Mechanisms for the target patterns formation in a stochastic bistable excitable medium

NASA Astrophysics Data System (ADS)

Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

2018-04-01

We study the features of formation and evolution of spatiotemporal chaotic regime generated by autonomous pacemakers in excitable deterministic and stochastic bistable active media using the example of the FitzHugh - Nagumo biological neuron model under discrete medium conditions. The following possible mechanisms for the formation of autonomous pacemakers have been studied: 1) a temporal external force applied to a small region of the medium, 2) geometry of the solution region (the medium contains regions with Dirichlet or Neumann boundaries). In our work we explore the conditions for the emergence of pacemakers inducing target patterns in a stochastic bistable excitable system and propose the algorithm for their analysis.

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning

NASA Astrophysics Data System (ADS)

Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik

2016-07-01

Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning.

PubMed

Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik

2016-07-13

Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.

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.

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.

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.

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.

Stochastic simulation of nucleation in binary alloys

NASA Astrophysics Data System (ADS)

L’vov, P. E.; Svetukhin, V. V.

2018-06-01

In this study, we simulate nucleation in binary alloys with respect to thermal fluctuations of the alloy composition. The simulation is based on the Cahn–Hilliard–Cook equation. We have considered the influence of some fluctuation parameters (wave vector cutoff and noise amplitude) on the kinetics of nucleation and growth of minority phase precipitates. The obtained results are validated by the example of iron–chromium alloys.

The Ising Decision Maker: a binary stochastic network for choice response time.

PubMed

Verdonck, Stijn; Tuerlinckx, Francis

2014-07-01

The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (c) 2014 APA, all rights reserved.

Gray and multigroup radiation transport models for two-dimensional binary stochastic media using effective opacities

DOE PAGES

Olson, Gordon L.

2015-09-24

One-dimensional models for the transport of radiation through binary stochastic media do not work in multi-dimensions. In addition, authors have attempted to modify or extend the 1D models to work in multidimensions without success. Analytic one-dimensional models are successful in 1D only when assuming greatly simplified physics. State of the art theories for stochastic media radiation transport do not address multi-dimensions and temperature-dependent physics coefficients. Here, the concept of effective opacities and effective heat capacities is found to well represent the ensemble averaged transport solutions in cases with gray or multigroup temperature-dependent opacities and constant or temperature-dependent heat capacities. Inmore » every case analyzed here, effective physics coefficients fit the transport solutions over a useful range of parameter space. The transport equation is solved with the spherical harmonics method with angle orders of n=1 and 5. Although the details depend on what order of solution is used, the general results are similar, independent of angular order.« 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.

Gray and multigroup radiation transport models for two-dimensional binary stochastic media using effective opacities

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

Olson, Gordon L.

One-dimensional models for the transport of radiation through binary stochastic media do not work in multi-dimensions. In addition, authors have attempted to modify or extend the 1D models to work in multidimensions without success. Analytic one-dimensional models are successful in 1D only when assuming greatly simplified physics. State of the art theories for stochastic media radiation transport do not address multi-dimensions and temperature-dependent physics coefficients. Here, the concept of effective opacities and effective heat capacities is found to well represent the ensemble averaged transport solutions in cases with gray or multigroup temperature-dependent opacities and constant or temperature-dependent heat capacities. Inmore » every case analyzed here, effective physics coefficients fit the transport solutions over a useful range of parameter space. The transport equation is solved with the spherical harmonics method with angle orders of n=1 and 5. Although the details depend on what order of solution is used, the general results are similar, independent of angular order.« less

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.

Reliable binary cell-fate decisions based on oscillations

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2014-02-01

Biological systems have often to perform binary decisions under highly dynamic and noisy environments, such as during cell-fate determination. These decisions can be implemented by two main bifurcation mechanisms based on the transitions from either monostability or oscillation to bistability. We compare these two mechanisms by using stochastic models with time-varying fields and by establishing asymptotic formulas for the choice probabilities. Different scaling laws for decision sensitivity with respect to noise strength and signal timescale are obtained, supporting a role for oscillatory dynamics in performing noise-robust and temporally tunable binary decision-making. This result provides a rationale for recent experimental evidences showing that oscillatory expression of proteins often precedes binary cell-fate decisions.

Mixing Single Scattering Properties in Vector Radiative Transfer for Deterministic and Stochastic Solutions

NASA Astrophysics Data System (ADS)

Mukherjee, L.; Zhai, P.; Hu, Y.; Winker, D. M.

2016-12-01

Among the primary factors, which determine the polarized radiation, field of a turbid medium are the single scattering properties of the medium. When multiple types of scatterers are present, the single scattering properties of the scatterers need to be properly mixed in order to find the solutions to the vector radiative transfer theory (VRT). The VRT solvers can be divided into two types: deterministic and stochastic. The deterministic solver can only accept one set of single scattering property in its smallest discretized spatial volume. When the medium contains more than one kind of scatterer, their single scattering properties are averaged, and then used as input for the deterministic solver. The stochastic solver, can work with different kinds of scatterers explicitly. In this work, two different mixing schemes are studied using the Successive Order of Scattering (SOS) method and Monte Carlo (MC) methods. One scheme is used for deterministic and the other is used for the stochastic Monte Carlo method. It is found that the solutions from the two VRT solvers using two different mixing schemes agree with each other extremely well. This confirms the equivalence to the two mixing schemes and also provides a benchmark for the VRT solution for the medium studied.

The Primordial Binary Fraction in Trumpler 14: Frequency and Multiplicity Parameters

NASA Astrophysics Data System (ADS)

Sabbi, Elena

2017-08-01

This is an astrometric proposal designed to identify and characterize the properties of medium- and long-period (orbital periods ranging from 1.8 to 100 years) visual binaries in the mass range between 4 and 20 Mo in the young compact cluster Trumpler 14 in the Carina Nebula. We aim to probe the virtually unexplored population of intermediate- and high-mass binaries that will experience a Roche-lobe overflow during their post-main-sequence evolution. These binaries are of particular interest because they are expected to be the progenitors of supernovae Type Ia, b, and c, X-ray binaries, double neutron stars and double black holes. Multiplicity properties of young stars can be further used to constrain the outcome of the star-formation process and hence distinguish between various formation scenarios. The medium- and long-period binaries (P> 0.5 yr) are hard to detect and expensive to characterize with traditional ground-based spectroscopy. Knowledge of their orbital properties is however crucial to properly estimate the overall fraction of OB stars whose evolution is affected by binary interaction and to predict the outcome of such interaction. Because of the well characterized PSF of WFC3/UVIS and its temporal stability, HST is the only facility able to characterize the properties of OB-type medium-period binaries in Tr14, and Tr14 is the only nearby high-density OB-type young cluster.

Mesh Denoising based on Normal Voting Tensor and Binary Optimization.

