar activity and neuronal systems. It is demonstrated that the dynamics of the PI for various oscillations can be characterized successfully by the Hyper-Gamma stochastic process.

Constraining stochastic gravitational wave background from weak lensing of CMB B-modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shaikh, Shabbir; Mukherjee, Suvodip; Souradeep, Tarun

2016-09-01

A stochastic gravitational wave background (SGWB) will affect the CMB anisotropies via weak lensing. Unlike weak lensing due to large scale structure which only deflects photon trajectories, a SGWB has an additional effect of rotating the polarization vector along the trajectory. We study the relative importance of these two effects, deflection and rotation, specifically in the context of E-mode to B-mode power transfer caused by weak lensing due to SGWB. Using weak lensing distortion of the CMB as a probe, we derive constraints on the spectral energy density (Ω{sub GW}) of the SGWB, sourced at different redshifts, without assuming anymore » particular model for its origin. We present these bounds on Ω{sub GW} for different power-law models characterizing the SGWB, indicating the threshold above which observable imprints of SGWB must be present in CMB.« less

The stochastic spectator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardwick, Robert J.; Vennin, Vincent; Wands, David

We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can bemore » much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.« less

A common stochastic accumulator with effector-dependent noise can explain eye-hand coordination

PubMed Central

Gopal, Atul; Viswanathan, Pooja

2015-01-01

The computational architecture that enables the flexible coupling between otherwise independent eye and hand effector systems is not understood. By using a drift diffusion framework, in which variability of the reaction time (RT) distribution scales with mean RT, we tested the ability of a common stochastic accumulator to explain eye-hand coordination. Using a combination of behavior, computational modeling and electromyography, we show how a single stochastic accumulator to threshold, followed by noisy effector-dependent delays, explains eye-hand RT distributions and their correlation, while an alternate independent, interactive eye and hand accumulator model does not. Interestingly, the common accumulator model did not explain the RT distributions of the same subjects when they made eye and hand movements in isolation. Taken together, these data suggest that a dedicated circuit underlies coordinated eye-hand planning. PMID:25568161

Stochastic density waves of granular flows: strong-intermittent dissipation fields with self-organization

NASA Astrophysics Data System (ADS)

Bershadskii, A.

1994-10-01

The quantitative (scaling) results of a recent lattice-gas simulation of granular flows [1] are interpreted in terms of Kolmogorov-Obukhov approach revised for strong space-intermittent systems. Renormalised power spectrum with exponent '-4/3' seems to be an universal spectrum of scalar fluctuations convected by stochastic velocity fields in dissipative systems with inverse energy transfer (some other laboratory and geophysic turbulent flows with this power spectrum as well as an analogy between this phenomenon and turbulent percolation on elastic backbone are pointed out).

Phase locking of a seven-channel continuous wave fibre laser system by a stochastic parallel gradient algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volkov, M V; Garanin, S G; Dolgopolov, Yu V

2014-11-30

A seven-channel fibre laser system operated by the master oscillator – multichannel power amplifier scheme is the phase locked using a stochastic parallel gradient algorithm. The phase modulators on lithium niobate crystals are controlled by a multichannel electronic unit with the microcontroller processing signals in real time. The dynamic phase locking of the laser system with the bandwidth of 14 kHz is demonstrated, the time of phasing is 3 – 4 ms. (fibre and integrated-optical structures)

Stochastic wave-function unravelling of the generalized Lindblad equation

NASA Astrophysics Data System (ADS)

Semin, V.; Semina, I.; Petruccione, F.

2017-12-01

We investigate generalized non-Markovian stochastic Schrödinger equations (SSEs), driven by a multidimensional counting process and multidimensional Brownian motion introduced by A. Barchielli and C. Pellegrini [J. Math. Phys. 51, 112104 (2010), 10.1063/1.3514539]. We show that these SSEs can be translated in a nonlinear form, which can be efficiently simulated. The simulation is illustrated by the model of a two-level system in a structured bath, and the results of the simulations are compared with the exact solution of the generalized master equation.

The divine clockwork: Bohr's correspondence principle and Nelson's stochastic mechanics for the atomic elliptic state

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durran, Richard; Neate, Andrew; Truman, Aubrey

2008-03-15

We consider the Bohr correspondence limit of the Schroedinger wave function for an atomic elliptic state. We analyze this limit in the context of Nelson's stochastic mechanics, exposing an underlying deterministic dynamical system in which trajectories converge to Keplerian motion on an ellipse. This solves the long standing problem of obtaining Kepler's laws of planetary motion in a quantum mechanical setting. In this quantum mechanical setting, local mild instabilities occur in the Keplerian orbit for eccentricities greater than (1/{radical}(2)) which do not occur classically.

Cellular Mechanisms of Calcium-Mediated Triggered Activity

NASA Astrophysics Data System (ADS)

Song, Zhen

Life-threatening cardiac arrhythmias continue to pose a major health problem. Ventricular fibrillation, which is a complex form of electrical wave turbulence in the lower chambers of the heart, stops the heart from pumping and is the largest cause of natural death in the United States. Atrial fibrillation, a related form of wave turbulence in the upper heart chambers, is in turn the most common arrhythmia diagnosed in clinical practice. Despite extensive research to date, mechanisms of cardiac arrhythmias remain poorly understood. It is well established that both spatial disorder of the refractory period of heart cells and triggered activity (TA) jointly contribute to the initiation and maintenance of arrhythmias. TA broadly refers to the abnormal generation of a single or a sequence of abnormal excitation waves from a small submillimeter region of the heart in the interval of time between two normal waves generated by the heart's natural pacemaker (the sinoatrial node). TA has been widely investigated experimentally and occurs in several pathological conditions where the intracellular concentration of free Ca2+ ions in heart cells becomes elevated. Under such conditions, Ca2+ can be spontaneously released from intracellular stores, thereby driving an electrogenic current that exchanges 3Na+ ions for one Ca2+ ion across the cell membrane. This current in turn depolarizes the membrane of heart cells after a normal excitation. If this calcium-mediated "delayed after depolarization'' (DAD) is sufficiently large, it can generate an action potential. While the arrhythmogenic importance of spontaneous Ca2+ release and DADs is well appreciated, the conditions under which they occur in heart pathologies remain poorly understood. Calcium overload is only one factor among several other factors that can promote DADs, including sympathetic nerve stimulation, different expression levels of membrane ion channels and calcium handling proteins, and different mutations of those proteins. How those various factors interact synergistically to promote DADs is not well understood. Furthermore, at an even more basic level, it remains unclear to what degree spontaneous Ca2+ release and the appearance of DADs are deterministic, meaning reproducible under identical conditions, or inherently stochastic like nucleation in the physical context of phase transitions. In this thesis, we use and further develop a biologically detailed computational model to investigate basic aspects of TA in isolated heart cells (cardiac myocytes). Isolated cells can be obtained by enzymatic dissociation of heart tissue and studied experimentally using standard electrophysiological recording methods and confocal imaging of Ca2+ dynamics. Hence they provide a well controlled setting to investigate the generation of DADs under well controlled conditions. Our computational model captures essential aspects of the hierarchical architecture of ventricular myocytes, which consists of a large number of approximately 20,000 to 50,000 regularly spaced submicron regions containing clusters of 50-100 Ryanodine receptor (RyR) Ca2+ release channels. Each of those regions acts as a discrete "calcium release unit'' (CRU). Therefore our model allows us to address for the first time quantitatively the fundamental question of whether Ca2+ release, which is highly stochastic at the level of a single calcium release unit, is stochastic or deterministic at the whole cell level where the Ca 2+ signal is the summation of releases from a large number of units. Addressing this question is the focus of the first part of this thesis. Our results demonstrate that both the initiation and termination of TA are highly stochastic at the whole cell level due to the spatiotemporal organization of discrete release events into multiple Ca2+ waves. Our results allow us to characterize the probability distributions that govern the number of DADs preceding a triggered action potential and the number of triggered action potentials after termination of periodic stimulation. We show that a limit cycle underlies the bi-directionally coupled dynamics of membrane of voltage and Ca2+ when TA is sustained for long intervals. Furthermore, we construct a simple theoretical model that allows us to relate the shape of those distributions to the statistics and properties of Ca 2+ waves. The second part of this thesis focuses on investigating TA in the context of a specific mutation of a calcium buffering protein calsequestrin (CSQN). This mutation underlies catecholaminergic polymorphic ventricular tachycardia (CPVT), which is a pathophysiological condition that affects a subset of the human population. Our results shed light on the mechanisms by which altered Ca2+ buffering and altered kinetics of RyR Ca 2+ release channels as a direct and indirect effect of this mutation, respectively, promote TA.

K-Minimax Stochastic Programming Problems

NASA Astrophysics Data System (ADS)

Nedeva, C.

2007-10-01

The purpose of this paper is a discussion of a numerical procedure based on the simplex method for stochastic optimization problems with partially known distribution functions. The convergence of this procedure is proved by the condition on dual problems.

Mechanism of spiral formation in heterogeneous discretized excitable media.

PubMed

Kinoshita, Shu-ichi; Iwamoto, Mayuko; Tateishi, Keita; Suematsu, Nobuhiko J; Ueyama, Daishin

2013-06-01

Spiral waves on excitable media strongly influence the functions of living systems in both a positive and negative way. The spiral formation mechanism has thus been one of the major themes in the field of reaction-diffusion systems. Although the widely believed origin of spiral waves is the interaction of traveling waves, the heterogeneity of an excitable medium has recently been suggested as a probable cause. We suggest one possible origin of spiral waves using a Belousov-Zhabotinsky reaction and a discretized FitzHugh-Nagumo model. The heterogeneity of the reaction field is shown to stochastically generate unidirectional sites, which can induce spiral waves. Furthermore, we found that the spiral wave vanished with only a small reduction in the excitability of the reaction field. These results reveal a gentle approach for controlling the appearance of a spiral wave on an excitable medium.

Universality in stochastic exponential growth.

PubMed

Iyer-Biswas, Srividya; Crooks, Gavin E; Scherer, Norbert F; Dinner, Aaron R

2014-07-11

Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth.

A New Methodology for Open Pit Slope Design in Karst-Prone Ground Conditions Based on Integrated Stochastic-Limit Equilibrium Analysis

NASA Astrophysics Data System (ADS)

Zhang, Ke; Cao, Ping; Ma, Guowei; Fan, Wenchen; Meng, Jingjing; Li, Kaihui

2016-07-01

Using the Chengmenshan Copper Mine as a case study, a new methodology for open pit slope design in karst-prone ground conditions is presented based on integrated stochastic-limit equilibrium analysis. The numerical modeling and optimization design procedure contain a collection of drill core data, karst cave stochastic model generation, SLIDE simulation and bisection method optimization. Borehole investigations are performed, and the statistical result shows that the length of the karst cave fits a negative exponential distribution model, but the length of carbonatite does not exactly follow any standard distribution. The inverse transform method and acceptance-rejection method are used to reproduce the length of the karst cave and carbonatite, respectively. A code for karst cave stochastic model generation, named KCSMG, is developed. The stability of the rock slope with the karst cave stochastic model is analyzed by combining the KCSMG code and the SLIDE program. This approach is then applied to study the effect of the karst cave on the stability of the open pit slope, and a procedure to optimize the open pit slope angle is presented.

Universality in Stochastic Exponential Growth

NASA Astrophysics Data System (ADS)

Iyer-Biswas, Srividya; Crooks, Gavin E.; Scherer, Norbert F.; Dinner, Aaron R.

2014-07-01

Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth.

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

NASA Astrophysics Data System (ADS)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Superstatistical generalised Langevin equation: non-Gaussian viscoelastic anomalous diffusion

NASA Astrophysics Data System (ADS)

Ślęzak, Jakub; Metzler, Ralf; Magdziarz, Marcin

2018-02-01

Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.

On the probabilistic structure of water age: Probabilistic Water Age

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porporato, Amilcare; Calabrese, Salvatore

We report the age distribution of water in hydrologic systems has received renewed interest recently, especially in relation to watershed response to rainfall inputs. The purpose of this contribution is first to draw attention to existing theories of age distributions in population dynamics, fluid mechanics and stochastic groundwater, and in particular to the McKendrick-von Foerster equation and its generalizations and solutions. A second and more important goal is to clarify that, when hydrologic fluxes are modeled by means of time-varying stochastic processes, the age distributions must themselves be treated as random functions. Once their probabilistic structure is obtained, it canmore » be used to characterize the variability of age distributions in real systems and thus help quantify the inherent uncertainty in the field determination of water age. Finally, we illustrate these concepts with reference to a stochastic storage model, which has been used as a minimalist model of soil moisture and streamflow dynamics.« less

On the probabilistic structure of water age: Probabilistic Water Age

DOE PAGES

Porporato, Amilcare; Calabrese, Salvatore

2015-04-23

We report the age distribution of water in hydrologic systems has received renewed interest recently, especially in relation to watershed response to rainfall inputs. The purpose of this contribution is first to draw attention to existing theories of age distributions in population dynamics, fluid mechanics and stochastic groundwater, and in particular to the McKendrick-von Foerster equation and its generalizations and solutions. A second and more important goal is to clarify that, when hydrologic fluxes are modeled by means of time-varying stochastic processes, the age distributions must themselves be treated as random functions. Once their probabilistic structure is obtained, it canmore » be used to characterize the variability of age distributions in real systems and thus help quantify the inherent uncertainty in the field determination of water age. Finally, we illustrate these concepts with reference to a stochastic storage model, which has been used as a minimalist model of soil moisture and streamflow dynamics.« less

On the detection of a stochastic background of gravitational radiation by the Doppler tracking of spacecraft

NASA Technical Reports Server (NTRS)

Mashhoon, B.; Grishchuk, L. P.

1980-01-01

Consideration is given to the possibility of detection of an isotropic background gravitational radiation of a stochastic nature by the method of Doppler tracking of spacecraft. Attention is given in the geometrical optics limit, to the general formula for the frequency shift of an electromagnetic signal in the gravitational radiation field, and it is shown to be gauge independent. The propagation of a free electromagnetic wave in a gravitational radiation field is examined with the conclusion that no resonance phenomena can be expected. Finally, the 'Doppler noise' due to a stochastic background is evaluated, and it is shown to depend on the total energy density of the background and a parameter that is a characteristic of the radiation spectrum and the detection system used.

Price-Dynamics of Shares and Bohmian Mechanics: Deterministic or Stochastic Model?

NASA Astrophysics Data System (ADS)

Choustova, Olga

2007-02-01

We apply the mathematical formalism of Bohmian mechanics to describe dynamics of shares. The main distinguishing feature of the financial Bohmian model is the possibility to take into account market psychology by describing expectations of traders by the pilot wave. We also discuss some objections (coming from conventional financial mathematics of stochastic processes) against the deterministic Bohmian model. In particular, the objection that such a model contradicts to the efficient market hypothesis which is the cornerstone of the modern market ideology. Another objection is of pure mathematical nature: it is related to the quadratic variation of price trajectories. One possibility to reply to this critique is to consider the stochastic Bohm-Vigier model, instead of the deterministic one. We do this in the present note.

Stochastic Seismic Response of an Algiers Site with Random Depth to Bedrock

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badaoui, M.; Mebarki, A.; Berrah, M. K.

2010-05-21

Among the important effects of the Boumerdes earthquake (Algeria, May 21{sup st} 2003) was that, within the same zone, the destructions in certain parts were more important than in others. This phenomenon is due to site effects which alter the characteristics of seismic motions and cause concentration of damage during earthquakes. Local site effects such as thickness and mechanical properties of soil layers have important effects on the surface ground motions.This paper deals with the effect of the randomness aspect of the depth to bedrock (soil layers heights) which is assumed to be a random variable with lognormal distribution. Thismore » distribution is suitable for strictly non-negative random variables with large values of the coefficient of variation. In this case, Monte Carlo simulations are combined with the stiffness matrix method, used herein as a deterministic method, for evaluating the effect of the depth to bedrock uncertainty on the seismic response of a multilayered soil. This study considers a P and SV wave propagation pattern using input accelerations collected at Keddara station, located at 20 km from the epicenter, as it is located directly on the bedrock.A parametric study is conducted do derive the stochastic behavior of the peak ground acceleration and its response spectrum, the transfer function and the amplification factors. It is found that the soil height heterogeneity causes a widening of the frequency content and an increase in the fundamental frequency of the soil profile, indicating that the resonance phenomenon concerns a larger number of structures.« less

Phase-space dependent critical gradient behavior of fast-ion transport due to Alfvén eigenmodes

DOE PAGES

Collins, C. S.; Heidbrink, W. W.; Podestà, M.; ...

2017-06-09

Experiments in the DIII-D tokamak show that many overlapping small-amplitude Alfv en eigenmodes (AEs) cause fast-ion transport to sharply increase above a critical threshold, leading to fast-ion density profile resilience and reduced fusion performance. The threshold is above the AE linear stability limit and varies between diagnostics that are sensitive to different parts of fast-ion phase-space. A comparison with theoretical analysis using the nova and orbit codes shows that, for the neutral particle diagnostic, the threshold corresponds to the onset of stochastic particle orbits due to wave-particle resonances with AEs in the measured region of phase space. We manipulated themore » bulk fast-ion distribution and instability behavior through variations in beam deposition geometry, and no significant differences in the onset threshold outside of measurement uncertainties were found, in agreement with the theoretical stochastic threshold analysis. Simulations using the `kick model' produce beam ion density gradients consistent with the empirically measured radial critical gradient and highlight the importance of including the energy and pitch dependence of the fast-ion distribution function in critical gradient models. The addition of electron cyclotron heating changes the types of AEs present in the experiment, comparatively increasing the measured fast-ion density and radial gradient. Our studies provide the basis for understanding how to avoid AE transport that can undesirably redistribute current and cause fast-ion losses, and the measurements are being used to validate AE-induced transport models that use the critical gradient paradigm, giving greater confidence when applied to ITER.« less

Phase-space dependent critical gradient behavior of fast-ion transport due to Alfvén eigenmodes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, C. S.; Heidbrink, W. W.; Podestà, M.

Experiments in the DIII-D tokamak show that many overlapping small-amplitude Alfv en eigenmodes (AEs) cause fast-ion transport to sharply increase above a critical threshold, leading to fast-ion density profile resilience and reduced fusion performance. The threshold is above the AE linear stability limit and varies between diagnostics that are sensitive to different parts of fast-ion phase-space. A comparison with theoretical analysis using the nova and orbit codes shows that, for the neutral particle diagnostic, the threshold corresponds to the onset of stochastic particle orbits due to wave-particle resonances with AEs in the measured region of phase space. We manipulated themore » bulk fast-ion distribution and instability behavior through variations in beam deposition geometry, and no significant differences in the onset threshold outside of measurement uncertainties were found, in agreement with the theoretical stochastic threshold analysis. Simulations using the `kick model' produce beam ion density gradients consistent with the empirically measured radial critical gradient and highlight the importance of including the energy and pitch dependence of the fast-ion distribution function in critical gradient models. The addition of electron cyclotron heating changes the types of AEs present in the experiment, comparatively increasing the measured fast-ion density and radial gradient. Our studies provide the basis for understanding how to avoid AE transport that can undesirably redistribute current and cause fast-ion losses, and the measurements are being used to validate AE-induced transport models that use the critical gradient paradigm, giving greater confidence when applied to ITER.« less

Improved estimation of hydraulic conductivity by combining stochastically simulated hydrofacies with geophysical data.

PubMed

Zhu, Lin; Gong, Huili; Chen, Yun; Li, Xiaojuan; Chang, Xiang; Cui, Yijiao

2016-03-01

Hydraulic conductivity is a major parameter affecting the output accuracy of groundwater flow and transport models. The most commonly used semi-empirical formula for estimating conductivity is Kozeny-Carman equation. However, this method alone does not work well with heterogeneous strata. Two important parameters, grain size and porosity, often show spatial variations at different scales. This study proposes a method for estimating conductivity distributions by combining a stochastic hydrofacies model with geophysical methods. The Markov chain model with transition probability matrix was adopted to re-construct structures of hydrofacies for deriving spatial deposit information. The geophysical and hydro-chemical data were used to estimate the porosity distribution through the Archie's law. Results show that the stochastic simulated hydrofacies model reflects the sedimentary features with an average model accuracy of 78% in comparison with borehole log data in the Chaobai alluvial fan. The estimated conductivity is reasonable and of the same order of magnitude of the outcomes of the pumping tests. The conductivity distribution is consistent with the sedimentary distributions. This study provides more reliable spatial distributions of the hydraulic parameters for further numerical modeling.

Integrated seismic stochastic inversion and multi-attributes to delineate reservoir distribution: Case study MZ fields, Central Sumatra Basin

NASA Astrophysics Data System (ADS)

Haris, A.; Novriyani, M.; Suparno, S.; Hidayat, R.; Riyanto, A.

2017-07-01

This study presents the integration of seismic stochastic inversion and multi-attributes for delineating the reservoir distribution in term of lithology and porosity in the formation within depth interval between the Top Sihapas and Top Pematang. The method that has been used is a stochastic inversion, which is integrated with multi-attribute seismic by applying neural network Probabilistic Neural Network (PNN). Stochastic methods are used to predict the probability mapping sandstone as the result of impedance varied with 50 realizations that will produce a good probability. Analysis of Stochastic Seismic Tnversion provides more interpretive because it directly gives the value of the property. Our experiment shows that AT of stochastic inversion provides more diverse uncertainty so that the probability value will be close to the actual values. The produced AT is then used for an input of a multi-attribute analysis, which is used to predict the gamma ray, density and porosity logs. To obtain the number of attributes that are used, stepwise regression algorithm is applied. The results are attributes which are used in the process of PNN. This PNN method is chosen because it has the best correlation of others neural network method. Finally, we interpret the product of the multi-attribute analysis are in the form of pseudo-gamma ray volume, density volume and volume of pseudo-porosity to delineate the reservoir distribution. Our interpretation shows that the structural trap is identified in the southeastern part of study area, which is along the anticline.

Selection of intracellular calcium patterns in a model with clustered Ca2+ release channels

NASA Astrophysics Data System (ADS)

Shuai, J. W.; Jung, P.

