While these samples are representative of the content of Science.gov,

they are not comprehensive nor are they the most current set.

We encourage you to perform a real-time search of Science.gov

to obtain the most current and comprehensive results.

Last update: August 15, 2014.

1

Successful combination of the stochastic linearization and Monte Carlo methods

NASA Technical Reports Server (NTRS)

A combination of a stochastic linearization and Monte Carlo techniques is presented for the first time in literature. A system with separable nonlinear damping and nonlinear restoring force is considered. The proposed combination of the energy-wise linearization with the Monte Carlo method yields an error under 5 percent, which corresponds to the error reduction associated with the conventional stochastic linearization by a factor of 4.6.

Elishakoff, I.; Colombi, P.

1993-01-01

2

Stabilized multilevel Monte Carlo method for stiff stochastic differential equations

A multilevel Monte Carlo (MLMC) method for mean square stable stochastic differential equations with multiple scales is proposed. For such problems, that we call stiff, the performance of MLMC methods based on classical explicit methods deteriorates because of the time step restriction to resolve the fastest scales that prevents to exploit all the levels of the MLMC approach. We show that by switching to explicit stabilized stochastic methods and balancing the stabilization procedure simultaneously with the hierarchical sampling strategy of MLMC methods, the computational cost for stiff systems is significantly reduced, while keeping the computational algorithm fully explicit and easy to implement. Numerical experiments on linear and nonlinear stochastic differential equations and on a stochastic partial differential equation illustrate the performance of the stabilized MLMC method and corroborate our theoretical findings.

Abdulle, Assyr, E-mail: assyr.abdulle@epfl.ch; Blumenthal, Adrian, E-mail: adrian.blumenthal@epfl.ch

2013-10-15

3

Semi-stochastic full configuration interaction quantum Monte Carlo

NASA Astrophysics Data System (ADS)

In the recently proposed full configuration interaction quantum Monte Carlo (FCIQMC) [1,2], the ground state is projected out stochastically, using a population of walkers each of which represents a basis state in the Hilbert space spanned by Slater determinants. The infamous fermion sign problem manifests itself in the fact that walkers of either sign can be spawned on a given determinant. We propose an improvement on this method in the form of a hybrid stochastic/deterministic technique, which we expect will improve the efficiency of the algorithm by ameliorating the sign problem. We test the method on atoms and molecules, e.g., carbon, carbon dimer, N2 molecule, and stretched N2. [4pt] [1] Fermion Monte Carlo without fixed nodes: a Game of Life, death and annihilation in Slater Determinant space. George Booth, Alex Thom, Ali Alavi. J Chem Phys 131, 050106, (2009).[0pt] [2] Survival of the fittest: Accelerating convergence in full configuration-interaction quantum Monte Carlo. Deidre Cleland, George Booth, and Ali Alavi. J Chem Phys 132, 041103 (2010).

Holmes, Adam; Petruzielo, Frank; Khadilkar, Mihir; Changlani, Hitesh; Nightingale, M. P.; Umrigar, C. J.

2012-02-01

4

Optimization of Monte Carlo transport simulations in stochastic media

This paper presents an accurate and efficient approach to optimize radiation transport simulations in a stochastic medium of high heterogeneity, like the Very High Temperature Gas-cooled Reactor (VHTR) configurations packed with TRISO fuel particles. Based on a fast nearest neighbor search algorithm, a modified fast Random Sequential Addition (RSA) method is first developed to speed up the generation of the stochastic media systems packed with both mono-sized and poly-sized spheres. A fast neutron tracking method is then developed to optimize the next sphere boundary search in the radiation transport procedure. In order to investigate their accuracy and efficiency, the developed sphere packing and neutron tracking methods are implemented into an in-house continuous energy Monte Carlo code to solve an eigenvalue problem in VHTR unit cells. Comparison with the MCNP benchmark calculations for the same problem indicates that the new methods show considerably higher computational efficiency. (authors)

Liang, C.; Ji, W. [Dept. of Mechanical, Aerospace and Nuclear Engineering, Rensselaer Polytechnic Inst., 110 8th street, Troy, NY (United States)

2012-07-01

5

Stochastic kinetic Monte Carlo algorithms for long-range Hamiltonians

We present a higher order kinetic Monte Carlo methodology suitable to model the evolution of systems in which the transition rates are non-trivial to calculate or in which Monte Carlo moves are likely to be non-productive flicker events. The second order residence time algorithm first introduced by Athčnes et al. [Phil. Mag. A 76 (1997) 565] is rederived from the n-fold

D. R. Mason; R. E. Rudd; A. P. Sutton

2004-01-01

6

Stochastic Perturbation Algorithms for Kinetic Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

The accuracy of the kinetic Monte Carlo (KMC) simulations depends on the reliability of transition data used in the calculations. The sensitivity analyses may be useful to quantify the uncertainty of the KMC output and enhance the accuracy by ordering the transition data by importance. I derive a formulation of the differential operator sampling method for the KMC perturbation analysis from the Neumann series solution to the KMC master equation. The effectiveness of the KMC perturbation method is demonstrated in a simplified radioactive decay problem and the Langmuirian adsorption dynamics problem.