PubMed

Yadav, Sunil Kumar; Reitebuch, Ulrich; Polthier, Konrad

2017-08-17

This paper presents a two-stage mesh denoising algorithm. Unlike other traditional averaging approaches, our approach uses an element-based normal voting tensor to compute smooth surfaces. By introducing a binary optimization on the proposed tensor together with a local binary neighborhood concept, our algorithm better retains sharp features and produces smoother umbilical regions than previous approaches. On top of that, we provide a stochastic analysis on the different kinds of noise based on the average edge length. The quantitative results demonstrate that the performance of our method is better compared to state-of-the-art smoothing approaches.

Solution of the finite Milne problem in stochastic media with RVT Technique

NASA Astrophysics Data System (ADS)

Slama, Howida; El-Bedwhey, Nabila A.; El-Depsy, Alia; Selim, Mustafa M.

2017-12-01

This paper presents the solution to the Milne problem in the steady state with isotropic scattering phase function. The properties of the medium are considered as stochastic ones with Gaussian or exponential distributions and hence the problem treated as a stochastic integro-differential equation. To get an explicit form for the radiant energy density, the linear extrapolation distance, reflectivity and transmissivity in the deterministic case the problem is solved using the Pomraning-Eddington method. The obtained solution is found to be dependent on the optical space variable and thickness of the medium which are considered as random variables. The random variable transformation (RVT) technique is used to find the first probability density function (1-PDF) of the solution process. Then the stochastic linear extrapolation distance, reflectivity and transmissivity are calculated. For illustration, numerical results with conclusions are provided.

DNS, LES and Stochastic Modeling of Turbulent Reacting Flows

DTIC Science & Technology

1994-03-01

NY, 1972. 3 [181 Miller , R. S., Frankel, S. H., Madnia, C. K., and Givi, P., Johnson-Edgeworth Trans- lation for Probability Modeling of Binary Mixing...Givi, " Modeling of Isotropic are also grateful to Richard Miller for many useful discussions. This Reacting Turbulence by a Hybrid Mapping-EDQNM...United State of America * Johnson-Edgeworth Translation for Probability Modeling of Binary Scalar Mixing in Turbulent Flows I R. S. MILLER , S. H

Reconstruction of pulse noisy images via stochastic resonance

PubMed Central

Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

2015-01-01

We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911

Implementing transmission eigenchannels of disordered media by a binary-control digital micromirror device

NASA Astrophysics Data System (ADS)

Kim, Donggyu; Choi, Wonjun; Kim, Moonseok; Moon, Jungho; Seo, Keumyoung; Ju, Sanghyun; Choi, Wonshik

2014-11-01

We report a method for measuring the transmission matrix of a disordered medium using a binary-control of a digital micromirror device (DMD). With knowledge of the measured transmission matrix, we identified the transmission eigenchannels of the medium. We then used binary control of the DMD to shape the wavefront of incident waves and to experimentally couple light to individual eigenchannels. When the wave was coupled to the eigenchannel with the largest eigenvalue, in particular, we were able to achieve about two times more energy transmission than the mean transmittance of the medium. Our study provides an elaborated use of the DMD as a high-speed wavefront shaping device for controlling the multiple scattering of waves in highly scattering media.

Multi-hazard evacuation route and shelter planning for buildings.

DOT National Transportation Integrated Search

2014-06-01

A bi-level, two-stage, binary stochastic program with equilibrium constraints, and three variants, are presented that : support the planning and design of shelters and exits, along with hallway fortification strategies and associated : evacuation pat...

Stochastic phase segregation on surfaces

PubMed Central

Gera, Prerna

2017-01-01

Phase separation and coarsening is a phenomenon commonly seen in binary physical and chemical systems that occur in nature. Often, thermal fluctuations, modelled as stochastic noise, are present in the system and the phase segregation process occurs on a surface. In this work, the segregation process is modelled via the Cahn–Hilliard–Cook model, which is a fourth-order parabolic stochastic system. Coarsening is analysed on two sample surfaces: a unit sphere and a dumbbell. On both surfaces, a statistical analysis of the growth rate is performed, and the influence of noise level and mobility is also investigated. For the spherical interface, it is also shown that a lognormal distribution fits the growth rate well. PMID:28878994

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 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.

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.

Modeling the binary circumstellar medium of Type IIb/L/n supernova progenitors

NASA Astrophysics Data System (ADS)

Kolb, Christopher; Blondin, John; Borkowski, Kazik; Reynolds, Stephen

2018-01-01

Circumstellar interaction in close binary systems can produce a highly asymmetric environment, particularly for systems with a mass outflow velocity comparable to the binary orbital speed. This asymmetric circumstellar medium (CSM) becomes visible after a supernova explosion, when SN radiation illuminates the gas and when SN ejecta collide with the CSM. We aim to better understand the development of this asymmetric CSM, particularly for binary systems containing a red supergiant progenitor, and to study its impact on supernova morphology. To achieve this, we model the asymmetric wind and subsequent supernova explosion in full 3D hydrodynamics using the shock-capturing hydro code VH-1 on a spherical yin-yang grid. Wind interaction is computed in a frame co-rotating with the binary system, and gas is accelerated using a radiation pressure-driven wind model where optical depth of the radiative force is dependent on azimuthally-averaged gas density. We present characterization of our asymmetric wind density distribution model by fitting a polar-to-equatorial density contrast function to free parameters such as binary separation distance, primary mass loss rate, and binary mass ratio.

Molecular logic behind the three-way stochastic choices that expand butterfly colour vision.

PubMed

Perry, Michael; Kinoshita, Michiyo; Saldi, Giuseppe; Huo, Lucy; Arikawa, Kentaro; Desplan, Claude

2016-07-14

Butterflies rely extensively on colour vision to adapt to the natural world. Most species express a broad range of colour-sensitive Rhodopsin proteins in three types of ommatidia (unit eyes), which are distributed stochastically across the retina. The retinas of Drosophila melanogaster use just two main types, in which fate is controlled by the binary stochastic decision to express the transcription factor Spineless in R7 photoreceptors. We investigated how butterflies instead generate three stochastically distributed ommatidial types, resulting in a more diverse retinal mosaic that provides the basis for additional colour comparisons and an expanded range of colour vision. We show that the Japanese yellow swallowtail (Papilio xuthus, Papilionidae) and the painted lady (Vanessa cardui, Nymphalidae) butterflies have a second R7-like photoreceptor in each ommatidium. Independent stochastic expression of Spineless in each R7-like cell results in expression of a blue-sensitive (Spineless(ON)) or an ultraviolet (UV)-sensitive (Spineless(OFF)) Rhodopsin. In P. xuthus these choices of blue/blue, blue/UV or UV/UV sensitivity in the two R7 cells are coordinated with expression of additional Rhodopsin proteins in the remaining photoreceptors, and together define the three types of ommatidia. Knocking out spineless using CRISPR/Cas9 (refs 5, 6) leads to the loss of the blue-sensitive fate in R7-like cells and transforms retinas into homogeneous fields of UV/UV-type ommatidia, with corresponding changes in other coordinated features of ommatidial type. Hence, the three possible outcomes of Spineless expression define the three ommatidial types in butterflies. This developmental strategy allowed the deployment of an additional red-sensitive Rhodopsin in P. xuthus, allowing for the evolution of expanded colour vision with a greater variety of receptors. This surprisingly simple mechanism that makes use of two binary stochastic decisions coupled with local coordination may prove to be a general means of generating an increased diversity of developmental outcomes.