2003-03-01

A two-dimensional model is proposed for intracellular Ca2+ waves, which incorporates both the discrete nature of Ca2+ release sites in the endoplasmic reticulum membrane and the stochastic dynamics of the clustered inositol 1,4,5-triphosphate (IP3) receptors. Depending on the Ca2+ diffusion coefficient and concentration of IP3, various spontaneous Ca2+ patterns, such as calcium puffs, local waves, abortive waves, global oscillation, and tide waves, can be observed. We further investigate the speed of the global waves as a function of the IP3 concentration and the Ca2+ diffusion coefficient and under what conditions the spatially averaged Ca2+ response can be described by a simple set of ordinary differential equations.

Endogenous Crisis Waves: Stochastic Model with Synchronized Collective Behavior

NASA Astrophysics Data System (ADS)

Gualdi, Stanislao; Bouchaud, Jean-Philippe; Cencetti, Giulia; Tarzia, Marco; Zamponi, Francesco

2015-02-01

We propose a simple framework to understand commonly observed crisis waves in macroeconomic agent-based models, which is also relevant to a variety of other physical or biological situations where synchronization occurs. We compute exactly the phase diagram of the model and the location of the synchronization transition in parameter space. Many modifications and extensions can be studied, confirming that the synchronization transition is extremely robust against various sources of noise or imperfections.

Asymptotic behavior of distributions of mRNA and protein levels in a model of stochastic gene expression

NASA Astrophysics Data System (ADS)

Bobrowski, Adam; Lipniacki, Tomasz; Pichór, Katarzyna; Rudnicki, Ryszard

2007-09-01

The paper is devoted to a stochastic process introduced in the recent paper by Lipniacki et al. [T. Lipniacki, P. Paszek, A. Marciniak-Czochra, A.RE Brasier, M. Kimmel, Transcriptional stochasticity in gene expression, JE Theor. Biol. 238 (2006) 348-367] in modelling gene expression in eukaryotes. Starting from the full generator of the process we show that its distributions satisfy a (Fokker-Planck-type) system of partial differential equations. Then, we construct a c0 Markov semigroup in L1 space corresponding to this system. The main result of the paper is asymptotic stability of the involved semigroup in the set of densities.

Directed Abelian algebras and their application to stochastic models.

PubMed

Alcaraz, F C; Rittenberg, V

2008-10-01

With each directed acyclic graph (this includes some D-dimensional lattices) one can associate some Abelian algebras that we call directed Abelian algebras (DAAs). On each site of the graph one attaches a generator of the algebra. These algebras depend on several parameters and are semisimple. Using any DAA, one can define a family of Hamiltonians which give the continuous time evolution of a stochastic process. The calculation of the spectra and ground-state wave functions (stationary state probability distributions) is an easy algebraic exercise. If one considers D-dimensional lattices and chooses Hamiltonians linear in the generators, in finite-size scaling the Hamiltonian spectrum is gapless with a critical dynamic exponent z=D. One possible application of the DAA is to sandpile models. In the paper we present this application, considering one- and two-dimensional lattices. In the one-dimensional case, when the DAA conserves the number of particles, the avalanches belong to the random walker universality class (critical exponent sigma_(tau)=32 ). We study the local density of particles inside large avalanches, showing a depletion of particles at the source of the avalanche and an enrichment at its end. In two dimensions we did extensive Monte-Carlo simulations and found sigma_(tau)=1.780+/-0.005 .

A simple approximation of moments of the quasi-equilibrium distribution of an extended stochastic theta-logistic model with non-integer powers.

PubMed

Bhowmick, Amiya Ranjan; Bandyopadhyay, Subhadip; Rana, Sourav; Bhattacharya, Sabyasachi

2016-01-01

The stochastic versions of the logistic and extended logistic growth models are applied successfully to explain many real-life population dynamics and share a central body of literature in stochastic modeling of ecological systems. To understand the randomness in the population dynamics of the underlying processes completely, it is important to have a clear idea about the quasi-equilibrium distribution and its moments. Bartlett et al. (1960) took a pioneering attempt for estimating the moments of the quasi-equilibrium distribution of the stochastic logistic model. Matis and Kiffe (1996) obtain a set of more accurate and elegant approximations for the mean, variance and skewness of the quasi-equilibrium distribution of the same model using cumulant truncation method. The method is extended for stochastic power law logistic family by the same and several other authors (Nasell, 2003; Singh and Hespanha, 2007). Cumulant truncation and some alternative methods e.g. saddle point approximation, derivative matching approach can be applied if the powers involved in the extended logistic set up are integers, although plenty of evidence is available for non-integer powers in many practical situations (Sibly et al., 2005). In this paper, we develop a set of new approximations for mean, variance and skewness of the quasi-equilibrium distribution under more general family of growth curves, which is applicable for both integer and non-integer powers. The deterministic counterpart of this family of models captures both monotonic and non-monotonic behavior of the per capita growth rate, of which theta-logistic is a special case. The approximations accurately estimate the first three order moments of the quasi-equilibrium distribution. The proposed method is illustrated with simulated data and real data from global population dynamics database. Copyright © 2015 Elsevier Inc. All rights reserved.

First-passage times for pattern formation in nonlocal partial differential equations

NASA Astrophysics Data System (ADS)

Cáceres, Manuel O.; Fuentes, Miguel A.

2015-10-01

We describe the lifetimes associated with the stochastic evolution from an unstable uniform state to a patterned one when the time evolution of the field is controlled by a nonlocal Fisher equation. A small noise is added to the evolution equation to define the lifetimes and to calculate the mean first-passage time of the stochastic field through a given threshold value, before the patterned steady state is reached. In order to obtain analytical results we introduce a stochastic multiscale perturbation expansion. This multiscale expansion can also be used to tackle multiplicative stochastic partial differential equations. A critical slowing down is predicted for the marginal case when the Fourier phase of the unstable initial condition is null. We carry out Monte Carlo simulations to show the agreement with our theoretical predictions. Analytic results for the bifurcation point and asymptotic analysis of traveling wave-front solutions are included to get insight into the noise-induced transition phenomena mediated by invading fronts.

First-passage times for pattern formation in nonlocal partial differential equations.

PubMed

Cáceres, Manuel O; Fuentes, Miguel A

2015-10-01

We describe the lifetimes associated with the stochastic evolution from an unstable uniform state to a patterned one when the time evolution of the field is controlled by a nonlocal Fisher equation. A small noise is added to the evolution equation to define the lifetimes and to calculate the mean first-passage time of the stochastic field through a given threshold value, before the patterned steady state is reached. In order to obtain analytical results we introduce a stochastic multiscale perturbation expansion. This multiscale expansion can also be used to tackle multiplicative stochastic partial differential equations. A critical slowing down is predicted for the marginal case when the Fourier phase of the unstable initial condition is null. We carry out Monte Carlo simulations to show the agreement with our theoretical predictions. Analytic results for the bifurcation point and asymptotic analysis of traveling wave-front solutions are included to get insight into the noise-induced transition phenomena mediated by invading fronts.

Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

PubMed

Garijo, N; Manzano, R; Osta, R; Perez, M A

2012-12-07

Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stochastic and Resolvable Gravitational Waves from Ultralight Bosons.

PubMed

Brito, Richard; Ghosh, Shrobana; Barausse, Enrico; Berti, Emanuele; Cardoso, Vitor; Dvorkin, Irina; Klein, Antoine; Pani, Paolo

2017-09-29

Ultralight scalar fields around spinning black holes can trigger superradiant instabilities, forming a long-lived bosonic condensate outside the horizon. We use numerical solutions of the perturbed field equations and astrophysical models of massive and stellar-mass black hole populations to compute, for the first time, the stochastic gravitational-wave background from these sources. In optimistic scenarios the background is observable by Advanced LIGO and LISA for field masses m_{s} in the range ∼[2×10^{-13},10^{-12}] and ∼5×[10^{-19},10^{-16}]  eV, respectively, and it can affect the detectability of resolvable sources. Our estimates suggest that an analysis of the stochastic background limits from LIGO O1 might already be used to marginally exclude axions with mass ∼10^{-12.5}  eV. Semicoherent searches with Advanced LIGO (LISA) should detect ∼15(5) to 200(40) resolvable sources for scalar field masses 3×10^{-13} (10^{-17})  eV. LISA measurements of massive BH spins could either rule out bosons in the range ∼[10^{-18},2×10^{-13}]  eV, or measure m_{s} with 10% accuracy in the range ∼[10^{-17},10^{-13}]  eV.

The ‘hit’ phenomenon: a mathematical model of human dynamics interactions as a stochastic process

NASA Astrophysics Data System (ADS)

Ishii, Akira; Arakaki, Hisashi; Matsuda, Naoya; Umemura, Sanae; Urushidani, Tamiko; Yamagata, Naoya; Yoshida, Narihiko

2012-06-01

A mathematical model for the ‘hit’ phenomenon in entertainment within a society is presented as a stochastic process of human dynamics interactions. The model uses only the advertisement budget time distribution as an input, and word-of-mouth (WOM), represented by posts on social network systems, is used as data to make a comparison with the calculated results. The unit of time is days. The WOM distribution in time is found to be very close to the revenue distribution in time. Calculations for the Japanese motion picture market based on the mathematical model agree well with the actual revenue distribution in time.

New Results on a Stochastic Duel Game with Each Force Consisting of Heterogeneous Units

DTIC Science & Technology

2013-02-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA NEW RESULTS ON A STOCHASTIC DUEL GAME WITH EACH FORCE CONSISTING OF...on a Stochastic Duel Game With Each Force Consisting of Heterogeneous Units 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...distribution is unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Two forces engage in a duel , with each force initially consisting of several

Stochastic 3D modeling of Ostwald ripening at ultra-high volume fractions of the coarsening phase

NASA Astrophysics Data System (ADS)

Spettl, A.; Wimmer, R.; Werz, T.; Heinze, M.; Odenbach, S.; Krill, C. E., III; Schmidt, V.

2015-09-01

We present a (dynamic) stochastic simulation model for 3D grain morphologies undergoing a grain coarsening phenomenon known as Ostwald ripening. For low volume fractions of the coarsening phase, the classical LSW theory predicts a power-law evolution of the mean particle size and convergence toward self-similarity of the particle size distribution; experiments suggest that this behavior holds also for high volume fractions. In the present work, we have analyzed 3D images that were recorded in situ over time in semisolid Al-Cu alloys manifesting ultra-high volume fractions of the coarsening (solid) phase. Using this information we developed a stochastic simulation model for the 3D morphology of the coarsening grains at arbitrary time steps. Our stochastic model is based on random Laguerre tessellations and is by definition self-similar—i.e. it depends only on the mean particle diameter, which in turn can be estimated at each point in time. For a given mean diameter, the stochastic model requires only three additional scalar parameters, which influence the distribution of particle sizes and their shapes. An evaluation shows that even with this minimal information the stochastic model yields an excellent representation of the statistical properties of the experimental data.

Controlled Quantum Packets

NASA Technical Reports Server (NTRS)

DeMartino, Salvatore; DeSiena, Silvio

1996-01-01

We look at time evolution of a physical system from the point of view of dynamical control theory. Normally we solve motion equation with a given external potential and we obtain time evolution. Standard examples are the trajectories in classical mechanics or the wave functions in Quantum Mechanics. In the control theory, we have the configurational variables of a physical system, we choose a velocity field and with a suited strategy we force the physical system to have a well defined evolution. The evolution of the system is the 'premium' that the controller receives if he has adopted the right strategy. The strategy is given by well suited laboratory devices. The control mechanisms are in many cases non linear; it is necessary, namely, a feedback mechanism to retain in time the selected evolution. Our aim is to introduce a scheme to obtain Quantum wave packets by control theory. The program is to choose the characteristics of a packet, that is, the equation of evolution for its centre and a controlled dispersion, and to give a building scheme from some initial state (for example a solution of stationary Schroedinger equation). It seems natural in this view to use stochastic approach to Quantum Mechanics, that is, Stochastic Mechanics [S.M.]. It is a quantization scheme different from ordinary ones only formally. This approach introduces in quantum theory the whole mathematical apparatus of stochastic control theory. Stochastic Mechanics, in our view, is more intuitive when we want to study all the classical-like problems. We apply our scheme to build two classes of quantum packets both derived generalizing some properties of coherent states.

Generation of Kappa Distributions in Solar Wind at 1 au

NASA Astrophysics Data System (ADS)

Livadiotis, G.; Desai, M. I.; Wilson, L. B., III

2018-02-01

We examine the generation of kappa distributions in the solar wind plasma near 1 au. Several mechanisms are mentioned in the literature, each characterized by a specific relationship between the solar wind plasma features, the interplanetary magnetic field (IMF), and the kappa index—the parameter that governs the kappa distributions. This relationship serves as a signature condition that helps the identification of the mechanism in the plasma. In general, a mechanism that generates kappa distributions involves a single or a series of stochastic or physical processes that induces local correlations among particles. We identify three fundamental solar wind plasma conditions that can generate kappa distributions, noted as (i) Debye shielding, (ii) frozen IMF, and (iii) temperature fluctuations, each one prevailing in different scales of solar wind plasma and magnetic field properties. Moreover, our findings show that the kappa distributions, and thus, their generating mechanisms, vary significantly with solar wind features: (i) the kappa index has different dependence on the solar wind speed for slow and fast modes, i.e., slow wind is characterized by a quasi-constant kappa index, κ ≈ 4.3 ± 0.7, while fast wind exhibits kappa indices that increase with bulk speed; (ii) the dispersion of magnetosonic waves is more effective for lower kappa indices (i.e., further from thermal equilibrium); and (iii) the kappa and polytropic indices are positively correlated, as it was anticipated by the theory.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution*

PubMed Central

Leão, William L.; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor’s 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model. PMID:29333210

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student's t-distribution.

PubMed

Leão, William L; Abanto-Valle, Carlos A; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor's 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model.

Permanence and asymptotic behaviors of stochastic predator-prey system with Markovian switching and Lévy noise

NASA Astrophysics Data System (ADS)

Wang, Sheng; Wang, Linshan; Wei, Tengda

2018-04-01

This paper concerns the dynamics of a stochastic predator-prey system with Markovian switching and Lévy noise. First, the existence and uniqueness of global positive solution to the system is proved. Then, by combining stochastic analytical techniques with M-matrix analysis, sufficient conditions of stochastic permanence and extinction are obtained. Furthermore, for the stochastic permanence case, by means of four constants related to the stationary probability distribution of the Markov chain and the parameters of the subsystems, both the superior limit and the inferior limit of the average in time of the sample path of the solution are estimated. Finally, our conclusions are illustrated through an example.

Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models.

PubMed

Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik

2017-12-15

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.

A Computational Framework for Analyzing Stochasticity in Gene Expression

PubMed Central

Sherman, Marc S.; Cohen, Barak A.

2014-01-01

Stochastic fluctuations in gene expression give rise to distributions of protein levels across cell populations. Despite a mounting number of theoretical models explaining stochasticity in protein expression, we lack a robust, efficient, assumption-free approach for inferring the molecular mechanisms that underlie the shape of protein distributions. Here we propose a method for inferring sets of biochemical rate constants that govern chromatin modification, transcription, translation, and RNA and protein degradation from stochasticity in protein expression. We asked whether the rates of these underlying processes can be estimated accurately from protein expression distributions, in the absence of any limiting assumptions. To do this, we (1) derived analytical solutions for the first four moments of the protein distribution, (2) found that these four moments completely capture the shape of protein distributions, and (3) developed an efficient algorithm for inferring gene expression rate constants from the moments of protein distributions. Using this algorithm we find that most protein distributions are consistent with a large number of different biochemical rate constant sets. Despite this degeneracy, the solution space of rate constants almost always informs on underlying mechanism. For example, we distinguish between regimes where transcriptional bursting occurs from regimes reflecting constitutive transcript production. Our method agrees with the current standard approach, and in the restrictive regime where the standard method operates, also identifies rate constants not previously obtainable. Even without making any assumptions we obtain estimates of individual biochemical rate constants, or meaningful ratios of rate constants, in 91% of tested cases. In some cases our method identified all of the underlying rate constants. The framework developed here will be a powerful tool for deducing the contributions of particular molecular mechanisms to specific patterns of gene expression. PMID:24811315

Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation.

PubMed

Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

2016-04-01

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.

Stochastic Forcing for High-Resolution Regional and Global Ocean and Atmosphere-Ocean Coupled Ensemble Forecast System

NASA Astrophysics Data System (ADS)

Rowley, C. D.; Hogan, P. J.; Martin, P.; Thoppil, P.; Wei, M.

2017-12-01

An extended range ensemble forecast system is being developed in the US Navy Earth System Prediction Capability (ESPC), and a global ocean ensemble generation capability to represent uncertainty in the ocean initial conditions has been developed. At extended forecast times, the uncertainty due to the model error overtakes the initial condition as the primary source of forecast uncertainty. Recently, stochastic parameterization or stochastic forcing techniques have been applied to represent the model error in research and operational atmospheric, ocean, and coupled ensemble forecasts. A simple stochastic forcing technique has been developed for application to US Navy high resolution regional and global ocean models, for use in ocean-only and coupled atmosphere-ocean-ice-wave ensemble forecast systems. Perturbation forcing is added to the tendency equations for state variables, with the forcing defined by random 3- or 4-dimensional fields with horizontal, vertical, and temporal correlations specified to characterize different possible kinds of error. Here, we demonstrate the stochastic forcing in regional and global ensemble forecasts with varying perturbation amplitudes and length and time scales, and assess the change in ensemble skill measured by a range of deterministic and probabilistic metrics.

Scattering of electromagnetic wave by the layer with one-dimensional random inhomogeneities

NASA Astrophysics Data System (ADS)

Kogan, Lev; Zaboronkova, Tatiana; Grigoriev, Gennadii., IV.

A great deal of attention has been paid to the study of probability characteristics of electro-magnetic waves scattered by one-dimensional fluctuations of medium dielectric permittivity. However, the problem of a determination of a density of a probability and average intensity of the field inside the stochastically inhomogeneous medium with arbitrary extension of fluc-tuations has not been considered yet. It is the purpose of the present report to find and to analyze the indicated functions for the plane electromagnetic wave scattered by the layer with one-dimensional fluctuations of permittivity. We assumed that the length and the amplitude of individual fluctuations as well the interval between them are random quantities. All of indi-cated fluctuation parameters are supposed as independent random values possessing Gaussian distribution. We considered the stationary time cases both small-scale and large-scale rarefied inhomogeneities. Mathematically such problem can be reduced to the solution of integral Fred-holm equation of second kind for Hertz potential (U). Using the decomposition of the field into the series of multiply scattered waves we obtained the expression for a probability density of the field of the plane wave and determined the moments of the scattered field. We have shown that all odd moments of the centered field (U-¡U¿) are equal to zero and the even moments depend on the intensity. It was obtained that the probability density of the field possesses the Gaussian distribution. The average field is small compared with the standard fluctuation of scattered field for all considered cases of inhomogeneities. The value of average intensity of the field is an order of a standard of fluctuations of field intensity and drops with increases the inhomogeneities length in the case of small-scale inhomogeneities. The behavior of average intensity is more complicated in the case of large-scale medium inhomogeneities. The value of average intensity is the oscillating function versus the average fluctuations length if the standard of fluctuations of inhomogeneities length is greater then the wave length. When the standard of fluctuations of medium inhomogeneities extension is smaller then the wave length, the av-erage intensity value weakly depends from the average fluctuations extension. The obtained results may be used for analysis of the electromagnetic wave propagation into the media with the fluctuating parameters caused by such factors as leafs of trees, cumulus, internal gravity waves with a chaotic phase and etc. Acknowledgment: This work was supported by the Russian Foundation for Basic Research (projects 08-02-97026 and 09-05-00450).

Stochastic Frontier Model Approach for Measuring Stock Market Efficiency with Different Distributions

PubMed Central

Hasan, Md. Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md. Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time- varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation. PMID:22629352

Stochastic frontier model approach for measuring stock market efficiency with different distributions.

PubMed

Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.

Finding optimal vaccination strategies for pandemic influenza using genetic algorithms.

PubMed

Patel, Rajan; Longini, Ira M; Halloran, M Elizabeth

2005-05-21

In the event of pandemic influenza, only limited supplies of vaccine may be available. We use stochastic epidemic simulations, genetic algorithms (GA), and random mutation hill climbing (RMHC) to find optimal vaccine distributions to minimize the number of illnesses or deaths in the population, given limited quantities of vaccine. Due to the non-linearity, complexity and stochasticity of the epidemic process, it is not possible to solve for optimal vaccine distributions mathematically. However, we use GA and RMHC to find near optimal vaccine distributions. We model an influenza pandemic that has age-specific illness attack rates similar to the Asian pandemic in 1957-1958 caused by influenza A(H2N2), as well as a distribution similar to the Hong Kong pandemic in 1968-1969 caused by influenza A(H3N2). We find the optimal vaccine distributions given that the number of doses is limited over the range of 10-90% of the population. While GA and RMHC work well in finding optimal vaccine distributions, GA is significantly more efficient than RMHC. We show that the optimal vaccine distribution found by GA and RMHC is up to 84% more effective than random mass vaccination in the mid range of vaccine availability. GA is generalizable to the optimization of stochastic model parameters for other infectious diseases and population structures.

Prequantum classical statistical field theory: background field as a source of everything?

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2011-07-01

Prequantum classical statistical field theory (PCSFT) is a new attempt to consider quantum mechanics (QM) as an emergent phenomenon, cf. with De Broglie's "double solution" approach, Bohmian mechanics, stochastic electrodynamics (SED), Nelson's stochastic QM and its generalization by Davidson, 't Hooft's models and their development by Elze. PCSFT is a comeback to a purely wave viewpoint on QM, cf. with early Schrodinger. There is no quantum particles at all, only waves. In particular, photons are simply wave-pulses of the classical electromagnetic field, cf. SED. Moreover, even massive particles are special "prequantum fields": the electron field, the neutron field, and so on. PCSFT claims that (sooner or later) people will be able to measure components of these fields: components of the "photonic field" (the classical electromagnetic field of low intensity), electronic field, neutronic field, and so on. At the moment we are able to produce quantum correlations as correlations of classical Gaussian random fields. In this paper we are interested in mathematical and physical reasons of usage of Gaussian fields. We consider prequantum signals (corresponding to quantum systems) as composed of a huge number of wave-pulses (on very fine prequantum time scale). We speculate that the prequantum background field (the field of "vacuum fluctuations") might play the role of a source of such pulses, i.e., the source of everything.

