Energy Science and Technology Software Center (ESTSC)
2010-10-20
The "Monte Carlo Benchmark" (MCB) is intended to model the computatiional performance of Monte Carlo algorithms on parallel architectures. It models the solution of a simple heuristic transport equation using a Monte Carlo technique. The MCB employs typical features of Monte Carlo algorithms such as particle creation, particle tracking, tallying particle information, and particle destruction. Particles are also traded among processors using MPI calls.
Energy Science and Technology Software Center (ESTSC)
2006-05-09
The Monte Carlo example programs VARHATOM and DMCATOM are two small, simple FORTRAN programs that illustrate the use of the Monte Carlo Mathematical technique for calculating the ground state energy of the hydrogen atom.
Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry
Bostani, Maryam McMillan, Kyle; Cagnon, Chris H.; McNitt-Gray, Michael F.; Mueller, Jonathon W.; Cody, Dianna D.; DeMarco, John J.
2015-02-15
Purpose: The purpose of this study was to assess the accuracy of a Monte Carlo simulation-based method for estimating radiation dose from multidetector computed tomography (MDCT) by comparing simulated doses in ten patients to in-vivo dose measurements. Methods: MD Anderson Cancer Center Institutional Review Board approved the acquisition of in-vivo rectal dose measurements in a pilot study of ten patients undergoing virtual colonoscopy. The dose measurements were obtained by affixing TLD capsules to the inner lumen of rectal catheters. Voxelized patient models were generated from the MDCT images of the ten patients, and the dose to the TLD for all exposures was estimated using Monte Carlo based simulations. The Monte Carlo simulation results were compared to the in-vivo dose measurements to determine accuracy. Results: The calculated mean percent difference between TLD measurements and Monte Carlo simulations was −4.9% with standard deviation of 8.7% and a range of −22.7% to 5.7%. Conclusions: The results of this study demonstrate very good agreement between simulated and measured doses in-vivo. Taken together with previous validation efforts, this work demonstrates that the Monte Carlo simulation methods can provide accurate estimates of radiation dose in patients undergoing CT examinations.
Brown, F.B.; Sutton, T.M.
1996-02-01
This report is composed of the lecture notes from the first half of a 32-hour graduate-level course on Monte Carlo methods offered at KAPL. These notes, prepared by two of the principle developers of KAPL`s RACER Monte Carlo code, cover the fundamental theory, concepts, and practices for Monte Carlo analysis. In particular, a thorough grounding in the basic fundamentals of Monte Carlo methods is presented, including random number generation, random sampling, the Monte Carlo approach to solving transport problems, computational geometry, collision physics, tallies, and eigenvalue calculations. Furthermore, modern computational algorithms for vector and parallel approaches to Monte Carlo calculations are covered in detail, including fundamental parallel and vector concepts, the event-based algorithm, master/slave schemes, parallel scaling laws, and portability issues.
NASA Astrophysics Data System (ADS)
Dytman, Steven
2011-10-01
Every neutrino experiment requires a Monte Carlo event generator for various purposes. Historically, each series of experiments developed their own code which tuned to their needs. Modern experiments would benefit from a universal code (e.g. PYTHIA) which would allow more direct comparison between experiments. GENIE attempts to be that code. This paper compares most commonly used codes and provides some details of GENIE.
X-ray dosimetry: comparing Monte Carlo simulations and experimental data
NASA Astrophysics Data System (ADS)
Stichelbaut, F.; Bol, J.-L.; Lundhal, B.; Martin, F.; Rose, G.; Schlecht, J.; Smith, R.
2004-09-01
IBA is operating an X-ray irradiation facility located in Bridgeport, New Jersey. This facility is equipped with a Rhodotron ® TT300 and three separated beam lines delivering high-intensity electron beams with 5, 7, and 10 MeV energy. X-ray targets are mounted on the 5 and 7 MeV beam lines to produce high-intensity X-ray fields. During the installation, operation, and process qualifications of the X-ray irradiation system, use has been made of the GEANT Monte Carlo simulation toolkit to predict the results from these tests. These Monte Carlo predictions are compared to the experimental data measured in the various qualification phases.
Comparing analytical and Monte Carlo optical diffusion models in phosphor-based X-ray detectors
NASA Astrophysics Data System (ADS)
Kalyvas, N.; Liaparinos, P.
2014-03-01
Luminescent materials are employed as radiation to light converters in detectors of medical imaging systems, often referred to as phosphor screens. Several processes affect the light transfer properties of phosphors. Amongst the most important is the interaction of light. Light attenuation (absorption and scattering) can be described either through "diffusion" theory in theoretical models or "quantum" theory in Monte Carlo methods. Although analytical methods, based on photon diffusion equations, have been preferentially employed to investigate optical diffusion in the past, Monte Carlo simulation models can overcome several of the analytical modelling assumptions. The present study aimed to compare both methodologies and investigate the dependence of the analytical model optical parameters as a function of particle size. It was found that the optical photon attenuation coefficients calculated by analytical modeling are decreased with respect to the particle size (in the region 1- 12 μm). In addition, for particles sizes smaller than 6μm there is no simultaneous agreement between the theoretical modulation transfer function and light escape values with respect to the Monte Carlo data.
Cramer, S.N.
1984-01-01
The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described.
Monte Carlo variance reduction
NASA Technical Reports Server (NTRS)
Byrn, N. R.
1980-01-01
Computer program incorporates technique that reduces variance of forward Monte Carlo method for given amount of computer time in determining radiation environment in complex organic and inorganic systems exposed to significant amounts of radiation.
von Ferber, C; Holovatch, Yu
2002-04-01
We analyze the scaling laws for a set of two different species of long flexible polymer chains joined together at one of their extremities (copolymer stars) in space dimension D=2. We use a formerly constructed field-theoretic description and compare our perturbative results for the scaling exponents with recent conjectures for exact conformal scaling dimensions derived by a conformal invariance technique in the context of D=2 quantum gravity. A simple Monte Carlo simulation brings about reasonable agreement with both approaches. We analyze the remarkable multifractal properties of the spectrum of scaling exponents. PMID:12005898
Mignon, David; Simonson, Thomas
2016-07-15
Computational protein design depends on an energy function and an algorithm to search the sequence/conformation space. We compare three stochastic search algorithms: a heuristic, Monte Carlo (MC), and a Replica Exchange Monte Carlo method (REMC). The heuristic performs a steepest-descent minimization starting from thousands of random starting points. The methods are applied to nine test proteins from three structural families, with a fixed backbone structure, a molecular mechanics energy function, and with 1, 5, 10, 20, 30, or all amino acids allowed to mutate. Results are compared to an exact, "Cost Function Network" method that identifies the global minimum energy conformation (GMEC) in favorable cases. The designed sequences accurately reproduce experimental sequences in the hydrophobic core. The heuristic and REMC agree closely and reproduce the GMEC when it is known, with a few exceptions. Plain MC performs well for most cases, occasionally departing from the GMEC by 3-4 kcal/mol. With REMC, the diversity of the sequences sampled agrees with exact enumeration where the latter is possible: up to 2 kcal/mol above the GMEC. Beyond, room temperature replicas sample sequences up to 10 kcal/mol above the GMEC, providing thermal averages and a solution to the inverse protein folding problem. © 2016 Wiley Periodicals, Inc. PMID:27197555
Morokoff, W.J.; Caflisch, R.E.
1995-12-01
The standard Monte Carlo approach to evaluating multidimensional integrals using (pseudo)-random integration nodes is frequently used when quadrature methods are too difficult or expensive to implement. As an alternative to the random methods, it has been suggested that lower error and improved convergence may be obtained by replacing the pseudo-random sequences with more uniformly distributed sequences known as quasi-random. In this paper quasi-random (Halton, Sobol`, and Faure) and pseudo-random sequences are compared in computational experiments designed to determine the effects on convergence of certain properties of the integrand, including variance, variation, smoothness, and dimension. The results show that variation, which plays an important role in the theoretical upper bound given by the Koksma-Hlawka inequality, does not affect convergence, while variance, the determining factor in random Monte Carlo, is shown to provide a rough upper bound, but does not accurately predict performance. In general, quasi-Monte Carlo methods are superior to random Monte Carlo, but the advantage may be slight, particularly in high dimensions or for integrands that are not smooth. For discontinuous integrands, we derive a bound which shows that the exponent for algebraic decay of the integration error from quasi-Monte Carlo is only slightly larger than {1/2} in high dimensions. 21 refs., 6 figs., 5 tabs.
NASA Astrophysics Data System (ADS)
Morokoff, William J.; Caflisch, Russel E.
1995-12-01
The standard Monte Carlo approach to evaluating multidimensional integrals using (pseudo)-random integration nodes is frequently used when quadrature methods are too difficult or expensive to implement. As an alternative to the random methods, it has been suggested that lower error and improved convergence may be obtained by replacing the pseudo-random sequences with more uniformly distributed sequences known as quasi-random. In this paper quasi-random (Halton, Sobol', and Faure) and pseudo-random sequences are compared in computational experiments designed to determine the effects on convergence of certain properties of the integrand, including variance, variation, smoothness, and dimension. The results show that variation, which plays an important role in the theoretical upper bound given by the Koksma-Hlawka inequality, does not affect convergence, while variance, the determining factor in random Monte Carlo, is shown to provide a rough upper bound, but does not accurately predict performance. In general, quasi-Monte Carlo methods are superior to random Monte Carlo, but the advantage may be slight, particularly in high dimensions or for integrands that are not smooth. For discontinuous integrands, we derive a bound which shows that the exponent for algebraic decay of the integration error from quasi-Monte Carlo is only slightly larger than {1}/{2} in high dimensions.
Reflection of polarized light by rough surfaces: Monte Carlo modeling compared to measurements
NASA Astrophysics Data System (ADS)
Guirado, Daniel; Marcos Sanz, Juan; María Saiz, José; Muñoz, Olga; Stam, Daphne M.
2013-04-01
A Monte Carlo model of light scattering in a dense medium was developed in order to simulate the reflection of polarized light by rough surfaces [1]. This model calculates all four Stokes parameters of light scattered in all directions by a surface made of any material. Although multiple scattering is allowed, there is a limitation in the packing density of the medium, as independent scattering is assumed. The model can be applied to the study of light scattering by fluffy icy/dusty surfaces, e.g., various types of planetary or lunar regolith-type surfaces, icy moons or comets. The main goal of this work is to test the model by comparing scattering matrix elements calculated with the Monte Carlo model to experimentally measured scattering matrix elements as functions of the phase angle. We use a Sahara sand surface for this. The experimental scattering matrix is measured at the new apparatus developed at the University of Cantabria (Spain) [2]. Sample surfaces are prepared by putting together dust grains with a water-diluted glue coating. A surface's top layer was made with pure sand, to preserve the air-sand refractive index ratio. Calibration measurements have already been carried out successfully by using Spectralon as a Lambertian surface. After calibration, measurements of a surface made of Sahara sand were performed. In such measurements, deviations from Lambertian behavior were found, as well as a very prominent forward peak in the (1,1)-element of the matrix for grazing illumination angles. The values of I and -Q/I calculated by the model for the vertical scattering plane and non-polarized incident light were compared to the measured F11 and -F21/F11 elements for several incident directions. A good agreement between measurements and calculations was achieved. The forward-scattering peak of the (1,1)-element can be interpreted as a result of single scattering of horizontally incident light by the small features of the non-flat surface. In this case, light
Polyakov, Evgeny A; Vorontsov-Velyaminov, Pavel N
2014-08-28
Properties of ferrofluid bilayer (modeled as a system of two planar layers separated by a distance h and each layer carrying a soft sphere dipolar liquid) are calculated in the framework of inhomogeneous Ornstein-Zernike equations with reference hypernetted chain closure (RHNC). The bridge functions are taken from a soft sphere (1/r(12)) reference system in the pressure-consistent closure approximation. In order to make the RHNC problem tractable, the angular dependence of the correlation functions is expanded into special orthogonal polynomials according to Lado. The resulting equations are solved using the Newton-GRMES algorithm as implemented in the public-domain solver NITSOL. Orientational densities and pair distribution functions of dipoles are compared with Monte Carlo simulation results. A numerical algorithm for the Fourier-Hankel transform of any positive integer order on a uniform grid is presented. PMID:25173007
Chin, P.W. . E-mail: mary.chin@physics.org
2005-10-15
This project developed a solution for verifying external photon beam radiotherapy. The solution is based on a calibration chain for deriving portal dose maps from acquired portal images, and a calculation framework for predicting portal dose maps. Quantitative comparison between acquired and predicted portal dose maps accomplishes both geometric (patient positioning with respect to the beam) and dosimetric (two-dimensional fluence distribution of the beam) verifications. A disagreement would indicate that beam delivery had not been according to plan. The solution addresses the clinical need for verifying radiotherapy both pretreatment (without the patient in the beam) and on treatment (with the patient in the beam). Medical linear accelerators mounted with electronic portal imaging devices (EPIDs) were used to acquire portal images. Two types of EPIDs were investigated: the amorphous silicon (a-Si) and the scanning liquid ion chamber (SLIC). The EGSnrc family of Monte Carlo codes were used to predict portal dose maps by computer simulation of radiation transport in the beam-phantom-EPID configuration. Monte Carlo simulations have been implemented on several levels of high throughput computing (HTC), including the grid, to reduce computation time. The solution has been tested across the entire clinical range of gantry angle, beam size (5 cmx5 cm to 20 cmx20 cm), and beam-patient and patient-EPID separations (4 to 38 cm). In these tests of known beam-phantom-EPID configurations, agreement between acquired and predicted portal dose profiles was consistently within 2% of the central axis value. This Monte Carlo portal dosimetry solution therefore achieved combined versatility, accuracy, and speed not readily achievable by other techniques.
Monte Carlo and quasi-Monte Carlo methods
NASA Astrophysics Data System (ADS)
Caflisch, Russel E.
Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N-1/2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Carlo quadrature is attained using quasi-random (also called low-discrepancy) sequences, which are a deterministic alternative to random or pseudo-random sequences. The points in a quasi-random sequence are correlated to provide greater uniformity. The resulting quadrature method, called quasi-Monte Carlo, has a convergence rate of approximately O((logN)kN-1). For quasi-Monte Carlo, both theoretical error estimates and practical limitations are presented. Although the emphasis in this article is on integration, Monte Carlo simulation of rarefied gas dynamics is also discussed. In the limit of small mean free path (that is, the fluid dynamic limit), Monte Carlo loses its effectiveness because the collisional distance is much less than the fluid dynamic length scale. Computational examples are presented throughout the text to illustrate the theory. A number of open problems are described.
Marcus, Ryan C.
2012-07-25
MCMini is a proof of concept that demonstrates the possibility for Monte Carlo neutron transport using OpenCL with a focus on performance. This implementation, written in C, shows that tracing particles and calculating reactions on a 3D mesh can be done in a highly scalable fashion. These results demonstrate a potential path forward for MCNP or other Monte Carlo codes.
Parallelizing Monte Carlo with PMC
Rathkopf, J.A.; Jones, T.R.; Nessett, D.M.; Stanberry, L.C.
1994-11-01
PMC (Parallel Monte Carlo) is a system of generic interface routines that allows easy porting of Monte Carlo packages of large-scale physics simulation codes to Massively Parallel Processor (MPP) computers. By loading various versions of PMC, simulation code developers can configure their codes to run in several modes: serial, Monte Carlo runs on the same processor as the rest of the code; parallel, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on other MPP processor(s); distributed, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on a different machine. This multi-mode approach allows maintenance of a single simulation code source regardless of the target machine. PMC handles passing of messages between nodes on the MPP, passing of messages between a different machine and the MPP, distributing work between nodes, and providing independent, reproducible sequences of random numbers. Several production codes have been parallelized under the PMC system. Excellent parallel efficiency in both the distributed and parallel modes results if sufficient workload is available per processor. Experiences with a Monte Carlo photonics demonstration code and a Monte Carlo neutronics package are described.
Wormhole Hamiltonian Monte Carlo
Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak
2015-01-01
In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function. PMID:25861551
Isotropic Monte Carlo Grain Growth
Energy Science and Technology Software Center (ESTSC)
2013-04-25
IMCGG performs Monte Carlo simulations of normal grain growth in metals on a hexagonal grid in two dimensions with periodic boundary conditions. This may be performed with either an isotropic or a misorientation - and incliantion-dependent grain boundary energy.
Díaz-González, Lorena; Quiroz-Ruiz, Alfredo
2014-01-01
Using highly precise and accurate Monte Carlo simulations of 20,000,000 replications and 102 independent simulation experiments with extremely low simulation errors and total uncertainties, we evaluated the performance of four single outlier discordancy tests (Grubbs test N2, Dixon test N8, skewness test N14, and kurtosis test N15) for normal samples of sizes 5 to 20. Statistical contaminations of a single observation resulting from parameters called δ from ±0.1 up to ±20 for modeling the slippage of central tendency or ε from ±1.1 up to ±200 for slippage of dispersion, as well as no contamination (δ = 0 and ε = ±1), were simulated. Because of the use of precise and accurate random and normally distributed simulated data, very large replications, and a large number of independent experiments, this paper presents a novel approach for precise and accurate estimations of power functions of four popular discordancy tests and, therefore, should not be considered as a simple simulation exercise unrelated to probability and statistics. From both criteria of the Power of Test proposed by Hayes and Kinsella and the Test Performance Criterion of Barnett and Lewis, Dixon test N8 performs less well than the other three tests. The overall performance of these four tests could be summarized as N2≅N15 > N14 > N8. PMID:24737992
Verma, Surendra P; Díaz-González, Lorena; Rosales-Rivera, Mauricio; Quiroz-Ruiz, Alfredo
2014-01-01
Using highly precise and accurate Monte Carlo simulations of 20,000,000 replications and 102 independent simulation experiments with extremely low simulation errors and total uncertainties, we evaluated the performance of four single outlier discordancy tests (Grubbs test N2, Dixon test N8, skewness test N14, and kurtosis test N15) for normal samples of sizes 5 to 20. Statistical contaminations of a single observation resulting from parameters called δ from ±0.1 up to ±20 for modeling the slippage of central tendency or ε from ±1.1 up to ±200 for slippage of dispersion, as well as no contamination (δ = 0 and ε = ±1), were simulated. Because of the use of precise and accurate random and normally distributed simulated data, very large replications, and a large number of independent experiments, this paper presents a novel approach for precise and accurate estimations of power functions of four popular discordancy tests and, therefore, should not be considered as a simple simulation exercise unrelated to probability and statistics. From both criteria of the Power of Test proposed by Hayes and Kinsella and the Test Performance Criterion of Barnett and Lewis, Dixon test N8 performs less well than the other three tests. The overall performance of these four tests could be summarized as N2≅N15 > N14 > N8. PMID:24737992
NASA Astrophysics Data System (ADS)
Doumas, A.; Smith, G. C.
2009-12-01
Various neutron detectors are being developed for the next generation user facilities, which incorporate new as well as existing approaches for the detection of thermal neutrons. Improvements in neutron detector efficiency, detector size and position resolution have occurred over the last three decades and further advances are expected in the next ten years. Since gas detectors are expected to continue in a key role for future thermal neutron experiments, it is advantageous to review some of the criteria for the choice of proton/triton stopping gases for gas-based detectors. Monte Carlo simulations, using the group of programs "Stopping and Range of Ions in Matter", have been run to determine key performance characteristics for neutron detectors which utilize the reaction 3He(n,p)t. This paper will focus on investigating the use of three common hydrocarbons and CF 4 as stopping gases for thermal neutron detectors. A discussion of these gases will include their behavior in terms of proton and triton range, ion distribution and straggle.
Monte Carlo surface flux tallies
Favorite, Jeffrey A
2010-11-19
Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.
Ng, Yee-Hong; Bettens, Ryan P A
2016-03-01
Using the method of modified Shepard's interpolation to construct potential energy surfaces of the H2O, O3, and HCOOH molecules, we compute vibrationally averaged isotropic nuclear shielding constants ⟨σ⟩ of the three molecules via quantum diffusion Monte Carlo (QDMC). The QDMC results are compared to that of second-order perturbation theory (PT), to see if second-order PT is adequate for obtaining accurate values of nuclear shielding constants of molecules with large amplitude motions. ⟨σ⟩ computed by the two approaches differ for the hydrogens and carbonyl oxygen of HCOOH, suggesting that for certain molecules such as HCOOH where big displacements away from equilibrium happen (internal OH rotation), ⟨σ⟩ of experimental quality may only be obtainable with the use of more sophisticated and accurate methods, such as quantum diffusion Monte Carlo. The approach of modified Shepard's interpolation is also extended to construct shielding constants σ surfaces of the three molecules. By using a σ surface with the equilibrium geometry as a single data point to compute isotropic nuclear shielding constants for each descendant in the QDMC ensemble representing the ground state wave function, we reproduce the results obtained through ab initio computed σ to within statistical noise. Development of such an approach could thereby alleviate the need for any future costly ab initio σ calculations. PMID:26835785
Proton Upset Monte Carlo Simulation
NASA Technical Reports Server (NTRS)
O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.
2009-01-01
The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.