Random variable transformation for generalized stochastic radiative transfer in finite participating slab media

NASA Astrophysics Data System (ADS)

El-Wakil, S. A.; Sallah, M.; El-Hanbaly, A. M.

2015-10-01

The stochastic radiative transfer problem is studied in a participating planar finite continuously fluctuating medium. The problem is considered for specular- and diffusly-reflecting boundaries with linear anisotropic scattering. Random variable transformation (RVT) technique is used to get the complete average for the solution functions, that are represented by the probability-density function (PDF) of the solution process. In the RVT algorithm, a simple integral transformation to the input stochastic process (the extinction function of the medium) is applied. This linear transformation enables us to rewrite the stochastic transport equations in terms of the optical random variable (x) and the optical random thickness (L). Then the transport equation is solved deterministically to get a closed form for the solution as a function of x and L. So, the solution is used to obtain the PDF of the solution functions applying the RVT technique among the input random variable (L) and the output process (the solution functions). The obtained averages of the solution functions are used to get the complete analytical averages for some interesting physical quantities, namely, reflectivity and transmissivity at the medium boundaries. In terms of the average reflectivity and transmissivity, the average of the partial heat fluxes for the generalized problem with internal source of radiation are obtained and represented graphically.

Origin of the computational hardness for learning with binary synapses.

PubMed

Huang, Haiping; Kabashima, Yoshiyuki

2014-11-01

Through supervised learning in a binary perceptron one is able to classify an extensive number of random patterns by a proper assignment of binary synaptic weights. However, to find such assignments in practice is quite a nontrivial task. The relation between the weight space structure and the algorithmic hardness has not yet been fully understood. To this end, we analytically derive the Franz-Parisi potential for the binary perceptron problem by starting from an equilibrium solution of weights and exploring the weight space structure around it. Our result reveals the geometrical organization of the weight space; the weight space is composed of isolated solutions, rather than clusters of exponentially many close-by solutions. The pointlike clusters far apart from each other in the weight space explain the previously observed glassy behavior of stochastic local search heuristics.

Did ASAS-SN Kill the Supermassive Black Hole Binary Candidate PG1302-102?

NASA Astrophysics Data System (ADS)

Liu, Tingting; Gezari, Suvi; Miller, M. Coleman

2018-05-01

Graham et al. reported a periodically varying quasar and supermassive black hole binary candidate, PG1302-102 (hereafter PG1302), which was discovered in the Catalina Real-time Transient Survey (CRTS). Its combined Lincoln Near-Earth Asteroid Research (LINEAR) and CRTS optical light curve is well fitted to a sinusoid of an observed period of ≈1884 days and well modeled by the relativistic Doppler boosting of the secondary mini-disk. However, the LINEAR+CRTS light curve from MJD ≈52,700 to MJD ≈56,400 covers only ∼2 cycles of periodic variation, which is a short baseline that can be highly susceptible to normal, stochastic quasar variability. In this Letter, we present a reanalysis of PG1302 using the latest light curve from the All-sky Automated Survey for Supernovae (ASAS-SN), which extends the observational baseline to the present day (MJD ≈58,200), and adopting a maximum likelihood method that searches for a periodic component in addition to stochastic quasar variability. When the ASAS-SN data are combined with the previous LINEAR+CRTS data, the evidence for periodicity decreases. For genuine periodicity one would expect that additional data would strengthen the evidence, so the decrease in significance may be an indication that the binary model is disfavored.

Threshold Based Stochastic Resonance for the Binary-Input Ternary-Output Discrete Memoryless Channels

DTIC Science & Technology

2012-05-01

noise (AGN) [1] and [11]. We focus on threshold communication systems due to the underwater environment, noncoherent communication techniques are...the threshold level. In the context of the underwater communications, where noncoherent communication techniques are affected both by noise and

Constraints on the Dynamical Environments of Supermassive Black-Hole Binaries Using Pulsar-Timing Arrays.

PubMed

Taylor, Stephen R; Simon, Joseph; Sampson, Laura

2017-05-05

We introduce a technique for gravitational-wave analysis, where Gaussian process regression is used to emulate the strain spectrum of a stochastic background by training on population-synthesis simulations. This leads to direct Bayesian inference on astrophysical parameters. For pulsar timing arrays specifically, we interpolate over the parameter space of supermassive black-hole binary environments, including three-body stellar scattering, and evolving orbital eccentricity. We illustrate our approach on mock data, and assess the prospects for inference with data similar to the NANOGrav 9-yr data release.

Modeling stochasticity and robustness in gene regulatory networks.

PubMed

Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

2009-06-15

Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Fractional Gaussian noise-enhanced information capacity of a nonlinear neuron model with binary signal input

NASA Astrophysics Data System (ADS)

Gao, Feng-Yin; Kang, Yan-Mei; Chen, Xi; Chen, Guanrong

2018-05-01

This paper reveals the effect of fractional Gaussian noise with Hurst exponent H ∈(1 /2 ,1 ) on the information capacity of a general nonlinear neuron model with binary signal input. The fGn and its corresponding fractional Brownian motion exhibit long-range, strong-dependent increments. It extends standard Brownian motion to many types of fractional processes found in nature, such as the synaptic noise. In the paper, for the subthreshold binary signal, sufficient conditions are given based on the "forbidden interval" theorem to guarantee the occurrence of stochastic resonance, while for the suprathreshold binary signal, the simulated results show that additive fGn with Hurst exponent H ∈(1 /2 ,1 ) could increase the mutual information or bits count. The investigation indicated that the synaptic noise with the characters of long-range dependence and self-similarity might be the driving factor for the efficient encoding and decoding of the nervous system.

Gene regulation and noise reduction by coupling of stochastic processes

NASA Astrophysics Data System (ADS)

Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John

2015-02-01

Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

Gene regulation and noise reduction by coupling of stochastic processes

PubMed Central

Hornos, José Eduardo M.; Reinitz, John

2015-01-01

Here we characterize the low noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the the two gene states depends on protein number. This fact has a very important implication: there exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction. PMID:25768447

Gene regulation and noise reduction by coupling of stochastic processes.

PubMed

Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John

2015-02-01

Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation.

PubMed

Huang, Yong; Tao, Gang

2014-09-01

The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.

A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation

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

Huang, Yong, E-mail: hy@njust.edu.cn, E-mail: taogang@njust.edu.cn; Tao, Gang, E-mail: hy@njust.edu.cn, E-mail: taogang@njust.edu.cn

2014-09-01

The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.