Shim, Hyung Jin

2014-06-01

7

A benchmark comparison of Monte Carlo particle transport algorithms for binary stochastic mixtures

We numerically investigate the accuracy of two Monte Carlo algorithms originally proposed by Zimmerman [1] and Zimmerman and Adams [2] for particle transport through binary stochastic mixtures. We assess the accuracy of these algorithms using a standard suite of planar geometry incident angular flux benchmark problems and a new suite of interior source benchmark problems. In addition to comparisons of

Patrick S. Brantley

2011-01-01

8

Stochastic variability in effective dose tissue weighting factors: A Monte Carlo study

Tissue-weighting factors used in the calculation of the effective dose have undergone revision in the light of new data from the atomic bomb survivors. A Monte Carlo simulation was designed to evaluate the magnitude of stochastic errors in the derived factors. Results demonstrate substantial variability in the suggested factors. 19 refs., 2 figs., 4 tabs.

Leslie, W.D. [St. Boniface General Hospital, Winnipeg (Canada)

1994-07-01

9

A Hybrid Monte Carlo-Deterministic Method for Global Binary Stochastic Medium Transport Problems

Global deep-penetration transport problems are difficult to solve using traditional Monte Carlo techniques. In these problems, the scalar flux distribution is desired at all points in the spatial domain (global nature), and the scalar flux typically drops by several orders of magnitude across the problem (deep-penetration nature). As a result, few particle histories may reach certain regions of the domain, producing a relatively large variance in tallies in those regions. Implicit capture (also known as survival biasing or absorption suppression) can be used to increase the efficiency of the Monte Carlo transport algorithm to some degree. A hybrid Monte Carlo-deterministic technique has previously been developed by Cooper and Larsen to reduce variance in global problems by distributing particles more evenly throughout the spatial domain. This hybrid method uses an approximate deterministic estimate of the forward scalar flux distribution to automatically generate weight windows for the Monte Carlo transport simulation, avoiding the necessity for the code user to specify the weight window parameters. In a binary stochastic medium, the material properties at a given spatial location are known only statistically. The most common approach to solving particle transport problems involving binary stochastic media is to use the atomic mix (AM) approximation in which the transport problem is solved using ensemble-averaged material properties. The most ubiquitous deterministic model developed specifically for solving binary stochastic media transport problems is the Levermore-Pomraning (L-P) model. Zimmerman and Adams proposed a Monte Carlo algorithm (Algorithm A) that solves the Levermore-Pomraning equations and another Monte Carlo algorithm (Algorithm B) that is more accurate as a result of improved local material realization modeling. Recent benchmark studies have shown that Algorithm B is often significantly more accurate than Algorithm A (and therefore the L-P model) for deep penetration problems such as examined in this paper. In this research, we investigate the application of a variant of the hybrid Monte Carlo-deterministic method proposed by Cooper and Larsen to global deep penetration problems involving binary stochastic media. To our knowledge, hybrid Monte Carlo-deterministic methods have not previously been applied to problems involving a stochastic medium. We investigate two approaches for computing the approximate deterministic estimate of the forward scalar flux distribution used to automatically generate the weight windows. The first approach uses the atomic mix approximation to the binary stochastic medium transport problem and a low-order discrete ordinates angular approximation. The second approach uses the Levermore-Pomraning model for the binary stochastic medium transport problem and a low-order discrete ordinates angular approximation. In both cases, we use Monte Carlo Algorithm B with weight windows automatically generated from the approximate forward scalar flux distribution to obtain the solution of the transport problem.

Keady, K P; Brantley, P

2010-03-04

10

In this paper, we explore the impact of several sources of uncertainties on the assessment of energy and climate policies\\u000a when one uses in a harmonized way stochastic programming in a large-scale bottom-up (BU) model and Monte Carlo simulation\\u000a in a large-scale top-down (TD) model. The BU model we use is the TIMES Integrated Assessment Model, which is run in

Frédéric Babonneau; Alain Haurie; Richard Loulou; Marc Vielle

11

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a LotkaVolterra system and a prokaryotic auto-regulatory network.