Campbell, C L; Wood, K; Brown, C T A; Moseley, H
2016-07-01
We explore the effects of three dimensional (3D) tumour structures on depth dependent fluence rates, photodynamic doses (PDD) and fluorescence images through Monte Carlo radiation transfer modelling of photodynamic therapy. The aim with this work was to compare the commonly used uniform tumour densities with non-uniform densities to determine the importance of including 3D models in theoretical investigations. It was found that fractal 3D models resulted in deeper penetration on average of therapeutic radiation and higher PDD. An increase in effective treatment depth of 1 mm was observed for one of the investigated fractal structures, when comparing to the equivalent smooth model. Wide field fluorescence images were simulated, revealing information about the relationship between tumour structure and the appearance of the fluorescence intensity. Our models indicate that the 3D tumour structure strongly affects the spatial distribution of therapeutic light, the PDD and the wide field appearance of surface fluorescence images. PMID:27273196
NASA Astrophysics Data System (ADS)
Campbell, C. L.; Wood, K.; Brown, C. T. A.; Moseley, H.
2016-07-01
We explore the effects of three dimensional (3D) tumour structures on depth dependent fluence rates, photodynamic doses (PDD) and fluorescence images through Monte Carlo radiation transfer modelling of photodynamic therapy. The aim with this work was to compare the commonly used uniform tumour densities with non-uniform densities to determine the importance of including 3D models in theoretical investigations. It was found that fractal 3D models resulted in deeper penetration on average of therapeutic radiation and higher PDD. An increase in effective treatment depth of 1 mm was observed for one of the investigated fractal structures, when comparing to the equivalent smooth model. Wide field fluorescence images were simulated, revealing information about the relationship between tumour structure and the appearance of the fluorescence intensity. Our models indicate that the 3D tumour structure strongly affects the spatial distribution of therapeutic light, the PDD and the wide field appearance of surface fluorescence images.
Monte Carlo simulation of neutron scattering instruments
Seeger, P.A.
1995-12-31
A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h0>h1 ...>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less
Synchronous Parallel Kinetic Monte Carlo
Mart?nez, E; Marian, J; Kalos, M H
2006-12-14
A novel parallel kinetic Monte Carlo (kMC) algorithm formulated on the basis of perfect time synchronicity is presented. The algorithm provides an exact generalization of any standard serial kMC model and is trivially implemented in parallel architectures. We demonstrate the mathematical validity and parallel performance of the method by solving several well-understood problems in diffusion.
Monte Carlo calculations of nuclei
Pieper, S.C.
1997-10-01
Nuclear many-body calculations have the complication of strong spin- and isospin-dependent potentials. In these lectures the author discusses the variational and Green`s function Monte Carlo techniques that have been developed to address this complication, and presents a few results.
Comparative Dosimetric Estimates of a 25 keV Electron Micro-beam with three Monte Carlo Codes
Mainardi, Enrico; Donahue, Richard J.; Blakely, Eleanor A.
2002-09-11
The calculations presented compare the different performances of the three Monte Carlo codes PENELOPE-1999, MCNP-4C and PITS, for the evaluation of Dose profiles from a 25 keV electron micro-beam traversing individual cells. The overall model of a cell is a water cylinder equivalent for the three codes but with a different internal scoring geometry: hollow cylinders for PENELOPE and MCNP, whereas spheres are used for the PITS code. A cylindrical cell geometry with scoring volumes with the shape of hollow cylinders was initially selected for PENELOPE and MCNP because of its superior simulation of the actual shape and dimensions of a cell and for its improved computer-time efficiency if compared to spherical internal volumes. Some of the transfer points and energy transfer that constitute a radiation track may actually fall in the space between spheres, that would be outside the spherical scoring volume. This internal geometry, along with the PENELOPE algorithm, drastically reduced the computer time when using this code if comparing with event-by-event Monte Carlo codes like PITS. This preliminary work has been important to address dosimetric estimates at low electron energies. It demonstrates that codes like PENELOPE can be used for Dose evaluation, even with such small geometries and energies involved, which are far below the normal use for which the code was created. Further work (initiated in Summer 2002) is still needed however, to create a user-code for PENELOPE that allows uniform comparison of exact cell geometries, integral volumes and also microdosimetric scoring quantities, a field where track-structure codes like PITS, written for this purpose, are believed to be superior.
NASA Astrophysics Data System (ADS)
Devienne, A.; Aymerich, N.; García-Fusté, M. J.; Queralt, X.
2015-11-01
ALBA is the Spanish synchrotron facility formed with a 3 GeV electron synchrotron accelerator generating bright beams of synchrotron radiation, located in Cerdanyola del Vallès (Spain). The aim of this work is to study the origin of the radiation produced inside and outside the optical hutch of BOREAS beamline, an experimental station dedicated to study the resonant absorption and scattering of the photons. The objective is to characterize the radiation at the beamline, evaluating in particular the solid bremsstrahlung component of the radiation. The results are obtained after comparing radiation monitors detectors data with Monte Carlo modeling (FLUKA), giving the characteristics of the shielding required to consider the outside of the hutch as a public zone.
Spatial Correlations in Monte Carlo Criticality Simulations
NASA Astrophysics Data System (ADS)
Dumonteil, E.; Malvagi, F.; Zoia, A.; Mazzolo, A.; Artusio, D.; Dieudonné, C.; De Mulatier, C.
2014-06-01
Temporal correlations arising in Monte Carlo criticality codes have focused the attention of both developers and practitioners for a long time. Those correlations affects the evaluation of tallies of loosely coupled systems, where the system's typical size is very large compared to the diffusion/absorption length scale of the neutrons. These time correlations are closely related to spatial correlations, both variables being linked by the transport equation. Therefore this paper addresses the question of diagnosing spatial correlations in Monte Carlo criticality simulations. In that aim, we will propose a spatial correlation function well suited to Monte Carlo simulations, and show its use while simulating a fuel pin-cell. The results will be discussed, modeled and interpreted using the tools of branching processes of statistical mechanics. A mechanism called "neutron clustering", affecting simulations, will be discussed in this frame.
Interaction picture density matrix quantum Monte Carlo
Malone, Fionn D. Lee, D. K. K.; Foulkes, W. M. C.; Blunt, N. S.; Shepherd, James J.; Spencer, J. S.
2015-07-28
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples the N-body thermal density matrix and hence provides access to exact properties of many-particle quantum systems at arbitrary temperatures. We demonstrate that moving to the interaction picture provides substantial benefits when applying DMQMC to interacting fermions. In this first study, we focus on a system of much recent interest: the uniform electron gas in the warm dense regime. The basis set incompleteness error at finite temperature is investigated and extrapolated via a simple Monte Carlo sampling procedure. Finally, we provide benchmark calculations for a four-electron system, comparing our results to previous work where possible.
Monte Carlo Simulation for Perusal and Practice.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.
The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…
Structural Reliability and Monte Carlo Simulation.
ERIC Educational Resources Information Center
Laumakis, P. J.; Harlow, G.
2002-01-01
Analyzes a simple boom structure and assesses its reliability using elementary engineering mechanics. Demonstrates the power and utility of Monte-Carlo simulation by showing that such a simulation can be implemented more readily with results that compare favorably to the theoretical calculations. (Author/MM)
Zimmerman, G.B.
1997-06-24
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ion and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burns nd burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
Shell model Monte Carlo methods
Koonin, S.E.; Dean, D.J.
1996-10-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of {gamma}-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs.
Womersley, J. . Dept. of Physics)
1992-10-01
The D0 detector at the Fermilab Tevatron began its first data taking run in May 1992. For analysis of the expected 25 pb[sup [minus]1] data sample, roughly half a million simulated events will be needed. The GEANT-based Monte Carlo program used to generate these events is described, together with comparisons to test beam data. Some novel techniques used to speed up execution and simplify geometrical input are described.
Extending canonical Monte Carlo methods
NASA Astrophysics Data System (ADS)
Velazquez, L.; Curilef, S.
2010-02-01
In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C < 0. The resulting framework appears to be a suitable generalization of the methodology associated with the so-called dynamical ensemble, which is applied to the extension of two well-known Monte Carlo methods: the Metropolis importance sampling and the Swendsen-Wang cluster algorithm. These Monte Carlo algorithms are employed to study the anomalous thermodynamic behavior of the Potts models with many spin states q defined on a d-dimensional hypercubic lattice with periodic boundary conditions, which successfully reduce the exponential divergence of the decorrelation time τ with increase of the system size N to a weak power-law divergence \\tau \\propto N^{\\alpha } with α≈0.2 for the particular case of the 2D ten-state Potts model.
Compressible generalized hybrid Monte Carlo
NASA Astrophysics Data System (ADS)
Fang, Youhan; Sanz-Serna, J. M.; Skeel, Robert D.
2014-05-01
One of the most demanding calculations is to generate random samples from a specified probability distribution (usually with an unknown normalizing prefactor) in a high-dimensional configuration space. One often has to resort to using a Markov chain Monte Carlo method, which converges only in the limit to the prescribed distribution. Such methods typically inch through configuration space step by step, with acceptance of a step based on a Metropolis(-Hastings) criterion. An acceptance rate of 100% is possible in principle by embedding configuration space in a higher dimensional phase space and using ordinary differential equations. In practice, numerical integrators must be used, lowering the acceptance rate. This is the essence of hybrid Monte Carlo methods. Presented is a general framework for constructing such methods under relaxed conditions: the only geometric property needed is (weakened) reversibility; volume preservation is not needed. The possibilities are illustrated by deriving a couple of explicit hybrid Monte Carlo methods, one based on barrier-lowering variable-metric dynamics and another based on isokinetic dynamics.
Song, Jin Ho; Kang, Ki Mun; Choi, Hoon-Sik; Jeong, Hojin; Ha, In Bong; Lee, Jong Deog; Kim, Ho Cheol; Jeong, Yi Yeong; Cho, Yu Ji; Lee, Seung Jun; Kim, Sung Hwan; Jang, In-Seok; Jeong, Bae Kwon
2016-01-01
Purpose The purpose of this study was to compare the clinical outcomes between the groups using Ray-Tracing (RAT) and Monte-Carlo (MC) calculation algorithms for stereotactic body radiotherapy (SBRT) of lung tumors. Materials and Methods Thirty-five patients received SBRT with CyberKnife for 47 primary or metastatic lung tumors. RAT was used for 22 targets in 12 patients, and MC for 25 targets in 23 patients. Total dose of 48 to 60 Gy was prescribed in 3 to 5 fractions on median 80% isodose line. The response rate, local control rate, and toxicities were compared between RAT and MC groups. Results The response rate was lower in the RAT group (77.3%) compared to the MC group (100%) (p = 0.008). The response rates showed an association with the mean dose to the gross tumor volume, which the doses were re-calculated with MC algorithm in both groups. However, the local control rate and toxicities did not differ between the groups. Conclusions The clinical outcome and toxicity of lung SBRT between the RAT and MC groups were similar except for the response rate when the same apparent doses were prescribed. The lower response rate in the RAT group, however, did not compromise the local control rates. As such, reducing the prescription dose for MC algorithm may be performed but done with caution. PMID:26544622
Factor Analysis with Ordinal Indicators: A Monte Carlo Study Comparing DWLS and ULS Estimation
ERIC Educational Resources Information Center
Forero, Carlos G.; Maydeu-Olivares, Alberto; Gallardo-Pujol, David
2009-01-01
Factor analysis models with ordinal indicators are often estimated using a 3-stage procedure where the last stage involves obtaining parameter estimates by least squares from the sample polychoric correlations. A simulation study involving 324 conditions (1,000 replications per condition) was performed to compare the performance of diagonally…
A Comparative Study of Exact versus Propensity Matching Techniques Using Monte Carlo Simulation
ERIC Educational Resources Information Center
Itang'ata, Mukaria J. J.
2013-01-01
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…
Multidimensional stochastic approximation Monte Carlo.
Zablotskiy, Sergey V; Ivanov, Victor A; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g(E), of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g(E_{1},E_{2}). We show when and why care has to be exercised when obtaining the microcanonical density of states g(E_{1}+E_{2}) from g(E_{1},E_{2}). PMID:27415383
Multidimensional stochastic approximation Monte Carlo
NASA Astrophysics Data System (ADS)
Zablotskiy, Sergey V.; Ivanov, Victor A.; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g (E ) , of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g (E1,E2) . We show when and why care has to be exercised when obtaining the microcanonical density of states g (E1+E2) from g (E1,E2) .
1-D EQUILIBRIUM DISCRETE DIFFUSION MONTE CARLO
T. EVANS; ET AL
2000-08-01
We present a new hybrid Monte Carlo method for 1-D equilibrium diffusion problems in which the radiation field coexists with matter in local thermodynamic equilibrium. This method, the Equilibrium Discrete Diffusion Monte Carlo (EqDDMC) method, combines Monte Carlo particles with spatially discrete diffusion solutions. We verify the EqDDMC method with computational results from three slab problems. The EqDDMC method represents an incremental step toward applying this hybrid methodology to non-equilibrium diffusion, where it could be simultaneously coupled to Monte Carlo transport.
Monte Carlo dose mapping on deforming anatomy
NASA Astrophysics Data System (ADS)
Zhong, Hualiang; Siebers, Jeffrey V.
2009-10-01
This paper proposes a Monte Carlo-based energy and mass congruent mapping (EMCM) method to calculate the dose on deforming anatomy. Different from dose interpolation methods, EMCM separately maps each voxel's deposited energy and mass from a source image to a reference image with a displacement vector field (DVF) generated by deformable image registration (DIR). EMCM was compared with other dose mapping methods: energy-based dose interpolation (EBDI) and trilinear dose interpolation (TDI). These methods were implemented in EGSnrc/DOSXYZnrc, validated using a numerical deformable phantom and compared for clinical CT images. On the numerical phantom with an analytically invertible deformation map, EMCM mapped the dose exactly the same as its analytic solution, while EBDI and TDI had average dose errors of 2.5% and 6.0%. For a lung patient's IMRT treatment plan, EBDI and TDI differed from EMCM by 1.96% and 7.3% in the lung patient's entire dose region, respectively. As a 4D Monte Carlo dose calculation technique, EMCM is accurate and its speed is comparable to 3D Monte Carlo simulation. This method may serve as a valuable tool for accurate dose accumulation as well as for 4D dosimetry QA.
Gentile, N A
2000-10-01
We present a method for accelerating time dependent Monte Carlo radiative transfer calculations by using a discretization of the diffusion equation to calculate probabilities that are used to advance particles in regions with small mean free path. The method is demonstrated on problems with on 1 and 2 dimensional orthogonal grids. It results in decreases in run time of more than an order of magnitude on these problems, while producing answers with accuracy comparable to pure IMC simulations. We call the method Implicit Monte Carlo Diffusion, which we abbreviate IMD.
Interaction picture density matrix quantum Monte Carlo.
Malone, Fionn D; Blunt, N S; Shepherd, James J; Lee, D K K; Spencer, J S; Foulkes, W M C
2015-07-28
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples the N-body thermal density matrix and hence provides access to exact properties of many-particle quantum systems at arbitrary temperatures. We demonstrate that moving to the interaction picture provides substantial benefits when applying DMQMC to interacting fermions. In this first study, we focus on a system of much recent interest: the uniform electron gas in the warm dense regime. The basis set incompleteness error at finite temperature is investigated and extrapolated via a simple Monte Carlo sampling procedure. Finally, we provide benchmark calculations for a four-electron system, comparing our results to previous work where possible. PMID:26233116
Monte Carlo modeling of exospheric bodies - Mercury
NASA Technical Reports Server (NTRS)
Smith, G. R.; Broadfoot, A. L.; Wallace, L.; Shemansky, D. E.
1978-01-01
In order to study the interaction with the surface, a Monte Carlo program is developed to determine the distribution with altitude as well as the global distribution of density at the surface in a single operation. The analysis presented shows that the appropriate source distribution should be Maxwell-Boltzmann flux if the particles in the distribution are to be treated as components of flux. Monte Carlo calculations with a Maxwell-Boltzmann flux source are compared with Mariner 10 UV spectrometer data. Results indicate that the presently operating models are not capable of fitting the observed Mercury exosphere. It is suggested that an atmosphere calculated with a barometric source distribution is suitable for more realistic future exospheric models.
Numerical reproducibility for implicit Monte Carlo simulations
Cleveland, M.; Brunner, T.; Gentile, N.
2013-07-01
We describe and compare different approaches for achieving numerical reproducibility in photon Monte Carlo simulations. Reproducibility is desirable for code verification, testing, and debugging. Parallelism creates a unique problem for achieving reproducibility in Monte Carlo simulations because it changes the order in which values are summed. This is a numerical problem because double precision arithmetic is not associative. In [1], a way of eliminating this roundoff error using integer tallies was described. This approach successfully achieves reproducibility at the cost of lost accuracy by rounding double precision numbers to fewer significant digits. This integer approach, and other extended reproducibility techniques, are described and compared in this work. Increased precision alone is not enough to ensure reproducibility of photon Monte Carlo simulations. A non-arbitrary precision approaches required a varying degree of rounding to achieve reproducibility. For the problems investigated in this work double precision global accuracy was achievable by using 100 bits of precision or greater on all unordered sums which where subsequently rounded to double precision at the end of every time-step. (authors)
Debbarma, Rousan; Malani, Ateeque
2016-02-01
Clay minerals are used in variety of applications ranging from composites to electronic devices. For their efficient use in such areas, understanding the effect of surface-active agents on interfacial properties is essential. We investigated the role of surface ions in the adsorption of water molecules by using a muscovite mica surface populated with two different, H(+) and K(+), surface ions. A series of grand canonical Monte Carlo (GCMC) simulations at various relative vapor pressures (p/p0) were performed to obtain the water structure and adsorption isotherm on the H(+)-exposed mica (H-mica) surface. The obtained results were compared to the recent simulation data of water adsorption on the K(+)-exposed mica (K-mica) surface reported by Malani and Ayyappa (Malani, A.; Ayappa, K. G. J. Phys. Chem. B 2009, 113, 1058-1067). Water molecules formed two prominent layers adjacent to the H-mica surface, whereas molecular layering was observed adjacent to the K-mica surface. The adsorption isotherm of water on the K-mica surface was characterized by three stages that corresponded to rapid adsorption in the initial regime below p/p0 = 0.1, followed by a linear development regime for p/p0 = 0.1-0.7 and rapid film thickening for p/p0 ≥ 0.7, whereas only latter two regimes were observed in the H-mica system. In addition, the film thickness of adsorbed water molecules for p/p0 < 0.7 was lower as compared to that for the K-mica surface and comparable beyond. The film thickness obtained from the MC simulations was in excellent agreement with the interferometry experimental data of Balmer et al. (Balmer, T. E.; Christenson, H. K.; Spencer, N. D.; Heuberger, M. Langmuir 2008, 24, 1566-1569). It was observed that the hydration behaviors of the two ions were completely different and depended on the size of their hydration shell and their ability to form hydrogen bonds. The behavior of water adsorption between these two cases was illustrated using the water density distribution
Hayakawa, Carole K; Spanier, Jerome; Venugopalan, Vasan
2014-02-01
We examine the relative error of Monte Carlo simulations of radiative transport that employ two commonly used estimators that account for absorption differently, either discretely, at interaction points, or continuously, between interaction points. We provide a rigorous derivation of these discrete and continuous absorption weighting estimators within a stochastic model that we show to be equivalent to an analytic model, based on the radiative transport equation (RTE). We establish that both absorption weighting estimators are unbiased and, therefore, converge to the solution of the RTE. An analysis of spatially resolved reflectance predictions provided by these two estimators reveals no advantage to either in cases of highly scattering and highly anisotropic media. However, for moderate to highly absorbing media or isotropically scattering media, the discrete estimator provides smaller errors at proximal source locations while the continuous estimator provides smaller errors at distal locations. The origin of these differing variance characteristics can be understood through examination of the distribution of exiting photon weights. PMID:24562029
Hayakawa, Carole K.; Spanier, Jerome; Venugopalan, Vasan
2014-01-01
We examine the relative error of Monte Carlo simulations of radiative transport that employ two commonly used estimators that account for absorption differently, either discretely, at interaction points, or continuously, between interaction points. We provide a rigorous derivation of these discrete and continuous absorption weighting estimators within a stochastic model that we show to be equivalent to an analytic model, based on the radiative transport equation (RTE). We establish that both absorption weighting estimators are unbiased and, therefore, converge to the solution of the RTE. An analysis of spatially resolved reflectance predictions provided by these two estimators reveals no advantage to either in cases of highly scattering and highly anisotropic media. However, for moderate to highly absorbing media or isotropically scattering media, the discrete estimator provides smaller errors at proximal source locations while the continuous estimator provides smaller errors at distal locations. The origin of these differing variance characteristics can be understood through examination of the distribution of exiting photon weights. PMID:24562029
Monte Carlo Shower Counter Studies
NASA Technical Reports Server (NTRS)
Snyder, H. David
1991-01-01
Activities and accomplishments related to the Monte Carlo shower counter studies are summarized. A tape of the VMS version of the GEANT software was obtained and installed on the central computer at Gallaudet University. Due to difficulties encountered in updating this VMS version, a decision was made to switch to the UNIX version of the package. This version was installed and used to generate the set of data files currently accessed by various analysis programs. The GEANT software was used to write files of data for positron and proton showers. Showers were simulated for a detector consisting of 50 alternating layers of lead and scintillator. Each file consisted of 1000 events at each of the following energies: 0.1, 0.5, 2.0, 10, 44, and 200 GeV. Data analysis activities related to clustering, chi square, and likelihood analyses are summarized. Source code for the GEANT user subprograms and data analysis programs are provided along with example data plots.