A comparison of two- and three-dimensional stochastic models of regional solute movement

USGS Publications Warehouse

Shapiro, A.M.; Cvetkovic, V.D.

1990-01-01

Recent models of solute movement in porous media that are based on a stochastic description of the porous medium properties have been dedicated primarily to a three-dimensional interpretation of solute movement. In many practical problems, however, it is more convenient and consistent with measuring techniques to consider flow and solute transport as an areal, two-dimensional phenomenon. The physics of solute movement, however, is dependent on the three-dimensional heterogeneity in the formation. A comparison of two- and three-dimensional stochastic interpretations of solute movement in a porous medium having a statistically isotropic hydraulic conductivity field is investigated. To provide an equitable comparison between the two- and three-dimensional analyses, the stochastic properties of the transmissivity are defined in terms of the stochastic properties of the hydraulic conductivity. The variance of the transmissivity is shown to be significantly reduced in comparison to that of the hydraulic conductivity, and the transmissivity is spatially correlated over larger distances. These factors influence the two-dimensional interpretations of solute movement by underestimating the longitudinal and transverse growth of the solute plume in comparison to its description as a three-dimensional phenomenon. Although this analysis is based on small perturbation approximations and the special case of a statistically isotropic hydraulic conductivity field, it casts doubt on the use of a stochastic interpretation of the transmissivity in describing regional scale movement. However, by assuming the transmissivity to be the vertical integration of the hydraulic conductivity field at a given position, the stochastic properties of the hydraulic conductivity can be estimated from the stochastic properties of the transmissivity and applied to obtain a more accurate interpretation of solute movement. ?? 1990 Kluwer Academic Publishers.

Stationary and oscillatory convection of binary fluids in a porous medium.

PubMed

Augustin, M; Umla, R; Huke, B; Lücke, M

2010-11-01

We investigate numerically stationary convection and traveling wave structures of binary fluid mixtures with negative separation ratio in the Rayleigh-Bénard system filled with a porous medium. The bifurcation behavior of these roll structures is elucidated as well as the properties of the velocity, temperature, and concentration fields. Moreover, we discuss lateral averaged currents of temperature and concentration. Finally, we investigate the influence of the Lewis number, of the separation ratio, and of the normalized porosity on the bifurcation branches.

Development of a Single-Pass Amplifier for an Optical Stochastic Cooling Proof-of-Principle Experiment at Fermilab's IOTA Facility

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

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

2015-06-01

Optical stochastic cooling (OSC) is a method of beam cooling which is expected to provide cooling rates orders of magnitude larger than ordinary stochastic cooling. Light from an undulator (the pickup) is amplified and fed back onto the particle beam via another undulator (the kicker). Fermilab is currently exploring a possible proof-of-principle experiment of the OSC at the integrable-optics test accelerator (IOTA) ring. To implement effective OSC a good correction of phase distortions in the entire band of the optical amplifier is required. In this contribution we present progress in experimental characterization of phase distortions associated to a Titanium Sapphiremore » crystal laser-gain medium (a possible candidate gain medium for the OSC experiment to be performed at IOTA). We also discuss a possible option for a mid-IR amplifier« less

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.

Bayesian Hierarchical Classes Analysis

ERIC Educational Resources Information Center

Leenen, Iwin; Van Mechelen, Iven; Gelman, Andrew; De Knop, Stijn

2008-01-01

Hierarchical classes models are models for "N"-way "N"-mode data that represent the association among the "N" modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original…

Optical Variability Signatures from Massive Black Hole Binaries

NASA Astrophysics Data System (ADS)

Kasliwal, Vishal P.; Frank, Koby Alexander; Lidz, Adam

2017-01-01

The hierarchical merging of dark matter halos and their associated galaxies should lead to a population of supermassive black hole binaries (MBHBs). We consider plausible optical variability signatures from MBHBs at sub-parsec separations and search for these using data from the Catalina Real-Time Transient Survey (CRTS). Specifically, we model the impact of relativistic Doppler beaming on the accretion disk emission from the less massive, secondary black hole. We explore whether this Doppler modulation may be separated from other sources of stochastic variability in the accretion flow around the MBHBs, which we describe as a damped random walk (DRW). In the simple case of a circular orbit, relativistic beaming leads to a series of broad peaks — located at multiples of the orbital frequency — in the fluctuation power spectrum. We extend our analysis to the case of elliptical orbits and discuss the effect of beaming on the flux power spectrum and auto-correlation function using simulations. We present a code to model an observed light curve as a stochastic DRW-type time series modulated by relativistic beaming and apply the code to CRTS data.

Limits on Anisotropy in the Nanohertz Stochastic Gravitational Wave Background.

PubMed

Taylor, S R; Mingarelli, C M F; Gair, J R; Sesana, A; Theureau, G; Babak, S; Bassa, C G; Brem, P; Burgay, M; Caballero, R N; Champion, D J; Cognard, I; Desvignes, G; Guillemot, L; Hessels, J W T; Janssen, G H; Karuppusamy, R; Kramer, M; Lassus, A; Lazarus, P; Lentati, L; Liu, K; Osłowski, S; Perrodin, D; Petiteau, A; Possenti, A; Purver, M B; Rosado, P A; Sanidas, S A; Smits, R; Stappers, B; Tiburzi, C; van Haasteren, R; Vecchio, A; Verbiest, J P W

2015-07-24

The paucity of observed supermassive black hole binaries (SMBHBs) may imply that the gravitational wave background (GWB) from this population is anisotropic, rendering existing analyses suboptimal. We present the first constraints on the angular distribution of a nanohertz stochastic GWB from circular, inspiral-driven SMBHBs using the 2015 European Pulsar Timing Array data. Our analysis of the GWB in the ~2-90 nHz band shows consistency with isotropy, with the strain amplitude in l>0 spherical harmonic multipoles ≲40% of the monopole value. We expect that these more general techniques will become standard tools to probe the angular distribution of source populations.

Limits on Anisotropy in the Nanohertz Stochastic Gravitational Wave Background

NASA Astrophysics Data System (ADS)

Taylor, S. R.; Mingarelli, C. M. F.; Gair, J. R.; Sesana, A.; Theureau, G.; Babak, S.; Bassa, C. G.; Brem, P.; Burgay, M.; Caballero, R. N.; Champion, D. J.; Cognard, I.; Desvignes, G.; Guillemot, L.; Hessels, J. W. T.; Janssen, G. H.; Karuppusamy, R.; Kramer, M.; Lassus, A.; Lazarus, P.; Lentati, L.; Liu, K.; Osłowski, S.; Perrodin, D.; Petiteau, A.; Possenti, A.; Purver, M. B.; Rosado, P. A.; Sanidas, S. A.; Smits, R.; Stappers, B.; Tiburzi, C.; van Haasteren, R.; Vecchio, A.; Verbiest, J. P. W.; EPTA Collaboration

2015-07-01

The paucity of observed supermassive black hole binaries (SMBHBs) may imply that the gravitational wave background (GWB) from this population is anisotropic, rendering existing analyses suboptimal. We present the first constraints on the angular distribution of a nanohertz stochastic GWB from circular, inspiral-driven SMBHBs using the 2015 European Pulsar Timing Array data. Our analysis of the GWB in the ˜2 - 90 nHz band shows consistency with isotropy, with the strain amplitude in l >0 spherical harmonic multipoles ≲40 % of the monopole value. We expect that these more general techniques will become standard tools to probe the angular distribution of source populations.