Travelling waves and spatial hierarchies in measles epidemics

NASA Astrophysics Data System (ADS)

Grenfell, B. T.; Bjørnstad, O. N.; Kappey, J.

2001-12-01

Spatio-temporal travelling waves are striking manifestations of predator-prey and host-parasite dynamics. However, few systems are well enough documented both to detect repeated waves and to explain their interaction with spatio-temporal variations in population structure and demography. Here, we demonstrate recurrent epidemic travelling waves in an exhaustive spatio-temporal data set for measles in England and Wales. We use wavelet phase analysis, which allows for dynamical non-stationarity-a complication in interpreting spatio-temporal patterns in these and many other ecological time series. In the pre-vaccination era, conspicuous hierarchical waves of infection moved regionally from large cities to small towns; the introduction of measles vaccination restricted but did not eliminate this hierarchical contagion. A mechanistic stochastic model suggests a dynamical explanation for the waves-spread via infective `sparks' from large `core' cities to smaller `satellite' towns. Thus, the spatial hierarchy of host population structure is a prerequisite for these infection waves.

Theory of Stochastic Duels - Miscellaneous Results

DTIC Science & Technology

1978-03-01

TECHNICAL MEMORANDUM 2-77, "THEORY OF STOCHASTIC DUELS - MISCELLANEOUS RESULTS"______________ 6. PERFORMING ORG. REPORT NUMBER _USA TRASANA 7. AUT)IOR...Identify by block number) This memorandum presents particular applications of various aspects of the theory of stochastic duels that the author has...Marksman Problem with Erlang n Firing Time 1 Distribution 2.3 Tactical Equity Duel with Erlang 2 Firing Times 4 2.4 Different Tactical Equity Duel 6 S2.5

PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

DOE PAGES

Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

2016-05-01

Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve furthermore » as more functionality is added in the future.« less

Stochastic modelling of non-stationary financial assets

NASA Astrophysics Data System (ADS)

Estevens, Joana; Rocha, Paulo; Boto, João P.; Lind, Pedro G.

2017-11-01

We model non-stationary volume-price distributions with a log-normal distribution and collect the time series of its two parameters. The time series of the two parameters are shown to be stationary and Markov-like and consequently can be modelled with Langevin equations, which are derived directly from their series of values. Having the evolution equations of the log-normal parameters, we reconstruct the statistics of the first moments of volume-price distributions which fit well the empirical data. Finally, the proposed framework is general enough to study other non-stationary stochastic variables in other research fields, namely, biology, medicine, and geology.

Modeling Stochastic Energy and Water Consumption to Manage Residential Water Uses

NASA Astrophysics Data System (ADS)

Abdallah, A. M.; Rosenberg, D. E.; Water; Energy Conservation

2011-12-01

Water energy linkages have received growing attention from the water and energy utilities as utilities recognize that collaborative efforts can implement more effective conservation and efficiency improvement programs at lower cost with less effort. To date, limited energy-water household data has allowed only deterministic analysis for average, representative households and required coarse assumptions - like the water heater (the primary energy use in a home apart from heating and cooling) be a single end use. Here, we use recent available disaggregated hot and cold water household end-use data to estimate water and energy consumption for toilet, shower, faucet, dishwasher, laundry machine, leaks, and other household uses and savings from appliance retrofits. The disaggregated hot water and bulk water end-use data was previously collected by the USEPA for 96 single family households in Seattle WA and Oakland CA, and Tampa FL between the period from 2000 and 2003 for two weeks before and four weeks after each household was retrofitted with water efficient appliances. Using the disaggregated data, we developed a stochastic model that represents factors that influence water use for each appliance: behavioral (use frequency and duration), demographical (household size), and technological (use volume or flowrate). We also include stochastic factors that govern energy to heat hot water: hot water fraction (percentage of hot water volume to total water volume used in a certain end-use event), heater water intake and dispense temperatures, and energy source for the heater (gas, electric, etc). From the empirical household end-use data, we derive stochastic probability distributions for each water and energy factor where each distribution represents the range and likelihood of values that the factor may take. The uncertainty of the stochastic water and energy factors is propagated using Monte Carlo simulations to calculate the composite probability distribution for water and energy use, potential savings, and payback periods to install efficient water end-use appliances and fixtures. Stochastic model results show the distributions among households for (i) water end-use, (ii) energy consumed to use water, and (iii) financial payback periods. Compared to deterministic analysis, stochastic modeling results show that hot water fractions for appliances follow normal distributions with high standard deviation and reveal pronounced variations among households that significantly affect energy savings and payback period estimates. These distributions provide an important tool to select and size water conservation programs to simultaneously meet both water and energy conservation goals. They also provide a way to identify and target a small fraction of customers with potential to save large water volumes and energy from appliance retrofits. Future work will embed this household scale stochastic model in city-scale models to identify win-win water management opportunities where households save money by conserving water and energy while cities avoid costs, downsize, or delay infrastructure development.

Stochastic series expansion simulation of the t -V model

NASA Astrophysics Data System (ADS)

Wang, Lei; Liu, Ye-Hua; Troyer, Matthias

2016-04-01

We present an algorithm for the efficient simulation of the half-filled spinless t -V model on bipartite lattices, which combines the stochastic series expansion method with determinantal quantum Monte Carlo techniques widely used in fermionic simulations. The algorithm scales linearly in the inverse temperature, cubically with the system size, and is free from the time-discretization error. We use it to map out the finite-temperature phase diagram of the spinless t -V model on the honeycomb lattice and observe a suppression of the critical temperature of the charge-density-wave phase in the vicinity of a fermionic quantum critical point.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Justin; Slaughter, Andrew; Veeraraghavan, Swetha

Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) is a finite element application that aims at analyzing the response of 3-D soil-structure systems to natural and man-made hazards such as earthquakes, floods and fire. MASTODON currently focuses on the simulation of seismic events and has the capability to perform extensive ‘source-to-site’ simulations including earthquake fault rupture, nonlinear wave propagation and nonlinear soil-structure interaction (NLSSI) analysis. MASTODON is being developed to be a dynamic probabilistic risk assessment framework that enables analysts to not only perform deterministic analyses, but also easily perform probabilistic or stochastic simulations for the purpose of risk assessment.

Transient ensemble dynamics in time-independent galactic potentials

NASA Astrophysics Data System (ADS)

Mahon, M. Elaine; Abernathy, Robert A.; Bradley, Brendan O.; Kandrup, Henry E.

1995-07-01

This paper summarizes a numerical investigation of the short-time, possibly transient, behaviour of ensembles of stochastic orbits evolving in fixed non-integrable potentials, with the aim of deriving insights into the structure and evolution of galaxies. The simulations involved three different two-dimensional potentials, quite different in appearance. However, despite these differences, ensembles in all three potentials exhibit similar behaviour. This suggests that the conclusions inferred from the simulations are robust, relying only on basic topological properties, e.g., the existence of KAM tori and cantori. Generic ensembles of initial conditions, corresponding to stochastic orbits, exhibit a rapid coarse-grained approach towards a near-invariant distribution on a time-scale <>t_H, although various irregularities associated with external and/or internal irregularities can drastically accelerate this process. A principal tool in the analysis is the notion of a local Liapounov exponent, which provides a statistical characterization of the overall instability of stochastic orbits over finite time intervals. In particular, there is a precise sense in which confined stochastic orbits are less unstable, with smaller local Liapounov exponents, than are unconfined stochastic orbits.

Numerical methods for the stochastic Landau-Lifshitz Navier-Stokes equations.

PubMed

Bell, John B; Garcia, Alejandro L; Williams, Sarah A

2007-07-01

The Landau-Lifshitz Navier-Stokes (LLNS) equations incorporate thermal fluctuations into macroscopic hydrodynamics by using stochastic fluxes. This paper examines explicit Eulerian discretizations of the full LLNS equations. Several computational fluid dynamics approaches are considered (including MacCormack's two-step Lax-Wendroff scheme and the piecewise parabolic method) and are found to give good results for the variance of momentum fluctuations. However, neither of these schemes accurately reproduces the fluctuations in energy or density. We introduce a conservative centered scheme with a third-order Runge-Kutta temporal integrator that does accurately produce fluctuations in density, energy, and momentum. A variety of numerical tests, including the random walk of a standing shock wave, are considered and results from the stochastic LLNS solver are compared with theory, when available, and with molecular simulations using a direct simulation Monte Carlo algorithm.

A New Global Multi-fluid MHD Model of the Solar Corona

NASA Astrophysics Data System (ADS)

van der Holst, B.; Chandran, B. D. G.; Alterman, B. L.; Kasper, J. C.; Toth, G.

2017-12-01

We present a multi-fluid generalization of the AWSoM model, a global magnetohydrodynamic (MHD) solar corona model with low-frequency Alfven wave turbulence (van der Holst et al., 2014). This new extended model includes electron and multi-ion temperatures and velocities (protons and alpha particles). The coronal heating and acceleration is addressed via outward propagating low-frequency Alfven waves that are partially reflected by Alfven speed gradients. The nonlinear interaction of these counter-propagating waves results in turbulent energy cascade. To apportion the wave dissipation to the electron and ion temperatures, we employ the results of the theories of linear wave damping and nonlinear stochastic heating as described by Chandran et al. (2011, 2013). This heat partitioning results in a more than mass proportional heating among ions.

Langmuir-like waves and radiation in planetary foreshocks

NASA Technical Reports Server (NTRS)

Cairns, Iver H.; Robinson, P. A.; Anderson, R. R.; Gurnett, D. A.; Kurth, W. S.

1995-01-01

The basic objectives of this NASA Grant are to develop theoretical understandings (tested with spacecraft data) of the generation and characteristics of electron plasma waves, commonly known as Langmuir-like waves, and associated radiation near f(sub p) and 2f(sub p) in planetary foreshocks. (Here f(sub p) is plasma frequency.) Related waves and radiation in the source regions of interplanetary type III solar radio bursts provide a simpler observational and theoretical context for developing and testing such understandings. Accordingly, applications to type III bursts constitute a significant fraction of the research effort. The testing of the new Stochastic Growth Theory (SGT) for type III bursts, and its extension and testing for foreshock waves and radiation, constitutes a major longterm strategic goal of the research effort.

A stochastic model with a low-frequency amplification feedback for the stratospheric northern annular mode

NASA Astrophysics Data System (ADS)

Yu, Yueyue; Cai, Ming; Ren, Rongcai

2017-08-01

We consider three indices to measure the polar stratospheric mass and stratospheric meridional mass circulation variability: anomalies of (1) total mass in the polar stratospheric cap (60-90°N, above the isentropic surface 400 K, PSM), (2) total adiabatic mass transport across 60°N into the polar stratosphere cap (AMT), (3) and total diabetic mass transport across 400 K from the polar stratosphere into the troposphere below (DMT). It is confirmed that the negative stratospheric Northern Annular Mode (NAM) and PSM indices have a nearly indistinguishable temporal evolution and a similar red-noise-like spectrum with a de-correlation timescale of 4 weeks. This enables us to examine the low-frequency nature of the NAM in the framework of mass circulation, namely, d/{dt}{PSM}={AMT} - {DMT} . The DMT index tends to be positively correlated with the PSM with a red-noise-like spectrum, representing slow radiative cooling processes giving rise to a de-correlation timescale of 3-4 weeks. The AMT is nearly perfectly correlated with the day-to-day tendency of PSM, reflecting a robust quasi 90° out-of-phase relation between the AMT and PSM at all frequency bands. Variations of vertically westward tilting of planetary waves contribute mainly to the high-frequency portion of AMT. It is the wave amplitude's slow vacillation that plays the leading role in the quasi 90° out-of-phase relation between the AMT and PSM. Based on this, we put forward a linear stochastic model with a low-frequency amplification feedback from low-frequency amplitude vacillations of planetary waves to explain the amplified low-frequency response of PSM/NAM to a stochastic forcing from the westward tilting variability.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process

NASA Astrophysics Data System (ADS)

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-01

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Taming stochastic bifurcations in fractional-order systems via noise and delayed feedback

NASA Astrophysics Data System (ADS)

Sun, Zhongkui; Zhang, Jintian; Yang, Xiaoli; Xu, Wei

2017-08-01

The dynamics in fractional-order systems have been widely studied during the past decade due to the potential applications in new materials and anomalous diffusions, but the investigations have been so far restricted to a fractional-order system without time delay(s). In this paper, we report the first study of random responses of fractional-order system coupled with noise and delayed feedback. Stochastic averaging method has been utilized to determine the stationary probability density functions (PDFs) by means of the principle of minimum mean-square error, based on which stochastic bifurcations could be identified through recognizing the shape of the PDFs. It has been found that by changing the fractional order the shape of the PDFs can switch from unimodal distribution to bimodal one, or from bimodal distribution to unimodal one, thus announcing the onset of stochastic bifurcation. Further, we have demonstrated that by merely modulating the time delay, the feedback strengths, or the noise intensity, the shapes of PDFs can transit between a single peak and a double peak. Therefore, it provides an efficient candidate to control, say, induce or suppress, the stochastic bifurcations in fractional-order systems.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

PubMed

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-27

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Wang, Ting; Plecháč, Petr

2017-12-01

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

Higher-order stochastic differential equations and the positive Wigner function

NASA Astrophysics Data System (ADS)

Drummond, P. D.

2017-12-01

General higher-order stochastic processes that correspond to any diffusion-type tensor of higher than second order are obtained. The relationship of multivariate higher-order stochastic differential equations with tensor decomposition theory and tensor rank is explained. Techniques for generating the requisite complex higher-order noise are proved to exist either using polar coordinates and γ distributions, or from products of Gaussian variates. This method is shown to allow the calculation of the dynamics of the Wigner function, after it is extended to a complex phase space. The results are illustrated physically through dynamical calculations of the positive Wigner distribution for three-mode parametric downconversion, widely used in quantum optics. The approach eliminates paradoxes arising from truncation of the higher derivative terms in Wigner function time evolution. Anomalous results of negative populations and vacuum scattering found in truncated Wigner quantum simulations in quantum optics and Bose-Einstein condensate dynamics are shown not to occur with this type of stochastic theory.

Pricing foreign equity option under stochastic volatility tempered stable Lévy processes

NASA Astrophysics Data System (ADS)

Gong, Xiaoli; Zhuang, Xintian

2017-10-01

Considering that financial assets returns exhibit leptokurtosis, asymmetry properties as well as clustering and heteroskedasticity effect, this paper substitutes the logarithm normal jumps in Heston stochastic volatility model by the classical tempered stable (CTS) distribution and normal tempered stable (NTS) distribution to construct stochastic volatility tempered stable Lévy processes (TSSV) model. The TSSV model framework permits infinite activity jump behaviors of return dynamics and time varying volatility consistently observed in financial markets through subordinating tempered stable process to stochastic volatility process, capturing leptokurtosis, fat tailedness and asymmetry features of returns. By employing the analytical characteristic function and fast Fourier transform (FFT) technique, the formula for probability density function (PDF) of TSSV returns is derived, making the analytical formula for foreign equity option (FEO) pricing available. High frequency financial returns data are employed to verify the effectiveness of proposed models in reflecting the stylized facts of financial markets. Numerical analysis is performed to investigate the relationship between the corresponding parameters and the implied volatility of foreign equity option.

Constraints on Nonlinear and Stochastic Growth Theories for Type 3 Solar Radio Bursts from the Corona to 1 AU

NASA Technical Reports Server (NTRS)

Cairns, Iver H.; Robinson, P. A.

1998-01-01

Existing, competing theories for coronal and interplanetary type III solar radio bursts appeal to one or more of modulational instability, electrostatic (ES) decay processes, or stochastic growth physics to preserve the electron beam, limit the levels of Langmuir-like waves driven by the beam, and produce wave spectra capable of coupling nonlinearly to generate the observed radio emission. Theoretical constraints exist on the wavenumbers and relative sizes of the wave bandwidth and nonlinear growth rate for which Langmuir waves are subject to modulational instability and the parametric and random phase versions of ES decay. A constraint also exists on whether stochastic growth theory (SGT) is appropriate. These constraints are evaluated here using the beam, plasma, and wave properties (1) observed in specific interplanetary type III sources, (2) predicted nominally for the corona, and (3) predicted at heliocentric distances greater than a few solar radii by power-law models based on interplanetary observations. It is found that the Langmuir waves driven directly by the beam have wavenumbers that are almost always too large for modulational instability but are appropriate to ES decay. Even for waves scattered to lower wavenumbers (by ES decay, for instance), the wave bandwidths are predicted to be too large and the nonlinear growth rates too small for modulational instability to occur for the specific interplanetary events studied or the great majority of Langmuir wave packets in type III sources at arbitrary heliocentric distances. Possible exceptions are for very rare, unusually intense, narrowband wave packets, predominantly close to the Sun, and for the front portion of very fast beams traveling through unusually dilute, cold solar wind plasmas. Similar arguments demonstrate that the ES decay should proceed almost always as a random phase process rather than a parametric process, with similar exceptions. These results imply that it is extremely rare for modulational instability or parametric decay to proceed in type III sources at any heliocentric distance: theories for type III bursts based on modulational instability or parametric decay are therefore not viable in general. In contrast, the constraint on SGT can be satisfied and random phase ES decay can proceed at all heliocentric distances under almost all circumstances. (The contrary circumstances involve unusually slow, broad beams moving through unusually hot regions of the Corona.) The analyses presented here strongly justify extending the existing SGT-based model for interplanetary type III bursts (which includes SGT physics, random phase ES decay, and specific electromagnetic emission mechanisms) into a general theory for type III bursts from the corona to beyond 1 AU. This extended theory enjoys strong theoretical support, explains the characteristics of specific interplanetary type III bursts very well, and can account for the detailed dynamic spectra of type III bursts from the lower corona and solar wind.

The Effects of Wave Escape on Fast Magnetosonic Wave Turbulence in Solar Flares

NASA Technical Reports Server (NTRS)

Pongkitiwanichakul, Peera; Chandran, Benjamin D. G.; Karpen, Judith T.; DeVore, C. Richard

2012-01-01

One of the leading models for electron acceleration in solar flares is stochastic acceleration by weakly turbulent fast magnetosonic waves ("fast waves"). In this model, large-scale flows triggered by magnetic reconnection excite large-wavelength fast waves, and fast-wave energy then cascades from large wavelengths to small wavelengths. Electron acceleration by large-wavelength fast-waves is weak, and so the model relies on the small-wavelength waves produced by the turbulent cascade. In order for the model to work, the energy cascade time for large-wavelength fast waves must be shorter than the time required for the waves to propagate out of the solar-flare acceleration region. To investigate the effects of wave escape, we solve the wave kinetic equation for fast waves in weak turbulence theory, supplemented with a homogeneous wave-loss term.We find that the amplitude of large-wavelength fast waves must exceed a minimum threshold in order for a significant fraction of the wave energy to cascade to small wavelengths before the waves leave the acceleration region.We evaluate this threshold as a function of the dominant wavelength of the fast waves that are initially excited by reconnection outflows.

Improved estimation of hydraulic conductivity by combining stochastically simulated hydrofacies with geophysical data

PubMed Central

Zhu, Lin; Gong, Huili; Chen, Yun; Li, Xiaojuan; Chang, Xiang; Cui, Yijiao

2016-01-01

Hydraulic conductivity is a major parameter affecting the output accuracy of groundwater flow and transport models. The most commonly used semi-empirical formula for estimating conductivity is Kozeny-Carman equation. However, this method alone does not work well with heterogeneous strata. Two important parameters, grain size and porosity, often show spatial variations at different scales. This study proposes a method for estimating conductivity distributions by combining a stochastic hydrofacies model with geophysical methods. The Markov chain model with transition probability matrix was adopted to re-construct structures of hydrofacies for deriving spatial deposit information. The geophysical and hydro-chemical data were used to estimate the porosity distribution through the Archie’s law. Results show that the stochastic simulated hydrofacies model reflects the sedimentary features with an average model accuracy of 78% in comparison with borehole log data in the Chaobai alluvial fan. The estimated conductivity is reasonable and of the same order of magnitude of the outcomes of the pumping tests. The conductivity distribution is consistent with the sedimentary distributions. This study provides more reliable spatial distributions of the hydraulic parameters for further numerical modeling. PMID:26927886

PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.

PubMed

Ma, Chihua; Luciani, Timothy; Terebus, Anna; Liang, Jie; Marai, G Elisabeta

2017-02-15

Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists' understanding of phenotypic behavior associated with specific genes. We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks. We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases.

On the deterministic and stochastic use of hydrologic models

USGS Publications Warehouse

Farmer, William H.; Vogel, Richard M.

2016-01-01

Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.

Ignition probability of polymer-bonded explosives accounting for multiple sources of material stochasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, S.; Barua, A.; Zhou, M., E-mail: min.zhou@me.gatech.edu

2014-05-07

Accounting for the combined effect of multiple sources of stochasticity in material attributes, we develop an approach that computationally predicts the probability of ignition of polymer-bonded explosives (PBXs) under impact loading. The probabilistic nature of the specific ignition processes is assumed to arise from two sources of stochasticity. The first source involves random variations in material microstructural morphology; the second source involves random fluctuations in grain-binder interfacial bonding strength. The effect of the first source of stochasticity is analyzed with multiple sets of statistically similar microstructures and constant interfacial bonding strength. Subsequently, each of the microstructures in the multiple setsmore » is assigned multiple instantiations of randomly varying grain-binder interfacial strengths to analyze the effect of the second source of stochasticity. Critical hotspot size-temperature states reaching the threshold for ignition are calculated through finite element simulations that explicitly account for microstructure and bulk and interfacial dissipation to quantify the time to criticality (t{sub c}) of individual samples, allowing the probability distribution of the time to criticality that results from each source of stochastic variation for a material to be analyzed. Two probability superposition models are considered to combine the effects of the multiple sources of stochasticity. The first is a parallel and series combination model, and the second is a nested probability function model. Results show that the nested Weibull distribution provides an accurate description of the combined ignition probability. The approach developed here represents a general framework for analyzing the stochasticity in the material behavior that arises out of multiple types of uncertainty associated with the structure, design, synthesis and processing of materials.« less

Shallow-velocity models at the Kilauea Volcano, Hawaii, determined from array analyses of tremor wavefields

USGS Publications Warehouse

Saccorotti, G.; Chouet, B.; Dawson, P.