Improved Monte Carlo Renormalization Group Method
DOE R&D Accomplishments Database
Gupta, R.; Wilson, K. G.; Umrigar, C.
1985-01-01
An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.
Monte Carlo Ion Transport Analysis Code.
Energy Science and Technology Software Center (ESTSC)
2009-04-15
Version: 00 TRIPOS is a versatile Monte Carlo ion transport analysis code. It has been applied to the treatment of both surface and bulk radiation effects. The media considered is composed of multilayer polyatomic materials.
Monte Carlo Transport for Electron Thermal Transport
NASA Astrophysics Data System (ADS)
Chenhall, Jeffrey; Cao, Duc; Moses, Gregory
2015-11-01
The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.
Extra Chance Generalized Hybrid Monte Carlo
NASA Astrophysics Data System (ADS)
Campos, Cédric M.; Sanz-Serna, J. M.
2015-01-01
We study a method, Extra Chance Generalized Hybrid Monte Carlo, to avoid rejections in the Hybrid Monte Carlo method and related algorithms. In the spirit of delayed rejection, whenever a rejection would occur, extra work is done to find a fresh proposal that, hopefully, may be accepted. We present experiments that clearly indicate that the additional work per sample carried out in the extra chance approach clearly pays in terms of the quality of the samples generated.
Fission Matrix Capability for MCNP Monte Carlo
Carney, Sean E.; Brown, Forrest B.; Kiedrowski, Brian C.; Martin, William R.
2012-09-05
spatially low-order kernel, the fundamental eigenvector of which should converge faster than that of continuous kernel. We can then redistribute the fission bank to match the fundamental fission matrix eigenvector, effectively eliminating all higher modes. For all computations here biasing is not used, with the intention of comparing the unaltered, conventional Monte Carlo process with the fission matrix results. The source convergence of standard Monte Carlo criticality calculations are, to some extent, always subject to the characteristics of the problem. This method seeks to partially eliminate this problem-dependence by directly calculating the spatial coupling. The primary cost of this, which has prevented widespread use since its inception [2,3,4], is the extra storage required. To account for the coupling of all N spatial regions to every other region requires storing N{sup 2} values. For realistic problems, where a fine resolution is required for the suppression of discretization error, the storage becomes inordinate. Two factors lead to a renewed interest here: the larger memory available on modern computers and the development of a better storage scheme based on physical intuition. When the distance between source and fission events is short compared with the size of the entire system, saving memory by accounting for only local coupling introduces little extra error. We can gain other information from directly tallying the fission kernel: higher eigenmodes and eigenvalues. Conventional Monte Carlo cannot calculate this data - here we have a way to get new information for multiplying systems. In Ref. [5], higher mode eigenfunctions are analyzed for a three-region 1-dimensional problem and 2-dimensional homogenous problem. We analyze higher modes for more realistic problems. There is also the question of practical use of this information; here we examine a way of using eigenmode information to address the negative confidence interval bias due to inter
Shift: A Massively Parallel Monte Carlo Radiation Transport Package
Pandya, Tara M; Johnson, Seth R; Davidson, Gregory G; Evans, Thomas M; Hamilton, Steven P
2015-01-01
This paper discusses the massively-parallel Monte Carlo radiation transport package, Shift, developed at Oak Ridge National Laboratory. It reviews the capabilities, implementation, and parallel performance of this code package. Scaling results demonstrate very good strong and weak scaling behavior of the implemented algorithms. Benchmark results from various reactor problems show that Shift results compare well to other contemporary Monte Carlo codes and experimental results.
NASA Astrophysics Data System (ADS)
Wang, Lili; Wang, Lu; Zhao, Jijun; Yan, Tianying
2012-06-01
The adsorption properties of H2, CO, NO, and NO2 in several typical nanoporous materials (covalent organic framework (COF)-105, COF-108, metal-organic framework (MOF)-5, and MOF-177) at 298 K were investigated by grand canonical Monte Carlo simulations. Good agreement between simulated results and experimental data has been achieved for H2 adsorption on MOF-5 and MOF-177, indicating the reliability of the theoretical approach. The simulated adsorption isotherms for these four gases show analogical trend, i.e., increasing nearly linearly with pressure. Among the four host materials, COF-108 exhibits the highest hydrogen uptake (˜0.89 wt. % at 100 bars) owing to its low densities and high surface area. The adsorption amounts of NO2 in these materials are higher than those of the other three gases because of the stronger gas-sorbent interaction. In particular, NO2 adsorption amount in MOF-177 can reach as high as 10.7 mmol/g at 298 K and 10 bars. The interaction between the four gases (H2, CO, NO, and NO2) and the COF/MOF adsorbents is further discussed in terms of the isosteric heat.
COMPARISON OF MONTE CARLO METHODS FOR NONLINEAR RADIATION TRANSPORT
W. R. MARTIN; F. B. BROWN
2001-03-01
Five Monte Carlo methods for solving the nonlinear thermal radiation transport equations are compared. The methods include the well-known Implicit Monte Carlo method (IMC) developed by Fleck and Cummings, an alternative to IMC developed by Carter and Forest, an ''exact'' method recently developed by Ahrens and Larsen, and two methods recently proposed by Martin and Brown. The five Monte Carlo methods are developed and applied to the radiation transport equation in a medium assuming local thermodynamic equilibrium. Conservation of energy is derived and used to define appropriate material energy update equations for each of the methods. Details of the Monte Carlo implementation are presented, both for the random walk simulation and the material energy update. Simulation results for all five methods are obtained for two infinite medium test problems and a 1-D test problem, all of which have analytical solutions. Conclusions regarding the relative merits of the various schemes are presented.
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.
2013-07-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
Chemical application of diffusion quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Reynolds, P. J.; Lester, W. A., Jr.
1983-10-01
The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. As an example the singlet-triplet splitting of the energy of the methylene molecule CH2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on our VAX 11/780, and second by explicitly writing vector code for all loops longer than a crossover length C. The speed of the codes relative to one another as a function of C, and relative to the VAX is discussed. Since CH2 has only eight electrons, most of the loops in this application are fairly short. The longest inner loops run over the set of atomic basis functions. The CPU time dependence obtained versus the number of basis functions is discussed and compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures. Finally, preliminary work on restructuring the algorithm to compute the separate Monte Carlo realizations in parallel is discussed.
Discrete range clustering using Monte Carlo methods
NASA Technical Reports Server (NTRS)
Chatterji, G. B.; Sridhar, B.
1993-01-01
For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.
Monte Carlo methods in lattice gauge theories
Otto, S.W.
1983-01-01
The mass of the O/sup +/ glueball for SU(2) gauge theory in 4 dimensions is calculated. This computation was done on a prototype parallel processor and the implementation of gauge theories on this system is described in detail. Using an action of the purely Wilson form (tract of plaquette in the fundamental representation), results with high statistics are obtained. These results are not consistent with scaling according to the continuum renormalization group. Using actions containing higher representations of the group, a search is made for one which is closer to the continuum limit. The choice is based upon the phase structure of these extended theories and also upon the Migdal-Kadanoff approximation to the renormalizaiton group on the lattice. The mass of the O/sup +/ glueball for this improved action is obtained and the mass divided by the square root of the string tension is a constant as the lattice spacing is varied. The other topic studied is the inclusion of dynamical fermions into Monte Carlo calculations via the pseudo fermion technique. Monte Carlo results obtained with this method are compared with those from an exact algorithm based on Gauss-Seidel inversion. First applied were the methods to the Schwinger model and SU(3) theory.
Approaching chemical accuracy with quantum Monte Carlo.
Petruzielo, F R; Toulouse, Julien; Umrigar, C J
2012-03-28
A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction formed from Hartree-Fock orbitals. With the largest basis set, the mean absolute deviation from experimental atomization energies for the G2 set is 3.0 kcal/mol. Optimizing the orbitals within variational Monte Carlo improves the agreement between diffusion Monte Carlo and experiment, reducing the mean absolute deviation to 2.1 kcal/mol. Moving beyond a single determinant Slater-Jastrow trial wavefunction, diffusion Monte Carlo with a small complete active space Slater-Jastrow trial wavefunction results in near chemical accuracy. In this case, the mean absolute deviation from experimental atomization energies is 1.2 kcal/mol. It is shown from calculations on systems containing phosphorus that the accuracy can be further improved by employing a larger active space. PMID:22462844
Quantum speedup of Monte Carlo methods
Montanaro, Ashley
2015-01-01
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079
Quantum Monte Carlo calculations of light nuclei
Pieper, S.C.
1998-12-01
Quantum Monte Carlo calculations using realistic two- and three-nucleon interactions are presented for nuclei with up to eight nucleons. We have computed the ground and a few excited states of all such nuclei with Greens function Monte Carlo (GFMC) and all of the experimentally known excited states using variational Monte Carlo (VMC). The GFMC calculations show that for a given Hamiltonian, the VMC calculations of excitation spectra are reliable, but the VMC ground-state energies are significantly above the exact values. We find that the Hamiltonian we are using (which was developed based on {sup 3}H,{sup 4}He, and nuclear matter calculations) underpredicts the binding energy of p-shell nuclei. However our results for excitation spectra are very good and one can see both shell-model and collective spectra resulting from fundamental many-nucleon calculations. Possible improvements in the three-nucleon potential are also be discussed. {copyright} {ital 1998 American Institute of Physics.}
Quantum Monte Carlo calculations of light nuclei
Pieper, Steven C.
1998-12-21
Quantum Monte Carlo calculations using realistic two- and three-nucleon interactions are presented for nuclei with up to eight nucleons. We have computed the ground and a few excited states of all such nuclei with Greens function Monte Carlo (GFMC) and all of the experimentally known excited states using variational Monte Carlo (VMC). The GFMC calculations show that for a given Hamiltonian, the VMC calculations of excitation spectra are reliable, but the VMC ground-state energies are significantly above the exact values. We find that the Hamiltonian we are using (which was developed based on {sup 3}H,{sup 4}He, and nuclear matter calculations) underpredicts the binding energy of p-shell nuclei. However our results for excitation spectra are very good and one can see both shell-model and collective spectra resulting from fundamental many-nucleon calculations. Possible improvements in the three-nucleon potential are also be discussed.
Quantum Monte Carlo calculations of light nuclei.
Pieper, S. C.
1998-08-25
Quantum Monte Carlo calculations using realistic two- and three-nucleon interactions are presented for nuclei with up to eight nucleons. We have computed the ground and a few excited states of all such nuclei with Greens function Monte Carlo (GFMC) and all of the experimentally known excited states using variational Monte Carlo (VMC). The GFMC calculations show that for a given Hamiltonian, the VMC calculations of excitation spectra are reliable, but the VMC ground-state energies are significantly above the exact values. We find that the Hamiltonian we are using (which was developed based on {sup 3}H, {sup 4}He, and nuclear matter calculations) underpredicts the binding energy of p-shell nuclei. However our results for excitation spectra are very good and one can see both shell-model and collective spectra resulting from fundamental many-nucleon calculations. Possible improvements in the three-nucleon potential are also be discussed.
Fast quantum Monte Carlo on a GPU
NASA Astrophysics Data System (ADS)
Lutsyshyn, Y.
2015-02-01
We present a scheme for the parallelization of quantum Monte Carlo method on graphical processing units, focusing on variational Monte Carlo simulation of bosonic systems. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent utilization of the accelerator. The CUDA code is provided along with a package that simulates liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the Kepler architecture K20 GPU. Special optimization was developed for the Kepler cards, including placement of data structures in the register space of the Kepler GPUs. Kepler-specific optimization is discussed.
Monte Carlo dose computation for IMRT optimization*
NASA Astrophysics Data System (ADS)
Laub, W.; Alber, M.; Birkner, M.; Nüsslin, F.
2000-07-01
A method which combines the accuracy of Monte Carlo dose calculation with a finite size pencil-beam based intensity modulation optimization is presented. The pencil-beam algorithm is employed to compute the fluence element updates for a converging sequence of Monte Carlo dose distributions. The combination is shown to improve results over the pencil-beam based optimization in a lung tumour case and a head and neck case. Inhomogeneity effects like a broader penumbra and dose build-up regions can be compensated for by intensity modulation.
Monte Carlo simulation of an expanding gas
NASA Technical Reports Server (NTRS)
Boyd, Iain D.
1989-01-01
By application of simple computer graphics techniques, the statistical performance of two Monte Carlo methods used in the simulation of rarefied gas flows are assessed. Specifically, two direct simulation Monte Carlo (DSMC) methods developed by Bird and Nanbu are considered. The graphics techniques are found to be of great benefit in the reduction and interpretation of the large volume of data generated, thus enabling important conclusions to be drawn about the simulation results. Hence, it is discovered that the method of Nanbu suffers from increased statistical fluctuations, thereby prohibiting its use in the solution of practical problems.
Geodesic Monte Carlo on Embedded Manifolds.
Byrne, Simon; Girolami, Mark
2013-12-01
Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton-Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024
Geodesic Monte Carlo on Embedded Manifolds
Byrne, Simon; Girolami, Mark
2013-01-01
Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024
Chemical application of diffusion quantum Monte Carlo
NASA Technical Reports Server (NTRS)
Reynolds, P. J.; Lester, W. A., Jr.
1984-01-01
The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. This approach is receiving increasing attention in chemical applications as a result of its high accuracy. However, reducing statistical uncertainty remains a priority because chemical effects are often obtained as small differences of large numbers. As an example, the single-triplet splitting of the energy of the methylene molecule CH sub 2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on the VAX 11/780, and second by explicitly writing vector code for all loops longer than a crossover length C. The speed of the codes relative to one another as a function of C, and relative to the VAX, are discussed. The computational time dependence obtained versus the number of basis functions is discussed and this is compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures.
Theory and Applications of Quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Deible, Michael John
With the development of peta-scale computers and exa-scale only a few years away, the quantum Monte Carlo (QMC) method, with favorable scaling and inherent parrallelizability, is poised to increase its impact on the electronic structure community. The most widely used variation of QMC is the diffusion Monte Carlo (DMC) method. The accuracy of the DMC method is only limited by the trial wave function that it employs. The effect of the trial wave function is studied here by initially developing correlation-consistent Gaussian basis sets for use in DMC calculations. These basis sets give a low variance in variance Monte Carlo calculations and improved convergence in DMC. The orbital type used in the trial wave function is then investigated, and it is shown that Brueckner orbitals result in a DMC energy comparable to a DMC energy with orbitals from density functional theory and significantly lower than orbitals from Hartree-Fock theory. Three large weakly interacting systems are then studied; a water-16 isomer, a methane clathrate, and a carbon dioxide clathrate. The DMC method is seen to be in good agreement with MP2 calculations and provides reliable benchmarks. Several strongly correlated systems are then studied. An H4 model system that allows for a fine tuning of the multi-configurational character of the wave function shows when the accuracy of the DMC method with a single Slater-determinant trial function begins to deviate from multi-reference benchmarks. The weakly interacting face-to-face ethylene dimer is studied with and without a rotation around the pi bond, which is used to increase the multi-configurational nature of the wave function. This test shows that the effect of a multi-configurational wave function in weakly interacting systems causes DMC with a single Slater-determinant to be unable to achieve sub-chemical accuracy. The beryllium dimer is studied, and it is shown that a very large determinant expansion is required for DMC to predict a binding
A comparison of Monte Carlo generators
NASA Astrophysics Data System (ADS)
Golan, Tomasz
2015-05-01
A comparison of GENIE, NEUT, NUANCE, and NuWro Monte Carlo neutrino event generators is presented using a set of four observables: protons multiplicity, total visible energy, most energetic proton momentum, and π+ two-dimensional energy vs cosine distribution.
MCMAC: Monte Carlo Merger Analysis Code
NASA Astrophysics Data System (ADS)
Dawson, William A.
2014-07-01
Monte Carlo Merger Analysis Code (MCMAC) aids in the study of merging clusters. It takes observed priors on each subcluster's mass, radial velocity, and projected separation, draws randomly from those priors, and uses them in a analytic model to get posterior PDF's for merger dynamic properties of interest (e.g. collision velocity, time since collision).
A quasi-Monte Carlo Metropolis algorithm
Owen, Art B.; Tribble, Seth D.
2005-01-01
This work presents a version of the Metropolis–Hastings algorithm using quasi-Monte Carlo inputs. We prove that the method yields consistent estimates in some problems with finite state spaces and completely uniformly distributed inputs. In some numerical examples, the proposed method is much more accurate than ordinary Metropolis–Hastings sampling. PMID:15956207
Monte Carlo methods in genetic analysis
Lin, Shili
1996-12-31
Many genetic analyses require computation of probabilities and likelihoods of pedigree data. With more and more genetic marker data deriving from new DNA technologies becoming available to researchers, exact computations are often formidable with standard statistical methods and computational algorithms. The desire to utilize as much available data as possible, coupled with complexities of realistic genetic models, push traditional approaches to their limits. These methods encounter severe methodological and computational challenges, even with the aid of advanced computing technology. Monte Carlo methods are therefore increasingly being explored as practical techniques for estimating these probabilities and likelihoods. This paper reviews the basic elements of the Markov chain Monte Carlo method and the method of sequential imputation, with an emphasis upon their applicability to genetic analysis. Three areas of applications are presented to demonstrate the versatility of Markov chain Monte Carlo for different types of genetic problems. A multilocus linkage analysis example is also presented to illustrate the sequential imputation method. Finally, important statistical issues of Markov chain Monte Carlo and sequential imputation, some of which are unique to genetic data, are discussed, and current solutions are outlined. 72 refs.
Scalable Domain Decomposed Monte Carlo Particle Transport
O'Brien, Matthew Joseph
2013-12-05
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.
A comparison of Monte Carlo generators
Golan, Tomasz
2015-05-15
A comparison of GENIE, NEUT, NUANCE, and NuWro Monte Carlo neutrino event generators is presented using a set of four observables: protons multiplicity, total visible energy, most energetic proton momentum, and π{sup +} two-dimensional energy vs cosine distribution.
Monte Carlo simulations of lattice gauge theories
Rebbi, C
1980-02-01
Monte Carlo simulations done for four-dimensional lattice gauge systems are described, where the gauge group is one of the following: U(1); SU(2); Z/sub N/, i.e., the subgroup of U(1) consisting of the elements e 2..pi..in/N with integer n and N; the eight-element group of quaternions, Q; the 24- and 48-element subgroups of SU(2), denoted by T and O, which reduce to the rotation groups of the tetrahedron and the octahedron when their centers Z/sub 2/, are factored out. All of these groups can be considered subgroups of SU(2) and a common normalization was used for the action. The following types of Monte Carlo experiments are considered: simulations of a thermal cycle, where the temperature of the system is varied slightly every few Monte Carlo iterations and the internal energy is measured; mixed-phase runs, where several Monte Carlo iterations are done at a few temperatures near a phase transition starting with a lattice which is half ordered and half disordered; measurements of averages of Wilson factors for loops of different shape. 5 figures, 1 table. (RWR)
Frequency domain optical tomography using a Monte Carlo perturbation method
NASA Astrophysics Data System (ADS)
Yamamoto, Toshihiro; Sakamoto, Hiroki
2016-04-01
A frequency domain Monte Carlo method is applied to near-infrared optical tomography, where an intensity-modulated light source with a given modulation frequency is used to reconstruct optical properties. The frequency domain reconstruction technique allows for better separation between the scattering and absorption properties of inclusions, even for ill-posed inverse problems, due to cross-talk between the scattering and absorption reconstructions. The frequency domain Monte Carlo calculation for light transport in an absorbing and scattering medium has thus far been analyzed mostly for the reconstruction of optical properties in simple layered tissues. This study applies a Monte Carlo calculation algorithm, which can handle complex-valued particle weights for solving a frequency domain transport equation, to optical tomography in two-dimensional heterogeneous tissues. The Jacobian matrix that is needed to reconstruct the optical properties is obtained by a first-order "differential operator" technique, which involves less variance than the conventional "correlated sampling" technique. The numerical examples in this paper indicate that the newly proposed Monte Carlo method provides reconstructed results for the scattering and absorption coefficients that compare favorably with the results obtained from conventional deterministic or Monte Carlo methods.
Quantum Monte Carlo simulations of tunneling in quantum adiabatic optimization
NASA Astrophysics Data System (ADS)
Brady, Lucas T.; van Dam, Wim
2016-03-01
We explore to what extent path-integral quantum Monte Carlo methods can efficiently simulate quantum adiabatic optimization algorithms during a quantum tunneling process. Specifically we look at symmetric cost functions defined over n bits with a single potential barrier that a successful quantum adiabatic optimization algorithm will have to tunnel through. The height and width of this barrier depend on n , and by tuning these dependencies, we can make the optimization algorithm succeed or fail in polynomial time. In this article we compare the strength of quantum adiabatic tunneling with that of path-integral quantum Monte Carlo methods. We find numerical evidence that quantum Monte Carlo algorithms will succeed in the same regimes where quantum adiabatic optimization succeeds.