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.

Shell-binary nanoparticle materials with variable electrical and electro-mechanical properties.

PubMed

Zhang, P; Bousack, H; Dai, Y; Offenhäusser, A; Mayer, D

2018-01-18

Nanoparticle (NP) materials with the capability to adjust their electrical and electro-mechanical properties facilitate applications in strain sensing technology. Traditional NP materials based on single component NPs lack a systematic and effective means of tuning their electrical and electro-mechanical properties. Here, we report on a new type of shell-binary NP material fabricated by self-assembly with either homogeneous or heterogeneous arrangements of NPs. Variable electrical and electro-mechanical properties were obtained for both materials. We show that the electrical and electro-mechanical properties of these shell-binary NP materials are highly tunable and strongly affected by the NP species as well as their corresponding volume fraction ratio. The conductivity and the gauge factor of these shell-binary NP materials can be altered by about five and two orders of magnitude, respectively. These shell-binary NP materials with different arrangements of NPs also demonstrate different volume fraction dependent electro-mechanical properties. The shell-binary NP materials with a heterogeneous arrangement of NPs exhibit a peaking of the sensitivity at medium mixing ratios, which arises from the aggregation induced local strain enhancement. Studies on the electron transport regimes and micro-morphologies of these shell-binary NP materials revealed the different mechanisms accounting for the variable electrical and electro-mechanical properties. A model based on effective medium theory is used to describe the electrical and electro-mechanical properties of such shell-binary nanomaterials and shows an excellent match with experiment data. These shell-binary NP materials possess great potential applications in high-performance strain sensing technology due to their variable electrical and electro-mechanical properties.

SHAPING THE BROWN DWARF DESERT: PREDICTING THE PRIMORDIAL BROWN DWARF BINARY DISTRIBUTIONS FROM TURBULENT FRAGMENTATION

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

Jumper, Peter H.; Fisher, Robert T., E-mail: robert.fisher@umassd.edu

2013-05-20

The formation of brown dwarfs (BDs) poses a key challenge to star formation theory. The observed dearth of nearby ({<=}5 AU) BD companions to solar mass stars, known as the BD desert, as well as the tendency for low-mass binary systems to be more tightly bound than stellar binaries, has been cited as evidence for distinct formation mechanisms for BDs and stars. In this paper, we explore the implications of the minimal hypothesis that BDs in binary systems originate via the same fundamental fragmentation mechanism as stars, within isolated, turbulent giant molecular cloud cores. We demonstrate analytically that the scalingmore » of specific angular momentum with turbulent core mass naturally gives rise to the BD desert, as well as wide BD binary systems. Further, we show that the turbulent core fragmentation model also naturally predicts that very low mass binary and BD/BD systems are more tightly bound than stellar systems. In addition, in order to capture the stochastic variation intrinsic to turbulence, we generate 10{sup 4} model turbulent cores with synthetic turbulent velocity fields to show that the turbulent fragmentation model accommodates a small fraction of binary BDs with wide separations, similar to observations. Indeed, the picture which emerges from the turbulent fragmentation model is that a single fragmentation mechanism may largely shape both stellar and BD binary distributions during formation.« less

A Telescopic Binary Learning Machine for Training Neural Networks.

PubMed

Brunato, Mauro; Battiti, Roberto

2017-03-01

This paper proposes a new algorithm based on multiscale stochastic local search with binary representation for training neural networks [binary learning machine (BLM)]. We study the effects of neighborhood evaluation strategies, the effect of the number of bits per weight and that of the maximum weight range used for mapping binary strings to real values. Following this preliminary investigation, we propose a telescopic multiscale version of local search, where the number of bits is increased in an adaptive manner, leading to a faster search and to local minima of better quality. An analysis related to adapting the number of bits in a dynamic way is presented. The control on the number of bits, which happens in a natural manner in the proposed method, is effective to increase the generalization performance. The learning dynamics are discussed and validated on a highly nonlinear artificial problem and on real-world tasks in many application domains; BLM is finally applied to a problem requiring either feedforward or recurrent architectures for feedback control.

Accreting binary population synthesis and feedback prescriptions

NASA Astrophysics Data System (ADS)

Fragos, Tassos

2016-04-01

Studies of extagalactic X-ray binary populations have shown that the characteristics of these populations depend strongly on the characteristics of the host galaxy's parent stellar population (e.g. star-formation history and metallicity). These dependencies not only make X-ray binaries promising for aiding in the measurement of galaxy properties themselves, but they also have important astrophysical and cosmological implications. For example, due to the relatively young stellar ages and primordial metallicities in the early Universe (z > 3), it is predicted that X-ray binaries were more luminous than today. The more energetic X-ray photons, because of their long mean-free paths, can escape the galaxies where they are produced, and interact at long distances with the intergalactic medium. This could result in a smoother spatial distribution of ionized regions, and more importantly in an overall warmer intergalactic medium. The energetic X-ray photons emitted from X-ray binaries dominate the X-ray radiation field over active galactic nuclei at z > 6 - 8, and hence Χ-ray binary feedback can be a non-negligible contributor to the heating and reionization of the inter-galactic medium in the early universe. The spectral energy distribution shape of the XRB emission does not change significantly with redshift, suggesting that the same XRB subpopulation, namely black-hole XRBs in the high-soft state, dominates the cumulative emission at all times. On the contrary, the normalization of the spectral energy distribution does evolve with redshift. To zeroth order, this evolution is driven by the cosmic star-formation rate evolution. However, the metallicity evolution of the universe and the mean stellar population age are two important factors that affect the X-ray emission from high-mass and low-mass XRBs, respectively. In this talk, I will review recent studies on the potential feedback from accreting binary populations in galactic and cosmological scales. Furthermore, I will discuss which are the next steps towards a more physically realisitc modelling of accreting compact object populations in the early Universe.