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

12

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka-Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

Golightly, Andrew; Wilkinson, Darren J

2011-12-01

13

A Comparison of Monte Carlo Particle Transport Algorithms for Binary Stochastic Mixtures

Two Monte Carlo algorithms originally proposed by Zimmerman and Zimmerman and Adams for particle transport through a binary stochastic mixture are numerically compared using a standard set of planar geometry benchmark problems. In addition to previously-published comparisons of the ensemble-averaged probabilities of reflection and transmission, we include comparisons of detailed ensemble-averaged total and material scalar flux distributions. Because not all benchmark scalar flux distribution data used to produce plots in previous publications remains available, we have independently regenerated the benchmark solutions including scalar flux distributions. Both Monte Carlo transport algorithms robustly produce physically-realistic scalar flux distributions for the transport problems examined. The first algorithm reproduces the standard Levermore-Pomraning model results for the probabilities of reflection and transmission. The second algorithm generally produces significantly more accurate probabilities of reflection and transmission and also significantly more accurate total and material scalar flux distributions.

Brantley, P S

2009-02-23

14

NASA Astrophysics Data System (ADS)

Image blurring as a result of stochastic particle-particle interactions has been investigated for a particle projection system. A comparative analysis of the currently available analytical theories is presented. The results from these theories are also compared with Monte Carlo simulation results. Large variations in results and serious disagreements between the different theoretical approaches are found. The origin of the discrepancies arising from the earlier theories are understood and explained on the basis of our recently developed theory with two key concepts: consideration of nearest-neighbor interactions only, and a randomization length, over which the interactions are correlated.

Mkrtchyan, Masis M.; Berger, Steven D.; Liddle, J. A.; Harriott, Lloyd R.

1995-09-01

15

Particle transport through binary stochastic mixtures has received considerable research attention in the last two decades. Zimmerman and Adams proposed a Monte Carlo algorithm (Algorithm A) that solves the Levermore-Pomraning equations and another Monte Carlo algorithm (Algorithm B) that should be more accurate as a result of improved local material realization modeling. Zimmerman and Adams numerically confirmed these aspects of the Monte Carlo algorithms by comparing the reflection and transmission values computed using these algorithms to a standard suite of planar geometry binary stochastic mixture benchmark transport solutions. The benchmark transport problems are driven by an isotropic angular flux incident on one boundary of a binary Markovian statistical planar geometry medium. In a recent paper, we extended the benchmark comparisons of these Monte Carlo algorithms to include the scalar flux distributions produced. This comparison is important, because as demonstrated, an approximate model that gives accurate reflection and transmission probabilities can produce unphysical scalar flux distributions. Brantley and Palmer recently investigated the accuracy of the Levermore-Pomraning model using a new interior source binary stochastic medium benchmark problem suite. In this paper, we further investigate the accuracy of the Monte Carlo algorithms proposed by Zimmerman and Adams by comparing to the benchmark results from the interior source binary stochastic medium benchmark suite, including scalar flux distributions. Because the interior source scalar flux distributions are of an inherently different character than the distributions obtained for the incident angular flux benchmark problems, the present benchmark comparison extends the domain of problems for which the accuracy of these Monte Carlo algorithms has been investigated.

Brantley, P S

2009-06-30

16

Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error. PMID:23246109

Huang, Guanghui; Wan, Jianping; Chen, Hui

2013-02-01

17

Deterministic flows of order-parameters in stochastic processes of quantum Monte Carlo method

NASA Astrophysics Data System (ADS)

In terms of the stochastic process of quantum-mechanical version of Markov chain Monte Carlo method (the MCMC), we analytically derive macroscopically deterministic flow equations of order parameters such as spontaneous magnetization in infinite-range (d(= ?)-dimensional) quantum spin systems. By means of the Trotter decomposition, we consider the transition probability of Glauber-type dynamics of microscopic states for the corresponding (d + 1)-dimensional classical system. Under the static approximation, differential equations with respect to macroscopic order parameters are explicitly obtained from the master equation that describes the microscopic-law. In the steady state, we show that the equations are identical to the saddle point equations for the equilibrium state of the same system. The equation for the dynamical Ising model is recovered in the classical limit. We also check the validity of the static approximation by making use of computer simulations for finite size systems and discuss several possible extensions of our approach to disordered spin systems for statistical-mechanical informatics. Especially, we shall use our procedure to evaluate the decoding process of Bayesian image restoration. With the assistance of the concept of dynamical replica theory (the DRT), we derive the zero-temperature flow equation of image restoration measure showing some 'non-monotonic' behaviour in its time evolution.