2003-01-01

The properties of the surface wavefield at Kilauea Volcano are analysed using data from small-aperture arrays of short-period seismometers deployed in and around the Kilauea caldera. Tremor recordings were obtained during two Japan-US cooperative experiments conducted in 1996 and 1997. The seismometers were deployed in three semi-circular arrays with apertures of 300, 300 and 400 m, and a linear array with length of 1680 m. Data are analysed using a spatio-temporal correlation technique well suited for the study of the stationary stochastic wavefields of Rayleigh and Love waves associated with volcanic activity and scattering sources distributed in and around the summit caldera. Spatial autocorrelation coefficients are obtained as a function of frequency and are inverted for the dispersion characteristics of Rayleigh and Love waves using a grid search that seeks phase velocities for which the L-2 norm between data and forward modelling operators is minimized. Within the caldera, the phase velocities of Rayleigh waves range from 1400 to 1800 m s-1 at 1 Hz down to 300-400 m s-1 at 10 Hz, and the phase velocities of Love waves range from 2600 to 400 m s-1 within the same frequency band. Outside the caldera, Rayleigh wave velocities range from 1800 to 1600 m s-1 at 1 Hz down to 260-360 m s-1 at 10 Hz, and Love wave velocities range from 600 to 150 m s-1 within the same frequency band. The dispersion curves are inverted for velocity structure beneath each array, assuming these dispersions represent the fundamental modes of Rayleigh and Love waves. The velocity structures observed at different array sites are consistent with results from a recent 3-D traveltime tomography of the caldera region, and point to a marked velocity discontinuity associated with the southern caldera boundary.

Deterministic analysis of extrinsic and intrinsic noise in an epidemiological model.

PubMed

Bayati, Basil S

2016-05-01

We couple a stochastic collocation method with an analytical expansion of the canonical epidemiological master equation to analyze the effects of both extrinsic and intrinsic noise. It is shown that depending on the distribution of the extrinsic noise, the master equation yields quantitatively different results compared to using the expectation of the distribution for the stochastic parameter. This difference is incident to the nonlinear terms in the master equation, and we show that the deviation away from the expectation of the extrinsic noise scales nonlinearly with the variance of the distribution. The method presented here converges linearly with respect to the number of particles in the system and exponentially with respect to the order of the polynomials used in the stochastic collocation calculation. This makes the method presented here more accurate than standard Monte Carlo methods, which suffer from slow, nonmonotonic convergence. In epidemiological terms, the results show that extrinsic fluctuations should be taken into account since they effect the speed of disease breakouts and that the gamma distribution should be used to model the basic reproductive number.

Modelling the stochastic nature of the available coefficient of friction at footwear-floor interfaces.

PubMed

Gragg, Jared; Klose, Ellison; Yang, James

2017-07-01

The available coefficient of friction (ACOF) is a measure of the friction available between two surfaces, which for human gait would be the footwear-floor interface. It is often compared to the required coefficient of friction (RCOF) to determine the likelihood of a slip in gait. Both the ACOF and RCOF are stochastic by nature meaning that neither should be represented by a deterministic value, such as the sample mean. Previous research has determined that the RCOF can be modelled well by either the normal or lognormal distributions, but previous research aimed at determining an appropriate distribution for the ACOF was inconclusive. This study focuses on modelling the stochastic nature of the ACOF by fitting eight continuous probability distributions to ACOF data for six scenarios. In addition, the data were used to study the effect that a simple housekeeping action such as sweeping could have on the ACOF. Practitioner Summary: Previous research aimed at determining an appropriate distribution for the ACOF was inconclusive. The study addresses this issue as well as looking at the effect that an act such as sweeping has on the ACOF.

Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models

PubMed Central

Burr, Tom

2013-01-01

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the “go-to” option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example. PMID:24288668

Selecting summary statistics in approximate Bayesian computation for calibrating stochastic models.

PubMed

Burr, Tom; Skurikhin, Alexei

2013-01-01

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the "go-to" option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example.

Did LIGO Detect Dark Matter?

PubMed

Bird, Simeon; Cholis, Ilias; Muñoz, Julian B; Ali-Haïmoud, Yacine; Kamionkowski, Marc; Kovetz, Ely D; Raccanelli, Alvise; Riess, Adam G

2016-05-20

We consider the possibility that the black-hole (BH) binary detected by LIGO may be a signature of dark matter. Interestingly enough, there remains a window for masses 20M_{⊙}≲M_{bh}≲100M_{⊙} where primordial black holes (PBHs) may constitute the dark matter. If two BHs in a galactic halo pass sufficiently close, they radiate enough energy in gravitational waves to become gravitationally bound. The bound BHs will rapidly spiral inward due to the emission of gravitational radiation and ultimately will merge. Uncertainties in the rate for such events arise from our imprecise knowledge of the phase-space structure of galactic halos on the smallest scales. Still, reasonable estimates span a range that overlaps the 2-53  Gpc^{-3} yr^{-1} rate estimated from GW150914, thus raising the possibility that LIGO has detected PBH dark matter. PBH mergers are likely to be distributed spatially more like dark matter than luminous matter and have neither optical nor neutrino counterparts. They may be distinguished from mergers of BHs from more traditional astrophysical sources through the observed mass spectrum, their high ellipticities, or their stochastic gravitational wave background. Next-generation experiments will be invaluable in performing these tests.

Stochastic theory of fatigue corrosion

NASA Astrophysics Data System (ADS)

Hu, Haiyun

1999-10-01

A stochastic theory of corrosion has been constructed. The stochastic equations are described giving the transportation corrosion rate and fluctuation corrosion coefficient. In addition the pit diameter distribution function, the average pit diameter and the most probable pit diameter including other related empirical formula have been derived. In order to clarify the effect of stress range on the initiation and growth behaviour of pitting corrosion, round smooth specimen were tested under cyclic loading in 3.5% NaCl solution.

Path probability of stochastic motion: A functional approach

NASA Astrophysics Data System (ADS)

Hattori, Masayuki; Abe, Sumiyoshi

2016-06-01

The path probability of a particle undergoing stochastic motion is studied by the use of functional technique, and the general formula is derived for the path probability distribution functional. The probability of finding paths inside a tube/band, the center of which is stipulated by a given path, is analytically evaluated in a way analogous to continuous measurements in quantum mechanics. Then, the formalism developed here is applied to the stochastic dynamics of stock price in finance.

Stochastic analysis of concentration field in a wake region.

PubMed

Yassin, Mohamed F; Elmi, Abdirashid A

2011-02-01

Identifying geographic locations in urban areas from which air pollutants enter the atmosphere is one of the most important information needed to develop effective mitigation strategies for pollution control. Stochastic analysis is a powerful tool that can be used for estimating concentration fluctuation in plume dispersion in a wake region around buildings. Only few studies have been devoted to evaluate applications of stochastic analysis to pollutant dispersion in an urban area. This study was designed to investigate the concentration fields in the wake region using obstacle model such as an isolated building model. We measured concentration fluctuations at centerline of various downwind distances from the source, and different heights with the frequency of 1 KHz. Concentration fields were analyzed stochastically, using the probability density functions (pdf). Stochastic analysis was performed on the concentration fluctuation and the pdf of mean concentration, fluctuation intensity, and crosswind mean-plume dispersion. The pdf of the concentration fluctuation data have shown a significant non-Gaussian behavior. The lognormal distribution appeared to be the best fit to the shape of concentration measured in the boundary layer. We observed that the plume dispersion pdf near the source was shorter than the plume dispersion far from the source. Our findings suggest that the use of stochastic technique in complex building environment can be a powerful tool to help understand the distribution and location of air pollutants.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.

Saturation of multi-laser beams laser-plasma instabilities from stochastic ion heating

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michel, P.; Williams, E. A.; Divol, L.

2013-05-15

Cross-beam energy transfer (CBET) has been used as a tool on the National Ignition Facility (NIF) since the first energetics experiments in 2009 to control the energy deposition in ignition hohlraums and tune the implosion symmetry. As large amounts of power are transferred between laser beams at the entrance holes of NIF hohlraums, the presence of many overlapping beat waves can lead to stochastic ion heating in the regions where laser beams overlap [P. Michel et al., Phys. Rev. Lett. 109, 195004 (2012)]. This increases the ion acoustic velocity and modifies the ion acoustic waves’ dispersion relation, thus reducing themore » plasma response to the beat waves and the efficiency of CBET. This pushes the plasma oscillations driven by CBET in a regime where the phase velocities are much smaller than both the electron and ion thermal velocities. CBET gains are derived for this new regime and generalized to the case of multi ion species plasmas.« less

Self-organization of the magnetization in ferromagnetic nanowires

NASA Astrophysics Data System (ADS)

Ivanov, A. A.; Orlov, V. A.

2017-10-01

In this work we demonstrate the occurrence of the characteristic spatial scale in the distribution of magnetization unrelated to the domain wall or crystallite size with using computer simulation of magnetization in a polycrystalline ferromagnetic nanowire. This is the stochastic domain size. We show that this length is included in the spectral density of the pinning force of domain wall on inhomogeneities of the crystallographic anisotropy. The constant and distribution of easy axes directions of the effective anisotropy of stochastic domain, are analytically calculated.

Design and Scheduling of Microgrids using Benders Decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagarajan, Adarsh; Ayyanar, Raja

2016-11-21

The distribution feeder laterals in a distribution feeder with relatively high PV generation as compared to the load can be operated as microgrids to achieve reliability, power quality and economic benefits. However, renewable resources are intermittent and stochastic in nature. A novel approach for sizing and scheduling an energy storage system and microturbine for reliable operation of microgrids is proposed. The size and schedule of an energy storage system and microturbine are determined using Benders' decomposition, considering PV generation as a stochastic resource.

An efficient distribution method for nonlinear transport problems in stochastic porous media

NASA Astrophysics Data System (ADS)

Ibrahima, F.; Tchelepi, H.; Meyer, D. W.

2015-12-01

Because geophysical data are inexorably sparse and incomplete, stochastic treatments of simulated responses are convenient to explore possible scenarios and assess risks in subsurface problems. In particular, understanding how uncertainties propagate in porous media with nonlinear two-phase flow is essential, yet challenging, in reservoir simulation and hydrology. We give a computationally efficient and numerically accurate method to estimate the one-point probability density (PDF) and cumulative distribution functions (CDF) of the water saturation for the stochastic Buckley-Leverett problem when the probability distributions of the permeability and porosity fields are available. The method draws inspiration from the streamline approach and expresses the distributions of interest essentially in terms of an analytically derived mapping and the distribution of the time of flight. In a large class of applications the latter can be estimated at low computational costs (even via conventional Monte Carlo). Once the water saturation distribution is determined, any one-point statistics thereof can be obtained, especially its average and standard deviation. Moreover, rarely available in other approaches, yet crucial information such as the probability of rare events and saturation quantiles (e.g. P10, P50 and P90) can be derived from the method. We provide various examples and comparisons with Monte Carlo simulations to illustrate the performance of the method.

Multidimensional stochastic approximation using locally contractive functions

NASA Technical Reports Server (NTRS)

Lawton, W. M.

1975-01-01

A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.

Matter-wave coherence limit owing to cosmic gravitational wave background

NASA Astrophysics Data System (ADS)

Steane, Andrew M.

2017-12-01

We study matter-wave interferometry in the presence of a stochastic background of gravitational waves. It is shown that if the background has a scale-invariant spectrum over a wide bandwidth (which is expected in a class of inflationary models of Big Bang cosmology), then separated-path interference cannot be observed for a lump of matter of size above a limit which is very insensitive to the strength and bandwidth of the fluctuations, unless the interferometer is servo-controlled or otherwise protected. For ordinary solid matter this limit is of order 1-10 mm. A servo-controlled or cross-correlated device would also exhibit limits to the observation of macroscopic interference, which we estimate for ordinary matter moving at speeds small compared to c.

European Pulsar Timing Array limits on an isotropic stochastic gravitational-wave background

NASA Astrophysics Data System (ADS)

Lentati, L.; Taylor, S. R.; Mingarelli, C. M. F.; Sesana, A.; Sanidas, S. A.; Vecchio, A.; Caballero, R. N.; Lee, K. J.; van Haasteren, R.; Babak, S.; Bassa, C. G.; Brem, P.; Burgay, M.; Champion, D. J.; Cognard, I.; Desvignes, G.; Gair, J. R.; Guillemot, L.; Hessels, J. W. T.; Janssen, G. H.; Karuppusamy, R.; Kramer, M.; Lassus, A.; Lazarus, P.; Liu, K.; Osłowski, S.; Perrodin, D.; Petiteau, A.; Possenti, A.; Purver, M. B.; Rosado, P. A.; Smits, R.; Stappers, B.; Theureau, G.; Tiburzi, C.; Verbiest, J. P. W.

2015-11-01

We present new limits on an isotropic stochastic gravitational-wave background (GWB) using a six pulsar data set spanning 18 yr of observations from the 2015 European Pulsar Timing Array data release. Performing a Bayesian analysis, we fit simultaneously for the intrinsic noise parameters for each pulsar, along with common correlated signals including clock, and Solar system ephemeris errors, obtaining a robust 95 per cent upper limit on the dimensionless strain amplitude A of the background of A < 3.0 × 10-15 at a reference frequency of 1 yr-1 and a spectral index of 13/3, corresponding to a background from inspiralling supermassive black hole binaries, constraining the GW energy density to Ωgw(f)h2 < 1.1 × 10-9 at 2.8 nHz. We also present limits on the correlated power spectrum at a series of discrete frequencies, and show that our sensitivity to a fiducial isotropic GWB is highest at a frequency of ˜5 × 10-9 Hz. Finally, we discuss the implications of our analysis for the astrophysics of supermassive black hole binaries, and present 95 per cent upper limits on the string tension, Gμ/c2, characterizing a background produced by a cosmic string network for a set of possible scenarios, and for a stochastic relic GWB. For a Nambu-Goto field theory cosmic string network, we set a limit Gμ/c2 < 1.3 × 10-7, identical to that set by the Planck Collaboration, when combining Planck and high-ℓ cosmic microwave background data from other experiments. For a stochastic relic background, we set a limit of Ω ^relic_gw(f)h^2<1.2 × 10^{-9}, a factor of 9 improvement over the most stringent limits previously set by a pulsar timing array.

SIMULATION OF ENERGETIC PARTICLE TRANSPORT AND ACCELERATION AT SHOCK WAVES IN A FOCUSED TRANSPORT MODEL: IMPLICATIONS FOR MIXED SOLAR PARTICLE EVENTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kartavykh, Y. Y.; Dröge, W.; Gedalin, M.

2016-03-20

We use numerical solutions of the focused transport equation obtained by an implicit stochastic differential equation scheme to study the evolution of the pitch-angle dependent distribution function of protons in the vicinity of shock waves. For a planar stationary parallel shock, the effects of anisotropic distribution functions, pitch-angle dependent spatial diffusion, and first-order Fermi acceleration at the shock are examined, including the timescales on which the energy spectrum approaches the predictions of diffusive shock acceleration theory. We then consider the case that a flare-accelerated population of ions is released close to the Sun simultaneously with a traveling interplanetary shock formore » which we assume a simplified geometry. We investigate the consequences of adiabatic focusing in the diverging magnetic field on the particle transport at the shock, and of the competing effects of acceleration at the shock and adiabatic energy losses in the expanding solar wind. We analyze the resulting intensities, anisotropies, and energy spectra as a function of time and find that our simulations can naturally reproduce the morphologies of so-called mixed particle events in which sometimes the prompt and sometimes the shock component is more prominent, by assuming parameter values which are typically observed for scattering mean free paths of ions in the inner heliosphere and energy spectra of the flare particles which are injected simultaneously with the release of the shock.« less

Gravitational wave signatures of inflationary models from Primordial Black Hole dark matter

DOE Office of Scientific and Technical Information (OSTI.GOV)

García-Bellido, Juan; Peloso, Marco; Unal, Caner, E-mail: juan.garciabellido@uam.es, E-mail: peloso@physics.umn.edu, E-mail: unal@physics.umn.edu

Primordial Black Holes (PBH) could be the cold dark matter of the universe. They could have arisen from large (order one) curvature fluctuations produced during inflation that reentered the horizon in the radiation era. At reentry, these fluctuations source gravitational waves (GW) via second order anisotropic stresses. These GW, together with those (possibly) sourced during inflation by the same mechanism responsible for the large curvature fluctuations, constitute a primordial stochastic GW background (SGWB) that unavoidably accompanies the PBH formation. We study how the amplitude and the range of frequencies of this signal depend on the statistics (Gaussian versus χ{sup 2})more » of the primordial curvature fluctuations, and on the evolution of the PBH mass function due to accretion and merging. We then compare this signal with the sensitivity of present and future detectors, at PTA and LISA scales. We find that this SGWB will help to probe, or strongly constrain, the early universe mechanism of PBH production. The comparison between the peak mass of the PBH distribution and the peak frequency of this SGWB will provide important information on the merging and accretion evolution of the PBH mass distribution from their formation to the present era. Different assumptions on the statistics and on the PBH evolution also result in different amounts of CMB μ-distortions. Therefore the above results can be complemented by the detection (or the absence) of μ-distortions with an experiment such as PIXIE.« less

Stochastic associative memory

NASA Astrophysics Data System (ADS)

Baumann, Erwin W.; Williams, David L.

1993-08-01

Artificial neural networks capable of learning and recalling stochastic associations between non-deterministic quantities have received relatively little attention to date. One potential application of such stochastic associative networks is the generation of sensory 'expectations' based on arbitrary subsets of sensor inputs to support anticipatory and investigate behavior in sensor-based robots. Another application of this type of associative memory is the prediction of how a scene will look in one spectral band, including noise, based upon its appearance in several other wavebands. This paper describes a semi-supervised neural network architecture composed of self-organizing maps associated through stochastic inter-layer connections. This 'Stochastic Associative Memory' (SAM) can learn and recall non-deterministic associations between multi-dimensional probability density functions. The stochastic nature of the network also enables it to represent noise distributions that are inherent in any true sensing process. The SAM architecture, training process, and initial application to sensor image prediction are described. Relationships to Fuzzy Associative Memory (FAM) are discussed.

Cox process representation and inference for stochastic reaction-diffusion processes

NASA Astrophysics Data System (ADS)

Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

2016-05-01

Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

Individualism in plant populations: using stochastic differential equations to model individual neighbourhood-dependent plant growth.

PubMed

Lv, Qiming; Schneider, Manuel K; Pitchford, Jonathan W

2008-08-01

We study individual plant growth and size hierarchy formation in an experimental population of Arabidopsis thaliana, within an integrated analysis that explicitly accounts for size-dependent growth, size- and space-dependent competition, and environmental stochasticity. It is shown that a Gompertz-type stochastic differential equation (SDE) model, involving asymmetric competition kernels and a stochastic term which decreases with the logarithm of plant weight, efficiently describes individual plant growth, competition, and variability in the studied population. The model is evaluated within a Bayesian framework and compared to its deterministic counterpart, and to several simplified stochastic models, using distributional validation. We show that stochasticity is an important determinant of size hierarchy and that SDE models outperform the deterministic model if and only if structural components of competition (asymmetry; size- and space-dependence) are accounted for. Implications of these results are discussed in the context of plant ecology and in more general modelling situations.

Enhancement of the beam quality of non-uniform output slab laser amplifier with a 39-actuator rectangular piezoelectric deformable mirror.

PubMed

Yang, Ping; Ning, Yu; Lei, Xiang; Xu, Bing; Li, Xinyang; Dong, Lizhi; Yan, Hu; Liu, Wenjing; Jiang, Wenhan; Liu, Lei; Wang, Chao; Liang, Xingbo; Tang, Xiaojun

2010-03-29

We present a slab laser amplifier beam cleanup experimental system based on a 39-actuator rectangular piezoelectric deformable mirror. Rather than use a wave-front sensor to measure distortions in the wave-front and then apply a conjugation wave-front for compensating them, the system uses a Stochastic Parallel Gradient Descent algorithm to maximize the power contained within a far-field designated bucket. Experimental results demonstrate that at the output power of 335W, more than 30% energy concentrates in the 1x diffraction-limited area while the beam quality is enhanced greatly.

On resonant coupling of acoustic waves and gravity waves

NASA Astrophysics Data System (ADS)

Millet, Christophe

2017-11-01

Acoustic propagation in the atmosphere is often modeled using modes that are confined within waveguides causing the sound to propagate through multiple paths to the receiver. On the other hand, direct observations in the lower stratosphere show that the gravity wave field is intermittent, and is often dominated by rather well defined large-amplitude wave packets. In the present work, we use normal modes to describe both the gravity wave field and the acoustic field. The gravity wave spectrum is obtained by launching few monochromatic waves whose properties are chosen stochastically to mimic the intermittency. Owing to the disparity of the gravity and acoustic length scales, the interactions between the gravity wave field and each of the acoustic modes can be described using a multiple-scale analysis. The appropriate amplitude evolution equation for the acoustic field involves certain random terms that can be directly related to the gravity wave sources. We will show that the cumulative effect of gravity wave breakings makes the sensitivity of ground-based acoustic signals large, in that small changes in the gravity wave parameterization can create or destroy specific acoustic features.

Chemical event chain model of coupled genetic oscillators.

PubMed

Jörg, David J; Morelli, Luis G; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

The threshold of a stochastic avian-human influenza epidemic model with psychological effect

NASA Astrophysics Data System (ADS)

Zhang, Fengrong; Zhang, Xinhong

2018-02-01

In this paper, a stochastic avian-human influenza epidemic model with psychological effect in human population and saturation effect within avian population is investigated. This model describes the transmission of avian influenza among avian population and human population in random environments. For stochastic avian-only system, persistence in the mean and extinction of the infected avian population are studied. For the avian-human influenza epidemic system, sufficient conditions for the existence of an ergodic stationary distribution are obtained. Furthermore, a threshold of this stochastic model which determines the outcome of the disease is obtained. Finally, numerical simulations are given to support the theoretical results.

Stochastic Investigation of Natural Frequency for Functionally Graded Plates

NASA Astrophysics Data System (ADS)

Karsh, P. K.; Mukhopadhyay, T.; Dey, S.

2018-03-01

This paper presents the stochastic natural frequency analysis of functionally graded plates by applying artificial neural network (ANN) approach. Latin hypercube sampling is utilised to train the ANN model. The proposed algorithm for stochastic natural frequency analysis of FGM plates is validated and verified with original finite element method and Monte Carlo simulation (MCS). The combined stochastic variation of input parameters such as, elastic modulus, shear modulus, Poisson ratio, and mass density are considered. Power law is applied to distribute the material properties across the thickness. The present ANN model reduces the sample size and computationally found efficient as compared to conventional Monte Carlo simulation.