Nonlinear Phase Distortion in a Ti:Sapphire Optical Amplifier for Optical Stochastic Cooling

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

Andorf, Matthew; Lebedev, Valeri; Piot, Philippe

2016-06-01

Optical Stochastic Cooling (OSC) has been considered for future high-luminosity colliders as it offers much faster cooling time in comparison to the micro-wave stochastic cooling. The OSC technique relies on collecting and amplifying a broadband optical signal from a pickup undulator and feeding the amplified signal back to the beam. It creates a corrective kick in a kicker undulator. Owing to its superb gain qualities and broadband amplification features, Titanium:Sapphire medium has been considered as a gain medium for the optical amplifier (OA) needed in the OSC*. A limiting factor for any OA used in OSC is the possibility ofmore » nonlinear phase distortions. In this paper we experimentally measure phase distortions by inserting a single-pass OA into one leg of a Mach-Zehnder interferometer. The measurement results are used to estimate the reduction of the corrective kick a particle would receive due to these phase distortions in the kicker undulator.« less

Organic–inorganic binary mixture matrix for comprehensive laser-desorption ionization mass spectrometric analysis and imaging of medium-size molecules including phospholipids, glycerolipids, and oligosaccharides

DOE PAGES

Feenstra, Adam D.; Ames Lab., Ames, IA; O'Neill, Kelly C.; ...

2016-10-13

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a widely adopted, versatile technique, especially in high-throughput analysis and imaging. However, matrix-dependent selectivity of analytes is often a severe limitation. In this work, a mixture of organic 2,5-dihydroxybenzoic acid and inorganic Fe 3O 4 nanoparticles is developed as a binary MALDI matrix to alleviate the well-known issue of triacylglycerol (TG) ion suppression by phosphatidylcholine (PC). In application to lipid standards and maize seed cross-sections, the binary matrix not only dramatically reduced the ion suppression of TG, but also efficiently desorbed and ionized a wide variety of lipids such as cationic PC, anionicmore » phosphatidylethanolamine (PE) and phosphatidylinositol (PI), and neutral digalactosyldiacylglycerol (DGDG). The binary matrix was also very efficient for large polysaccharides, which were not detected by either of the individual matrices. As a result, the usefulness of the binary matrix is demonstrated in MS imaging of maize seed sections, successfully visualizing diverse medium-size molecules and acquiring high-quality MS/MS spectra for these compounds.« less

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Input reconstruction for networked control systems subject to deception attacks and data losses on control signals

NASA Astrophysics Data System (ADS)

Keller, J. Y.; Chabir, K.; Sauter, D.

2016-03-01

State estimation of stochastic discrete-time linear systems subject to unknown inputs or constant biases has been widely studied but no work has been dedicated to the case where a disturbance switches between unknown input and constant bias. We show that such disturbance can affect a networked control system subject to deception attacks and data losses on the control signals transmitted by the controller to the plant. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter recently developed by the authors. Sufficient stochastic stability conditions are established when the arrival binary sequence of data losses follows a Bernoulli random process.

Bayesian model-emulation of stochastic gravitational-wave spectra for probes of the final-parsec problem with pulsar-timing arrays

NASA Astrophysics Data System (ADS)

Taylor, Stephen R.; Simon, Joseph; Sampson, Laura

2017-01-01

The final parsec of supermassive black-hole binary evolution is subject to the complex interplay of stellar loss-cone scattering, circumbinary disk accretion, and gravitational-wave emission, with binary eccentricity affected by all of these. The strain spectrum of gravitational-waves in the pulsar-timing band thus encodes rich information about the binary population's response to these various environmental mechanisms. Current spectral models have heretofore followed basic analytic prescriptions, and attempt to investigate these final-parsec mechanisms in an indirect fashion. Here we describe a new technique to directly probe the environmental properties of supermassive black-hole binaries through "Bayesian model-emulation". We perform black-hole binary population synthesis simulations at a restricted set of environmental parameter combinations, compute the strain spectra from these, then train a Gaussian process to learn the shape of the spectrum at any point in parameter space. We describe this technique, demonstrate its efficacy with a program of simulated datasets, then illustrate its power by directly constraining final-parsec physics in a Bayesian analysis of the NANOGrav 5-year dataset. The technique is fast, flexible, and robust.

Bayesian model-emulation of stochastic gravitational-wave spectra for probes of the final-parsec problem with pulsar-timing arrays

NASA Astrophysics Data System (ADS)

Taylor, Stephen; Simon, Joseph; Sampson, Laura

2017-01-01

The final parsec of supermassive black-hole binary evolution is subject to the complex interplay of stellar loss-cone scattering, circumbinary disk accretion, and gravitational-wave emission, with binary eccentricity affected by all of these. The strain spectrum of gravitational-waves in the pulsar-timing band thus encodes rich information about the binary population's response to these various environmental mechanisms. Current spectral models have heretofore followed basic analytic prescriptions, and attempt to investigate these final-parsec mechanisms in an indirect fashion. Here we describe a new technique to directly probe the environmental properties of supermassive black-hole binaries through ``Bayesian model-emulation''. We perform black-hole binary population synthesis simulations at a restricted set of environmental parameter combinations, compute the strain spectra from these, then train a Gaussian process to learn the shape of spectrum at any point in parameter space. We describe this technique, demonstrate its efficacy with a program of simulated datasets, then illustrate its power by directly constraining final-parsec physics in a Bayesian analysis of the NANOGrav 5-year dataset. The technique is fast, flexible, and robust.

Gravitational waves: search results, data analysis and parameter estimation: Amaldi 10 Parallel session C2.

PubMed

Astone, Pia; Weinstein, Alan; Agathos, Michalis; Bejger, Michał; Christensen, Nelson; Dent, Thomas; Graff, Philip; Klimenko, Sergey; Mazzolo, Giulio; Nishizawa, Atsushi; Robinet, Florent; Schmidt, Patricia; Smith, Rory; Veitch, John; Wade, Madeline; Aoudia, Sofiane; Bose, Sukanta; Calderon Bustillo, Juan; Canizares, Priscilla; Capano, Colin; Clark, James; Colla, Alberto; Cuoco, Elena; Da Silva Costa, Carlos; Dal Canton, Tito; Evangelista, Edgar; Goetz, Evan; Gupta, Anuradha; Hannam, Mark; Keitel, David; Lackey, Benjamin; Logue, Joshua; Mohapatra, Satyanarayan; Piergiovanni, Francesco; Privitera, Stephen; Prix, Reinhard; Pürrer, Michael; Re, Virginia; Serafinelli, Roberto; Wade, Leslie; Wen, Linqing; Wette, Karl; Whelan, John; Palomba, C; Prodi, G

The Amaldi 10 Parallel Session C2 on gravitational wave (GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity.

Capacity improvement using simulation optimization approaches: A case study in the thermotechnology industry

NASA Astrophysics Data System (ADS)

Yelkenci Köse, Simge; Demir, Leyla; Tunalı, Semra; Türsel Eliiyi, Deniz

2015-02-01

In manufacturing systems, optimal buffer allocation has a considerable impact on capacity improvement. This study presents a simulation optimization procedure to solve the buffer allocation problem in a heat exchanger production plant so as to improve the capacity of the system. For optimization, three metaheuristic-based search algorithms, i.e. a binary-genetic algorithm (B-GA), a binary-simulated annealing algorithm (B-SA) and a binary-tabu search algorithm (B-TS), are proposed. These algorithms are integrated with the simulation model of the production line. The simulation model, which captures the stochastic and dynamic nature of the production line, is used as an evaluation function for the proposed metaheuristics. The experimental study with benchmark problem instances from the literature and the real-life problem show that the proposed B-TS algorithm outperforms B-GA and B-SA in terms of solution quality.