Monte Carlo simulations of phosphate polyhedron connectivity in glasses
ALAM,TODD M.
2000-01-01
Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.
Monte Carlo Simulations of Phosphate Polyhedron Connectivity in Glasses
ALAM,TODD M.
1999-12-21
Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.
NASA Astrophysics Data System (ADS)
Nettelbeck, H.; Takacs, G. J.; Rosenfeld, A. B.
2008-09-01
The application of a strong transverse magnetic field to a volume undergoing irradiation by a photon beam can produce localized regions of dose enhancement and dose reduction. This study uses the PENELOPE Monte Carlo code to investigate the effect of a slice of uniform transverse magnetic field on a photon beam using different magnetic field strengths and photon beam energies. The maximum and minimum dose yields obtained in the regions of dose enhancement and dose reduction are compared to those obtained with the EGS4 Monte Carlo code in a study by Li et al (2001), who investigated the effect of a slice of uniform transverse magnetic field (1 to 20 Tesla) applied to high-energy photon beams. PENELOPE simulations yielded maximum dose enhancements and dose reductions as much as 111% and 77%, respectively, where most results were within 6% of the EGS4 result. Further PENELOPE simulations were performed with the Sheikh-Bagheri and Rogers (2002) input spectra for 6, 10 and 15 MV photon beams, yielding results within 4% of those obtained with the Mohan et al (1985) spectra. Small discrepancies between a few of the EGS4 and PENELOPE results prompted an investigation into the influence of the PENELOPE elastic scattering parameters C1 and C2 and low-energy electron and photon transport cut-offs. Repeating the simulations with smaller scoring bins improved the resolution of the regions of dose enhancement and dose reduction, especially near the magnetic field boundaries where the dose deposition can abruptly increase or decrease. This study also investigates the effect of a magnetic field on the low-energy electron spectrum that may correspond to a change in the radiobiological effectiveness (RBE). Simulations show that the increase in dose is achieved predominantly through the lower energy electron population.
Microbial contamination in poultry chillers estimated by Monte Carlo simulations
Technology Transfer Automated Retrieval System (TEKTRAN)
The risk of microbial contamination during poultry processing may be reduced by the operating characteristics of the chiller. The performance of air chillers and immersion chillers were compared in terms of pre-chill and post-chill contamination using Monte Carlo simulations. Three parameters were u...
Quantum Monte Carlo calculations for carbon nanotubes
NASA Astrophysics Data System (ADS)
Luu, Thomas; Lähde, Timo A.
2016-04-01
We show how lattice quantum Monte Carlo can be applied to the electronic properties of carbon nanotubes in the presence of strong electron-electron correlations. We employ the path-integral formalism and use methods developed within the lattice QCD community for our numerical work. Our lattice Hamiltonian is closely related to the hexagonal Hubbard model augmented by a long-range electron-electron interaction. We apply our method to the single-quasiparticle spectrum of the (3,3) armchair nanotube configuration, and consider the effects of strong electron-electron correlations. Our approach is equally applicable to other nanotubes, as well as to other carbon nanostructures. We benchmark our Monte Carlo calculations against the two- and four-site Hubbard models, where a direct numerical solution is feasible.
Status of Monte Carlo at Los Alamos
Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.
1980-05-01
Four papers were presented by Group X-6 on April 22, 1980, at the Oak Ridge Radiation Shielding Information Center (RSIC) Seminar-Workshop on Theory and Applications of Monte Carlo Methods. These papers are combined into one report for convenience and because they are related to each other. The first paper (by Thompson and Cashwell) is a general survey about X-6 and MCNP and is an introduction to the other three papers. It can also serve as a resume of X-6. The second paper (by Godfrey) explains some of the details of geometry specification in MCNP. The third paper (by Cashwell and Schrandt) illustrates calculating flux at a point with MCNP; in particular, the once-more-collided flux estimator is demonstrated. Finally, the fourth paper (by Thompson, Deutsch, and Booth) is a tutorial on some variance-reduction techniques. It should be required for a fledging Monte Carlo practitioner.
Quantum Monte Carlo calculations of light nuclei.
Pieper, S. C.; Physics
2008-01-01
Variational Monte Carlo and Green's function Monte Carlo are powerful tools for cal- culations of properties of light nuclei using realistic two-nucleon (NN) and three-nucleon (NNN) potentials. Recently the GFMC method has been extended to multiple states with the same quantum numbers. The combination of the Argonne v18 two-nucleon and Illinois-2 three-nucleon potentials gives a good prediction of many energies of nuclei up to 12 C. A number of other recent results are presented: comparison of binding energies with those obtained by the no-core shell model; the incompatibility of modern nuclear Hamiltonians with a bound tetra-neutron; difficulties in computing RMS radii of very weakly bound nuclei, such as 6He; center-of-mass effects on spectroscopic factors; and the possible use of an artificial external well in calculations of neutron-rich isotopes.
Status of Monte Carlo at Los Alamos
Thompson, W.L.; Cashwell, E.D.
1980-01-01
At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time.
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc. PMID:26226927
Fast Lattice Monte Carlo Simulations of Polymers
NASA Astrophysics Data System (ADS)
Wang, Qiang; Zhang, Pengfei
2014-03-01
The recently proposed fast lattice Monte Carlo (FLMC) simulations (with multiple occupancy of lattice sites (MOLS) and Kronecker δ-function interactions) give much faster/better sampling of configuration space than both off-lattice molecular simulations (with pair-potential calculations) and conventional lattice Monte Carlo simulations (with self- and mutual-avoiding walk and nearest-neighbor interactions) of polymers.[1] Quantitative coarse-graining of polymeric systems can also be performed using lattice models with MOLS.[2] Here we use several model systems, including polymer melts, solutions, blends, as well as confined and/or grafted polymers, to demonstrate the great advantages of FLMC simulations in the study of equilibrium properties of polymers.
Monte-Carlo Opening Books for Amazons
NASA Astrophysics Data System (ADS)
Kloetzer, Julien
Automatically creating opening books is a natural step towards the building of strong game-playing programs, especially when there is little available knowledge about the game. However, while recent popular Monte-Carlo Tree-Search programs showed strong results for various games, we show here that programs based on such methods cannot efficiently use opening books created using algorithms based on minimax. To overcome this issue, we propose to use an MCTS-based technique, Meta-MCTS, to create such opening books. This method, while requiring some tuning to arrive at the best opening book possible, shows promising results to create an opening book for the game of the Amazons, even if this is at the cost of removing its Monte-Carlo part.
Monte Carlo Methods in the Physical Sciences
Kalos, M H
2007-06-06
I will review the role that Monte Carlo methods play in the physical sciences. They are very widely used for a number of reasons: they permit the rapid and faithful transformation of a natural or model stochastic process into a computer code. They are powerful numerical methods for treating the many-dimensional problems that derive from important physical systems. Finally, many of the methods naturally permit the use of modern parallel computers in efficient ways. In the presentation, I will emphasize four aspects of the computations: whether or not the computation derives from a natural or model stochastic process; whether the system under study is highly idealized or realistic; whether the Monte Carlo methodology is straightforward or mathematically sophisticated; and finally, the scientific role of the computation.
Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy
NASA Astrophysics Data System (ADS)
Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James
2012-03-01
Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.
Monte Carlo simulation of Alaska wolf survival
NASA Astrophysics Data System (ADS)
Feingold, S. J.
1996-02-01
Alaskan wolves live in a harsh climate and are hunted intensively. Penna's biological aging code, using Monte Carlo methods, has been adapted to simulate wolf survival. It was run on the case in which hunting causes the disruption of wolves' social structure. Social disruption was shown to increase the number of deaths occurring at a given level of hunting. For high levels of social disruption, the population did not survive.
Applications of Maxent to quantum Monte Carlo
Silver, R.N.; Sivia, D.S.; Gubernatis, J.E. ); Jarrell, M. . Dept. of Physics)
1990-01-01
We consider the application of maximum entropy methods to the analysis of data produced by computer simulations. The focus is the calculation of the dynamical properties of quantum many-body systems by Monte Carlo methods, which is termed the Analytical Continuation Problem.'' For the Anderson model of dilute magnetic impurities in metals, we obtain spectral functions and transport coefficients which obey Kondo Universality.'' 24 refs., 7 figs.
Linear-scaling quantum Monte Carlo calculations.
Williamson, A J; Hood, R Q; Grossman, J C
2001-12-10
A method is presented for using truncated, maximally localized Wannier functions to introduce sparsity into the Slater determinant part of the trial wave function in quantum Monte Carlo calculations. When combined with an efficient numerical evaluation of these localized orbitals, the dominant cost in the calculation, namely, the evaluation of the Slater determinant, scales linearly with system size. This technique is applied to accurate total energy calculation of hydrogenated silicon clusters and carbon fullerenes containing 20-1000 valence electrons. PMID:11736525
Monte Carlo calculation of monitor unit for electron arc therapy
Chow, James C. L.; Jiang Runqing
2010-04-15
Purpose: Monitor unit (MU) calculations for electron arc therapy were carried out using Monte Carlo simulations and verified by measurements. Variations in the dwell factor (DF), source-to-surface distance (SSD), and treatment arc angle ({alpha}) were studied. Moreover, the possibility of measuring the DF, which requires gantry rotation, using a solid water rectangular, instead of cylindrical, phantom was investigated. Methods: A phase space file based on the 9 MeV electron beam with rectangular cutout (physical size=2.6x21 cm{sup 2}) attached to the block tray holder of a Varian 21 EX linear accelerator (linac) was generated using the EGSnrc-based Monte Carlo code and verified by measurement. The relative output factor (ROF), SSD offset, and DF, needed in the MU calculation, were determined using measurements and Monte Carlo simulations. An ionization chamber, a radiographic film, a solid water rectangular phantom, and a cylindrical phantom made of polystyrene were used in dosimetry measurements. Results: Percentage deviations of ROF, SSD offset, and DF between measured and Monte Carlo results were 1.2%, 0.18%, and 1.5%, respectively. It was found that the DF decreased with an increase in {alpha}, and such a decrease in DF was more significant in the {alpha} range of 0 deg. - 60 deg. than 60 deg. - 120 deg. Moreover, for a fixed {alpha}, the DF increased with an increase in SSD. Comparing the DF determined using the rectangular and cylindrical phantom through measurements and Monte Carlo simulations, it was found that the DF determined by the rectangular phantom agreed well with that by the cylindrical one within {+-}1.2%. It shows that a simple setup of a solid water rectangular phantom was sufficient to replace the cylindrical phantom using our specific cutout to determine the DF associated with the electron arc. Conclusions: By verifying using dosimetry measurements, Monte Carlo simulations proved to be an alternative way to perform MU calculations effectively
jTracker and Monte Carlo Comparison
NASA Astrophysics Data System (ADS)
Selensky, Lauren; SeaQuest/E906 Collaboration
2015-10-01
SeaQuest is designed to observe the characteristics and behavior of `sea-quarks' in a proton by reconstructing them from the subatomic particles produced in a collision. The 120 GeV beam from the main injector collides with a fixed target and then passes through a series of detectors which records information about the particles produced in the collision. However, this data becomes meaningful only after it has been processed, stored, analyzed, and interpreted. Several programs are involved in this process. jTracker (sqerp) reads wire or hodoscope hits and reconstructs the tracks of potential dimuon pairs from a run, and Geant4 Monte Carlo simulates dimuon production and background noise from the beam. During track reconstruction, an event must meet the criteria set by the tracker to be considered a viable dimuon pair; this ensures that relevant data is retained. As a check, a comparison between a new version of jTracker and Monte Carlo was made in order to see how accurately jTracker could reconstruct the events created by Monte Carlo. In this presentation, the results of the inquest and their potential effects on the programming will be shown. This work is supported by U.S. DOE MENP Grant DE-FG02-03ER41243.
Path Integral Monte Carlo Methods for Fermions
NASA Astrophysics Data System (ADS)
Ethan, Ethan; Dubois, Jonathan; Ceperley, David
2014-03-01
In general, Quantum Monte Carlo methods suffer from a sign problem when simulating fermionic systems. This causes the efficiency of a simulation to decrease exponentially with the number of particles and inverse temperature. To circumvent this issue, a nodal constraint is often implemented, restricting the Monte Carlo procedure from sampling paths that cause the many-body density matrix to change sign. Unfortunately, this high-dimensional nodal surface is not a priori known unless the system is exactly solvable, resulting in uncontrolled errors. We will discuss two possible routes to extend the applicability of finite-temperatue path integral Monte Carlo. First we extend the regime where signful simulations are possible through a novel permutation sampling scheme. Afterwards, we discuss a method to variationally improve the nodal surface by minimizing a free energy during simulation. Applications of these methods will include both free and interacting electron gases, concluding with discussion concerning extension to inhomogeneous systems. Support from DOE DE-FG52-09NA29456, DE-AC52-07NA27344, LLNL LDRD 10- ERD-058, and the Lawrence Scholar program.
Ahmad, I.; Back, B.B.; Betts, R.R.
1995-08-01
An essential component in the assessment of the significance of the results from APEX is a demonstrated understanding of the acceptance and response of the apparatus. This requires detailed simulations which can be compared to the results of various source and in-beam measurements. These simulations were carried out using the computer codes EGS and GEANT, both specifically designed for this purpose. As far as is possible, all details of the geometry of APEX were included. We compared the results of these simulations with measurements using electron conversion sources, positron sources and pair sources. The overall agreement is quite acceptable and some of the details are still being worked on. The simulation codes were also used to compare the results of measurements of in-beam positron and conversion electrons with expectations based on known physics or other methods. Again, satisfactory agreement is achieved. We are currently working on the simulation of various pair-producing scenarios such as the decay of a neutral object in the mass range 1.5-2.0 MeV and also the emission of internal pairs from nuclear transitions in the colliding ions. These results are essential input to the final results from APEX on cross section limits for various, previously proposed, sharp-line producing scenarios.
Improved method for implicit Monte Carlo
Brown, F. B.; Martin, W. R.
2001-01-01
The Implicit Monte Carlo (IMC) method has been used for over 30 years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Reference [2] provided an exact error analysis of IMC for 0-D problems and demonstrated that IMC can exhibit substantial errors when timesteps are large. These temporal errors are inherent in the method and are in addition to spatial discretization errors and approximations that address nonlinearities (due to variation of physical constants). In Reference [3], IMC and four other methods were analyzed in detail and compared on both theoretical grounds and the accuracy of numerical tests. As discussed in, two alternative schemes for solving the radiative transfer equations, the Carter-Forest (C-F) method and the Ahrens-Larsen (A-L) method, do not exhibit the errors found in IMC; for 0-D, both of these methods are exact for all time, while for 3-D, A-L is exact for all time and C-F is exact within a timestep. These methods can yield substantially superior results to IMC.
Monte Carlo simulation of chromatin stretching.
Aumann, Frank; Lankas, Filip; Caudron, Maïwen; Langowski, Jörg
2006-04-01
We present Monte Carlo (MC) simulations of the stretching of a single chromatin fiber. The model approximates the DNA by a flexible polymer chain with Debye-Hückel electrostatics and uses a two-angle zigzag model for the geometry of the linker DNA connecting the nucleosomes. The latter are represented by flat disks interacting via an attractive Gay-Berne potential. Our results show that the stiffness of the chromatin fiber strongly depends on the linker DNA length. Furthermore, changing the twisting angle between nucleosomes from 90 degrees to 130 degrees increases the stiffness significantly. An increase in the opening angle from 22 degrees to 34 degrees leads to softer fibers for small linker lengths. We observe that fibers containing a linker histone at each nucleosome are stiffer compared to those without the linker histone. The simulated persistence lengths and elastic moduli agree with experimental data. Finally, we show that the chromatin fiber does not behave as an isotropic elastic rod, but its rigidity depends on the direction of deformation: Chromatin is much more resistant to stretching than to bending. PMID:16711856
Monte Carlo simulation of chromatin stretching
NASA Astrophysics Data System (ADS)
Aumann, Frank; Lankas, Filip; Caudron, Maïwen; Langowski, Jörg
2006-04-01
We present Monte Carlo (MC) simulations of the stretching of a single 30nm chromatin fiber. The model approximates the DNA by a flexible polymer chain with Debye-Hückel electrostatics and uses a two-angle zigzag model for the geometry of the linker DNA connecting the nucleosomes. The latter are represented by flat disks interacting via an attractive Gay-Berne potential. Our results show that the stiffness of the chromatin fiber strongly depends on the linker DNA length. Furthermore, changing the twisting angle between nucleosomes from 90° to 130° increases the stiffness significantly. An increase in the opening angle from 22° to 34° leads to softer fibers for small linker lengths. We observe that fibers containing a linker histone at each nucleosome are stiffer compared to those without the linker histone. The simulated persistence lengths and elastic moduli agree with experimental data. Finally, we show that the chromatin fiber does not behave as an isotropic elastic rod, but its rigidity depends on the direction of deformation: Chromatin is much more resistant to stretching than to bending.
Novel Quantum Monte Carlo Approaches for Quantum Liquids
NASA Astrophysics Data System (ADS)
Rubenstein, Brenda M.
the eventual hope is to apply this algorithm to the exploration of yet unidentified high-pressure, low-temperature phases of hydrogen, I employ this algorithm to determine whether or not quantum hard spheres can form a low-temperature bcc solid if exchange is not taken into account. In the final chapter of this thesis, I use Path Integral Monte Carlo once again to explore whether glassy para-hydrogen exhibits superfluidity. Physicists have long searched for ways to coax hydrogen into becoming a superfluid. I present evidence that, while glassy hydrogen does not crystallize at the temperatures at which hydrogen might become a superfluid, it nevertheless does not exhibit superfluidity. This is because the average binding energy per p-H2 molecule poses a severe barrier to exchange regardless of whether the system is crystalline. All in all, this work extends the reach of Quantum Monte Carlo methods to new systems and brings the power of existing methods to bear on new problems. Portions of this work have been published in Rubenstein, PRE (2010) and Rubenstein, PRA (2012) [167;169]. Other papers not discussed here published during my Ph.D. include Rubenstein, BPJ (2008) and Rubenstein, PRL (2012) [166;168]. The work in Chapters 6 and 7 is currently unpublished. [166] Brenda M. Rubenstein, Ivan Coluzza, and Mark A. Miller. Controlling the folding and substrate-binding of proteins using polymer brushes. Physical Review Letters, 108(20):208104, May 2012. [167] Brenda M. Rubenstein, J.E. Gubernatis, and J.D. Doll. Comparative monte carlo efficiency by monte carlo analysis. Physical Review E, 82(3):036701, September 2010. [168] Brenda M. Rubenstein and Laura J. Kaufman. The role of extracellular matrix in glioma invasion: A cellular potts model approach. Biophysical Journal, 95(12):5661-- 5680, December 2008. [169] Brenda M. Rubenstein, Shiwei Zhang, and David R. Reichman. Finite-temperature auxiliary-field quantum monte carlo for bose-fermi mixtures. Physical Review A, 86
Multiple-time-stepping generalized hybrid Monte Carlo methods
Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Multiple-time-stepping generalized hybrid Monte Carlo methods
NASA Astrophysics Data System (ADS)
Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2-4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Four decades of implicit Monte Carlo
Wollaber, Allan B.
2016-04-25
In 1971, Fleck and Cummings derived a system of equations to enable robust Monte Carlo simulations of time-dependent, thermal radiative transfer problems. Denoted the “Implicit Monte Carlo” (IMC) equations, their solution remains the de facto standard of high-fidelity radiative transfer simulations. Over the course of 44 years, their numerical properties have become better understood, and accuracy enhancements, novel acceleration methods, and variance reduction techniques have been suggested. In this review, we rederive the IMC equations—explicitly highlighting assumptions as they are made—and outfit the equations with a Monte Carlo interpretation. We put the IMC equations in context with other approximate formsmore » of the radiative transfer equations and present a new demonstration of their equivalence to another well-used linearization solved with deterministic transport methods for frequency-independent problems. We discuss physical and numerical limitations of the IMC equations for asymptotically small time steps, stability characteristics and the potential of maximum principle violations for large time steps, and solution behaviors in an asymptotically thick diffusive limit. We provide a new stability analysis for opacities with general monomial dependence on temperature. Here, we consider spatial accuracy limitations of the IMC equations and discussion acceleration and variance reduction techniques.« less
Direct aperture optimization for IMRT using Monte Carlo generated beamlets.
Bergman, Alanah M; Bush, Karl; Milette, Marie-Pierre; Popescu, I Antoniu; Otto, Karl; Duzenli, Cheryl
2006-10-01
This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods. PMID:17089832
A Monte Carlo approach to water management
NASA Astrophysics Data System (ADS)
Koutsoyiannis, D.