Chemical event chain model of coupled genetic oscillators

NASA Astrophysics Data System (ADS)

Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Empirical likelihood-based tests for stochastic ordering

PubMed Central

BARMI, HAMMOU EL; MCKEAGUE, IAN W.

2013-01-01

This paper develops an empirical likelihood approach to testing for the presence of stochastic ordering among univariate distributions based on independent random samples from each distribution. The proposed test statistic is formed by integrating a localized empirical likelihood statistic with respect to the empirical distribution of the pooled sample. The asymptotic null distribution of this test statistic is found to have a simple distribution-free representation in terms of standard Brownian bridge processes. The approach is used to compare the lengths of rule of Roman Emperors over various historical periods, including the “decline and fall” phase of the empire. In a simulation study, the power of the proposed test is found to improve substantially upon that of a competing test due to El Barmi and Mukerjee. PMID:23874142

3D aquifer characterization using stochastic streamline calibration

NASA Astrophysics Data System (ADS)

Jang, Minchul

2007-03-01

In this study, a new inverse approach, stochastic streamline calibration is proposed. Using both a streamline concept and a stochastic technique, stochastic streamline calibration optimizes an identified field to fit in given observation data in a exceptionally fast and stable fashion. In the stochastic streamline calibration, streamlines are adopted as basic elements not only for describing fluid flow but also for identifying the permeability distribution. Based on the streamline-based inversion by Agarwal et al. [Agarwal B, Blunt MJ. Streamline-based method with full-physics forward simulation for history matching performance data of a North sea field. SPE J 2003;8(2):171-80], Wang and Kovscek [Wang Y, Kovscek AR. Streamline approach for history matching production data. SPE J 2000;5(4):353-62], permeability is modified rather along streamlines than at the individual gridblocks. Permeabilities in the gridblocks which a streamline passes are adjusted by being multiplied by some factor such that we can match flow and transport properties of the streamline. This enables the inverse process to achieve fast convergence. In addition, equipped with a stochastic module, the proposed technique supportively calibrates the identified field in a stochastic manner, while incorporating spatial information into the field. This prevents the inverse process from being stuck in local minima and helps search for a globally optimized solution. Simulation results indicate that stochastic streamline calibration identifies an unknown permeability exceptionally quickly. More notably, the identified permeability distribution reflected realistic geological features, which had not been achieved in the original work by Agarwal et al. with the limitations of the large modifications along streamlines for matching production data only. The constructed model by stochastic streamline calibration forecasted transport of plume which was similar to that of a reference model. By this, we can expect the proposed approach to be applied to the construction of an aquifer model and forecasting of the aquifer performances of interest.

Electron residual energy due to stochastic heating in field-ionized plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khalilzadeh, Elnaz; The Plasma Physics and Fusion Research School, Tehran; Yazdanpanah, Jam, E-mail: jamal.yazdan@gmail.com

2015-11-15

The electron residual energy originated from the stochastic heating in under-dense field-ionized plasma is investigated here. Initially, the optical response of plasma is modeled by using two counter-propagating electromagnetic waves. In this case, the solution of motion equation of a single electron indicates that by including the ionization, the electron with higher residual energy compared with that without ionization could be obtained. In agreement with chaotic nature of the motion, it is found that the electron residual energy will be significantly changed by applying a minor change in the initial conditions. Extensive kinetic 1D-3V particle-in-cell simulations have been performed inmore » order to resolve full plasma reactions. In this way, two different regimes of plasma behavior are observed by varying the pulse length. The results indicate that the amplitude of scattered fields in a proper long pulse length is high enough to act as a second counter-propagating wave and trigger the stochastic electron motion. On the contrary, the analyses of intensity spectrum reveal the fact that the dominant scattering mechanism tends to Thomson rather than Raman scattering by increasing the pulse length. A covariant formalism is used to describe the plasma heating so that it enables us to measure electron temperature inside and outside of the pulse region.« less

Modeling Blazar Spectra by Solving an Electron Transport Equation

NASA Astrophysics Data System (ADS)

Lewis, Tiffany; Finke, Justin; Becker, Peter A.

2018-01-01

Blazars are luminous active galaxies across the entire electromagnetic spectrum, but the spectral formation mechanisms, especially the particle acceleration, in these sources are not well understood. We develop a new theoretical model for simulating blazar spectra using a self-consistent electron number distribution. Specifically, we solve the particle transport equation considering shock acceleration, adiabatic expansion, stochastic acceleration due to MHD waves, Bohm diffusive particle escape, synchrotron radiation, and Compton radiation, where we implement the full Compton cross-section for seed photons from the accretion disk, the dust torus, and 26 individual broad lines. We used a modified Runge-Kutta method to solve the 2nd order equation, including development of a new mathematical method for normalizing stiff steady-state ordinary differential equations. We show that our self-consistent, transport-based blazar model can qualitatively fit the IR through Fermi g-ray data for 3C 279, with a single-zone, leptonic configuration. We use the solution for the electron distribution to calculate multi-wavelength SED spectra for 3C 279. We calculate the particle and magnetic field energy densities, which suggest that the emitting region is not always in equipartition (a common assumption), but sometimes matter dominated. The stratified broad line region (based on ratios in quasar reverberation mapping, and thus adding no free parameters) improves our estimate of the location of the emitting region, increasing it by ~5x. Our model provides a novel view into the physics at play in blazar jets, especially the relative strength of the shock and stochastic acceleration, where our model is well suited to distinguish between these processes, and we find that the latter tends to dominate.

Hamiltonian Analysis of Subcritical Stochastic Epidemic Dynamics

PubMed Central

2017-01-01

We extend a technique of approximation of the long-term behavior of a supercritical stochastic epidemic model, using the WKB approximation and a Hamiltonian phase space, to the subcritical case. The limiting behavior of the model and approximation are qualitatively different in the subcritical case, requiring a novel analysis of the limiting behavior of the Hamiltonian system away from its deterministic subsystem. This yields a novel, general technique of approximation of the quasistationary distribution of stochastic epidemic and birth-death models and may lead to techniques for analysis of these models beyond the quasistationary distribution. For a classic SIS model, the approximation found for the quasistationary distribution is very similar to published approximations but not identical. For a birth-death process without depletion of susceptibles, the approximation is exact. Dynamics on the phase plane similar to those predicted by the Hamiltonian analysis are demonstrated in cross-sectional data from trachoma treatment trials in Ethiopia, in which declining prevalences are consistent with subcritical epidemic dynamics. PMID:28932256

Stochastic nature of series of waiting times.

PubMed

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H; Salehi, E; Behjat, E; Qorbani, M; Nezhad, M Khazaei; Zirak, M; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the "waiting times" series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2

Stochastic nature of series of waiting times

NASA Astrophysics Data System (ADS)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2

Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

PubMed

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2018-03-01

This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

Characterization of within-day beginning times of storms for stochastic simulation

USDA-ARS?s Scientific Manuscript database

The beginning times of storms within a day are often required for stochastic modeling purposes and for studies on plant growth. This study investigated the variation in frequency distributions of storm-initiation time (SI time) within a day due to elevation changes and month. Actual storms without 2...

Statistical description and transport in stochastic magnetic fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanden Eijnden, E.; Balescu, R.

1996-03-01

The statistical description of particle motion in a stochastic magnetic field is presented. Starting form the stochastic Liouville equation (or, hybrid kinetic equation) associated with the equations of motion of a test particle, the probability distribution function of the system is obtained for various magnetic fields and collisional processes. The influence of these two ingredients on the statistics of the particle dynamics is stressed. In all cases, transport properties of the system are discussed. {copyright} {ital 1996 American Institute of Physics.}

Stochastic Calculus and Differential Equations for Physics and Finance

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.

2013-02-01

1. Random variables and probability distributions; 2. Martingales, Markov, and nonstationarity; 3. Stochastic calculus; 4. Ito processes and Fokker-Planck equations; 5. Selfsimilar Ito processes; 6. Fractional Brownian motion; 7. Kolmogorov's PDEs and Chapman-Kolmogorov; 8. Non Markov Ito processes; 9. Black-Scholes, martingales, and Feynman-Katz; 10. Stochastic calculus with martingales; 11. Statistical physics and finance, a brief history of both; 12. Introduction to new financial economics; 13. Statistical ensembles and time series analysis; 14. Econometrics; 15. Semimartingales; References; Index.

Stochastic demographic forecasting.

PubMed

Lee, R D

1992-11-01

"This paper describes a particular approach to stochastic population forecasting, which is implemented for the U.S.A. through 2065. Statistical time series methods are combined with demographic models to produce plausible long run forecasts of vital rates, with probability distributions. The resulting mortality forecasts imply gains in future life expectancy that are roughly twice as large as those forecast by the Office of the Social Security Actuary.... Resulting stochastic forecasts of the elderly population, elderly dependency ratios, and payroll tax rates for health, education and pensions are presented." excerpt

A stochastic SIS epidemic model with vaccination

NASA Astrophysics Data System (ADS)

Cao, Boqiang; Shan, Meijing; Zhang, Qimin; Wang, Weiming

2017-11-01

In this paper, we investigate the basic features of an SIS type infectious disease model with varying population size and vaccinations in presence of environment noise. By applying the Markov semigroup theory, we propose a stochastic reproduction number R0s which can be seen as a threshold parameter to utilize in identifying the stochastic extinction and persistence: If R0s < 1, under some mild extra conditions, there exists a disease-free absorbing set for the stochastic epidemic model, which implies that disease dies out with probability one; while if R0s > 1, under some mild extra conditions, the SDE model has an endemic stationary distribution which results in the stochastic persistence of the infectious disease. The most interesting finding is that large environmental noise can suppress the outbreak of the disease.

The Air-Sea Interface and Surface Stress under Tropical Cyclones

NASA Astrophysics Data System (ADS)

Soloviev, Alexander; Lukas, Roger; Donelan, Mark; Ginis, Isaac

2013-04-01

Air-sea interaction dramatically changes from moderate to very high wind speed conditions (Donelan et al. 2004). Unresolved physics of the air-sea interface are one of the weakest components in tropical cyclone prediction models. Rapid disruption of the air-water interface under very high wind speed conditions was reported in laboratory experiments (Koga 1981) and numerical simulations (Soloviev et al. 2012), which resembled the Kelvin-Helmholtz instability at an interface with very large density difference. Kelly (1965) demonstrated that the KH instability at the air-sea interface can develop through parametric amplification of waves. Farrell and Ioannou (2008) showed that gustiness results in the parametric KH instability of the air-sea interface, while the gusts are due to interacting waves and turbulence. The stochastic forcing enters multiplicatively in this theory and produces an exponential wave growth, augmenting the growth from the Miles (1959) theory as the turbulence level increases. Here we complement this concept by adding the effect of the two-phase environment near the mean interface, which introduces additional viscosity in the system (turning it into a rheological system). The two-phase environment includes air-bubbles and re-entering spray (spume), which eliminates a portion of the wind-wave wavenumber spectrum that is responsible for a substantial part of the air sea drag coefficient. The previously developed KH-type interfacial parameterization (Soloviev and Lukas 2010) is unified with two versions of the wave growth model. The unified parameterization in both cases exhibits the increase of the drag coefficient with wind speed until approximately 30 m/s. Above this wind speed threshold, the drag coefficient either nearly levels off or even slightly drops (for the wave growth model that accounts for the shear) and then starts again increasing above approximately 65 m/s wind speed. Remarkably, the unified parameterization reveals a local minimum of the drag coefficient wind speed dependence around 65 m/s. This minimum may contribute to the rapid intensification of storms to major tropical cyclones. The subsequent slow increase of the drag coefficient with wind above 65 m/s serves as an obstacle for further intensification of tropical cyclones. Such dependence may explain the observed bi-modal distribution of tropical cyclone intensity. Implementation of the new parameterization into operational models is expected to improve predictions of tropical cyclone intensity and the associated wave field. References: Donelan, M. A., B. K. Haus, N. Reul, W. Plant, M. Stiassnie, H. Graber, O. Brown, and E. Saltzman, 2004: On the limiting aerodynamic roughness of the ocean in very strong winds, Farrell, B.F, and P.J. Ioannou, 2008: The stochastic parametric mechanism for growth of wind-driven surface water waves. Journal of Physical Oceanography 38, 862-879. Kelly, R.E., 1965: The stability of an unsteady Kelvin-Helmholtz flow. J. Fluid Mech. 22, 547-560. Koga, M., 1981: Direct production of droplets from breaking wind-waves-Its observation by a multi-colored overlapping exposure technique, Tellus 33, 552-563. Miles, J.W., 1959: On the generation of surface waves by shear flows, part 3. J. Fluid. Mech. 6, 583-598. Soloviev, A.V. and R. Lukas, 2010: Effects of bubbles and sea spray on air-sea exchanges in hurricane conditions. Boundary-Layer Meteorology 136, 365-376. Soloviev, A., A. Fujimura, and S. Matt, 2012: Air-sea interface in hurricane conditions. J. Geophys. Res. 117, C00J34.

Spectral evolution and extreme value analysis of non-linear numerical simulations of narrow band random surface gravity waves.

NASA Astrophysics Data System (ADS)

Socquet-Juglard, H.; Dysthe, K. B.; Trulsen, K.; Liu, J.; Krogstad, H. E.

2003-04-01

Numerical simulations of a narrow band gaussian spectrum of random surface gravity waves have been carried out in two and three spatial dimensions [7]. Different types of non-linear Schr&{uml;o}dinger equations, [1] and [4], have been used in these simulations. Simulations have now been carried with a JONSWAP spectrum associated with a spreading function of the type cosine-squared [5]. The evolution of the spectrum, skewness, kurtosis, ... will be presented. In addition, some results about stochastic properties of the surface will be shown. Based on the approach found in [2], [3] and [6], the results are presented in terms of deviations from linear Gaussian theory and the standard second order small slope perturbation theory. begin{thebibliography}{9} bibitem{kk96} Trulsen, K. &Dysthe, K. B. (1996). A modified nonlinear Schr&{uml;o}dinger equation for broader bandwidth gravity waves on deep water. Wave Motion, 24, pp. 281-289. bibitem{BK2000} Krogstad, H.E. and S.F. Barstow (2000). A uniform approach to extreme value analysis of ocean waves, Proc. ISOPE'2000, Seattle, USA, 3, pp. 103-108. bibitem{PRK} Prevosto, M., H. E. Krogstad and A. Robin (2000). Probability distributions for maximum wave and crest heights, Coast. Eng., 40, 329-360. bibitem{ketal} Trulsen, K., Kliakhandler, I., Dysthe, K. B. &Velarde, M. G. (2000) On weakly nonlinear modulation of waves on deep water, Phys. Fluids, 12, pp. L25-L28. bibitem{onorato} Onorato, M., Osborne, A.R. and Serio, M. (2002) Extreme wave events in directional, random oceanic sea states, Phys. Fluids, 14, pp. 2432-2437. bibitem{BK2002} Krogstad, H.E. and S.F. Barstow (2002). Analysis and Applications of Second Order Models for the Maximum Crest height, % Proc. 21nd Int. Conf. Offshore Mechanics and Arctic Engineering, Oslo. Paper no. OMAE2002-28479. bibitem{JFMP} Dysthe, K. B., Trulsen, K., Krogstad, H. E. and Socquet-Juglard, H. (2002, in press) Evolution of a narrow band spectrum of random surface gravity waves, J. Fluid Mech.

Switchable genetic oscillator operating in quasi-stable mode

PubMed Central

Strelkowa, Natalja; Barahona, Mauricio

2010-01-01

Ring topologies of repressing genes have qualitatively different long-term dynamics if the number of genes is odd (they oscillate) or even (they exhibit bistability). However, these attractors may not fully explain the observed behaviour in transient and stochastic environments such as the cell. We show here that even repressilators possess quasi-stable, travelling wave periodic solutions that are reachable, long-lived and robust to parameter changes. These solutions underlie the sustained oscillations observed in even rings in the stochastic regime, even if these circuits are expected to behave as switches. The existence of such solutions can also be exploited for control purposes: operation of the system around the quasi-stable orbit allows us to turn on and off the oscillations reliably and on demand. We illustrate these ideas with a simple protocol based on optical interference that can induce oscillations robustly both in the stochastic and deterministic regimes. PMID:20097721

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andorf, M. B.; Lebedev, V. A.; Piot, P.

Optical stochastic cooling (OSC) is expected to enable fast cooling of dense particle beams. Transition from microwave to optical frequencies enables an achievement of stochastic cooling rates which are orders of magnitude higher than ones achievable with the classical microwave based stochastic cooling systems. A subsystemcritical to the OSC scheme is the focusing optics used to image radiation from the upstream “pickup” undulator to the downstream “kicker” undulator. In this paper, we present simulation results using wave-optics calculation carried out with the Synchrotron Radiation Workshop (SRW). Our simulations are performed in support to a proof-of-principle experiment planned at the Integrablemore » Optics Test Accelerator (IOTA) at Fermilab. The calculations provide an estimate of the energy kick received by a 100-MeV electron as it propagates in the kicker undulator and interacts with the electromagnetic pulse it radiated at an earlier time while traveling through the pickup undulator.« less

Influence of nonlinear interactions on the development of instability in hydrodynamic wave systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romanova, N. N.; Chkhetiani, O. G., E-mail: ochkheti@mx.iki.rssi.ru, E-mail: ochkheti@gmail.ru; Yakushkin, I. G.

2016-05-15

The problem of the development of shear instability in a three-layer medium simulating the flow of a stratified incompressible fluid is considered. The hydrodynamic equations are solved by expanding the Hamiltonian in a small parameter. The equations for three interacting waves, one of which is unstable, have been derived and solved numerically. The three-wave interaction is shown to stabilize the instability. Various regimes of the system’s dynamics, including the stochastic ones dependent on one of the invariants in the problem, can arise in this case. It is pointed out that the instability development scenario considered differs from the previously consideredmore » scenario of a different type, where the three-wave interaction does not stabilize the instability. The interaction of wave packets is considered briefly.« less

An offline approach for output-only Bayesian identification of stochastic nonlinear systems using unscented Kalman filtering

NASA Astrophysics Data System (ADS)

Erazo, Kalil; Nagarajaiah, Satish

2017-06-01

In this paper an offline approach for output-only Bayesian identification of stochastic nonlinear systems is presented. The approach is based on a re-parameterization of the joint posterior distribution of the parameters that define a postulated state-space stochastic model class. In the re-parameterization the state predictive distribution is included, marginalized, and estimated recursively in a state estimation step using an unscented Kalman filter, bypassing state augmentation as required by existing online methods. In applications expectations of functions of the parameters are of interest, which requires the evaluation of potentially high-dimensional integrals; Markov chain Monte Carlo is adopted to sample the posterior distribution and estimate the expectations. The proposed approach is suitable for nonlinear systems subjected to non-stationary inputs whose realization is unknown, and that are modeled as stochastic processes. Numerical verification and experimental validation examples illustrate the effectiveness and advantages of the approach, including: (i) an increased numerical stability with respect to augmented-state unscented Kalman filtering, avoiding divergence of the estimates when the forcing input is unmeasured; (ii) the ability to handle arbitrary prior and posterior distributions. The experimental validation of the approach is conducted using data from a large-scale structure tested on a shake table. It is shown that the approach is robust to inherent modeling errors in the description of the system and forcing input, providing accurate prediction of the dynamic response when the excitation history is unknown.

Testing collapse models by a thermometer

NASA Astrophysics Data System (ADS)

Bahrami, M.

2018-05-01

Collapse models postulate that space is filled with a collapse noise field, inducing quantum Brownian motions, which are dominant during the measurement, thus causing collapse of the wave function. An important manifestation of the collapse noise field, if any, is thermal energy generation, thus disturbing the temperature profile of a system. The experimental investigation of a collapse-driven heating effect has provided, so far, the most promising test of collapse models against standard quantum theory. In this paper, we calculate the collapse-driven heat generation for a three-dimensional multi-atomic Bravais lattice by solving stochastic Heisenberg equations. We perform our calculation for the mass-proportional continuous spontaneous localization collapse model with nonwhite noise. We obtain the temperature distribution of a sphere under stationary-state and insulated surface conditions. However, the exact quantification of the collapse-driven heat-generation effect highly depends on the actual value of cutoff in the collapse noise spectrum.

Bursty Precipitation Driven by Chorus Waves

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Telnikhin, A. A.; Kronberg, T. K.

2011-01-01

The electron precipitation bursts have been shown to be a major sink for the radiation belt relativistic electrons. As underlying mechanism of such bursts, we propose particle scattering into the loss cone due to nonlinear resonance interaction between electrons and chorus. Stochastic heating due to the coupling leads to diffusion in pitch angle, and the rate of diffusion would be sufficient to account for the emptying of the Earth's radiation belt over the time of the main phase of geomagnetic storms. The results obtained in the present paper account for a strong energy dependence in the electron precipitation event and the correlation between the energization and loss processes on macroscopic timescales, which is primarily attributed to the cooperative effects of the coupling. This mechanism of chorus scattering should produce pitch angle distributions that are energy-dependent and butterfly-shaped. The calculated timescales and the total energy input to the atmosphere from precipitating relativistic electrons are in reasonable agreement with experimental data.