Gravitational Waves: Search Results, Data Analysis and Parameter Estimation. Amaldi 10 Parallel Session C2

NASA Technical Reports Server (NTRS)

Astone, Pia; Weinstein, Alan; Agathos, Michalis; Bejger, Michal; Christensen, Nelson; Dent, Thomas; Graff, Philip; Klimenko, Sergey; Mazzolo, Giulio; Nishizawa, Atsushi

2015-01-01

The Amaldi 10 Parallel Session C2 on gravitational wave(GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity.

Stationary Size Distributions of Growing Cells with Binary and Multiple Cell Division

NASA Astrophysics Data System (ADS)

Rading, M. M.; Engel, T. A.; Lipowsky, R.; Valleriani, A.

2011-10-01

Populations of unicellular organisms that grow under constant environmental conditions are considered theoretically. The size distribution of these cells is calculated analytically, both for the usual process of binary division, in which one mother cell produces always two daughter cells, and for the more complex process of multiple division, in which one mother cell can produce 2 n daughter cells with n=1,2,3,… . The latter mode of division is inspired by the unicellular algae Chlamydomonas reinhardtii. The uniform response of the whole population to different environmental conditions is encoded in the individual rates of growth and division of the cells. The analytical treatment of the problem is based on size-dependent rules for cell growth and stochastic transition processes for cell division. The comparison between binary and multiple division shows that these different division processes lead to qualitatively different results for the size distribution and the population growth rates.

Stochastic Background from Coalescences of Neutron Star-Neutron Star Binaries

NASA Astrophysics Data System (ADS)

Regimbau, T.; de Freitas Pacheco, J. A.

2006-05-01

In this work, numerical simulations were used to investigate the gravitational stochastic background produced by coalescences of double neutron star systems occurring up to z~5. The cosmic coalescence rate was derived from Monte Carlo methods using the probability distributions for massive binaries to form and for a coalescence to occur in a given redshift. A truly continuous background is produced by events located only beyond the critical redshift z*=0.23. Events occurring in the redshift interval 0.027

Clustered-dot halftoning with direct binary search.

PubMed

Goyal, Puneet; Gupta, Madhur; Staelin, Carl; Fischer, Mani; Shacham, Omri; Allebach, Jan P

2013-02-01

In this paper, we present a new algorithm for aperiodic clustered-dot halftoning based on direct binary search (DBS). The DBS optimization framework has been modified for designing clustered-dot texture, by using filters with different sizes in the initialization and update steps of the algorithm. Following an intuitive explanation of how the clustered-dot texture results from this modified framework, we derive a closed-form cost metric which, when minimized, equivalently generates stochastic clustered-dot texture. An analysis of the cost metric and its influence on the texture quality is presented, which is followed by a modification to the cost metric to reduce computational cost and to make it more suitable for screen design.

Correction to verdonck and tuerlinckx (2014).

PubMed

2015-01-01

Reports an error in "The Ising Decision Maker: A binary stochastic network for choice response time" by Stijn Verdonck and Francis Tuerlinckx (Psychological Review, 2014[Jul], Vol 121[3], 422-462). An inaccurate assumption in Appendix B (provided in the erratum) led to an oversimplified result in Equation 18 (the diffusion equations associated with the microscopically defined dynamics). The authors sincerely thank Rani Moran for making them aware of the problem. Only the expression of the diffusion coefficient D is incorrect, and should be changed, as indicated in the erratum. Both the cause of the problem and the solution are also explained in the erratum. (The following abstract of the original article appeared in record 2014-31650-006.) The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix models

NASA Astrophysics Data System (ADS)

Almog, Assaf; Garlaschelli, Diego

2014-09-01

The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons, respectively. While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relations between binary and non-binary properties of financial time series. These relations are a novel quantification of the fact that extreme price increments occur more often when most stocks move in the same direction. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices and their mapping to spin models in statistical physics, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to accurately replicate, and mathematically characterize, the observed binary/non-binary relations. We also obtain a phase diagram allowing us to identify, based only on the instantaneous aggregate return of a set of multiple time series, a regime where the so-called ‘market mode’ has an optimal interpretation in terms of collective (endogenous) effects, a regime where it is parsimoniously explained by pure noise, and a regime where it can be regarded as a combination of endogenous and exogenous factors. Our approach allows us to connect spin models, simple stochastic processes, and ensembles of time series inferred from partial information.

RS CVn binaries: Testing the solar-stellar dynamo connection

NASA Technical Reports Server (NTRS)

Dempsey, R.

1995-01-01

We have used the Extreme Ultraviolet Explorer satellite to study the coronal emission from the EUV-bright RS CVn binaries Sigma2 CrB, observed February 10-21, 1994, and II Peg, observed October 1-5, 1993. We present time-resolved and integrated EUV short-, medium-, and long-wavelength spectra for these binaries. Sigma2 CrB shows significant first-order emission features in the long-wavelength region. The coronal emission distributions and electron densities are estimated for those active coronae dominated by high temperature plasma.

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.

Inferring the Composition of Super-Jupiter Mass Companions of Pulsars with Radio Line Spectroscopy

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

Ray, Alak; Loeb, Abraham, E-mail: akr@tifr.res.in, E-mail: aloeb@cfa.harvard.edu

We propose using radio line spectroscopy to detect molecular absorption lines (such as OH at 1.6–1.7 GHz) before and after the total eclipse of black widow and other short orbital period binary pulsars with low-mass companions. The companion in such a binary may be ablated away by energetic particles and high-energy radiation produced by the pulsar wind. The observations will probe the eclipsing wind being ablated by the pulsar and constrain the nature of the companion and its surroundings. Maser emission from the interstellar medium stimulated by a pulsar beam might also be detected from the intrabinary medium. The shortmore » temporal resolution allowed by the millisecond pulsars can probe this medium with the high angular resolution of the pulsar beam.« less

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

Treesearch

Gretchen G. Moisen; Elizabeth A. Freeman; Jock A. Blackard; Tracey S. Frescino; Niklaus E. Zimmermann; Thomas C. Edwards

2006-01-01

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's© See5 and Cubist (for binary and continuous responses,...

Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

PubMed Central

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

PubMed

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

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.

Method for retorting oil shale

DOEpatents

Shang, Jer-Yu; Lui, A.P.

1985-08-16

The recovery of oil from oil shale is provided in a fluidized bed by using a fluidizing medium of a binary mixture of carbon dioxide and 5 steam. The mixture with a steam concentration in the range of about 20 to 75 volume percent steam provides an increase in oil yield over that achievable by using a fluidizing gas of carbon dioxide or steam alone when the mixture contains higher steam concentrations. The operating parameters for the fluidized bed retorted are essentially the same as those utilized with other gaseous fluidizing mediums with the significant gain being in the oil yield recovered which is attributable solely to the use of the binary mixture of carbon dioxide and steam. 2 figs.