2012-04-01
Common methods for making optimal decisions in water management problems are insufficient. Linear programming methods are inappropriate because hydrosystems are nonlinear with respect to their dynamics, operation constraints and objectives. Dynamic programming methods are inappropriate because water management problems cannot be divided into sequential stages. Also, these deterministic methods cannot properly deal with the uncertainty of future conditions (inflows, demands, etc.). Even stochastic extensions of these methods (e.g. linear-quadratic-Gaussian control) necessitate such drastic oversimplifications of hydrosystems that may make the obtained results irrelevant to the real world problems. However, a Monte Carlo approach is feasible and can form a general methodology applicable to any type of hydrosystem. This methodology uses stochastic simulation to generate system inputs, either unconditional or conditioned on a prediction, if available, and represents the operation of the entire system through a simulation model as faithful as possible, without demanding a specific mathematical form that would imply oversimplifications. Such representation fully respects the physical constraints, while at the same time it evaluates the system operation constraints and objectives in probabilistic terms, and derives their distribution functions and statistics through Monte Carlo simulation. As the performance criteria of a hydrosystem operation will generally be highly nonlinear and highly nonconvex functions of the control variables, a second Monte Carlo procedure, implementing stochastic optimization, is necessary to optimize system performance and evaluate the control variables of the system. The latter is facilitated if the entire representation is parsimonious, i.e. if the number of control variables is kept at a minimum by involving a suitable system parameterization. The approach is illustrated through three examples for (a) a hypothetical system of two reservoirs
Status of Monte-Carlo Event Generators
Hoeche, Stefan; /SLAC
2011-08-11
Recent progress on general-purpose Monte-Carlo event generators is reviewed with emphasis on the simulation of hard QCD processes and subsequent parton cascades. Describing full final states of high-energy particle collisions in contemporary experiments is an intricate task. Hundreds of particles are typically produced, and the reactions involve both large and small momentum transfer. The high-dimensional phase space makes an exact solution of the problem impossible. Instead, one typically resorts to regarding events as factorized into different steps, ordered descending in the mass scales or invariant momentum transfers which are involved. In this picture, a hard interaction, described through fixed-order perturbation theory, is followed by multiple Bremsstrahlung emissions off initial- and final-state and, finally, by the hadronization process, which binds QCD partons into color-neutral hadrons. Each of these steps can be treated independently, which is the basic concept inherent to general-purpose event generators. Their development is nowadays often focused on an improved description of radiative corrections to hard processes through perturbative QCD. In this context, the concept of jets is introduced, which allows to relate sprays of hadronic particles in detectors to the partons in perturbation theory. In this talk, we briefly review recent progress on perturbative QCD in event generation. The main focus lies on the general-purpose Monte-Carlo programs HERWIG, PYTHIA and SHERPA, which will be the workhorses for LHC phenomenology. A detailed description of the physics models included in these generators can be found in [8]. We also discuss matrix-element generators, which provide the parton-level input for general-purpose Monte Carlo.
Monte Carlo simulation of intercalated carbon nanotubes.
Mykhailenko, Oleksiy; Matsui, Denis; Prylutskyy, Yuriy; Le Normand, Francois; Eklund, Peter; Scharff, Peter
2007-01-01
Monte Carlo simulations of the single- and double-walled carbon nanotubes (CNT) intercalated with different metals have been carried out. The interrelation between the length of a CNT, the number and type of metal atoms has also been established. This research is aimed at studying intercalated systems based on CNTs and d-metals such as Fe and Co. Factors influencing the stability of these composites have been determined theoretically by the Monte Carlo method with the Tersoff potential. The modeling of CNTs intercalated with metals by the Monte Carlo method has proved that there is a correlation between the length of a CNT and the number of endo-atoms of specific type. Thus, in the case of a metallic CNT (9,0) with length 17 bands (3.60 nm), in contrast to Co atoms, Fe atoms are extruded out of the CNT if the number of atoms in the CNT is not less than eight. Thus, this paper shows that a CNT of a certain size can be intercalated with no more than eight Fe atoms. The systems investigated are stabilized by coordination of 3d-atoms close to the CNT wall with a radius-vector of (0.18-0.20) nm. Another characteristic feature is that, within the temperature range of (400-700) K, small systems exhibit ground-state stabilization which is not characteristic of the higher ones. The behavior of Fe and Co endo-atoms between the walls of a double-walled carbon nanotube (DW CNT) is explained by a dominating van der Waals interaction between the Co atoms themselves, which is not true for the Fe atoms. PMID:17033783
Quantum Monte Carlo for vibrating molecules
Brown, W.R. |
1996-08-01
Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H{sub 2}O and C{sub 3} vibrational states, using 7 PES`s, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H{sub 2}O and C{sub 3}. In order to construct accurate trial wavefunctions for C{sub 3}, the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C{sub 3} the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C{sub 3} PES`s suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies.
Kinetic Monte Carlo simulations of proton conductivity
NASA Astrophysics Data System (ADS)
Masłowski, T.; Drzewiński, A.; Ulner, J.; Wojtkiewicz, J.; Zdanowska-Frączek, M.; Nordlund, K.; Kuronen, A.
2014-07-01
The kinetic Monte Carlo method is used to model the dynamic properties of proton diffusion in anhydrous proton conductors. The results have been discussed with reference to a two-step process called the Grotthuss mechanism. There is a widespread belief that this mechanism is responsible for fast proton mobility. We showed in detail that the relative frequency of reorientation and diffusion processes is crucial for the conductivity. Moreover, the current dependence on proton concentration has been analyzed. In order to test our microscopic model the proton transport in polymer electrolyte membranes based on benzimidazole C7H6N2 molecules is studied.
Quantum Monte Carlo calculations for light nuclei.
Wiringa, R. B.
1998-10-23
Quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A {le} 8 are made using a realistic Hamiltonian that fits NN scattering data. Results for more than 40 different (J{pi}, T) states, plus isobaric analogs, are obtained and the known excitation spectra are reproduced reasonably well. Various density and momentum distributions and electromagnetic form factors and moments have also been computed. These are the first microscopic calculations that directly produce nuclear shell structure from realistic NN interactions.
Marcus, Ryan C.
2012-07-24
Overview of this presentation is (1) Exascale computing - different technologies, getting there; (2) high-performance proof-of-concept MCMini - features and results; and (3) OpenCL toolkit - Oatmeal (OpenCL Automatic Memory Allocation Library) - purpose and features. Despite driver issues, OpenCL seems like a good, hardware agnostic tool. MCMini demonstrates the possibility for GPGPU-based Monte Carlo methods - it shows great scaling for HPC application and algorithmic equivalence. Oatmeal provides a flexible framework to aid in the development of scientific OpenCL codes.
Monte Carlo procedure for protein design
NASA Astrophysics Data System (ADS)
Irbäck, Anders; Peterson, Carsten; Potthast, Frank; Sandelin, Erik
1998-11-01
A method for sequence optimization in protein models is presented. The approach, which has inherited its basic philosophy from recent work by Deutsch and Kurosky [Phys. Rev. Lett. 76, 323 (1996)] by maximizing conditional probabilities rather than minimizing energy functions, is based upon a different and very efficient multisequence Monte Carlo scheme. By construction, the method ensures that the designed sequences represent good folders thermodynamically. A bootstrap procedure for the sequence space search is devised making very large chains feasible. The algorithm is successfully explored on the two-dimensional HP model [K. F. Lau and K. A. Dill, Macromolecules 32, 3986 (1989)] with chain lengths N=16, 18, and 32.
Discovering correlated fermions using quantum Monte Carlo.
Wagner, Lucas K; Ceperley, David M
2016-09-01
It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons, focusing on the fundamentals, capabilities, and current status of this technique. The QMC methods often offer the highest accuracy solutions available for systems in the continuum, and, since they address the many-body problem directly, the simulations can be analyzed to obtain insight into the nature of correlated quantum behavior. PMID:27518859
Monte Carlo methods to calculate impact probabilities
NASA Astrophysics Data System (ADS)
Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.
2014-09-01
Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward
Monte Carlo radiation transport¶llelism
Cox, L. J.; Post, S. E.
2002-01-01
This talk summarizes the main aspects of the LANL ASCI Eolus project and its major unclassified code project, MCNP. The MCNP code provide a state-of-the-art Monte Carlo radiation transport to approximately 3000 users world-wide. Almost all hardware platforms are supported because we strictly adhere to the FORTRAN-90/95 standard. For parallel processing, MCNP uses a mixture of OpenMp combined with either MPI or PVM (shared and distributed memory). This talk summarizes our experiences on various platforms using MPI with and without OpenMP. These platforms include PC-Windows, Intel-LINUX, BlueMountain, Frost, ASCI-Q and others.
Monte Carlo simulation for the transport beamline
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.
2013-07-26
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.
Discovering correlated fermions using quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Wagner, Lucas K.; Ceperley, David M.
2016-09-01
It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons, focusing on the fundamentals, capabilities, and current status of this technique. The QMC methods often offer the highest accuracy solutions available for systems in the continuum, and, since they address the many-body problem directly, the simulations can be analyzed to obtain insight into the nature of correlated quantum behavior.
Monte Carlo analysis of magnetic aftereffect phenomena
NASA Astrophysics Data System (ADS)
Andrei, Petru; Stancu, Alexandru
2006-04-01
Magnetic aftereffect phenomena are analyzed by using the Monte Carlo technique. This technique has the advantage that it can be applied to any model of hysteresis. It is shown that a log t-type dependence of the magnetization can be qualitatively predicted even in the framework of hysteresis models with local history, such as the Jiles-Atherton model. These models are computationally much more efficient than the models with global history such as the Preisach model. Numerical results related to the decay of the magnetization as of function of time, as well as to the viscosity coefficient, are presented.
Monte Carlo simulation of the enantioseparation process
NASA Astrophysics Data System (ADS)
Bustos, V. A.; Acosta, G.; Gomez, M. R.; Pereyra, V. D.
2012-09-01
By means of Monte Carlo simulation, a study of enantioseparation by capillary electrophoresis has been carried out. A simplified system consisting of two enantiomers S (R) and a selector chiral C, which reacts with the enantiomers to form complexes RC (SC), has been considered. The dependence of Δμ (enantioseparation) with the concentration of chiral selector and with temperature have been analyzed by simulation. The effect of the binding constant and the charge of the complexes are also analyzed. The results are qualitatively satisfactory, despite the simplicity of the model.
A Monte Carlo algorithm for degenerate plasmas
Turrell, A.E. Sherlock, M.; Rose, S.J.
2013-09-15
A procedure for performing Monte Carlo calculations of plasmas with an arbitrary level of degeneracy is outlined. It has possible applications in inertial confinement fusion and astrophysics. Degenerate particles are initialised according to the Fermi–Dirac distribution function, and scattering is via a Pauli blocked binary collision approximation. The algorithm is tested against degenerate electron–ion equilibration, and the degenerate resistivity transport coefficient from unmagnetised first order transport theory. The code is applied to the cold fuel shell and alpha particle equilibration problem of inertial confinement fusion.
Modulated pulse bathymetric lidar Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Luo, Tao; Wang, Yabo; Wang, Rong; Du, Peng; Min, Xia
2015-10-01
A typical modulated pulse bathymetric lidar system is investigated by simulation using a modulated pulse lidar simulation system. In the simulation, the return signal is generated by Monte Carlo method with modulated pulse propagation model and processed by mathematical tools like cross-correlation and digital filter. Computer simulation results incorporating the modulation detection scheme reveal a significant suppression of the water backscattering signal and corresponding target contrast enhancement. More simulation experiments are performed with various modulation and reception variables to investigate the effect of them on the bathymetric system performance.
Monte Carlo Simulations for Spinodal Decomposition
NASA Astrophysics Data System (ADS)
Sander, Evelyn; Wanner, Thomas
1999-06-01
This paper addresses the phenomenon of spinodal decomposition for the Cahn-Hilliard equation. Namely, we are interested in why most solutions to the Cahn-Hilliard equation which start near a homogeneous equilibrium u 0≡ μ in the spinodal interval exhibit phase separation with a characteristic wavelength when exiting a ball of radius R in a Hilbert space centered at u 0. There are two mathematical explanations for spinodal decomposition, due to Grant and to Maier-Paape and Wanner. In this paper, we numerically compare these two mathematical approaches. In fact, we are able to synthesize the understanding we gain from our numerics with the approach of Maier-Paape and Wanner, leading to a better understanding of the underlying mechanism for this behavior. With this new approach, we can explain spinodal decomposition for a longer time and larger radius than either of the previous two approaches. A rigorous mathematical explanation is contained in a separate paper. Our approach is to use Monte Carlo simulations to examine the dependence of R, the radius to which spinodal decomposition occurs, as a function of the parameter ɛ of the governing equation. We give a description of the dominating regions on the surface of the ball by estimating certain densities of the distributions of the exit points. We observe, and can show rigorously, that the behavior of most solutions originating near the equilibrium is determined completely by the linearization for an unexpectedly long time. We explain the mechanism for this unexpectedly linear behavior, and show that for some exceptional solutions this cannot be observed. We also describe the dynamics of these exceptional solutions.
Monte Carlo simulations for spinodal decomposition
Sander, E.; Wanner, T.
1999-06-01
This paper addresses the phenomenon of spinodal decomposition for the Cahn-Hilliard equation. Namely, the authors are interested in why most solutions to the Cahn-Hilliard equation which start near a homogeneous equilibrium u{sub 0} {equivalent_to} {mu} in the spinodal interval exhibit phase separation with a characteristic wavelength when exiting a ball of radius R in a Hilbert space centered at u{sub 0}. There are two mathematical explanations for spinodal decomposition, due to Grant and to Maier-Paape and Wanner. In this paper, the authors numerically compare these two mathematical approaches. In fact, they are able to synthesize the understanding they gain from the numerics with the approach of Maier-Paape and Wanner, leading to a better understanding of the underlying mechanism for this behavior. With this new approach, they can explain spinodal decomposition for a longer time and larger radius than either of the previous two approaches. A rigorous mathematical explanation is contained in a separate paper. The approach is to use Monte Carlo simulations to examine the dependence of R, the radius to which spinodal decomposition occurs, as a function of the parameter {var_epsilon} of the governing equation. The authors give a description of the dominating regions on the surface of the ball by estimating certain densities of the distributions of the exit points. They observe, and can show rigorously, that the behavior of most solutions originating near the equilibrium is determined completely by the linearization for an unexpectedly long time. They explain the mechanism for this unexpectedly linear behavior, and show that for some exceptional solutions this cannot be observed. They also describe the dynamics of these exceptional solutions.
Quantum Monte Carlo : not just for energy levels.
Nollett, K. M.; Physics
2007-01-01
Quantum Monte Carlo and realistic interactions can provide well-motivated vertices and overlaps for DWBA analyses of reactions. Given an interaction in vaccum, there are several computational approaches to nuclear systems, as you have been hearing: No-core shell model with Lee-Suzuki or Bloch-Horowitz for Hamiltonian Coupled clusters with G-matrix interaction Density functional theory, granted an energy functional derived from the interaction Quantum Monte Carlo - Variational Monte Carlo Green's function Monte Carlo. The last two work directly with a bare interaction and bare operators and describe the wave function without expanding in basis functions, so they have rather different sets of advantages and disadvantages from the others. Variational Monte Carlo (VMC) is built on a sophisticated Ansatz for the wave function, built on shell model like structure modified by operator correlations. Green's function Monte Carlo (GFMC) uses an operator method to project the true ground state out of a reasonable guess wave function.
Discrete diffusion Monte Carlo for frequency-dependent radiative transfer
Densmore, Jeffrey D; Kelly, Thompson G; Urbatish, Todd J
2010-11-17
Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique.
Quantum Monte Carlo Endstation for Petascale Computing
David Ceperley
2011-03-02
CUDA GPU platform. We restructured the CPU algorithms to express additional parallelism, minimize GPU-CPU communication, and efficiently utilize the GPU memory hierarchy. Using mixed precision on GT200 GPUs and MPI for intercommunication and load balancing, we observe typical full-application speedups of approximately 10x to 15x relative to quad-core Xeon CPUs alone, while reproducing the double-precision CPU results within statistical error. We developed an all-electron quantum Monte Carlo (QMC) method for solids that does not rely on pseudopotentials, and used it to construct a primary ultra-high-pressure calibration based on the equation of state of cubic boron nitride. We computed the static contribution to the free energy with the QMC method and obtained the phonon contribution from density functional theory, yielding a high-accuracy calibration up to 900 GPa usable directly in experiment. We computed the anharmonic Raman frequency shift with QMC simulations as a function of pressure and temperature, allowing optical pressure calibration. In contrast to present experimental approaches, small systematic errors in the theoretical EOS do not increase with pressure, and no extrapolation is needed. This all-electron method is applicable to first-row solids, providing a new reference for ab initio calculations of solids and benchmarks for pseudopotential accuracy. We compared experimental and theoretical results on the momentum distribution and the quasiparticle renormalization factor in sodium. From an x-ray Compton-profile measurement of the valence-electron momentum density, we derived its discontinuity at the Fermi wavevector finding an accurate measure of the renormalization factor that we compared with quantum-Monte-Carlo and G0W0 calculations performed both on crystalline sodium and on the homogeneous electron gas. Our calculated results are in good agreement with the experiment. We have been studying the heat of formation for various Kubas complexes of molecular
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; Pieper, Steven C.; Schiavilla, Rocco; Schmidt, K. E,; Wiringa, Robert B.
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Scalable Domain Decomposed Monte Carlo Particle Transport
NASA Astrophysics Data System (ADS)
O'Brien, Matthew Joseph
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.
Composite biasing in Monte Carlo radiative transfer
NASA Astrophysics Data System (ADS)
Baes, Maarten; Gordon, Karl D.; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf
2016-05-01
Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the potential introduction of large weight factors. We discuss a general strategy, composite biasing, to suppress the appearance of large weight factors. We use this composite biasing approach for two different problems faced by current state-of-the-art Monte Carlo radiative transfer codes: the generation of photon packages from multiple components, and the penetration of radiation through high optical depth barriers. In both cases, the implementation of the relevant algorithms is trivial and does not interfere with any other optimisation techniques. Through simple test models, we demonstrate the general applicability, accuracy and efficiency of the composite biasing approach. In particular, for the penetration of high optical depths, the gain in efficiency is spectacular for the specific problems that we consider: in simulations with composite path length stretching, high accuracy results are obtained even for simulations with modest numbers of photon packages, while simulations without biasing cannot reach convergence, even with a huge number of photon packages.
Calculating Pi Using the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Williamson, Timothy
2013-11-01
During the summer of 2012, I had the opportunity to participate in a research experience for teachers at the center for sustainable energy at Notre Dame University (RET @ cSEND) working with Professor John LoSecco on the problem of using antineutrino detection to accurately determine the fuel makeup and operating power of nuclear reactors. During full power operation, a reactor may produce 1021 antineutrinos per second with approximately 100 per day being detected. While becoming familiar with the design and operation of the detectors, and how total antineutrino flux could be obtained from such a small sample, I read about a simulation program called Monte Carlo. Further investigation led me to the Monte Carlo method page of Wikipedia2 where I saw an example of approximating pi using this simulation. Other examples where this method was applied were typically done with computer simulations2 or purely mathematical.3 It is my belief that this method may be easily related to the students by performing the simple activity of sprinkling rice on an arc drawn in a square. The activity that follows was inspired by those simulations and was used by my AP Physics class last year with very good results.
THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE
WATERS, LAURIE S.; MCKINNEY, GREGG W.; DURKEE, JOE W.; FENSIN, MICHAEL L.; JAMES, MICHAEL R.; JOHNS, RUSSELL C.; PELOWITZ, DENISE B.
2007-01-10
MCNPX (Monte Carlo N-Particle eXtended) is a general-purpose Monte Carlo radiation transport code with three-dimensional geometry and continuous-energy transport of 34 particles and light ions. It contains flexible source and tally options, interactive graphics, and support for both sequential and multi-processing computer platforms. MCNPX is based on MCNP4B, and has been upgraded to most MCNP5 capabilities. MCNP is a highly stable code tracking neutrons, photons and electrons, and using evaluated nuclear data libraries for low-energy interaction probabilities. MCNPX has extended this base to a comprehensive set of particles and light ions, with heavy ion transport in development. Models have been included to calculate interaction probabilities when libraries are not available. Recent additions focus on the time evolution of residual nuclei decay, allowing calculation of transmutation and delayed particle emission. MCNPX is now a code of great dynamic range, and the excellent neutronics capabilities allow new opportunities to simulate devices of interest to experimental particle physics; particularly calorimetry. This paper describes the capabilities of the current MCNPX version 2.6.C, and also discusses ongoing code development.
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-01
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-01
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit,more » and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; Pieper, Steven C.; Schiavilla, Rocco; Schmidt, K. E,; Wiringa, Robert B.
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-bodymore » interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
Monte Carlo simulations within avalanche rescue
NASA Astrophysics Data System (ADS)
Reiweger, Ingrid; Genswein, Manuel; Schweizer, Jürg
2016-04-01
Refining concepts for avalanche rescue involves calculating suitable settings for rescue strategies such as an adequate probing depth for probe line searches or an optimal time for performing resuscitation for a recovered avalanche victim in case of additional burials. In the latter case, treatment decisions have to be made in the context of triage. However, given the low number of incidents it is rarely possible to derive quantitative criteria based on historical statistics in the context of evidence-based medicine. For these rare, but complex rescue scenarios, most of the associated concepts, theories, and processes involve a number of unknown "random" parameters which have to be estimated in order to calculate anything quantitatively. An obvious approach for incorporating a number of random variables and their distributions into a calculation is to perform a Monte Carlo (MC) simulation. We here present Monte Carlo simulations for calculating the most suitable probing depth for probe line searches depending on search area and an optimal resuscitation time in case of multiple avalanche burials. The MC approach reveals, e.g., new optimized values for the duration of resuscitation that differ from previous, mainly case-based assumptions.