Fly's eye condenser based on chirped microlens arrays

NASA Astrophysics Data System (ADS)

Wippermann, Frank C.; Zeitner, Uwe-D.; Dannberg, Peter; Bräuer, Andreas; Sinzinger, Stefan

2007-09-01

Lens array arrangements are commonly used for the beam shaping of almost arbitrary input intensity distributions into a top-hat. The setup usually consists of a Fourier lens and two identical regular microlens arrays - often referred to as tandem lens array - where the second one is placed in the focal plane of the first microlenses. Due to the periodic structure of regular arrays the output intensity distribution is modulated by equidistant sharp intensity peaks which are disturbing the homogeneity. The equidistantly located intensity peaks can be suppressed when using a chirped and therefore non-periodic microlens array. A far field speckle pattern with more densely and irregularly located intensity peaks results leading to an improved homogeneity of the intensity distribution. In contrast to stochastic arrays, chirped arrays consist of individually shaped lenses defined by a parametric description of the cells optical function which can be derived completely from analytical functions. This gives the opportunity to build up tandem array setups enabling to achieve far field intensity distribution with an envelope of a top-hat. We propose a new concept for fly's eye condensers incorporating a chirped tandem microlens array for the generation of a top-hat far field intensity distribution with improved homogenization under coherent illumination. The setup is compliant to reflow of photoresist as fabrication technique since plane substrates accommodating the arrays are used. Considerations for the design of the chirped microlens arrays, design rules, wave optical simulations and measurements of the far field intensity distributions are presented.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Kai; Song, Linze; Shi, Qiang, E-mail: qshi@iccas.ac.cn

Based on the path integral approach, we derive a new realization of the exact non-Markovian stochastic Schrödinger equation (SSE). The main difference from the previous non-Markovian quantum state diffusion (NMQSD) method is that the complex Gaussian stochastic process used for the forward propagation of the wave function is correlated, which may be used to reduce the amplitude of the non-Markovian memory term at high temperatures. The new SSE is then written into the recently developed hierarchy of pure states scheme, in a form that is more closely related to the hierarchical equation of motion approach. Numerical simulations are then performedmore » to demonstrate the efficiency of the new method.« less

Single realization stochastic FDTD for weak scattering waves in biological random media.

PubMed

Tan, Tengmeng; Taflove, Allen; Backman, Vadim

2013-02-01

This paper introduces an iterative scheme to overcome the unresolved issues presented in S-FDTD (stochastic finite-difference time-domain) for obtaining ensemble average field values recently reported by Smith and Furse in an attempt to replace the brute force multiple-realization also known as Monte-Carlo approach with a single-realization scheme. Our formulation is particularly useful for studying light interactions with biological cells and tissues having sub-wavelength scale features. Numerical results demonstrate that such a small scale variation can be effectively modeled with a random medium problem which when simulated with the proposed S-FDTD indeed produces a very accurate result.

Single realization stochastic FDTD for weak scattering waves in biological random media

PubMed Central

Tan, Tengmeng; Taflove, Allen; Backman, Vadim

2015-01-01

This paper introduces an iterative scheme to overcome the unresolved issues presented in S-FDTD (stochastic finite-difference time-domain) for obtaining ensemble average field values recently reported by Smith and Furse in an attempt to replace the brute force multiple-realization also known as Monte-Carlo approach with a single-realization scheme. Our formulation is particularly useful for studying light interactions with biological cells and tissues having sub-wavelength scale features. Numerical results demonstrate that such a small scale variation can be effectively modeled with a random medium problem which when simulated with the proposed S-FDTD indeed produces a very accurate result. PMID:27158153

A new stochastic algorithm for inversion of dust aerosol size distribution

NASA Astrophysics Data System (ADS)

Wang, Li; Li, Feng; Yang, Ma-ying

2015-08-01

Dust aerosol size distribution is an important source of information about atmospheric aerosols, and it can be determined from multiwavelength extinction measurements. This paper describes a stochastic inverse technique based on artificial bee colony (ABC) algorithm to invert the dust aerosol size distribution by light extinction method. The direct problems for the size distribution of water drop and dust particle, which are the main elements of atmospheric aerosols, are solved by the Mie theory and the Lambert-Beer Law in multispectral region. And then, the parameters of three widely used functions, i.e. the log normal distribution (L-N), the Junge distribution (J-J), and the normal distribution (N-N), which can provide the most useful representation of aerosol size distributions, are inversed by the ABC algorithm in the dependent model. Numerical results show that the ABC algorithm can be successfully applied to recover the aerosol size distribution with high feasibility and reliability even in the presence of random noise.

Stochastic Modulations of the Pace and Patterns of Ageing: Impacts on Quasi-Stochastic Distributions of Multiple Geriatric Pathologies

PubMed Central

Martin, George M.

2011-01-01

All phenotypes result from interactions between Nature, Nurture and Chance. The constitutional genome is clearly the dominant factor in explaining the striking differences in the pace and patterns of ageing among species. We are now in a position to reveal salient features underlying these differential modulations, which are likely to be dominated by regulatory domains. By contrast, I shall argue that stochastic events are the major players underlying the surprisingly large intra-specific variations in lifespan and healthspan. I shall review well established as well as more speculative categories of chance events – somatic mutations, protein synthesis error catastrophe and variegations of gene expression (epigenetic drift), with special emphasis upon the latter. I shall argue that stochastic drifts in variegated gene expression are the major contributors to intra-specific differences in the pace and patterns of ageing within members of the same species. They may be responsible for the quasi-stochastic distributions of major types of geriatric pathologies, including the “big three” of Alzheimer's disease, atherosclerosis and, via the induction of hyperplasis, cancer. They may be responsible for altered stoichiometries of heteromultimeric mitochondrial complexes, potentially leading to such disorders as sarcopenia, nonischemic cardiomyopathy and Parkinson's disease. PMID:21963385

Inter-species competition-facilitation in stochastic riparian vegetation dynamics.

PubMed

Tealdi, Stefano; Camporeale, Carlo; Ridolfi, Luca

2013-02-07

Riparian vegetation is a highly dynamic community that lives on river banks and which depends to a great extent on the fluvial hydrology. The stochasticity of the discharge and erosion/deposition processes in fact play a key role in determining the distribution of vegetation along a riparian transect. These abiotic processes interact with biotic competition/facilitation mechanisms, such as plant competition for light, water, and nutrients. In this work, we focus on the dynamics of plants characterized by three components: (1) stochastic forcing due to river discharges, (2) competition for resources, and (3) inter-species facilitation due to the interplay between vegetation and fluid dynamics processes. A minimalist stochastic bio-hydrological model is proposed for the dynamics of the biomass of two vegetation species: one species is assumed dominant and slow-growing, the other is subdominant, but fast-growing. The stochastic model is solved analytically and the probability density function of the plant biomasses is obtained as a function of both the hydrologic and biologic parameters. The impact of the competition/facilitation processes on the distribution of vegetation species along the riparian transect is investigated and remarkable effects are observed. Finally, a good qualitative agreement is found between the model results and field data. Copyright © 2012 Elsevier Ltd. All rights reserved.

Design of Beneficial Wave Dynamics for Engine Life and Operability Enhancement

DTIC Science & Technology

2010-07-30

ST^(A), where S is the Dirac delta measure. Stochastic transition 9 function can be used to define two linear transfer operators called as Perron ... Frobenius and Koopman operators. Here we consider the finite dimensional approximation of the P-F operator. To do this we consider the finite

Particle Acceleration in Active Galactic Nuclei

NASA Technical Reports Server (NTRS)

Miller, James A.

1997-01-01

The high efficiency of energy generation inferred from radio observations of quasars and X-ray observations of Seyfert active galactic nuclei (AGNs) is apparently achieved only by the gravitational conversion of the rest mass energy of accreting matter onto supermassive black holes. Evidence for the acceleration of particles to high energies by a central engine is also inferred from observations of apparent superluminal motion in flat spectrum, core-dominated radio sources. This phenomenon is widely attributed to the ejection of relativistic bulk plasma from the nuclei of active galaxies, and accounts for the existence of large scale radio jets and lobes at large distances from the central regions of radio galaxies. Reports of radio jets and superluminal motion from galactic black hole candidate X-ray sources indicate that similar processes are operating in these sources. Observations of luminous, rapidly variable high-energy radiation from active galactic nuclei (AGNs) with the Compton Gamma Ray Observatory show directly that particles are accelerated to high energies in a compact environment. The mechanisms which transform the gravitational potential energy of the infalling matter into nonthermal particle energy in galactic black hole candidates and AGNs are not conclusively identified, although several have been proposed. These include direct acceleration by static electric fields (resulting from, for example, magnetic reconnection), shock acceleration, and energy extraction from the rotational energy of Kerr black holes. The dominant acceleration mechanism(s) operating in the black hole environment can only be determined, of course, by a comparison of model predictions with observations. The purpose of the work proposed for this grant was to investigate stochastic particle acceleration through resonant interactions with plasma waves that populate the magnetosphere surrounding an accreting black hole. Stochastic acceleration has been successfully applied to the problem of ion and electron energization in solar flares, and is capable of accounting for a wide range of both neutral and charged particle emissions. It is also a component in diffusive shock acceleration, since pitch-angle scattering (which is necessary for multiple shock crossings) is accompanied by diffusion in momentum space, which in turn yields a net systematic energy gain; however, stochastic energization will dominate the first-order shock process only in certain parameter regimes. Although stochastic acceleration has been applied to particle energization in the lobes of radio galaxies, its application to the central regions of AGNs has only recently been considered, but not in detail. We proposed to systematically investigate the plasma processes responsible for stochastic particle acceleration in black hole magnetospheres along with the energy-loss processes which impede particle energization. To this end we calculated acceleration rates and escape time scales for protons and electrons resonating with Alfven waves, and for electrons resonating with whistlers. Assuming either a Kolmogorov or Kraichnan wave spectrum, accretion at the Eddington limit, magnetic field strengths near equipartition, and turbulence energy densities approx. 10% of the total magnetic field energy density, we find that Alfven waves accelerate protons to Lorentz factors approx, equals 10(exp 4) - 10(exp 6) before they escape from the system. Acceleration of electrons by fast mode and whistler waves can produce a nonthermal population of relativistic electrons whose maximum energy is determined by a competition with radiation losses.

Stochastic Models for Laser Propagation in Atmospheric Turbulence.

NASA Astrophysics Data System (ADS)

Leland, Robert Patton

In this dissertation, stochastic models for laser propagation in atmospheric turbulence are considered. A review of the existing literature on laser propagation in the atmosphere and white noise theory is presented, with a view toward relating the white noise integral and Ito integral approaches. The laser beam intensity is considered as the solution to a random Schroedinger equation, or forward scattering equation. This model is formulated in a Hilbert space context as an abstract bilinear system with a multiplicative white noise input, as in the literature. The model is also modeled in the Banach space of Fresnel class functions to allow the plane wave case and the application of path integrals. Approximate solutions to the Schroedinger equation of the Trotter-Kato product form are shown to converge for each white noise sample path. The product forms are shown to be physical random variables, allowing an Ito integral representation. The corresponding Ito integrals are shown to converge in mean square, providing a white noise basis for the Stratonovich correction term associated with this equation. Product form solutions for Ornstein -Uhlenbeck process inputs were shown to converge in mean square as the input bandwidth was expanded. A digital simulation of laser propagation in strong turbulence was used to study properties of the beam. Empirical distributions for the irradiance function were estimated from simulated data, and the log-normal and Rice-Nakagami distributions predicted by the classical perturbation methods were seen to be inadequate. A gamma distribution fit the simulated irradiance distribution well in the vicinity of the boresight. Statistics of the beam were seen to converge rapidly as the bandwidth of an Ornstein-Uhlenbeck process was expanded to its white noise limit. Individual trajectories of the beam were presented to illustrate the distortion and bending of the beam due to turbulence. Feynman path integrals were used to calculate an approximate expression for the mean of the beam intensity without using the Markov, or white noise, assumption, and to relate local variations in the turbulence field to the behavior of the beam by means of two approximations.

Solar coronal loop heating by cross-field wave transport

NASA Technical Reports Server (NTRS)

Amendt, Peter; Benford, Gregory

1989-01-01

Solar coronal arches heated by turbulent ion-cyclotron waves may suffer significant cross-field transport by these waves. Nonlinear processes fix the wave-propagation speed at about a tenth of the ion thermal velocity, which seems sufficient to spread heat from a central core into a large cool surrounding cocoon. Waves heat cocoon ions both through classical ion-electron collisions and by turbulent stochastic ion motions. Plausible cocoon sizes set by wave damping are in roughly kilometers, although the wave-emitting core may be only 100 m wide. Detailed study of nonlinear stabilization and energy-deposition rates predicts that nearby regions can heat to values intermediate between the roughly electron volt foot-point temperatures and the about 100 eV core, which is heated by anomalous Ohmic losses. A volume of 100 times the core volume may be affected. This qualitative result may solve a persistent problem with current-driven coronal heating; that it affects only small volumes and provides no way to produce the extended warm structures perceptible to existing instruments.

A stochastic model of firm growth

NASA Astrophysics Data System (ADS)

Bottazzi, Giulio; Secchi, Angelo

2003-06-01

Recently from analyses on different databases the tent-shape of the distribution of firm growth rates has emerged as a robust and universal characteristic of the time evolution of corporates. We add new evidence on this topic and we present a new stochastic model that, under rather general assumptions, provides a robust explanation for the observed regularity.

Doubly stochastic radial basis function methods

NASA Astrophysics Data System (ADS)

Yang, Fenglian; Yan, Liang; Ling, Leevan

2018-06-01

We propose a doubly stochastic radial basis function (DSRBF) method for function recoveries. Instead of a constant, we treat the RBF shape parameters as stochastic variables whose distribution were determined by a stochastic leave-one-out cross validation (LOOCV) estimation. A careful operation count is provided in order to determine the ranges of all the parameters in our methods. The overhead cost for setting up the proposed DSRBF method is O (n2) for function recovery problems with n basis. Numerical experiments confirm that the proposed method not only outperforms constant shape parameter formulation (in terms of accuracy with comparable computational cost) but also the optimal LOOCV formulation (in terms of both accuracy and computational cost).

Using Colored Stochastic Petri Net (CS-PN) software for protocol specification, validation, and evaluation

NASA Technical Reports Server (NTRS)

Zenie, Alexandre; Luguern, Jean-Pierre

1987-01-01

The specification, verification, validation, and evaluation, which make up the different steps of the CS-PN software are outlined. The colored stochastic Petri net software is applied to a Wound/Wait protocol decomposable into two principal modules: request or couple (transaction, granule) treatment module and wound treatment module. Each module is specified, verified, validated, and then evaluated separately, to deduce a verification, validation and evaluation of the complete protocol. The colored stochastic Petri nets tool is shown to be a natural extension of the stochastic tool, adapted to distributed systems and protocols, because the color conveniently takes into account the numerous sites, transactions, granules and messages.

Stochastic effects in a thermochemical system with Newtonian heat exchange.

PubMed

Nowakowski, B; Lemarchand, A

2001-12-01

We develop a mesoscopic description of stochastic effects in the Newtonian heat exchange between a diluted gas system and a thermostat. We explicitly study the homogeneous Semenov model involving a thermochemical reaction and neglecting consumption of reactants. The master equation includes a transition rate for the thermal transfer process, which is derived on the basis of the statistics for inelastic collisions between gas particles and walls of the thermostat. The main assumption is that the perturbation of the Maxwellian particle velocity distribution can be neglected. The transition function for the thermal process admits a continuous spectrum of temperature changes, and consequently, the master equation has a complicated integro-differential form. We perform Monte Carlo simulations based on this equation to study the stochastic effects in the Semenov system in the explosive regime. The dispersion of ignition times is calculated as a function of system size. For sufficiently small systems, the probability distribution of temperature displays transient bimodality during the ignition period. The results of the stochastic description are successfully compared with those of direct simulations of microscopic particle dynamics.

Stochastic Multi-Commodity Facility Location Based on a New Scenario Generation Technique

NASA Astrophysics Data System (ADS)

Mahootchi, M.; Fattahi, M.; Khakbazan, E.

2011-11-01

This paper extends two models for stochastic multi-commodity facility location problem. The problem is formulated as two-stage stochastic programming. As a main point of this study, a new algorithm is applied to efficiently generate scenarios for uncertain correlated customers' demands. This algorithm uses Latin Hypercube Sampling (LHS) and a scenario reduction approach. The relation between customer satisfaction level and cost are considered in model I. The risk measure using Conditional Value-at-Risk (CVaR) is embedded into the optimization model II. Here, the structure of the network contains three facility layers including plants, distribution centers, and retailers. The first stage decisions are the number, locations, and the capacity of distribution centers. In the second stage, the decisions are the amount of productions, the volume of transportation between plants and customers.

Optimal regulation in systems with stochastic time sampling

NASA Technical Reports Server (NTRS)

Montgomery, R. C.; Lee, P. S.

1980-01-01

An optimal control theory that accounts for stochastic variable time sampling in a distributed microprocessor based flight control system is presented. The theory is developed by using a linear process model for the airplane dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved for the control law that minimizes the expected value of a quadratic cost function. The optimal cost obtained with a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained with a known and uniform information update interval.

Oxygen Distributions-Evaluation of Computational Methods, Using a Stochastic Model for Large Tumour Vasculature, to Elucidate the Importance of Considering a Complete Vascular Network.

PubMed

Lagerlöf, Jakob H; Bernhardt, Peter

2016-01-01

To develop a general model that utilises a stochastic method to generate a vessel tree based on experimental data, and an associated irregular, macroscopic tumour. These will be used to evaluate two different methods for computing oxygen distribution. A vessel tree structure, and an associated tumour of 127 cm3, were generated, using a stochastic method and Bresenham's line algorithm to develop trees on two different scales and fusing them together. The vessel dimensions were adjusted through convolution and thresholding and each vessel voxel was assigned an oxygen value. Diffusion and consumption were modelled using a Green's function approach together with Michaelis-Menten kinetics. The computations were performed using a combined tree method (CTM) and an individual tree method (ITM). Five tumour sub-sections were compared, to evaluate the methods. The oxygen distributions of the same tissue samples, using different methods of computation, were considerably less similar (root mean square deviation, RMSD≈0.02) than the distributions of different samples using CTM (0.001< RMSD<0.01). The deviations of ITM from CTM increase with lower oxygen values, resulting in ITM severely underestimating the level of hypoxia in the tumour. Kolmogorov Smirnov (KS) tests showed that millimetre-scale samples may not represent the whole. The stochastic model managed to capture the heterogeneous nature of hypoxic fractions and, even though the simplified computation did not considerably alter the oxygen distribution, it leads to an evident underestimation of tumour hypoxia, and thereby radioresistance. For a trustworthy computation of tumour oxygenation, the interaction between adjacent microvessel trees must not be neglected, why evaluation should be made using high resolution and the CTM, applied to the entire tumour.

Probability distribution of financial returns in a model of multiplicative Brownian motion with stochastic diffusion coefficient

NASA Astrophysics Data System (ADS)

Silva, Antonio

2005-03-01

It is well-known that the mathematical theory of Brownian motion was first developed in the Ph. D. thesis of Louis Bachelier for the French stock market before Einstein [1]. In Ref. [2] we studied the so-called Heston model, where the stock-price dynamics is governed by multiplicative Brownian motion with stochastic diffusion coefficient. We solved the corresponding Fokker-Planck equation exactly and found an analytic formula for the time-dependent probability distribution of stock price changes (returns). The formula interpolates between the exponential (tent-shaped) distribution for short time lags and the Gaussian (parabolic) distribution for long time lags. The theoretical formula agrees very well with the actual stock-market data ranging from the Dow-Jones index [2] to individual companies [3], such as Microsoft, Intel, etc. [] [1] Louis Bachelier, ``Th'eorie de la sp'eculation,'' Annales Scientifiques de l''Ecole Normale Sup'erieure, III-17:21-86 (1900).[] [2] A. A. Dragulescu and V. M. Yakovenko, ``Probability distribution of returns in the Heston model with stochastic volatility,'' Quantitative Finance 2, 443--453 (2002); Erratum 3, C15 (2003). [cond-mat/0203046] [] [3] A. C. Silva, R. E. Prange, and V. M. Yakovenko, ``Exponential distribution of financial returns at mesoscopic time lags: a new stylized fact,'' Physica A 344, 227--235 (2004). [cond-mat/0401225

Influence of Microphysical Variability on Stochastic Condensation in Turbulent Clouds

NASA Astrophysics Data System (ADS)

Desai, N.; Chandrakar, K. K.; Chang, K.; Glienke, S.; Cantrell, W. H.; Fugal, J. P.; Shaw, R. A.

2017-12-01

We investigate the influence of variability in droplet number concentration and radius on the evolution of cloud droplet size distributions. Measurements are made on the centimeter scale using digitial inline holography, both in a controlled laboratory setting and in the field using HOLODEC measurements from CSET. We created steady state cloud conditions in the laboratory Pi Chamber, in which a turbulent cloud can be sustained for long periods of time. Using holographic imaging, we directly observe the variations in local number concentration and droplet size distribution and, thereby, the integral radius. We interpret the measurements in the context of stochastic condensation theory to determine how fluctuations in integral radius contribute to droplet growth. We find that the variability in integral radius is primarily driven by variations in the droplet number concentration and not the droplet radius. This variability does not contribute significantly to the mean droplet growth rate, but contributes significantly to the rate of increase of the size distribution width. We compare these results with in-situ measurements and find evidence for microphysical signatures of stochastic condensation. The results suggest that supersaturation fluctuations lead to broader size distributions and allow droplets to reach the collision-coalescence stage.

A path integral methodology for obtaining thermodynamic properties of nonadiabatic systems using Gaussian mixture distributions

NASA Astrophysics Data System (ADS)

Raymond, Neil; Iouchtchenko, Dmitri; Roy, Pierre-Nicholas; Nooijen, Marcel

2018-05-01

We introduce a new path integral Monte Carlo method for investigating nonadiabatic systems in thermal equilibrium and demonstrate an approach to reducing stochastic error. We derive a general path integral expression for the partition function in a product basis of continuous nuclear and discrete electronic degrees of freedom without the use of any mapping schemes. We separate our Hamiltonian into a harmonic portion and a coupling portion; the partition function can then be calculated as the product of a Monte Carlo estimator (of the coupling contribution to the partition function) and a normalization factor (that is evaluated analytically). A Gaussian mixture model is used to evaluate the Monte Carlo estimator in a computationally efficient manner. Using two model systems, we demonstrate our approach to reduce the stochastic error associated with the Monte Carlo estimator. We show that the selection of the harmonic oscillators comprising the sampling distribution directly affects the efficiency of the method. Our results demonstrate that our path integral Monte Carlo method's deviation from exact Trotter calculations is dominated by the choice of the sampling distribution. By improving the sampling distribution, we can drastically reduce the stochastic error leading to lower computational cost.

Simple stochastic birth and death models of genome evolution: was there enough time for us to evolve?