[The temperature factor and magnetic noise under the conditions of stochastic resonance of magnetosomes].

PubMed

Bingi, V N; Chernavskiĭ, D S; Rubin, A B

2006-01-01

The influence of magnetic noise on the dynamics of magnetic nanoparticles under the conditions of stochastic resonance is considered. The effect of the magnetic noise is shown to be equivalent to the growth of the effective thermostat temperature for the particles at the permanent actual temperature of the medium. This regularity may be used for testing the hypothesis on the involvement of magnetic nanoparticles in the formation of biological effects of weak magnetic fields.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

PubMed

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

NASA Astrophysics Data System (ADS)

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

No tension between assembly models of super massive black hole binaries and pulsar observations.

PubMed

Middleton, Hannah; Chen, Siyuan; Del Pozzo, Walter; Sesana, Alberto; Vecchio, Alberto

2018-02-08

Pulsar timing arrays are presently the only means to search for the gravitational wave stochastic background from super massive black hole binary populations, considered to be within the grasp of current or near-future observations. The stringent upper limit from the Parkes Pulsar Timing Array has been interpreted as excluding (>90% confidence) the current paradigm of binary assembly through galaxy mergers and hardening via stellar interaction, suggesting evolution is accelerated or stalled. Using Bayesian hierarchical modelling we consider implications of this upper limit for a range of astrophysical scenarios, without invoking stalling, nor more exotic physical processes. All scenarios are fully consistent with the upper limit, but (weak) bounds on population parameters can be inferred. Recent upward revisions of the black hole-galaxy bulge mass relation are disfavoured at 1.6σ against lighter models. Once sensitivity improves by an order of magnitude, a non-detection will disfavour the most optimistic scenarios at 3.9σ.

Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system

PubMed Central

Weisheimer, Antje; Corti, Susanna; Palmer, Tim; Vitart, Frederic

2014-01-01

The finite resolution of general circulation models of the coupled atmosphere–ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere–ocean climate system in operational forecast mode, and the latest seasonal forecasting system—System 4—has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981–2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden–Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid-latitude circulation regimes over the Pacific–North America region. PMID:24842026

Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system.

PubMed

Weisheimer, Antje; Corti, Susanna; Palmer, Tim; Vitart, Frederic

2014-06-28

The finite resolution of general circulation models of the coupled atmosphere-ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere-ocean climate system in operational forecast mode, and the latest seasonal forecasting system--System 4--has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981-2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden-Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid-latitude circulation regimes over the Pacific-North America region.

The effect of stochastic modeling of ionospheric effect on the various lengths of baseline determination

NASA Astrophysics Data System (ADS)

Kwon, J.; Yang, H.

2006-12-01

Although GPS provides continuous and accurate position information, there are still some rooms for improvement of its positional accuracy, especially in the medium and long range baseline determination. In general, in case of more than 50 km baseline length, the effect of ionospheric delay is the one causing the largest degradation in positional accuracy. For example, the ionospheric delay in terms of double differenced mode easily reaches 10 cm with baseline length of 101 km. Therefore, many researchers have been tried to mitigate/reduce the effect using various modeling methods. In this paper, the optimal stochastic modeling of the ionospheric delay in terms of baseline length is presented. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. Here, the ionospheric delay is stochastically modeled by well-known Gaussian, 1st and 3rd order Gauss-Markov process. The parameters required in those models such as correlation distance and time is determined by the least-square adjustment using ionosphere-only observables. Mainly the results and analysis from this study show the effect of stochastic models of the ionospheric delay in terms of the baseline length, models, and parameters used. In the above example with 101 km baseline length, it was found that the positional accuracy with appropriate ionospheric modeling (Gaussian) was about ±2 cm whereas it reaches about ±15 cm with no stochastic modeling. It is expected that the approach in this study contributes to improve positional accuracy, especially in medium and long range baseline determination.

A multi-scaled approach for simulating chemical reaction systems.

PubMed

Burrage, Kevin; Tian, Tianhai; Burrage, Pamela

2004-01-01

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work. Copyright 2004 Elsevier Ltd.

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.

Solidification of a binary alloy: Finite-element, single-domain simulation and new benchmark solutions

NASA Astrophysics Data System (ADS)

Le Bars, Michael; Worster, M. Grae

2006-07-01

A finite-element simulation of binary alloy solidification based on a single-domain formulation is presented and tested. Resolution of phase change is first checked by comparison with the analytical results of Worster [M.G. Worster, Solidification of an alloy from a cooled boundary, J. Fluid Mech. 167 (1986) 481-501] for purely diffusive solidification. Fluid dynamical processes without phase change are then tested by comparison with previous numerical studies of thermal convection in a pure fluid [G. de Vahl Davis, Natural convection of air in a square cavity: a bench mark numerical solution, Int. J. Numer. Meth. Fluids 3 (1983) 249-264; D.A. Mayne, A.S. Usmani, M. Crapper, h-adaptive finite element solution of high Rayleigh number thermally driven cavity problem, Int. J. Numer. Meth. Heat Fluid Flow 10 (2000) 598-615; D.C. Wan, B.S.V. Patnaik, G.W. Wei, A new benchmark quality solution for the buoyancy driven cavity by discrete singular convolution, Numer. Heat Transf. 40 (2001) 199-228], in a porous medium with a constant porosity [G. Lauriat, V. Prasad, Non-darcian effects on natural convection in a vertical porous enclosure, Int. J. Heat Mass Transf. 32 (1989) 2135-2148; P. Nithiarasu, K.N. Seetharamu, T. Sundararajan, Natural convective heat transfer in an enclosure filled with fluid saturated variable porosity medium, Int. J. Heat Mass Transf. 40 (1997) 3955-3967] and in a mixed liquid-porous medium with a spatially variable porosity [P. Nithiarasu, K.N. Seetharamu, T. Sundararajan, Natural convective heat transfer in an enclosure filled with fluid saturated variable porosity medium, Int. J. Heat Mass Transf. 40 (1997) 3955-3967; N. Zabaras, D. Samanta, A stabilized volume-averaging finite element method for flow in porous media and binary alloy solidification processes, Int. J. Numer. Meth. Eng. 60 (2004) 1103-1138]. Finally, new benchmark solutions for simultaneous flow through both fluid and porous domains and for convective solidification processes are presented, based on the similarity solutions in corner-flow geometries recently obtained by Le Bars and Worster [M. Le Bars, M.G. Worster, Interfacial conditions between a pure fluid and a porous medium: implications for binary alloy solidification, J. Fluid Mech. (in press)]. Good agreement is found for all tests, hence validating our physical and numerical methods. More generally, the computations presented here could now be considered as standard and reliable analytical benchmarks for numerical simulations, specifically and independently testing the different processes underlying binary alloy solidification.

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.;

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.