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
2014-05-29
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε–2) or (ε–2(lnε)2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε–3) for direct simulation Monte Carlo or binary collision methods.more » We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10–5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.« less
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
2014-05-29
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε^{–2}) or (ε^{–2}(lnε)^{2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε^{–3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10^{–5}. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-09
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Quantum Monte Carlo for atoms and molecules
Barnett, R.N.
1989-11-01
The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H{sub 2}, LiH, Li{sub 2}, and H{sub 2}O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li{sub 2}, and H{sub 2}O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations, the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions.
Metallic lithium by quantum Monte Carlo
Sugiyama, G.; Zerah, G.; Alder, B.J.
1986-12-01
Lithium was chosen as the simplest known metal for the first application of quantum Monte Carlo methods in order to evaluate the accuracy of conventional one-electron band theories. Lithium has been extensively studied using such techniques. Band theory calculations have certain limitations in general and specifically in their application to lithium. Results depend on such factors as charge shape approximations (muffin tins), pseudopotentials (a special problem for lithium where the lack of rho core states requires a strong pseudopotential), and the form and parameters chosen for the exchange potential. The calculations are all one-electron methods in which the correlation effects are included in an ad hoc manner. This approximation may be particularly poor in the high compression regime, where the core states become delocalized. Furthermore, band theory provides only self-consistent results rather than strict limits on the energies. The quantum Monte Carlo method is a totally different technique using a many-body rather than a mean field approach which yields an upper bound on the energies. 18 refs., 4 figs., 1 tab.
Monte Carlo modeling of spatial coherence: free-space diffraction.
Fischer, David G; Prahl, Scott A; Duncan, Donald D
2008-10-01
We present a Monte Carlo method for propagating partially coherent fields through complex deterministic optical systems. A Gaussian copula is used to synthesize a random source with an arbitrary spatial coherence function. Physical optics and Monte Carlo predictions of the first- and second-order statistics of the field are shown for coherent and partially coherent sources for free-space propagation, imaging using a binary Fresnel zone plate, and propagation through a limiting aperture. Excellent agreement between the physical optics and Monte Carlo predictions is demonstrated in all cases. Convergence criteria are presented for judging the quality of the Monte Carlo predictions. PMID:18830335
Monte Carlo techniques for analyzing deep-penetration problems
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1986-02-01
Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications.
Estimation of beryllium ground state energy by Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Kabir, K. M. Ariful; Halder, Amal
2015-05-01
Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.
Estimation of beryllium ground state energy by Monte Carlo simulation
Kabir, K. M. Ariful; Halder, Amal
2015-05-15
Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.
Eells, Samantha J.; Bharadwa, Kiran; McKinnell, James A.; Miller, Loren G.
2014-01-01
Background. Recurrent urinary tract infections (UTIs) are a common problem among women. However, comparative effectiveness strategies for managing recurrent UTIs are lacking. Methods. We performed a systematic literature review of management of women experiencing ≥3 UTIs per year. We then developed a Markov chain Monte Carlo model of recurrent UTI for each management strategy with ≥2 adequate trials published. We simulated a cohort that experienced 3 UTIs/year and a secondary cohort that experienced 8 UTIs/year. Model outcomes were treatment efficacy, patient and payer cost, and health-related quality of life. Results. Five strategies had ≥2 clinical trials published: (1) daily antibiotic (nitrofurantoin) prophylaxis; (2) daily estrogen prophylaxis; (3) daily cranberry prophylaxis; (4) acupuncture prophylaxis; and (5) symptomatic self-treatment. In the 3 UTIs/year model, nitrofurantoin prophylaxis was most effective, reducing the UTI rate to 0.4 UTIs/year, and the most expensive to the payer ($821/year). All other strategies resulted in payer cost savings but were less efficacious. Symptomatic self-treatment was the only strategy that resulted in patient cost savings, and was the most favorable strategy in term of cost per quality-adjusted life-year (QALY) gained. Conclusions. Daily antibiotic use is the most effective strategy for recurrent UTI prevention compared to daily cranberry pills, daily estrogen therapy, and acupuncture. Cost savings to payers and patients were seen for most regimens, and improvement in QALYs were seen with all. Our findings provide clinically meaningful data to guide the physician–patient partnership in determining a preferred method of prevention for this common clinical problem. PMID:24065333
Quantum Monte Carlo Endstation for Petascale Computing
Lubos Mitas
2011-01-26
NCSU research group has been focused on accomplising the key goals of this initiative: establishing new generation of quantum Monte Carlo (QMC) computational tools as a part of Endstation petaflop initiative for use at the DOE ORNL computational facilities and for use by computational electronic structure community at large; carrying out high accuracy quantum Monte Carlo demonstration projects in application of these tools to the forefront electronic structure problems in molecular and solid systems; expanding the impact of QMC methods and approaches; explaining and enhancing the impact of these advanced computational approaches. In particular, we have developed quantum Monte Carlo code (QWalk, www.qwalk.org) which was significantly expanded and optimized using funds from this support and at present became an actively used tool in the petascale regime by ORNL researchers and beyond. These developments have been built upon efforts undertaken by the PI's group and collaborators over the period of the last decade. The code was optimized and tested extensively on a number of parallel architectures including petaflop ORNL Jaguar machine. We have developed and redesigned a number of code modules such as evaluation of wave functions and orbitals, calculations of pfaffians and introduction of backflow coordinates together with overall organization of the code and random walker distribution over multicore architectures. We have addressed several bottlenecks such as load balancing and verified efficiency and accuracy of the calculations with the other groups of the Endstation team. The QWalk package contains about 50,000 lines of high quality object-oriented C++ and includes also interfaces to data files from other conventional electronic structure codes such as Gamess, Gaussian, Crystal and others. This grant supported PI for one month during summers, a full-time postdoc and partially three graduate students over the period of the grant duration, it has resulted in 13
Monte Carlo Shell Model for ab initio nuclear structure
NASA Astrophysics Data System (ADS)
Abe, T.; Maris, P.; Otsuka, T.; Shimizu, N.; Utsuno, Y.; Vary, J. P.
2014-03-01
We report on our recent application of the Monte Carlo Shell Model to no-core calculations. At the initial stage of the application, we have performed benchmark calculations in the p-shell region. Results are compared with those in the Full Configuration Interaction and No-Core Full Configuration methods. These are found to be consistent with each other within quoted uncertainties when they could be quantified. The preliminary results in Nshell = 5 reveal the onset of systematic convergence pattern.
Adaptive mesh and algorithm refinement using direct simulation Monte Carlo
Garcia, A.L.; Bell, J.B.; Crutchfield, W.Y.; Alder, B.J.
1999-09-01
Adaptive mesh and algorithm refinement (AMAR) embeds a particle method within a continuum method at the finest level of an adaptive mesh refinement (AMR) hierarchy. The coupling between the particle region and the overlaying continuum grid is algorithmically equivalent to that between the fine and coarse levels of AMR. Direct simulation Monte Carlo (DSMC) is used as the particle algorithm embedded within a Godunov-type compressible Navier-Stokes solver. Several examples are presented and compared with purely continuum calculations.
Monte Carlo simulation of electron swarm parameters in O2
NASA Astrophysics Data System (ADS)
Settaouti, A.; Settaouti, L.
2007-03-01
Oxygen plasmas have found numerous applications in plasma processing, such as reactive sputtering, dry etching of polymers, oxidation, and resist removal of semiconductors. Swarm and transport coefficients are essential for better understanding and modelling of these gas discharge processes. The electron swarms in a gas under the influence of an electric field can be simulated with the help of a Monte Carlo method. The swarm parameters evaluated are compared with experimental results.
SU-E-T-188: Film Dosimetry Verification of Monte Carlo Generated Electron Treatment Plans
Enright, S; Asprinio, A; Lu, L
2014-06-01
Purpose: The purpose of this study was to compare dose distributions from film measurements to Monte Carlo generated electron treatment plans. Irradiation with electrons offers the advantages of dose uniformity in the target volume and of minimizing the dose to deeper healthy tissue. Using the Monte Carlo algorithm will improve dose accuracy in regions with heterogeneities and irregular surfaces. Methods: Dose distributions from GafChromic{sup ™} EBT3 films were compared to dose distributions from the Electron Monte Carlo algorithm in the Eclipse{sup ™} radiotherapy treatment planning system. These measurements were obtained for 6MeV, 9MeV and 12MeV electrons at two depths. All phantoms studied were imported into Eclipse by CT scan. A 1 cm thick solid water template with holes for bonelike and lung-like plugs was used. Different configurations were used with the different plugs inserted into the holes. Configurations with solid-water plugs stacked on top of one another were also used to create an irregular surface. Results: The dose distributions measured from the film agreed with those from the Electron Monte Carlo treatment plan. Accuracy of Electron Monte Carlo algorithm was also compared to that of Pencil Beam. Dose distributions from Monte Carlo had much higher pass rates than distributions from Pencil Beam when compared to the film. The pass rate for Monte Carlo was in the 80%–99% range, where the pass rate for Pencil Beam was as low as 10.76%. Conclusion: The dose distribution from Monte Carlo agreed with the measured dose from the film. When compared to the Pencil Beam algorithm, pass rates for Monte Carlo were much higher. Monte Carlo should be used over Pencil Beam for regions with heterogeneities and irregular surfaces.
Monte Carlo Strategies for Selecting Parameter Values in Simulation Experiments.
Leigh, Jessica W; Bryant, David
2015-09-01
Simulation experiments are used widely throughout evolutionary biology and bioinformatics to compare models, promote methods, and test hypotheses. The biggest practical constraint on simulation experiments is the computational demand, particularly as the number of parameters increases. Given the extraordinary success of Monte Carlo methods for conducting inference in phylogenetics, and indeed throughout the sciences, we investigate ways in which Monte Carlo framework can be used to carry out simulation experiments more efficiently. The key idea is to sample parameter values for the experiments, rather than iterate through them exhaustively. Exhaustive analyses become completely infeasible when the number of parameters gets too large, whereas sampled approaches can fare better in higher dimensions. We illustrate the framework with applications to phylogenetics and genetic archaeology. PMID:26012871
Research on GPU Acceleration for Monte Carlo Criticality Calculation
NASA Astrophysics Data System (ADS)
Xu, Qi; Yu, Ganglin; Wang, Kan
2014-06-01
The Monte Carlo neutron transport method can be naturally parallelized by multi-core architectures due to the dependency between particles during the simulation. The GPU+CPU heterogeneous parallel mode has become an increasingly popular way of parallelism in the field of scientific supercomputing. Thus, this work focuses on the GPU acceleration method for the Monte Carlo criticality simulation, as well as the computational efficiency that GPUs can bring. The "neutron transport step" is introduced to increase the GPU thread occupancy. In order to test the sensitivity of the MC code's complexity, a 1D one-group code and a 3D multi-group general purpose code are respectively transplanted to GPUs, and the acceleration effects are compared. The result of numerical experiments shows considerable acceleration effect of the "neutron transport step" strategy. However, the performance comparison between the 1D code and the 3D code indicates the poor scalability of MC codes on GPUs.
Rejection-free Monte Carlo scheme for anisotropic particles.
Sinkovits, Daniel W; Barr, Stephen A; Luijten, Erik
2012-04-14
We extend the geometric cluster algorithm [J. Liu and E. Luijten, Phys. Rev. Lett. 92, 035504 (2004)], a highly efficient, rejection-free Monte Carlo scheme for fluids and colloidal suspensions, to the case of anisotropic particles. This is made possible by adopting hyperspherical boundary conditions. A detailed derivation of the algorithm is presented, along with extensive implementation details as well as benchmark results. We describe how the quaternion notation is particularly suitable for the four-dimensional geometric operations employed in the algorithm. We present results for asymmetric Lennard-Jones dimers and for the Yukawa one-component plasma in hyperspherical geometry. The efficiency gain that can be achieved compared to conventional, Metropolis-type Monte Carlo simulations is investigated for rod-sphere mixtures as a function of rod aspect ratio, rod-sphere diameter ratio, and rod concentration. The effect of curved geometry on physical properties is addressed. PMID:22502505
Monte Carlo approach to tissue-cell populations
NASA Astrophysics Data System (ADS)
Drasdo, D.; Kree, R.; McCaskill, J. S.
1995-12-01
We describe a stochastic dynamics of tissue cells with special emphasis on epithelial cells and fibro- blasts and fibrocytes of the connective tissue. Pattern formation and growth characteristics of such cell populations in culture are investigated numerically by Monte Carlo simulations for quasi-two-dimensional systems of cells. A number of quantitative predictions are obtained which may be confronted with experimental results. Furthermore we introduce several biologically motivated variants of our basic model and briefly discuss the simulation of two dimensional analogs of two complex processes in tissues: the growth of a sarcoma across an epithelial boundary and the wound healing of a skin cut. As compared to other approaches, we find the Monte Carlo approach to tissue growth and structure to be particularly simple and flexible. It allows for a hierarchy of models reaching from global description of birth-death processes to very specific features of intracellular dynamics. (c) 1995 The American Physical Society
Chemical accuracy from quantum Monte Carlo for the benzene dimer
Azadi, Sam; Cohen, R. E.
2015-09-14
We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of −2.3(4) and −2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is −2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.
Chemical accuracy from quantum Monte Carlo for the benzene dimer.
Azadi, Sam; Cohen, R E
2015-09-14
We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of -2.3(4) and -2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is -2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods. PMID:26374029
The X-43A Six Degree of Freedom Monte Carlo Analysis
NASA Technical Reports Server (NTRS)
Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger
2008-01-01
This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.
The X-43A Six Degree of Freedom Monte Carlo Analysis
NASA Technical Reports Server (NTRS)
Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger; Richard, Michael
2007-01-01
This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.
Monte Carlo simulations of medical imaging modalities
Estes, G.P.
1998-09-01
Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computer power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.
Coherent scatter imaging Monte Carlo simulation.
Hassan, Laila; MacDonald, Carolyn A
2016-07-01
Conventional mammography can suffer from poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter slot scan imaging is an imaging technique which provides additional information and is compatible with conventional mammography. A Monte Carlo simulation of coherent scatter slot scan imaging was performed to assess its performance and provide system optimization. Coherent scatter could be exploited using a system similar to conventional slot scan mammography system with antiscatter grids tilted at the characteristic angle of cancerous tissues. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The simulated carcinomas were detectable for tumors as small as 5 mm in diameter, so coherent scatter analysis using a wide-slot setup could be promising as an enhancement for screening mammography. Employing coherent scatter information simultaneously with conventional mammography could yield a conventional high spatial resolution image with additional coherent scatter information. PMID:27610397
Green's function Monte Carlo in nuclear physics
Carlson, J.
1990-01-01
We review the status of Green's Function Monte Carlo (GFMC) methods as applied to problems in nuclear physics. New methods have been developed to handle the spin and isospin degrees of freedom that are a vital part of any realistic nuclear physics problem, whether at the level of quarks or nucleons. We discuss these methods and then summarize results obtained recently for light nuclei, including ground state energies, three-body forces, charge form factors and the coulomb sum. As an illustration of the applicability of GFMC to quark models, we also consider the possible existence of bound exotic multi-quark states within the framework of flux-tube quark models. 44 refs., 8 figs., 1 tab.
Accuracy control in Monte Carlo radiative calculations
NASA Technical Reports Server (NTRS)
Almazan, P. Planas
1993-01-01
The general accuracy law that rules the Monte Carlo, ray-tracing algorithms used commonly for the calculation of the radiative entities in the thermal analysis of spacecraft are presented. These entities involve transfer of radiative energy either from a single source to a target (e.g., the configuration factors). or from several sources to a target (e.g., the absorbed heat fluxes). In fact, the former is just a particular case of the latter. The accuracy model is later applied to the calculation of some specific radiative entities. Furthermore, some issues related to the implementation of such a model in a software tool are discussed. Although only the relative error is considered through the discussion, similar results can be derived for the absolute error.
MORSE Monte Carlo radiation transport code system
Emmett, M.B.
1983-02-01
This report is an addendum to the MORSE report, ORNL-4972, originally published in 1975. This addendum contains descriptions of several modifications to the MORSE Monte Carlo Code, replacement pages containing corrections, Part II of the report which was previously unpublished, and a new Table of Contents. The modifications include a Klein Nishina estimator for gamma rays. Use of such an estimator required changing the cross section routines to process pair production and Compton scattering cross sections directly from ENDF tapes and writing a new version of subroutine RELCOL. Another modification is the use of free form input for the SAMBO analysis data. This required changing subroutines SCORIN and adding new subroutine RFRE. References are updated, and errors in the original report have been corrected. (WHK)
Exploring theory space with Monte Carlo reweighting
Gainer, James S.; Lykken, Joseph; Matchev, Konstantin T.; Mrenna, Stephen; Park, Myeonghun
2014-10-13
Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. Specifically, we suggest procedures that allow more efficient collaboration between theorists andmore » experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.« less
Monte Carlo modeling and meteor showers
NASA Astrophysics Data System (ADS)
Kulikova, N. V.
1987-08-01
Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.
Quantum Monte Carlo simulations in novel geometries
NASA Astrophysics Data System (ADS)
Iglovikov, Vladimir
Quantum Monte Carlo simulations are giving increasing insight into the physics of strongly interacting bosons, spins, and fermions. Initial work focused on the simplest geometries, like a 2D square lattice. Increasingly, modern research is turning to more rich structures such as honeycomb lattice of graphene, the Lieb lattice of the CuO2 planes of cuprate superconductors, the triangular lattice, and coupled layers. These new geometries possess unique features which affect the physics in profound ways, eg a vanishing density of states and relativistic dispersion ("Dirac point'') of a honeycomb lattice, frustration on a triangular lattice, and a flat bands on a Lieb lattice. This thesis concerns both exploring the performance of QMC algorithms on different geometries(primarily via the "sign problem'') and also applying those algorithms to several interesting open problems.
Resist develop prediction by Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Sohn, Dong-Soo; Jeon, Kyoung-Ah; Sohn, Young-Soo; Oh, Hye-Keun
2002-07-01
Various resist develop models have been suggested to express the phenomena from the pioneering work of Dill's model in 1975 to the recent Shipley's enhanced notch model. The statistical Monte Carlo method can be applied to the process such as development and post exposure bake. The motions of developer during development process were traced by using this method. We have considered that the surface edge roughness of the resist depends on the weight percentage of protected and de-protected polymer in the resist. The results are well agreed with other papers. This study can be helpful for the developing of new photoresist and developer that can be used to pattern the device features smaller than 100 nm.
Exploring theory space with Monte Carlo reweighting
Gainer, James S.; Lykken, Joseph; Matchev, Konstantin T.; Mrenna, Stephen; Park, Myeonghun
2014-10-13
Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. Specifically, we suggest procedures that allow more efficient collaboration between theorists and experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.
Monte Carlo modeling and meteor showers
NASA Technical Reports Server (NTRS)
Kulikova, N. V.
1987-01-01
Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.
Noncovalent Interactions by Quantum Monte Carlo.
Dubecký, Matúš; Mitas, Lubos; Jurečka, Petr
2016-05-11
Quantum Monte Carlo (QMC) is a family of stochastic methods for solving quantum many-body problems such as the stationary Schrödinger equation. The review introduces basic notions of electronic structure QMC based on random walks in real space as well as its advances and adaptations to systems with noncovalent interactions. Specific issues such as fixed-node error cancellation, construction of trial wave functions, and efficiency considerations that allow for benchmark quality QMC energy differences are described in detail. Comprehensive overview of articles covers QMC applications to systems with noncovalent interactions over the last three decades. The current status of QMC with regard to efficiency, applicability, and usability by nonexperts together with further considerations about QMC developments, limitations, and unsolved challenges are discussed as well. PMID:27081724
Monte-Carlo Simulation Balancing in Practice
NASA Astrophysics Data System (ADS)
Huang, Shih-Chieh; Coulom, Rémi; Lin, Shun-Shii
Simulation balancing is a new technique to tune parameters of a playout policy for a Monte-Carlo game-playing program. So far, this algorithm had only been tested in a very artificial setting: it was limited to 5×5 and 6×6 Go, and required a stronger external program that served as a supervisor. In this paper, the effectiveness of simulation balancing is demonstrated in a more realistic setting. A state-of-the-art program, Erica, learned an improved playout policy on the 9×9 board, without requiring any external expert to provide position evaluations. The evaluations were collected by letting the program analyze positions by itself. The previous version of Erica learned pattern weights with the minorization-maximization algorithm. Thanks to simulation balancing, its playing strength was improved from a winning rate of 69% to 78% against Fuego 0.4.
Angular biasing in implicit Monte-Carlo
Zimmerman, G.B.
1994-10-20
Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise.
Monte Carlo simulations in Nuclear Medicine
Loudos, George K.
2007-11-26
Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.
Monte Carlo simulations in Nuclear Medicine
NASA Astrophysics Data System (ADS)
Loudos, George K.
2007-11-01
Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.
Optimized trial functions for quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Huang, Sheng-Yu; Sun, Zhiwei; Lester, William A., Jr.