PubMed

Karev, Georgy P; Wolf, Yuri I; Koonin, Eugene V

2003-10-12

The distributions of many genome-associated quantities, including the membership of paralogous gene families can be approximated with power laws. We are interested in developing mathematical models of genome evolution that adequately account for the shape of these distributions and describe the evolutionary dynamics of their formation. We show that simple stochastic models of genome evolution lead to power-law asymptotics of protein domain family size distribution. These models, called Birth, Death and Innovation Models (BDIM), represent a special class of balanced birth-and-death processes, in which domain duplication and deletion rates are asymptotically equal up to the second order. The simplest, linear BDIM shows an excellent fit to the observed distributions of domain family size in diverse prokaryotic and eukaryotic genomes. However, the stochastic version of the linear BDIM explored here predicts that the actual size of large paralogous families is reached on an unrealistically long timescale. We show that introduction of non-linearity, which might be interpreted as interaction of a particular order between individual family members, allows the model to achieve genome evolution rates that are much better compatible with the current estimates of the rates of individual duplication/loss events.

A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Lindsay; Zéphyr, Luckny; Cardell, Judith B.

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for cooptimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy managementmore » system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the development of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic optimization, including decomposition and stochastic dual dynamic programming.« less

Stochasticity and determinism in models of hematopoiesis.

PubMed

Kimmel, Marek

2014-01-01

This chapter represents a novel view of modeling in hematopoiesis, synthesizing both deterministic and stochastic approaches. Whereas the stochastic models work in situations where chance dominates, for example when the number of cells is small, or under random mutations, the deterministic models are more important for large-scale, normal hematopoiesis. New types of models are on the horizon. These models attempt to account for distributed environments such as hematopoietic niches and their impact on dynamics. Mixed effects of such structures and chance events are largely unknown and constitute both a challenge and promise for modeling. Our discussion is presented under the separate headings of deterministic and stochastic modeling; however, the connections between both are frequently mentioned. Four case studies are included to elucidate important examples. We also include a primer of deterministic and stochastic dynamics for the reader's use.

Gravitational waves from binary supermassive black holes missing in pulsar observations.

PubMed

Shannon, R M; Ravi, V; Lentati, L T; Lasky, P D; Hobbs, G; Kerr, M; Manchester, R N; Coles, W A; Levin, Y; Bailes, M; Bhat, N D R; Burke-Spolaor, S; Dai, S; Keith, M J; Osłowski, S; Reardon, D J; van Straten, W; Toomey, L; Wang, J-B; Wen, L; Wyithe, J S B; Zhu, X-J

2015-09-25

Gravitational waves are expected to be radiated by supermassive black hole binaries formed during galaxy mergers. A stochastic superposition of gravitational waves from all such binary systems would modulate the arrival times of pulses from radio pulsars. Using observations of millisecond pulsars obtained with the Parkes radio telescope, we constrained the characteristic amplitude of this background, A(c,yr), to be <1.0 × 10(-15) with 95% confidence. This limit excludes predicted ranges for A(c,yr) from current models with 91 to 99.7% probability. We conclude that binary evolution is either stalled or dramatically accelerated by galactic-center environments and that higher-cadence and shorter-wavelength observations would be more sensitive to gravitational waves. Copyright © 2015, American Association for the Advancement of Science.

Parametric pendulum based wave energy converter

NASA Astrophysics Data System (ADS)

Yurchenko, Daniil; Alevras, Panagiotis

2018-01-01

The paper investigates the dynamics of a novel wave energy converter based on the parametrically excited pendulum. The herein developed concept of the parametric pendulum allows reducing the influence of the gravity force thereby significantly improving the device performance at a regular sea state, which could not be achieved in the earlier proposed original point-absorber design. The suggested design of a wave energy converter achieves a dominant rotational motion without any additional mechanisms, like a gearbox, or any active control involvement. Presented numerical results of deterministic and stochastic modeling clearly reflect the advantage of the proposed design. A set of experimental results confirms the numerical findings and validates the new design of a parametric pendulum based wave energy converter. Power harvesting potential of the novel device is also presented.

Ground motion simulation for the 23 August 2011, Mineral, Virginia earthquake using physics-based and stochastic broadband methods

USGS Publications Warehouse

Sun, Xiaodan; Hartzell, Stephen; Rezaeian, Sanaz

2015-01-01

Three broadband simulation methods are used to generate synthetic ground motions for the 2011 Mineral, Virginia, earthquake and compare with observed motions. The methods include a physics‐based model by Hartzell et al. (1999, 2005), a stochastic source‐based model by Boore (2009), and a stochastic site‐based model by Rezaeian and Der Kiureghian (2010, 2012). The ground‐motion dataset consists of 40 stations within 600 km of the epicenter. Several metrics are used to validate the simulations: (1) overall bias of response spectra and Fourier spectra (from 0.1 to 10 Hz); (2) spatial distribution of residuals for GMRotI50 peak ground acceleration (PGA), peak ground velocity, and pseudospectral acceleration (PSA) at various periods; (3) comparison with ground‐motion prediction equations (GMPEs) for the eastern United States. Our results show that (1) the physics‐based model provides satisfactory overall bias from 0.1 to 10 Hz and produces more realistic synthetic waveforms; (2) the stochastic site‐based model also yields more realistic synthetic waveforms and performs superiorly for frequencies greater than about 1 Hz; (3) the stochastic source‐based model has larger bias at lower frequencies (<0.5  Hz) and cannot reproduce the varying frequency content in the time domain. The spatial distribution of GMRotI50 residuals shows that there is no obvious pattern with distance in the simulation bias, but there is some azimuthal variability. The comparison between synthetics and GMPEs shows similar fall‐off with distance for all three models, comparable PGA and PSA amplitudes for the physics‐based and stochastic site‐based models, and systematic lower amplitudes for the stochastic source‐based model at lower frequencies (<0.5  Hz).

Analyses of the stratospheric dynamics simulated by a GCM with a stochastic nonorographic gravity wave parameterization

NASA Astrophysics Data System (ADS)

Serva, Federico; Cagnazzo, Chiara; Riccio, Angelo

2016-04-01

The effects of the propagation and breaking of atmospheric gravity waves have long been considered crucial for their impact on the circulation, especially in the stratosphere and mesosphere, between heights of 10 and 110 km. These waves, that in the Earth's atmosphere originate from surface orography (OGWs) or from transient (nonorographic) phenomena such as fronts and convective processes (NOGWs), have horizontal wavelengths between 10 and 1000 km, vertical wavelengths of several km, and frequencies spanning from minutes to hours. Orographic and nonorographic GWs must be accounted for in climate models to obtain a realistic simulation of the stratosphere in both hemispheres, since they can have a substantial impact on circulation and temperature, hence an important role in ozone chemistry for chemistry-climate models. Several types of parameterization are currently employed in models, differing in the formulation and for the values assigned to parameters, but the common aim is to quantify the effect of wave breaking on large-scale wind and temperature patterns. In the last decade, both global observations from satellite-borne instruments and the outputs of very high resolution climate models provided insight on the variability and properties of gravity wave field, and these results can be used to constrain some of the empirical parameters present in most parameterization scheme. A feature of the NOGW forcing that clearly emerges is the intermittency, linked with the nature of the sources: this property is absent in the majority of the models, in which NOGW parameterizations are uncoupled with other atmospheric phenomena, leading to results which display lower variability compared to observations. In this work, we analyze the climate simulated in AMIP runs of the MAECHAM5 model, which uses the Hines NOGW parameterization and with a fine vertical resolution suitable to capture the effects of wave-mean flow interaction. We compare the results obtained with two version of the model, the default and a new stochastic version, in which the value of the perturbation field at launching level is not constant and uniform, but extracted at each time-step and grid-point from a given PDF. With this approach we are trying to add further variability to the effects given by the deterministic NOGW parameterization: the impact on the simulated climate will be assessed focusing on the Quasi-Biennial Oscillation of the equatorial stratosphere (known to be driven also by gravity waves) and on the variability of the mid-to-high latitudes atmosphere. The different characteristics of the circulation will be compared with recent reanalysis products in order to determine the advantages of the stochastic approach over the traditional deterministic scheme.

Application of stochastic particle swarm optimization algorithm to determine the graded refractive index distribution in participating media

NASA Astrophysics Data System (ADS)

Wei, Lin-Yang; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2016-11-01

Inverse estimation of the refractive index distribution in one-dimensional participating media with graded refractive index (GRI) is investigated. The forward radiative transfer problem is solved by the Chebyshev collocation spectral method. The stochastic particle swarm optimization (SPSO) algorithm is employed to retrieve three kinds of GRI distribution, i.e. the linear, sinusoidal and quadratic GRI distribution. The retrieval accuracy of GRI distribution with different wall emissivity, optical thickness, absorption coefficients and scattering coefficients are discussed thoroughly. To improve the retrieval accuracy of quadratic GRI distribution, a double-layer model is proposed to supply more measurement information. The influence of measurement errors upon the precision of estimated results is also investigated. Considering the GRI distribution is unknown beforehand in practice, a quadratic function is employed to retrieve the linear GRI by SPSO algorithm. All the results show that the SPSO algorithm is applicable to retrieve different GRI distributions in participating media accurately even with noisy data.

Performance of quantum annealing on random Ising problems implemented using the D-Wave Two

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Job, Joshua; Rønnow, Troels F.; Troyer, Matthias; Lidar, Daniel A.; USC Collaboration; ETH Collaboration

2014-03-01

Detecting a possible speedup of quantum annealing compared to classical algorithms is a pressing task in experimental adiabatic quantum computing. In this talk, we discuss the performance of the D-Wave Two quantum annealing device on Ising spin glass problems. The expected time to solution for the device to solve random instances with up to 503 spins and with specified coupling ranges is evaluated while carefully addressing the issue of statistical errors. We perform a systematic comparison of the expected time to solution between the D-Wave Two and classical stochastic solvers, specifically simulated annealing, and simulated quantum annealing based on quantum Monte Carlo, and discuss the question of speedup.

Theoretical and experimental studies of a planar inductive coupled rf plasma source as the driver in simulator facility (ISTAPHM) of interactions of waves with the edge plasma on tokamaks

NASA Astrophysics Data System (ADS)

Ghanei, V.; Nasrabadi, M. N.; Chin, O.-H.; Jayapalan, K. K.

2017-11-01

This research aims to design and build a planar inductive coupled RF plasma source device which is the driver of the simulator project (ISTAPHM) of the interactions between ICRF Antenna and Plasma on tokamak by using the AMPICP model. For this purpose, a theoretical derivation of the distribution of the RF magnetic field in the plasma-filled reactor chamber is presented. An experimental investigation of the field distributions is described and Langmuir measurements are developed numerically. A comparison of theory and experiment provides an evaluation of plasma parameters in the planar ICP reactor. The objective of this study is to characterize the plasma produced by the source alone. We present the results of the first analysis of the plasma characteristics (plasma density, electron temperature, electron-ion collision frequency, particle fluxes and their velocities, stochastic frequency, skin depth and electron energy distribution functions) as function of the operating parameters (injected power, neutral pressure and magnetic field) as measured with fixed and movable Langmuir probes. The plasma is currently produced only by the planar ICP. The exact goal of these experiments is that the produced plasma by external source can exist as a plasma representative of the edge of tokamaks.

The origin of human complex diversity: Stochastic epistatic modules and the intrinsic compatibility between distributional robustness and phenotypic changeability.

PubMed

Ijichi, Shinji; Ijichi, Naomi; Ijichi, Yukina; Imamura, Chikako; Sameshima, Hisami; Kawaike, Yoichi; Morioka, Hirofumi

2018-01-01

The continuing prevalence of a highly heritable and hypo-reproductive extreme tail of a human neurobehavioral quantitative diversity suggests the possibility that the reproductive majority retains the genetic mechanism for the extremes. From the perspective of stochastic epistasis, the effect of an epistatic modifier variant can randomly vary in both phenotypic value and effect direction among the careers depending on the genetic individuality, and the modifier careers are ubiquitous in the population distribution. The neutrality of the mean genetic effect in the careers warrants the survival of the variant under selection pressures. Functionally or metabolically related modifier variants make an epistatic network module and dozens of modules may be involved in the phenotype. To assess the significance of stochastic epistasis, a simplified module-based model was employed. The individual repertoire of the modifier variants in a module also participates in the genetic individuality which determines the genetic contribution of each modifier in the career. Because the entire contribution of a module to the phenotypic outcome is consequently unpredictable in the model, the module effect represents the total contribution of the related modifiers as a stochastic unit in the simulations. As a result, the intrinsic compatibility between distributional robustness and quantitative changeability could mathematically be simulated using the model. The artificial normal distribution shape in large-sized simulations was preserved in each generation even if the lowest fitness tail was un-reproductive. The robustness of normality beyond generations is analogous to the real situations of human complex diversity including neurodevelopmental conditions. The repeated regeneration of the un-reproductive extreme tail may be inevitable for the reproductive majority's competence to survive and change, suggesting implications of the extremes for others. Further model-simulations to illustrate how the fitness of extreme individuals can be low through generations may be warranted to increase the credibility of this stochastic epistasis model.

Regional difference in small-scale heterogeneities in the crust and upper mantle in Japan derived by the analysis of high-frequency P-wave

NASA Astrophysics Data System (ADS)

Takemura, S.; Furumura, T.

2010-12-01

In order to understand distribution properties of small-scale heterogeneities in the crust and upper mantle structure, we analyze three-component seismograms recorded by Hi-net in Japan. We examined relative strength of the P-wave in the transverse (T) component and its change as a function of frequency and propagation distances, which is strongly relating to the strength of seismic wave scattering in the lithosphere. We analyzed 53,220 Hi-net record from 310 shallow (h<30km) crustal earthquakes with MJMA =2.0-5.3. The three-component seismograms are firstly applied by band-pass filter with pass band frequency of f=1-2, 2-4, 4-8, 8-16, 16-32 Hz and then the Hilbert transform is used to synthesize envelope of each component. Then, the energy partition (EP) of P wave in the T component relative to total P-wave energy is evaluated around the P wave in 3-sec time window. The estimated EP value is almost constant 0.2 in high-frequencies (8-16 Hz) at shorter distance, while it is 0.07 in low-frequencies (1-2 Hz). We found clearly frequency-change property of EP value. But at larger distance over 150 km, EP values gradually increase with increasing distance. In high-frequencies (8-16, 16-32 Hz), especially EP values asymptotically reach from 0.2 to 0.33, equi-partitioning of P-wave energy into three components. This may because Pn-phase dominates in larger hypocentral distances. In order to examine difference in the EP in each area of Japan which would be relating to the strength of crustal heterogeneities in each area we divided the area of Japan into three regions, fore-arc side of Tohoku, back-arc side of Tohoku and Chugoku-Shikoku area. The difference in EP value in each area is clearly found in the high-frequency (4-8 Hz) band, where larger EP (0.2) was obtained at back-arc side of Tohoku relative to smaller EP (0.1) at fore-arc side of Tohoku and Chugoku-Shikoku. This is consistent with the results of Carcole and Sato (2009) who estimated the strength of crustal heterogeneities based on the multi lapse time-window analysis. In order to clarify the cause of such regional difference of EP, we conduct 3-D FDM simulations using stochastic random media. The model covers a zone 204.8 km by 204.8 km by 64.0 km descretized with 0.1 km in horizontal direction and 0.05 km in vertical direction. The small-scale heterogeneity in the lithosphere is constructed by velocity fluctuation from average velocity. The fluctuation is characterized by von Karman-type ACF with the correlation length a, the rms value e and decay order k. We assume average background velocities of P-wave and S-wave are VP = 5.8 km and VS = 3.36 km, respectively. We employ an explosive point source into the model. The FDM simulations were conducted on the Earth Simulator at JAMSTEC. We conducted a number of FDM simulation using different model parameters of stochastic random media for different e (= 0.03, 0.05, 0.07, 0.09) and fixed a and k (a = 5km, k = 0.5). The simulation results confirm EP value increases linearly with increasing e. We also found that larger EP obtained in the back-arc side of Tohoku can be explained by 4% larger e relative to those of other regions.

Finite Element Methods for Modelling Mechanical Loss in LIGO coating optics.

NASA Astrophysics Data System (ADS)

Newport, Jonathan; Harry, Gregg; LIGO Collaboration

2015-04-01

Gravitational waves from sources such as binary star systems, supernovae explosions and stochastic background radiation have yet to be directly detected by experimental observations. Alongside international collaborators, the Laser Interferometer Gravitational-Wave Observatory (LIGO) is designed to realize detection of gravitational waves using interferometric techniques. The second generation of gravitational wave observatories, known as Advanced LIGO, are currently undergoing installation and commissioning at sites in Hanford, Washington and Livingston, Louisiana. The ultimate sensitivity of Advanced LIGO within select spectral bands is limited by thermal noise in the coatings of the interferometer optics. The LIGO lab at American University is measuring the mechanical loss of coated substrates to predict thermal noise within these spectral bands. These predictions use increasingly sophisticated finite element models to ensure the ultimate design sensitivity of Advanced LIGO and to study coating and substrate materials for future gravitational wave detectors.

The gravitational wave contribution to cosmic microwave background anisotropies and the amplitude of mass fluctuations from COBE results

NASA Technical Reports Server (NTRS)

Lucchin, Francesco; Matarrese, Sabino; Mollerach, Silvia

1992-01-01

A stochastic background of primordial gravitational waves may substantially contribute, via the Sachs-Wolfe effect, to the large-scale cosmic microwave background (CMB) anisotropies recently detected by COBE. This implies a bias in any resulting determination of the primordial amplitude of density fluctuations. We consider the constraints imposed on n is less than 1 ('tilted') power-law fluctuation spectra, taking into account the contribution from both scalar and tensor waves, as predicted by power-law inflation. The gravitational wave contribution to CMB anisotropies generally reduces the required rms level of mass fluctuation, thereby increasing the linear bias parameter, even in models where the spectral index is close to the Harrison-Zel'dovich value n = 1. This 'gravitational wave bias' helps to reconcile the predictions of CDM models with observations on pairwise galaxy velocity dispersion on small scales.

Quantitative analysis of random ameboid motion

NASA Astrophysics Data System (ADS)

Bödeker, H. U.; Beta, C.; Frank, T. D.; Bodenschatz, E.

2010-04-01

We quantify random migration of the social ameba Dictyostelium discoideum. We demonstrate that the statistics of cell motion can be described by an underlying Langevin-type stochastic differential equation. An analytic expression for the velocity distribution function is derived. The separation into deterministic and stochastic parts of the movement shows that the cells undergo a damped motion with multiplicative noise. Both contributions to the dynamics display a distinct response to external physiological stimuli. The deterministic component depends on the developmental state and ambient levels of signaling substances, while the stochastic part does not.

Scenario Decomposition for 0-1 Stochastic Programs: Improvements and Asynchronous Implementation

DOE PAGES

Ryan, Kevin; Rajan, Deepak; Ahmed, Shabbir

2016-05-01

We recently proposed scenario decomposition algorithm for stochastic 0-1 programs finds an optimal solution by evaluating and removing individual solutions that are discovered by solving scenario subproblems. In our work, we develop an asynchronous, distributed implementation of the algorithm which has computational advantages over existing synchronous implementations of the algorithm. Improvements to both the synchronous and asynchronous algorithm are proposed. We also test the results on well known stochastic 0-1 programs from the SIPLIB test library and is able to solve one previously unsolved instance from the test set.

Frequency-Dependent Rupture Processes for the 2011 Tohoku Earthquake

NASA Astrophysics Data System (ADS)

Miyake, H.

2012-12-01

The 2011 Tohoku earthquake is characterized by frequency-dependent rupture process [e.g., Ide et al., 2011; Wang and Mori, 2011; Yao et al., 2011]. For understanding rupture dynamics of this earthquake, it is extremely important to investigate wave-based source inversions for various frequency bands. The above frequency-dependent characteristics have been derived from teleseismic analyses. This study challenges to infer frequency-dependent rupture processes from strong motion waveforms of K-NET and KiK-net stations. The observations suggested three or more S-wave phases, and ground velocities at several near-source stations showed different arrivals of their long- and short-period components. We performed complex source spectral inversions with frequency-dependent phase weighting developed by Miyake et al. [2002]. The technique idealizes both the coherent and stochastic summation of waveforms using empirical Green's functions. Due to the limitation of signal-to-noise ratio of the empirical Green's functions, the analyzed frequency bands were set within 0.05-10 Hz. We assumed a fault plane with 480 km in length by 180 km in width with a single time window for rupture following Koketsu et al. [2011] and Asano and Iwata [2012]. The inversion revealed source ruptures expanding from the hypocenter, and generated sharp slip-velocity intensities at the down-dip edge. In addition to test the effects of empirical/hybrid Green's functions and with/without rupture front constraints on the inverted solutions, we will discuss distributions of slip-velocity intensity and a progression of wave generation with increasing frequency.

Changes in Arctic Sea Ice Floe Size Distribution in the Marginal Ice Zone in a Thickness and Floe Size Distribution Model

NASA Astrophysics Data System (ADS)

Zhang, J.; Stern, H. L., III; Hwang, P. B.; Schweiger, A. J. B.; Stark, M.; Steele, M.

2015-12-01

To better describe the state of sea ice in the marginal ice zone (MIZ) with floes of varying thicknesses and sizes, both an ice thickness distribution (ITD) and a floe size distribution (FSD) are needed. We have developed a FSD theory [Zhang et al., 2015] that is coupled to the ITD theory of Thorndike et al. [1975] in order to explicitly simulate the evolution of FSD and ITD jointly. The FSD theory includes a FSD function and a FSD conservation equation in parallel with the ITD equation. The FSD equation takes into account changes in FSD due to ice advection, thermodynamic growth, and lateral melting. It also includes changes in FSD because of mechanical redistribution of floe size due to ice opening, ridging and, particularly, ice fragmentation induced by stochastic ocean surface waves. The floe size redistribution due to ice fragmentation is based on the assumption that wave-induced breakup is a random process such that when an ice floe is broken, floes of any smaller sizes have an equal opportunity to form, without being either favored or excluded. It is also based on the assumption that floes of larger sizes are easier to break because they are subject to larger flexure-induced stresses and strains than smaller floes that are easier to ride with waves with little bending; larger floes also have higher areal coverages and therefore higher probabilities to break. These assumptions with corresponding formulations ensure that the simulated FSD follows a power law as observed by satellites and airborne surveys. The FSD theory has been tested in the Pan-arctic Ice/Ocean Modeling and Assimilation System (PIOMAS). The existing PIOMAS has 12 categories each for ice thickness, ice enthalpy, and snow depth. With the implementation of the FSD theory, PIOMAS is able to represent 12 categories of floe sizes ranging from 0.1 m to ~3000 m. It is found that the simulated 12-category FSD agrees reasonably well with FSD derived from SAR and MODIS images. In this study, we will examine PIOMAS-estimated variability and changes in Arctic FSD over the period 1979-present. Thorndike, A. S., D. A. Rothrock, G. A. Maykut, and R. Colony, The thickness distribution of sea ice. J. Geophys. Res., 80, 1975. Zhang, J., A. Schweiger, M. Steele, and H. Stern, Sea ice floe size distribution in the marginal ice zone: Theory and numerical experiments, J. Geophys. Res., 120, 2015.