1990-01-01
An algorithm to optimize trial functions for fixed-node quantum Monte Carlo calculations has been developed based on variational random walks. The approach is applied to wave functions that are products of a simple Slater determinant and correlation factor explicitly dependent on interelectronic distance, and is found to provide improved ground-state total energies. A modification of the method for ground-states that makes use of a projection operator technique is shown to make possible the calculation of more accurate excited-state energies. In this optimization method the Young tableaux of the permutation group is used to facilitate the treatment of fermion properties and multiplets. Application to ground states of H2, Li2, H3, H+3, and to the first-excited singlets of H2, H3, and H4 are presented and discussed.
Optimized trial functions for quantum Monte Carlo
Huang, S.; Sun, Z.; Lester, W.A. Jr. )
1990-01-01
An algorithm to optimize trial functions for fixed-node quantum Monte Carlo calculations has been developed based on variational random walks. The approach is applied to wave functions that are products of a simple Slater determinant and correlation factor explicitly dependent on interelectronic distance, and is found to provide improved ground-state total energies. A modification of the method for ground-states that makes use of a projection operator technique is shown to make possible the calculation of more accurate excited-state energies. In this optimization method the Young tableaux of the permutation group is used to facilitate the treatment of fermion properties and multiplets. Application to ground states of H{sub 2}, Li{sub 2}, H{sub 3}, H{sup +}{sub 3}, and to the first-excited singlets of H{sub 2}, H{sub 3}, and H{sub 4} are presented and discussed.
abcpmc: Approximate Bayesian Computation for Population Monte-Carlo code
NASA Astrophysics Data System (ADS)
Akeret, Joel
2015-04-01
abcpmc is a Python Approximate Bayesian Computing (ABC) Population Monte Carlo (PMC) implementation based on Sequential Monte Carlo (SMC) with Particle Filtering techniques. It is extendable with k-nearest neighbour (KNN) or optimal local covariance matrix (OLCM) pertubation kernels and has built-in support for massively parallelized sampling on a cluster using MPI.
A Primer in Monte Carlo Integration Using Mathcad
ERIC Educational Resources Information Center
Hoyer, Chad E.; Kegerreis, Jeb S.
2013-01-01
The essentials of Monte Carlo integration are presented for use in an upper-level physical chemistry setting. A Mathcad document that aids in the dissemination and utilization of this information is described and is available in the Supporting Information. A brief outline of Monte Carlo integration is given, along with ideas and pedagogy for…
Monte Carlo Test Assembly for Item Pool Analysis and Extension
ERIC Educational Resources Information Center
Belov, Dmitry I.; Armstrong, Ronald D.
2005-01-01
A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal…
Economic Risk Analysis: Using Analytical and Monte Carlo Techniques.
ERIC Educational Resources Information Center
O'Donnell, Brendan R.; Hickner, Michael A.; Barna, Bruce A.
2002-01-01
Describes the development and instructional use of a Microsoft Excel spreadsheet template that facilitates analytical and Monte Carlo risk analysis of investment decisions. Discusses a variety of risk assessment methods followed by applications of the analytical and Monte Carlo methods. Uses a case study to illustrate use of the spreadsheet tool…
The Monte Carlo Method. Popular Lectures in Mathematics.
ERIC Educational Resources Information Center
Sobol', I. M.
The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…
Accelerated GPU based SPECT Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
Monte Carlo modelling of TRIGA research reactor
NASA Astrophysics Data System (ADS)
El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.
2010-10-01
The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.
Accelerated GPU based SPECT Monte Carlo simulations.
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational
Monte Carlo scatter correction for SPECT
NASA Astrophysics Data System (ADS)
Liu, Zemei
The goal of this dissertation is to present a quantitatively accurate and computationally fast scatter correction method that is robust and easily accessible for routine applications in SPECT imaging. A Monte Carlo based scatter estimation method is investigated and developed further. The Monte Carlo simulation program SIMIND (Simulating Medical Imaging Nuclear Detectors), was specifically developed to simulate clinical SPECT systems. The SIMIND scatter estimation (SSE) method was developed further using a multithreading technique to distribute the scatter estimation task across multiple threads running concurrently on multi-core CPU's to accelerate the scatter estimation process. An analytical collimator that ensures less noise was used during SSE. The research includes the addition to SIMIND of charge transport modeling in cadmium zinc telluride (CZT) detectors. Phenomena associated with radiation-induced charge transport including charge trapping, charge diffusion, charge sharing between neighboring detector pixels, as well as uncertainties in the detection process are addressed. Experimental measurements and simulation studies were designed for scintillation crystal based SPECT and CZT based SPECT systems to verify and evaluate the expanded SSE method. Jaszczak Deluxe and Anthropomorphic Torso Phantoms (Data Spectrum Corporation, Hillsborough, NC, USA) were used for experimental measurements and digital versions of the same phantoms employed during simulations to mimic experimental acquisitions. This study design enabled easy comparison of experimental and simulated data. The results have consistently shown that the SSE method performed similarly or better than the triple energy window (TEW) and effective scatter source estimation (ESSE) methods for experiments on all the clinical SPECT systems. The SSE method is proven to be a viable method for scatter estimation for routine clinical use.
Quantum Monte Carlo studies on small molecules
NASA Astrophysics Data System (ADS)
Galek, Peter T. A.; Handy, Nicholas C.; Lester, William A., Jr.
The Variational Monte Carlo (VMC) and Fixed-Node Diffusion Monte Carlo (FNDMC) methods have been examined, through studies on small molecules. New programs have been written which implement the (by now) standard algorithms for VMC and FNDMC. We have employed and investigated throughout our studies the accuracy of the common Slater-Jastrow trial wave function. Firstly, we have studied a range of sizes of the Jastrow correlation function of the Boys-Handy form, obtained using our optimization program with analytical derivatives of the central moments in the local energy. Secondly, we have studied the effects of Slater-type orbitals (STOs) that display the exact cusp behaviour at nuclei. The orbitals make up the all important trial determinant, which determines the fixed nodal surface. We report all-electron calculations for the ground state energies of Li2, Be2, H2O, NH3, CH4 and H2CO, in all cases but one with accuracy in excess of 95%. Finally, we report an investigation of the ground state energies, dissociation energies and ionization potentials of NH and NH+. Recent focus paid in the literature to these species allow for an extensive comparison with other ab initio methods. We obtain accurate properties for the species and reveal a favourable tendency for fixed-node and other systematic errors to cancel. As a result of our accurate predictions, we are able to obtain a value for the heat of formation of NH, which agrees to within less than 1 kcal mol-1 to other ab initio techniques and 0.2 kcal mol-1 of the experimental value.
Vectorized Monte Carlo methods for reactor lattice analysis
NASA Technical Reports Server (NTRS)
Brown, F. B.
1984-01-01
Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
A new method for commissioning Monte Carlo treatment planning systems
NASA Astrophysics Data System (ADS)
Aljarrah, Khaled Mohammed
2005-11-01
The Monte Carlo method is an accurate method for solving numerical problems in different fields. It has been used for accurate radiation dose calculation for radiation treatment of cancer. However, the modeling of an individual radiation beam produced by a medical linear accelerator for Monte Carlo dose calculation, i.e., the commissioning of a Monte Carlo treatment planning system, has been the bottleneck for the clinical implementation of Monte Carlo treatment planning. In this study a new method has been developed to determine the parameters of the initial electron beam incident on the target for a clinical linear accelerator. The interaction of the initial electron beam with the accelerator target produces x-ray and secondary charge particles. After successive interactions in the linac head components, the x-ray photons and the secondary charge particles interact with the patient's anatomy and deliver dose to the region of interest. The determination of the initial electron beam parameters is important for estimating the delivered dose to the patients. These parameters, such as beam energy and radial intensity distribution, are usually estimated through a trial and error process. In this work an easy and efficient method was developed to determine these parameters. This was accomplished by comparing calculated 3D dose distributions for a grid of assumed beam energies and radii in a water phantom with measurements data. Different cost functions were studied to choose the appropriate function for the data comparison. The beam parameters were determined on the light of this method. Due to the assumption that same type of linacs are exactly the same in their geometries and only differ by the initial phase space parameters, the results of this method were considered as a source data to commission other machines of the same type.
Quantum Monte Carlo theory and applications for molecular systems
NASA Astrophysics Data System (ADS)
Kollias, Alexander C.
New directions for the quantum Monte Carlo (QMC) electronic structure method are discussed. Diffusion Monte Carlo (DMC) results for the atomization energy and heats for formation of CO+2 are presented, while the bonding character is examined using the electron localization function. DMC all-electron and effective-core potential trial functions are used to obtain the atomization energies, heats of formation, and energy differences of the C2H4 singlet and triplet states. In addition, DMC is applied to obtain the heat of reaction and barrier height of the proton extraction reaction, CH3OH + Cl → CH 2OH + HCl. The results of the barrier height and heat of reaction are verified by examining the atomization energies and heats for formation of the reactants and products. DMC calculations were carried out on 22 small hydrocarbons. In this benchmark study the DMC atomization and bond dissociation energies, and heats of formation of these hydrocarbons are presented and compared to other ab initio methods. Methods for geometry optimization and calculating forces for QMC are discussed. The response surface methodology is applied to variational Monte Carlo (VMC) and DMC methods to obtain an optimized geometry, force constants and vibrational frequencies of CH2O. Finally, the zero-variance principle is applied to obtain VMC and DMC effective-core potential force estimators. These estimators are used to obtain a force curve for LiH.
On Monte Carlo Methods and Applications in Geoscience
NASA Astrophysics Data System (ADS)
Zhang, Z.; Blais, J.
2009-05-01
Monte Carlo methods are designed to study various deterministic problems using probabilistic approaches, and with computer simulations to explore much wider possibilities for the different algorithms. Pseudo- Random Number Generators (PRNGs) are based on linear congruences of some large prime numbers, while Quasi-Random Number Generators (QRNGs) provide low discrepancy sequences, both of which giving uniformly distributed numbers in (0,1). Chaotic Random Number Generators (CRNGs) give sequences of 'random numbers' satisfying some prescribed probabilistic density, often denser around the two corners of interval (0,1), but transforming this type of density to a uniform one is usually possible. Markov Chain Monte Carlo (MCMC), as indicated by its name, is associated with Markov Chain simulations. Basic descriptions of these random number generators will be given, and a comparative analysis of these four methods will be included based on their efficiencies and other characteristics. Some applications in geoscience using Monte Carlo simulations will be described, and a comparison of these algorithms will also be included with some concluding remarks.
Performance of quantum Monte Carlo for calculating molecular bond lengths
NASA Astrophysics Data System (ADS)
Cleland, Deidre M.; Per, Manolo C.
2016-03-01
This work investigates the accuracy of real-space quantum Monte Carlo (QMC) methods for calculating molecular geometries. We present the equilibrium bond lengths of a test set of 30 diatomic molecules calculated using variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods. The effect of different trial wavefunctions is investigated using single determinants constructed from Hartree-Fock (HF) and Density Functional Theory (DFT) orbitals with LDA, PBE, and B3LYP functionals, as well as small multi-configurational self-consistent field (MCSCF) multi-determinant expansions. When compared to experimental geometries, all DMC methods exhibit smaller mean-absolute deviations (MADs) than those given by HF, DFT, and MCSCF. The most accurate MAD of 3 ± 2 × 10-3 Å is achieved using DMC with a small multi-determinant expansion. However, the more computationally efficient multi-determinant VMC method has a similar MAD of only 4.0 ± 0.9 × 10-3 Å, suggesting that QMC forces calculated from the relatively simple VMC algorithm may often be sufficient for accurate molecular geometries.
Path integral Monte Carlo on a lattice: extended states.
O'Callaghan, Mark; Miller, Bruce N
2014-04-01
The equilibrium properties of a single quantum particle (qp) interacting with a classical gas for a wide range of temperatures that explore the system's behavior in the classical as well as in the quantum regime is investigated. Both the qp and atoms are restricted to the sites of a one-dimensional lattice. A path integral formalism is developed within the context of the canonical ensemble in which the qp is represented by a closed, variable-step random walk on the lattice. Monte Carlo methods are employed to determine the system's properties. For the case of a free particle, analytical expressions for the energy, its fluctuations, and the qp-qp correlation function are derived and compared with the Monte Carlo simulations. To test the usefulness of the path integral formalism, the Metropolis algorithm is employed to determine the equilibrium properties of the qp for a periodic interaction potential, forcing the qp to occupy extended states. We consider a striped potential in one dimension, where every other lattice site is occupied by an atom with potential ε, and every other lattice site is empty. This potential serves as a stress test for the path integral formalism because of its rapid site-to-site variation. An analytical solution was determined in this case by utilizing Bloch's theorem due to the periodicity of the potential. Comparisons of the potential energy, the total energy, the energy fluctuations, and the correlation function are made between the results of the Monte Carlo simulations and the analytical calculations. PMID:24827210
Bretscher, M.M.
1993-12-31
The WIMS-D4 code has been modified (WIMS-D4M) to produce microscopic isotopic cross sections in ISOTXS format for use in diffusion and transport calculations. Beginning with 69-group libraries based on ENDF/B-V data, numerous cell calculations have been made to prepare a set of broad group cross sections for use in diffusion calculations. Global calculations have been made for two control rod states of the Romanian steady state TRIGA reactor with 29 fresh HEU fuel clusters. Detailed Monte Carlo calculations also have been performed for the same reactor configurations using data based on ENDF/B-V. Results from these global calculations are compared with each other and with the measured excess reactivities. Although region-averaged macroscopic principal cross sections obtained from WIMS-D4M are in good agreement with the corresponding Monte Carlo values, problems exist with the high energy (E > 10 keV) microscopic hydrogen transport cross sections.
NASA Astrophysics Data System (ADS)
O'Shaughnessy, Richard; Farr, Ben; Ochsner, Evan; Cho, Hee-Suk; Kim, Chunglee; Lee, Chang-Hwan
2014-03-01
Most calculations of the gravitational wave signal from merging compact binaries limit attention to the leading-order quadrupole when constructing models for detection or parameter estimation. Some studies have claimed that if additional "higher harmonics" are included consistently in the gravitational wave signal and search model, binary parameters can be measured much more precisely. Using the lalinference Markov-chain Monte Carlo parameter estimation code, we construct posterior parameter constraints associated with two distinct nonprecessing black hole-neutron star (BH-NS) binaries, each with and without higher-order harmonics. All simulations place a plausible signal into a three-detector network with Gaussian noise. Our simulations suggest that higher harmonics provide little information, principally allowing us to measure a previously unconstrained angle associated with the source geometry well but otherwise improving knowledge of all other parameters by a few percent for our loud fiducial signal (ρ =20). Even at this optimistic signal amplitude, different noise realizations have a more significant impact on parameter accuracy than higher harmonics. We compare our results with the "effective Fisher matrix" introduced previously as a method to obtain robust analytic predictions for complicated signals with multiple significant harmonics. We find generally good agreement with these predictions, confirm that intrinsic parameter measurement accuracy is nearly independent of detector network geometry, and show that uncertainties in extrinsic and intrinsic parameters can, to a good approximation, be separated. For our fiducial example, the individual masses can be determined to lie between 7.11-11.48M⊙ and 1.77-1.276M⊙ at greater than 99% confidence level, accounting for unknown BH spin. Assuming comparable control over waveform systematics, measurements of BH-NS binaries can constrain the BH and perhaps NS mass distributions. Using analytic arguments to
NASA Astrophysics Data System (ADS)
Mumford, K. G.; Mustafa, N. A.; Gerhard, J.
2012-12-01
probability of exceedance at community risk receptors was explored. This was accomplished by conducting Monte Carlo suites of simulations of a three-dimensional 1000 m × 500 m × 14 m domain to calculate the probability of exceeding regulatory criteria at different locations. The results allowed comparison of the potential importance of heterogeneity in permeability, sorption, and degradation parameters in risk-based decision making. More than 650 simulations were conducted to investigate different values of mean and variance of permeability, sorption coefficients, degradation rate constants, and correlations between heterogeneous fields. This work showed that greater reductions in source concentration were required to meet regulations for inhalation of indoor air compared to ingestion of groundwater, and that mean concentrations and probabilities of exceedance were more sensitive when evaluated at receptors that were laterally offset from the plume center line.
Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue
Paquit, Vincent C; Price, Jeffery R; Meriaudeau, Fabrice; Tobin Jr, Kenneth William
2008-01-01
In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.
Independent pixel and Monte Carlo estimates of stratocumulus albedo
NASA Technical Reports Server (NTRS)
Cahalan, Robert F.; Ridgway, William; Wiscombe, Warren J.; Gollmer, Steven; HARSHVARDHAN
1994-01-01
Monte Carlo radiative transfer methods are employed here to estimate the plane-parallel albedo bias for marine stratocumulus clouds. This is the bias in estimates of the mesoscale-average albedo, which arises from the assumption that cloud liquid water is uniformly distributed. The authors compare such estimates with those based on a more realistic distribution generated from a fractal model of marine stratocumulus clouds belonging to the class of 'bounded cascade' models. In this model the cloud top and base are fixed, so that all variations in cloud shape are ignored. The model generates random variations in liquid water along a single horizontal direction, forming fractal cloud streets while conserving the total liquid water in the cloud field. The model reproduces the mean, variance, and skewness of the vertically integrated cloud liquid water, as well as its observed wavenumber spectrum, which is approximately a power law. The Monte Carlo method keeps track of the three-dimensional paths solar photons take through the cloud field, using a vectorized implementation of a direct technique. The simplifications in the cloud field studied here allow the computations to be accelerated. The Monte Carlo results are compared to those of the independent pixel approximation, which neglects net horizontal photon transport. Differences between the Monte Carlo and independent pixel estimates of the mesoscale-average albedo are on the order of 1% for conservative scattering, while the plane-parallel bias itself is an order of magnitude larger. As cloud absorption increases, the independent pixel approximation agrees even more closely with the Monte Carlo estimates. This result holds for a wide range of sun angles and aspect ratios. Thus, horizontal photon transport can be safely neglected in estimates of the area-average flux for such cloud models. This result relies on the rapid falloff of the wavenumber spectrum of stratocumulus, which ensures that the smaller
On-the-fly nuclear data processing methods for Monte Carlo simulations of fast spectrum systems
Walsh, Jon
2015-08-31
The presentation summarizes work performed over summer 2015 related to Monte Carlo simulations. A flexible probability table interpolation scheme has been implemented and tested with results comparing favorably to the continuous phase-space on-the-fly approach.
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Recent advances and future prospects for Monte Carlo
Brown, Forrest B
2010-01-01
The history of Monte Carlo methods is closely linked to that of computers: The first known Monte Carlo program was written in 1947 for the ENIAC; a pre-release of the first Fortran compiler was used for Monte Carlo In 1957; Monte Carlo codes were adapted to vector computers in the 1980s, clusters and parallel computers in the 1990s, and teraflop systems in the 2000s. Recent advances include hierarchical parallelism, combining threaded calculations on multicore processors with message-passing among different nodes. With the advances In computmg, Monte Carlo codes have evolved with new capabilities and new ways of use. Production codes such as MCNP, MVP, MONK, TRIPOLI and SCALE are now 20-30 years old (or more) and are very rich in advanced featUres. The former 'method of last resort' has now become the first choice for many applications. Calculations are now routinely performed on office computers, not just on supercomputers. Current research and development efforts are investigating the use of Monte Carlo methods on FPGAs. GPUs, and many-core processors. Other far-reaching research is exploring ways to adapt Monte Carlo methods to future exaflop systems that may have 1M or more concurrent computational processes.
Clinical implementation of full Monte Carlo dose calculation in proton beam therapy.
Paganetti, Harald; Jiang, Hongyu; Parodi, Katia; Slopsema, Roelf; Engelsman, Martijn
2008-09-01
The goal of this work was to facilitate the clinical use of Monte Carlo proton dose calculation to support routine treatment planning and delivery. The Monte Carlo code Geant4 was used to simulate the treatment head setup, including a time-dependent simulation of modulator wheels (for broad beam modulation) and magnetic field settings (for beam scanning). Any patient-field-specific setup can be modeled according to the treatment control system of the facility. The code was benchmarked against phantom measurements. Using a simulation of the ionization chamber reading in the treatment head allows the Monte Carlo dose to be specified in absolute units (Gy per ionization chamber reading). Next, the capability of reading CT data information was implemented into the Monte Carlo code to model patient anatomy. To allow time-efficient dose calculation, the standard Geant4 tracking algorithm was modified. Finally, a software link of the Monte Carlo dose engine to the patient database and the commercial planning system was established to allow data exchange, thus completing the implementation of the proton Monte Carlo dose calculation engine ('DoC++'). Monte Carlo re-calculated plans are a valuable tool to revisit decisions in the planning process. Identification of clinically significant differences between Monte Carlo and pencil-beam-based dose calculations may also drive improvements of current pencil-beam methods. As an example, four patients (29 fields in total) with tumors in the head and neck regions were analyzed. Differences between the pencil-beam algorithm and Monte Carlo were identified in particular near the end of range, both due to dose degradation and overall differences in range prediction due to bony anatomy in the beam path. Further, the Monte Carlo reports dose-to-tissue as compared to dose-to-water by the planning system. Our implementation is tailored to a specific Monte Carlo code and the treatment planning system XiO (Computerized Medical Systems Inc
NASA Astrophysics Data System (ADS)
Wang, Ping; Yuan, Hongwu; Mei, Haiping; Zhang, Qianghua
2013-08-01
Study the laser pulses transmission time characteristics in discrete random medium using the Monte Carlo method. Firstly, the medium optical parameters have been given by OPAC software. Then, create a Monte Carlo model and Monte Carlo simulation of photon transport behavior of a large number of tracking, statistics obtain the photon average arrival time and average pulse broadening case, the calculation result with calculation results of two-frequency mutual coherence function are compared, the results are very consistent. Finally, medium impulse response function given by polynomial fitting method can be used to correct discrete random medium inter-symbol interference in optical communications and reduce the rate of system error.
Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations
NASA Technical Reports Server (NTRS)
Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias
2015-01-01
Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.
Franke, B. C.; Prinja, A. K.
2013-07-01
The stochastic Galerkin method (SGM) is an intrusive technique for propagating data uncertainty in physical models. The method reduces the random model to a system of coupled deterministic equations for the moments of stochastic spectral expansions of result quantities. We investigate solving these equations using the Monte Carlo technique. We compare the efficiency with brute-force Monte Carlo evaluation of uncertainty, the non-intrusive stochastic collocation method (SCM), and an intrusive Monte Carlo implementation of the stochastic collocation method. We also describe the stability limitations of our SGM implementation. (authors)
Mowlavi, Ali Asghar; de Denaro, Mario; Fornasier, Maria Rosa; Binesh, Alireza
2006-03-01
This paper describes Monte Carlo simulation of intrinsic count rate performance of a scintillation gamma camera. MCNP Monte Carlo code was employed to calculate pulse height spectrum and detector efficiency. A custom code written in Fortran language was then developed to simulate, by Monte Carlo method, the distortion in pulse height spectrum due to the pile-up effect for paralyzable and nonparalyzable systems. The results of the simulations, compared with the experimental measurement of count rate performance, showed a good agreement between the two different approaches. PMID:16343910
A radiating shock evaluated using Implicit Monte Carlo Diffusion
Cleveland, M.; Gentile, N.
2013-07-01
Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)
Variance reduction in Monte Carlo analysis of rarefied gas diffusion.
NASA Technical Reports Server (NTRS)
Perlmutter, M.
1972-01-01
The problem of rarefied diffusion between parallel walls is solved using the Monte Carlo method. The diffusing molecules are evaporated or emitted from one of the two parallel walls and diffuse through another molecular species. The Monte Carlo analysis treats the diffusing molecule as undergoing a Markov random walk, and the local macroscopic properties are found as the expected value of the random variable, the random walk payoff. By biasing the transition probabilities and changing the collision payoffs, the expected Markov walk payoff is retained but its variance is reduced so that the Monte Carlo result has a much smaller error.
Linear Scaling Quantum Monte Carlo Calculations
NASA Astrophysics Data System (ADS)
Williamson, Andrew
2002-03-01
New developments to the quantum Monte Carlo approach are presented that improve the scaling of the time required to calculate the total energy of a configuration of electronic coordinates from N^3 to nearly linear[1]. The first factor of N is achieved by applying a unitary transform to the set of single particle orbitals used to construct the Slater determinant, creating a set of maximally localized Wannier orbitals. These localized functions are then truncated beyond a given cutoff radius to introduce sparsity into the Slater determinant. The second factor of N is achieved by evaluating the maximally localized Wannier orbitals on a cubic spline grid, which removes the size dependence of the basis set (e.g. plane waves, Gaussians) typically used to expand the orbitals. Application of this method to the calculation of the binding energy of carbon fullerenes and silicon nanostructures will be presented. An extension of the approach to deal with excited states of systems will also be presented in the context of the calculation of the excitonic gap of a variety of systems. This work was performed under the auspices of the U.S. Dept. of Energy at the University of California/LLNL under contract no. W-7405-Eng-48. [1] A.J. Williamson, R.Q. Hood and J.C. Grossman, Phys. Rev. Lett. 87 246406 (2001)
Computing Entanglement Entropy in Quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Melko, Roger
2012-02-01
The scaling of entanglement entropy in quantum many-body wavefunctions is expected to be a fruitful resource for studying quantum phases and phase transitions in condensed matter. However, until the recent development of estimators for Renyi entropy in quantum Monte Carlo (QMC), we have been in the dark about the behaviour of entanglement in all but the simplest two-dimensional models. In this talk, I will outline the measurement techniques that allow access to the Renyi entropies in several different QMC methodologies. I will then discuss recent simulation results demonstrating the richness of entanglement scaling in 2D, including: the prevalence of the ``area law''; topological entanglement entropy in a gapped spin liquid; anomalous subleading logarithmic terms due to Goldstone modes; universal scaling at critical points; and examples of emergent conformal-like scaling in several gapless wavefunctions. Finally, I will explore the idea that ``long range entanglement'' may complement the notion of ``long range order'' for quantum phases and phase transitions which lack a conventional order parameter description.
Error modes in implicit Monte Carlo
Martin, William Russell,; Brown, F. B.
2001-01-01
The Implicit Monte Carlo (IMC) method of Fleck and Cummings [1] has been used for years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Larsen and Mercier [2] have shown that the IMC method violates a maximum principle that is satisfied by the exact solution to the radiative transfer equation. Except for [2] and related papers regarding the maximum principle, there have been no other published results regarding the analysis of errors or convergence properties for the IMC method. This work presents an exact error analysis for the IMC method by using the analytical solutions for infinite medium geometry (0-D) to determine closed form expressions for the errors. The goal is to gain insight regarding the errors inherent in the IMC method by relating the exact 0-D errors to multi-dimensional geometry. Additional work (not described herein) has shown that adding a leakage term (i.e., a 'buckling' term) to the 0-D equations has relatively little effect on the IMC errors analyzed in this paper, so that the 0-D errors should provide useful guidance for the errors observed in multi-dimensional simulations.
Monte Carlo Production Management at CMS
NASA Astrophysics Data System (ADS)
Boudoul, G.; Franzoni, G.; Norkus, A.; Pol, A.; Srimanobhas, P.; Vlimant, J.-R.
2015-12-01
The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events. During the RunI of LHC (20102012), CMS has produced over 12 Billion simulated events, organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up). In order to aggregate the information needed for the configuration and prioritization of the events production, assure the book-keeping of all the processing requests placed by the physics analysis groups, and to interface with the CMS production infrastructure, the web- based service Monte Carlo Management (McM) has been developed and put in production in 2013. McM is based on recent server infrastructure technology (CherryPy + AngularJS) and relies on a CouchDB database back-end. This contribution covers the one and half year of operational experience managing samples of simulated events for CMS, the evolution of its functionalities and the extension of its capability to monitor the status and advancement of the events production.
Atomistic Monte Carlo Simulation of Lipid Membranes
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol. PMID:24469314
Finding Planet Nine: a Monte Carlo approach
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-06-01
Planet Nine is a hypothetical planet located well beyond Pluto that has been proposed in an attempt to explain the observed clustering in physical space of the perihelia of six extreme trans-Neptunian objects or ETNOs. The predicted approximate values of its orbital elements include a semimajor axis of 700 au, an eccentricity of 0.6, an inclination of 30°, and an argument of perihelion of 150°. Searching for this putative planet is already under way. Here, we use a Monte Carlo approach to create a synthetic population of Planet Nine orbits and study its visibility statistically in terms of various parameters and focusing on the aphelion configuration. Our analysis shows that, if Planet Nine exists and is at aphelion, it might be found projected against one out of the four specific areas in the sky. Each area is linked to a particular value of the longitude of the ascending node and two of them are compatible with an apsidal anti-alignment scenario. In addition and after studying the current statistics of ETNOs, a cautionary note on the robustness of the perihelia clustering is presented.
Accelerated Monte Carlo Methods for Coulomb Collisions
NASA Astrophysics Data System (ADS)
Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce
2014-03-01
We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ɛ in the numerical solution to collisional plasma problems from (ɛ-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (ɛ-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.
Monte Carlo Simulation of Critical Casimir Forces
NASA Astrophysics Data System (ADS)
Vasilyev, Oleg A.
2015-03-01
In the vicinity of the second order phase transition point long-range critical fluctuations of the order parameter appear. The second order phase transition in a critical binary mixture in the vicinity of the demixing point belongs to the universality class of the Ising model. The superfluid transition in liquid He belongs to the universality class of the XY model. The confinement of long-range fluctuations causes critical Casimir forces acting on confining surfaces or particles immersed in the critical substance. Last decade critical Casimir forces in binary mixtures and liquid helium were studied experimentally. The critical Casimir force in a film of a given thickness scales as a universal scaling function of the ratio of the film thickness to the bulk correlation length divided over the cube of the film thickness. Using Monte Carlo simulations we can compute critical Casimir forces and their scaling functions for lattice Ising and XY models which correspond to experimental results for the binary mixture and liquid helium, respectively. This chapter provides the description of numerical methods for computation of critical Casimir interactions for lattice models for plane-plane, plane-particle, and particle-particle geometries.
Commensurabilities between ETNOs: a Monte Carlo survey
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-04-01
Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nine hypothesis; in particular, a number of objects may be trapped in the 5:3 and 3:1 mean motion resonances with a putative Planet Nine with semimajor axis ˜700 au.
Markov Chain Monte Carlo and Irreversibility
NASA Astrophysics Data System (ADS)
Ottobre, Michela
2016-06-01
Markov Chain Monte Carlo (MCMC) methods are statistical methods designed to sample from a given measure π by constructing a Markov chain that has π as invariant measure and that converges to π. Most MCMC algorithms make use of chains that satisfy the detailed balance condition with respect to π; such chains are therefore reversible. On the other hand, recent work [18, 21, 28, 29] has stressed several advantages of using irreversible processes for sampling. Roughly speaking, irreversible diffusions converge to equilibrium faster (and lead to smaller asymptotic variance as well). In this paper we discuss some of the recent progress in the study of nonreversible MCMC methods. In particular: i) we explain some of the difficulties that arise in the analysis of nonreversible processes and we discuss some analytical methods to approach the study of continuous-time irreversible diffusions; ii) most of the rigorous results on irreversible diffusions are available for continuous-time processes; however, for computational purposes one needs to discretize such dynamics. It is well known that the resulting discretized chain will not, in general, retain all the good properties of the process that it is obtained from. In particular, if we want to preserve the invariance of the target measure, the chain might no longer be reversible. Therefore iii) we conclude by presenting an MCMC algorithm, the SOL-HMC algorithm [23], which results from a nonreversible discretization of a nonreversible dynamics.
Extending canonical Monte Carlo methods: II
NASA Astrophysics Data System (ADS)
Velazquez, L.; Curilef, S.
2010-04-01
We have previously presented a methodology for extending canonical Monte Carlo methods inspired by a suitable extension of the canonical fluctuation relation C = β2langδE2rang compatible with negative heat capacities, C < 0. Now, we improve this methodology by including the finite size effects that reduce the precision of a direct determination of the microcanonical caloric curve β(E) = ∂S(E)/∂E, as well as by carrying out a better implementation of the MC schemes. We show that, despite the modifications considered, the extended canonical MC methods lead to an impressive overcoming of the so-called supercritical slowing down observed close to the region of the temperature driven first-order phase transition. In this case, the size dependence of the decorrelation time τ is reduced from an exponential growth to a weak power-law behavior, \\tau (N)\\propto N^{\\alpha } , as is shown in the particular case of the 2D seven-state Potts model where the exponent α = 0.14-0.18.
Commensurabilities between ETNOs: a Monte Carlo survey
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-07-01
Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nine hypothesis; in particular, a number of objects may be trapped in the 5:3 and 3:1 mean motion resonances with a putative Planet Nine with semimajor axis ˜700 au.
Monte Carlo simulation framework for TMT
NASA Astrophysics Data System (ADS)
Vogiatzis, Konstantinos; Angeli, George Z.
2008-07-01
This presentation describes a strategy for assessing the performance of the Thirty Meter Telescope (TMT). A Monte Carlo Simulation Framework has been developed to combine optical modeling with Computational Fluid Dynamics simulations (CFD), Finite Element Analysis (FEA) and controls to model the overall performance of TMT. The framework consists of a two year record of observed environmental parameters such as atmospheric seeing, site wind speed and direction, ambient temperature and local sunset and sunrise times, along with telescope azimuth and elevation with a given sampling rate. The modeled optical, dynamic and thermal seeing aberrations are available in a matrix form for distinct values within the range of influencing parameters. These parameters are either part of the framework parameter set or can be derived from them at each time-step. As time advances, the aberrations are interpolated and combined based on the current value of their parameters. Different scenarios can be generated based on operating parameters such as venting strategy, optical calibration frequency and heat source control. Performance probability distributions are obtained and provide design guidance. The sensitivity of the system to design, operating and environmental parameters can be assessed in order to maximize the % of time the system meets the performance specifications.
Monte Carlo studies of interpenetrating polymer network formation
NASA Astrophysics Data System (ADS)
Schulz, Michael; Frisch, Harry L.
1994-12-01
We present a lattice Monte-Carlo simulation of polymer network formation using the bond fluctuation method. We apply this procedure to simulate the formation of a class of simultaneous interpenetrating polymer networks (IPNs) which has been experimentally studied consisting of one network crosslinked with a trifunctional monomer (PCU) and another crosslinked with a tetrafunctional monomer (the free radical vinyl polymer network). The numerical simulation reveals essentially all features found experimentally for this class of IPNs. The system composition and initial morphology, at least for reactions which are relatively fast compared to the uphill diffusion process causing phase separation, is in good agreement with a mean field [random-phase approximations (RPA)] theory.
3D Monte Carlo radiation transfer modelling of photodynamic therapy
NASA Astrophysics Data System (ADS)
Campbell, C. Louise; Christison, Craig; Brown, C. Tom A.; Wood, Kenneth; Valentine, Ronan M.; Moseley, Harry
2015-06-01
The effects of ageing and skin type on Photodynamic Therapy (PDT) for different treatment methods have been theoretically investigated. A multilayered Monte Carlo Radiation Transfer model is presented where both daylight activated PDT and conventional PDT are compared. It was found that light penetrates deeper through older skin with a lighter complexion, which translates into a deeper effective treatment depth. The effect of ageing was found to be larger for darker skin types. The investigation further strengthens the usage of daylight as a potential light source for PDT where effective treatment depths of about 2 mm can be achieved.
Metrics for Diagnosing Undersampling in Monte Carlo Tally Estimates
Perfetti, Christopher M.; Rearden, Bradley T.
2015-01-01
This study explored the potential of using Markov chain convergence diagnostics to predict the prevalence and magnitude of biases due to undersampling in Monte Carlo eigenvalue and flux tally estimates. Five metrics were applied to two models of pressurized water reactor fuel assemblies and their potential for identifying undersampling biases was evaluated by comparing the calculated test metrics with known biases in the tallies. Three of the five undersampling metrics showed the potential to accurately predict the behavior of undersampling biases in the responses examined in this study.
Monte Carlo simulation studies of backscatter factors in mammography
Chan, H.P.; Doi, K.
1981-04-01
Experimentally determined backscatter factors in mammography can contain significant systematic errors due to the energy response, dimensions, and location of the dosimeter used. In this study, the Monte Carlo method was applied to simulate photon scattering in tissue-equivalent media and to determine backscatter factors without the interference of a detector. The physical processes of measuring backscatter factors with a lithium fluoride thermoluminescent dosimeter (TLD) and an ideal tissue-equivalent detector were also simulated. Computed results were compared with the true backscatter factors and with measured values reported by other investigators. It was found that the TLD method underestimated backscatter factors in mammography by as much as 10% at high energies.
Active neutron multiplicity analysis and Monte Carlo calculations
NASA Astrophysics Data System (ADS)
Krick, M. S.; Ensslin, N.; Langner, D. G.; Miller, M. C.; Siebelist, R.; Stewart, J. E.; Ceo, R. N.; May, P. K.; Collins, L. L., Jr.
Active neutron multiplicity measurements of high-enrichment uranium metal and oxide samples have been made at Los Alamos and Y-12. The data from the measurements of standards at Los Alamos were analyzed to obtain values for neutron multiplication and source-sample coupling. These results are compared to equivalent results obtained from Monte Carlo calculations. An approximate relationship between coupling and multiplication is derived and used to correct doubles rates for multiplication and coupling. The utility of singles counting for uranium samples is also examined.
Positronic molecule calculations using Monte Carlo configuration interaction
NASA Astrophysics Data System (ADS)
Coe, Jeremy P.; Paterson, Martin J.
2016-02-01
We modify the Monte Carlo configuration interaction procedure to model atoms and molecules combined with a positron. We test this method with standard quantum chemistry basis sets on a number of positronic systems and compare results with the literature and full configuration interaction when appropriate. We consider positronium hydride, positronium hydroxide, lithium positride and a positron interacting with lithium, magnesium or lithium hydride. We demonstrate that we can capture much of the full configuration interaction results, but often require less than 10% of the configurations of these multireference wavefunctions. The effect of the number of frozen orbitals is also discussed.
Svatos, M.; Zankowski, C.; Bednarz, B.
2016-01-01
Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship within a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the
Mukumoto, Nobutaka; Tsujii, Katsutomo; Saito, Susumu; Yasunaga, Masayoshi; Takegawa, Hidek; Yamamoto, Tokihiro; Numasaki, Hodaka; Teshima, Teruki
2009-10-01
Purpose: To develop an infrastructure for the integrated Monte Carlo verification system (MCVS) to verify the accuracy of conventional dose calculations, which often fail to accurately predict dose distributions, mainly due to inhomogeneities in the patient's anatomy, for example, in lung and bone. Methods and Materials: The MCVS consists of the graphical user interface (GUI) based on a computational environment for radiotherapy research (CERR) with MATLAB language. The MCVS GUI acts as an interface between the MCVS and a commercial treatment planning system to import the treatment plan, create MC input files, and analyze MC output dose files. The MCVS consists of the EGSnrc MC codes, which include EGSnrc/BEAMnrc to simulate the treatment head and EGSnrc/DOSXYZnrc to calculate the dose distributions in the patient/phantom. In order to improve computation time without approximations, an in-house cluster system was constructed. Results: The phase-space data of a 6-MV photon beam from a Varian Clinac unit was developed and used to establish several benchmarks under homogeneous conditions. The MC results agreed with the ionization chamber measurements to within 1%. The MCVS GUI could import and display the radiotherapy treatment plan created by the MC method and various treatment planning systems, such as RTOG and DICOM-RT formats. Dose distributions could be analyzed by using dose profiles and dose volume histograms and compared on the same platform. With the cluster system, calculation time was improved in line with the increase in the number of central processing units (CPUs) at a computation efficiency of more than 98%. Conclusions: Development of the MCVS was successful for performing MC simulations and analyzing dose distributions.
Monte Carlo variance reduction approaches for non-Boltzmann tallies
Booth, T.E.
1992-12-01
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed.
OBJECT KINETIC MONTE CARLO SIMULATIONS OF CASCADE ANNEALING IN TUNGSTEN
Nandipati, Giridhar; Setyawan, Wahyu; Heinisch, Howard L.; Roche, Kenneth J.; Kurtz, Richard J.; Wirth, Brian D.
2014-03-31
The objective of this work is to study the annealing of primary cascade damage created by primary knock-on atoms (PKAs) of various energies, at various temperatures in bulk tungsten using the object kinetic Monte Carlo (OKMC) method.
Monte Carlo techniques for analyzing deep penetration problems
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1985-01-01
A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications. 29 refs.
Enhancements in Continuous-Energy Monte Carlo Capabilities in SCALE
Bekar, Kursat B; Celik, Cihangir; Wiarda, Dorothea; Peplow, Douglas E.; Rearden, Bradley T; Dunn, Michael E
2013-01-01
Monte Carlo tools in SCALE are commonly used in criticality safety calculations as well as sensitivity and uncertainty analysis, depletion, and criticality alarm system analyses. Recent improvements in the continuous-energy data generated by the AMPX code system and significant advancements in the continuous-energy treatment in the KENO Monte Carlo eigenvalue codes facilitate the use of SCALE Monte Carlo codes to model geometrically complex systems with enhanced solution fidelity. The addition of continuous-energy treatment to the SCALE Monaco code, which can be used with automatic variance reduction in the hybrid MAVRIC sequence, provides significant enhancements, especially for criticality alarm system modeling. This paper describes some of the advancements in continuous-energy Monte Carlo codes within the SCALE code system.
DETERMINING UNCERTAINTY IN PHYSICAL PARAMETER MEASUREMENTS BY MONTE CARLO SIMULATION
A statistical approach, often called Monte Carlo Simulation, has been used to examine propagation of error with measurement of several parameters important in predicting environmental transport of chemicals. These parameters are vapor pressure, water solubility, octanol-water par...
A Particle Population Control Method for Dynamic Monte Carlo
NASA Astrophysics Data System (ADS)
Sweezy, Jeremy; Nolen, Steve; Adams, Terry; Zukaitis, Anthony
2014-06-01
A general particle population control method has been derived from splitting and Russian Roulette for dynamic Monte Carlo particle transport. A well-known particle population control method, known as the particle population comb, has been shown to be a special case of this general method. This general method has been incorporated in Los Alamos National Laboratory's Monte Carlo Application Toolkit (MCATK) and examples of it's use are shown for both super-critical and sub-critical systems.