Can power-law scaling and neuronal avalanches arise from stochastic dynamics?

PubMed

Touboul, Jonathan; Destexhe, Alain

2010-02-11

The presence of self-organized criticality in biology is often evidenced by a power-law scaling of event size distributions, which can be measured by linear regression on logarithmic axes. We show here that such a procedure does not necessarily mean that the system exhibits self-organized criticality. We first provide an analysis of multisite local field potential (LFP) recordings of brain activity and show that event size distributions defined as negative LFP peaks can be close to power-law distributions. However, this result is not robust to change in detection threshold, or when tested using more rigorous statistical analyses such as the Kolmogorov-Smirnov test. Similar power-law scaling is observed for surrogate signals, suggesting that power-law scaling may be a generic property of thresholded stochastic processes. We next investigate this problem analytically, and show that, indeed, stochastic processes can produce spurious power-law scaling without the presence of underlying self-organized criticality. However, this power-law is only apparent in logarithmic representations, and does not survive more rigorous analysis such as the Kolmogorov-Smirnov test. The same analysis was also performed on an artificial network known to display self-organized criticality. In this case, both the graphical representations and the rigorous statistical analysis reveal with no ambiguity that the avalanche size is distributed as a power-law. We conclude that logarithmic representations can lead to spurious power-law scaling induced by the stochastic nature of the phenomenon. This apparent power-law scaling does not constitute a proof of self-organized criticality, which should be demonstrated by more stringent statistical tests.

Population density approach for discrete mRNA distributions in generalized switching models for stochastic gene expression.

PubMed

Stinchcombe, Adam R; Peskin, Charles S; Tranchina, Daniel

2012-06-01

We present a generalization of a population density approach for modeling and analysis of stochastic gene expression. In the model, the gene of interest fluctuates stochastically between an inactive state, in which transcription cannot occur, and an active state, in which discrete transcription events occur; and the individual mRNA molecules are degraded stochastically in an independent manner. This sort of model in simplest form with exponential dwell times has been used to explain experimental estimates of the discrete distribution of random mRNA copy number. In our generalization, the random dwell times in the inactive and active states, T_{0} and T_{1}, respectively, are independent random variables drawn from any specified distributions. Consequently, the probability per unit time of switching out of a state depends on the time since entering that state. Our method exploits a connection between the fully discrete random process and a related continuous process. We present numerical methods for computing steady-state mRNA distributions and an analytical derivation of the mRNA autocovariance function. We find that empirical estimates of the steady-state mRNA probability mass function from Monte Carlo simulations of laboratory data do not allow one to distinguish between underlying models with exponential and nonexponential dwell times in some relevant parameter regimes. However, in these parameter regimes and where the autocovariance function has negative lobes, the autocovariance function disambiguates the two types of models. Our results strongly suggest that temporal data beyond the autocovariance function is required in general to characterize gene switching.

The Nonstationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation

PubMed Central

Martin, Guillaume; Roques, Lionel

2016-01-01

Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher’s geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a “phase transition” with mutation rate. Beyond this phase transition, in Fisher’s geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies. PMID:27770037

Stochastic Representations of Seismic Anisotropy: Verification of Effective Media Models and Application to the Continental Crust

NASA Astrophysics Data System (ADS)

Song, X.; Jordan, T. H.

2017-12-01

The seismic anisotropy of the continental crust is dominated by two mechanisms: the local (intrinsic) anisotropy of crustal rocks caused by the lattice-preferred orientation of their constituent minerals, and the geometric (extrinsic) anisotropy caused by the alignment and layering of elastic heterogeneities by sedimentation and deformation. To assess the relative importance of these mechanisms, we have applied Jordan's (GJI, 2015) self-consistent, second-order theory to compute the effective elastic parameters of stochastic media with hexagonal local anisotropy and small-scale 3D heterogeneities that have transversely isotropic (TI) statistics. The theory pertains to stochastic TI media in which the eighth-order covariance tensor of the elastic moduli can be separated into a one-point variance tensor that describes the local anisotropy in terms of a anisotropy orientation ratio (ξ from 0 to ∞), and a two-point correlation function that describes the geometric anisotropy in terms of a heterogeneity aspect ratio (η from 0 to ∞). If there is no local anisotropy, then, in the limiting case of a horizontal stochastic laminate (η→∞), the effective-medium equations reduce to the second-order equations derived by Backus (1962) for a stochastically layered medium. This generalization of the Backus equations to 3D stochastic media, as well as the introduction of local, stochastically rotated anisotropy, provides a powerful theory for interpreting the anisotropic signatures of sedimentation and deformation in continental environments; in particular, the parameterizations that we propose are suitable for tomographic inversions. We have verified this theory through a series high-resolution numerical experiments using both isotropic and anisotropic wave-propagation codes.

Geophysical Model Research and Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasyanos, M; Walter, W; Tkalcic, H

2004-07-07

Geophysical models constitute an important component of calibration for nuclear explosion monitoring. We will focus on four major topics: (1) a priori geophysical models, (2) surface wave models, (3) receiver function derived profiles, and (4) stochastic geophysical models. The first, a priori models, can be used to predict a host of geophysical measurements, such as body wave travel times, and can be derived from direct regional studies or even by geophysical analogy. Use of these models is particularly important in aseismic regions or regions without seismic stations, where data of direct measurements might not exist. Lawrence Livermore National Laboratory (LLNL)more » has developed the Western Eurasia and North Africa (WENA) model which has been evaluated using a number of data sets, including travel times, surface waves, receiver functions, and waveform analysis (Pasyanos et al., 2004). We have joined this model with our Yellow Sea - Korean Peninsula (YSKP) model and the Los Alamos National Laboratory (LANL) East Asia model to construct a model for all of Eurasia and North Africa. Secondly, we continue to improve upon our surface wave model by adding more paths. This has allowed us to expand the region to all of Eurasia and into Africa, increase the resolution of our model, and extend results to even shorter periods (7 sec). High-resolution models exist for the Middle East and the YSKP region. The surface wave results can be inverted either alone, or in conjunction with other data, to derive models of the crust and upper mantle structure. We are also using receiver functions, in joint inversions with the surface waves, to produce profiles directly under seismic stations throughout the region. In a collaborative project with Ammon, et al., they have been focusing on stations throughout western Eurasia and North Africa, while we have been focusing on LLNL deployments in the Middle East, including Kuwait, Jordan, and the United Arab Emirates. Finally, we have been exploring methodologies such as Markov Chain Monte Carlo (MCMC) to generate data-driven stochastic models. We have applied this technique to the YSKP region using surface wave dispersion data, body wave travel time data, and receiver functions.« less

Stochastic dynamic modeling of regular and slow earthquakes

NASA Astrophysics Data System (ADS)

Aso, N.; Ando, R.; Ide, S.

2017-12-01

Both regular and slow earthquakes are slip phenomena on plate boundaries and are simulated by a (quasi-)dynamic modeling [Liu and Rice, 2005]. In these numerical simulations, spatial heterogeneity is usually considered not only for explaining real physical properties but also for evaluating the stability of the calculations or the sensitivity of the results on the condition. However, even though we discretize the model space with small grids, heterogeneity at smaller scales than the grid size is not considered in the models with deterministic governing equations. To evaluate the effect of heterogeneity at the smaller scales we need to consider stochastic interactions between slip and stress in a dynamic modeling. Tidal stress is known to trigger or affect both regular and slow earthquakes [Yabe et al., 2015; Ide et al., 2016], and such an external force with fluctuation can also be considered as a stochastic external force. A healing process of faults may also be stochastic, so we introduce stochastic friction law. In the present study, we propose a stochastic dynamic model to explain both regular and slow earthquakes. We solve mode III problem, which corresponds to the rupture propagation along the strike direction. We use BIEM (boundary integral equation method) scheme to simulate slip evolution, but we add stochastic perturbations in the governing equations, which is usually written in a deterministic manner. As the simplest type of perturbations, we adopt Gaussian deviations in the formulation of the slip-stress kernel, external force, and friction. By increasing the amplitude of perturbations of the slip-stress kernel, we reproduce complicated rupture process of regular earthquakes including unilateral and bilateral ruptures. By perturbing external force, we reproduce slow rupture propagation at a scale of km/day. The slow propagation generated by a combination of fast interaction at S-wave velocity is analogous to the kinetic theory of gasses: thermal diffusion appears much slower than the particle velocity of each molecule. The concept of stochastic triggering originates in the Brownian walk model [Ide, 2008], and the present study introduces the stochastic dynamics into dynamic simulations. The stochastic dynamic model has the potential to explain both regular and slow earthquakes more realistically.

Green function of the double-fractional Fokker-Planck equation: path integral and stochastic differential equations.

PubMed

Kleinert, H; Zatloukal, V

2013-11-01

The statistics of rare events, the so-called black-swan events, is governed by non-Gaussian distributions with heavy power-like tails. We calculate the Green functions of the associated Fokker-Planck equations and solve the related stochastic differential equations. We also discuss the subject in the framework of path integration.

Stability of a three-species stochastic delay predator-prey system with Lévy noise

NASA Astrophysics Data System (ADS)

Wu, Jian

2018-07-01

This work is concerned with a three-species stochastic delay prey-mesopredator-superpredator system with Lévy noise. We will characterize the complete dynamic scenarios of stability in distribution of solution (SDS) by three parameters κ1 ,κ2 ,κ3 which depend on the interaction and Lévy noise.

Relative Roles of Deterministic and Stochastic Processes in Driving the Vertical Distribution of Bacterial Communities in a Permafrost Core from the Qinghai-Tibet Plateau, China.

PubMed

Hu, Weigang; Zhang, Qi; Tian, Tian; Li, Dingyao; Cheng, Gang; Mu, Jing; Wu, Qingbai; Niu, Fujun; Stegen, James C; An, Lizhe; Feng, Huyuan

2015-01-01

Understanding the processes that influence the structure of biotic communities is one of the major ecological topics, and both stochastic and deterministic processes are expected to be at work simultaneously in most communities. Here, we investigated the vertical distribution patterns of bacterial communities in a 10-m-long soil core taken within permafrost of the Qinghai-Tibet Plateau. To get a better understanding of the forces that govern these patterns, we examined the diversity and structure of bacterial communities, and the change in community composition along the vertical distance (spatial turnover) from both taxonomic and phylogenetic perspectives. Measures of taxonomic and phylogenetic beta diversity revealed that bacterial community composition changed continuously along the soil core, and showed a vertical distance-decay relationship. Multiple stepwise regression analysis suggested that bacterial alpha diversity and phylogenetic structure were strongly correlated with soil conductivity and pH but weakly correlated with depth. There was evidence that deterministic and stochastic processes collectively drived bacterial vertically-structured pattern. Bacterial communities in five soil horizons (two originated from the active layer and three from permafrost) of the permafrost core were phylogenetically random, indicator of stochastic processes. However, we found a stronger effect of deterministic processes related to soil pH, conductivity, and organic carbon content that were structuring the bacterial communities. We therefore conclude that the vertical distribution of bacterial communities was governed primarily by deterministic ecological selection, although stochastic processes were also at work. Furthermore, the strong impact of environmental conditions (for example, soil physicochemical parameters and seasonal freeze-thaw cycles) on these communities underlines the sensitivity of permafrost microorganisms to climate change and potentially subsequent permafrost thaw.

Relative Roles of Deterministic and Stochastic Processes in Driving the Vertical Distribution of Bacterial Communities in a Permafrost Core from the Qinghai-Tibet Plateau, China

PubMed Central

Tian, Tian; Li, Dingyao; Cheng, Gang; Mu, Jing; Wu, Qingbai; Niu, Fujun; Stegen, James C.; An, Lizhe; Feng, Huyuan

2015-01-01

Understanding the processes that influence the structure of biotic communities is one of the major ecological topics, and both stochastic and deterministic processes are expected to be at work simultaneously in most communities. Here, we investigated the vertical distribution patterns of bacterial communities in a 10-m-long soil core taken within permafrost of the Qinghai-Tibet Plateau. To get a better understanding of the forces that govern these patterns, we examined the diversity and structure of bacterial communities, and the change in community composition along the vertical distance (spatial turnover) from both taxonomic and phylogenetic perspectives. Measures of taxonomic and phylogenetic beta diversity revealed that bacterial community composition changed continuously along the soil core, and showed a vertical distance-decay relationship. Multiple stepwise regression analysis suggested that bacterial alpha diversity and phylogenetic structure were strongly correlated with soil conductivity and pH but weakly correlated with depth. There was evidence that deterministic and stochastic processes collectively drived bacterial vertically-structured pattern. Bacterial communities in five soil horizons (two originated from the active layer and three from permafrost) of the permafrost core were phylogenetically random, indicator of stochastic processes. However, we found a stronger effect of deterministic processes related to soil pH, conductivity, and organic carbon content that were structuring the bacterial communities. We therefore conclude that the vertical distribution of bacterial communities was governed primarily by deterministic ecological selection, although stochastic processes were also at work. Furthermore, the strong impact of environmental conditions (for example, soil physicochemical parameters and seasonal freeze-thaw cycles) on these communities underlines the sensitivity of permafrost microorganisms to climate change and potentially subsequent permafrost thaw. PMID:26699734

Assessment of system reliability for a stochastic-flow distribution network with the spoilage property

NASA Astrophysics Data System (ADS)

Lin, Yi-Kuei; Huang, Cheng-Fu; Yeh, Cheng-Ta

2016-04-01

In supply chain management, satisfying customer demand is the most concerned for the manager. However, the goods may rot or be spoilt during delivery owing to natural disasters, inclement weather, traffic accidents, collisions, and so on, such that the intact goods may not meet market demand. This paper concentrates on a stochastic-flow distribution network (SFDN), in which a node denotes a supplier, a transfer station, or a market, while a route denotes a carrier providing the delivery service for a pair of nodes. The available capacity of the carrier is stochastic because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the system reliability, the probability that the SFDN can satisfy the market demand with the spoilage rate under the budget constraint from multiple suppliers to the customer. An algorithm is developed in terms of minimal paths to evaluate the system reliability along with a numerical example to illustrate the solution procedure. A practical case of fruit distribution is presented accordingly to emphasise the management implication of the system reliability.

Stochastic dosimetry model for radon progeny in the rat lung.

PubMed

Winkler-HeiI, R; Hofmann, W; Hussain, M

2014-07-01

The stochastic dosimetry model presented here considers the distinctly asymmetric, stochastic branching pattern reported in morphometric measurements. This monopodial structure suggests that an airway diameter is a more appropriate morphometric parameter to classify bronchial dose distributions for inhaled radon progeny than the commonly assigned airway generation numbers. Bronchial doses were calculated for the typical exposure conditions reported for the Pacific Northwest National Laboratory rat inhalation studies, yielding an average bronchial dose of 7.75 mGy WLM(-1). If plotted as functions of airway generations, the resulting dose distributions are highest in the central bronchial airways, while significantly decreasing towards peripheral generations. However, if plotted as functions of airway diameters, doses are much more uniformly distributed among bronchial airways. The comparison between rat and human lungs indicates that dose conversion coefficients for the rat lung are higher than the corresponding values for the human lung by a factor of 1.34 for the experimental PNNL exposure conditions, and of 1.25 for typical human indoor conditions. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Discrete and broadband electron acceleration in Jupiter's powerful aurora.

PubMed

Mauk, B H; Haggerty, D K; Paranicas, C; Clark, G; Kollmann, P; Rymer, A M; Bolton, S J; Levin, S M; Adriani, A; Allegrini, F; Bagenal, F; Bonfond, B; Connerney, J E P; Gladstone, G R; Kurth, W S; McComas, D J; Valek, P

2017-09-06

The most intense auroral emissions from Earth's polar regions, called discrete for their sharply defined spatial configurations, are generated by a process involving coherent acceleration of electrons by slowly evolving, powerful electric fields directed along the magnetic field lines that connect Earth's space environment to its polar regions. In contrast, Earth's less intense auroras are generally caused by wave scattering of magnetically trapped populations of hot electrons (in the case of diffuse aurora) or by the turbulent or stochastic downward acceleration of electrons along magnetic field lines by waves during transitory periods (in the case of broadband or Alfvénic aurora). Jupiter's relatively steady main aurora has a power density that is so much larger than Earth's that it has been taken for granted that it must be generated primarily by the discrete auroral process. However, preliminary in situ measurements of Jupiter's auroral regions yielded no evidence of such a process. Here we report observations of distinct, high-energy, downward, discrete electron acceleration in Jupiter's auroral polar regions. We also infer upward magnetic-field-aligned electric potentials of up to 400 kiloelectronvolts, an order of magnitude larger than the largest potentials observed at Earth. Despite the magnitude of these upward electric potentials and the expectations from observations at Earth, the downward energy flux from discrete acceleration is less at Jupiter than that caused by broadband or stochastic processes, with broadband and stochastic characteristics that are substantially different from those at Earth.

Mediterranean space-time extremes of wind wave sea states

NASA Astrophysics Data System (ADS)

Barbariol, Francesco; Carniel, Sandro; Sclavo, Mauro; Marcello Falcieri, Francesco; Bonaldo, Davide; Bergamasco, Andrea; Benetazzo, Alvise

2014-05-01

Traditionally, wind wave sea states during storms have been observed, modeled, and predicted mostly in the time domain, i.e. at a fixed point. In fact, the standard statistical models used in ocean waves analysis rely on the implicit assumption of long-crested waves. Nevertheless, waves in storms are mainly short-crested. Hence, spatio-temporal features of the wave field are crucial to accurately model the sea state characteristics and to provide reliable predictions, particurly of wave extremes. Indeed, the experimental evidence provided by novel instrumentations, e.g. WASS (Wave Acquisition Stereo System), showed that the maximum sea surface elevation gathered in time over an area, i.e. the space-time extreme, is larger than that one measured in time at a point, i.e. the time extreme. Recently, stochastic models used to estimate maxima of multidimensional Gaussian random fields have been applied to ocean waves statistics. These models are based either on Piterbarg's theorem or Adler and Taylor's Euler Characteristics approach. Besides a probability of exceedance of a certain threshold, they can provide the expected space-time extreme of a sea state, as long as space-time wave features (i.e. some parameters of the directional variance density spectrum) are known. These models have been recently validated against WASS observation from fixed and moving platforms. In this context, our focus was modeling and predicting extremes of wind waves during storms. Thus, to intensively gather space-time extremes data over the Mediterranean region, we used directional spectra provided by the numerical wave model SWAN (Simulating WAves Nearshore). Therefore, we set up a 6x6 km2 resolution grid entailing most of the Mediterranean Sea and we forced it with COSMO-I7 high resolution (7x7 km2) hourly wind fields, within 2007-2013 period. To obtain the space-time features, i.e. the spectral parameters, at each grid node and over the 6 simulated years, we developed a modified version of the SWAN model, the SWAN Space-Time (SWAN-ST). SWAN-ST results were post-processed to obtain the expected space-time extremes over the model domain. To this end, we applied the stochastic model of Fedele, developed starting from Adler and Taylor's approach, which we found to be more accurate and versatile with respect to Piterbarg's theorem. Results we obtained provide an alternative sight on Mediterranean extreme wave climate, which could represent the first step towards operationl forecasting of space-time wave extremes, on the one hand, and the basis for a novel statistical standard wave model, on the other. These results may benefit marine designers, seafarers and other subjects operating at sea and exposed to the frequent and severe hazard represented by extreme wave conditions.

A scaling law for random walks on networks

PubMed Central

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-01-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics. PMID:25311870

A scaling law for random walks on networks

NASA Astrophysics Data System (ADS)

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

A scaling law for random walks on networks.

PubMed

Perkins, Theodore J; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-14

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

Quantum error-correction failure distributions: Comparison of coherent and stochastic error models

NASA Astrophysics Data System (ADS)

Barnes, Jeff P.; Trout, Colin J.; Lucarelli, Dennis; Clader, B. D.

2017-06-01

We compare failure distributions of quantum error correction circuits for stochastic errors and coherent errors. We utilize a fully coherent simulation of a fault-tolerant quantum error correcting circuit for a d =3 Steane and surface code. We find that the output distributions are markedly different for the two error models, showing that no simple mapping between the two error models exists. Coherent errors create very broad and heavy-tailed failure distributions. This suggests that they are susceptible to outlier events and that mean statistics, such as pseudothreshold estimates, may not provide the key figure of merit. This provides further statistical insight into why coherent errors can be so harmful for quantum error correction. These output probability distributions may also provide a useful metric that can be utilized when optimizing quantum error correcting codes and decoding procedures for purely coherent errors.

Improved Stability and Stabilization Results for Stochastic Synchronization of Continuous-Time Semi-Markovian Jump Neural Networks With Time-Varying Delay.

PubMed

Wei, Yanling; Park, Ju H; Karimi, Hamid Reza; Tian, Yu-Chu; Jung, Hoyoul; Yanling Wei; Park, Ju H; Karimi, Hamid Reza; Yu-Chu Tian; Hoyoul Jung; Tian, Yu-Chu; Wei, Yanling; Jung, Hoyoul; Karimi, Hamid Reza; Park, Ju H

2018-06-01

Continuous-time semi-Markovian jump neural networks (semi-MJNNs) are those MJNNs whose transition rates are not constant but depend on the random sojourn time. Addressing stochastic synchronization of semi-MJNNs with time-varying delay, an improved stochastic stability criterion is derived in this paper to guarantee stochastic synchronization of the response systems with the drive systems. This is achieved through constructing a semi-Markovian Lyapunov-Krasovskii functional together as well as making use of a novel integral inequality and the characteristics of cumulative distribution functions. Then, with a linearization procedure, controller synthesis is carried out for stochastic synchronization of the drive-response systems. The desired state-feedback controller gains can be determined by solving a linear matrix inequality-based optimization problem. Simulation studies are carried out to demonstrate the effectiveness and less conservatism of the presented approach.