Inoue, Jun-ichi

2010-06-01

18

A Hybrid Monte Carlo-Deterministic Method for Global Binary Stochastic Medium Transport Problems

Global deep-penetration transport problems are difficult to solve using traditional Monte Carlo techniques. In these problems, the scalar flux distribution is desired at all points in the spatial domain (global nature), and the scalar flux typically drops by several orders of magnitude across the problem (deep-penetration nature). As a result, few particle histories may reach certain regions of the domain,

K P Keady; P Brantley

2010-01-01

19

NASA Astrophysics Data System (ADS)

Stochastic-media simulations require numerous boundary crossings. We consider two Monte Carlo electron transport approaches and evaluate accuracy with numerous material boundaries. In the condensed-history method, approximations are made based on infinite-medium solutions for multiple scattering over some track length. Typically, further approximations are employed for material-boundary crossings where infinite-medium solutions become invalid. We have previously explored an alternative "condensed transport" formulation, a Generalized Boltzmann-Fokker-Planck GBFP method, which requires no special boundary treatment but instead uses approximations to the electron-scattering cross sections. Some limited capabilities for analog transport and a GBFP method have been implemented in the Integrated Tiger Series (ITS) codes. Improvements have been made to the condensed history algorithm. The performance of the ITS condensed-history and condensed-transport algorithms are assessed for material-boundary crossings. These assessments are made both by introducing artificial material boundaries and by comparison to analog Monte Carlo simulations.

Franke, Brian C.; Kensek, Ronald P.; Prinja, Anil K.

2014-06-01

20

NASA Astrophysics Data System (ADS)

We propose a new variational Monte Carlo (VMC) approach based on the Krylov subspace for large-scale shell-model calculations. A random walker in the VMC is formulated with the M-scheme representation, and samples a small number of configurations from a whole Hilbert space stochastically. This VMC framework is demonstrated in the shell-model calculations of 48Cr and 60Zn, and we discuss its relation to a small number of Lanczos iterations. By utilizing the wave function obtained by the conventional particle-hole-excitation truncation as an initial state, this VMC approach provides us with a sequence of systematically improved results.

Shimizu, Noritaka; Mizusaki, Takahiro; Kaneko, Kazunari

2013-06-01

21

Stochastic method for accommodation of equilibrating basins in kinetic Monte Carlo simulations

A computationally simple way to accommodate "basins" of trapping states in standard kinetic Monte Carlo simulations is presented. By assuming the system is effectively equilibrated in the basin, the residence time (time spent in the basin before escape) and the probabilities for transition to states outside the basin may be calculated. This is demonstrated for point defect diffusion over a periodic grid of sites containing a complex basin.

Van Siclen, Clinton D

2007-02-01

22

NASA Astrophysics Data System (ADS)

Monte Carlo Ray Tracing (MCRT) method is a versatile application for simulating radiative transfer regime of the Solar - Atmosphere - Landscape system. Moreover, it can be used to compute the radiation distribution over a complex landscape configuration, as an example like a forest area. Due to its robustness to the complexity of the 3-D scene altering, MCRT method is also employed for simulating canopy radiative transfer regime as the validation source of other radiative transfer models. In MCRT modeling within vegetation, one basic step is the canopy scene set up. 3-D scanning application was used for representing canopy structure as accurately as possible, but it is time consuming. Botanical growth function can be used to model the single tree growth, but cannot be used to express the impaction among trees. L-System is also a functional controlled tree growth simulation model, but it costs large computing memory. Additionally, it only models the current tree patterns rather than tree growth during we simulate the radiative transfer regime. Therefore, it is much more constructive to use regular solid pattern like ellipsoidal, cone, cylinder etc. to indicate single canopy. Considering the allelopathy phenomenon in some open forest optical images, each tree in its own `domain' repels other trees. According to this assumption a stochastic circle packing algorithm is developed to generate the 3-D canopy scene in this study. The canopy coverage (%) and the tree amount (N) of the 3-D scene are declared at first, similar to the random open forest image. Accordingly, we randomly generate each canopy radius (rc). Then we set the circle central coordinate on XY-plane as well as to keep circles separate from each other by the circle packing algorithm. To model the individual tree, we employ the Ishikawa's tree growth regressive model to set the tree parameters including DBH (dt), tree height (H). However, the relationship between canopy height (Hc) and trunk height (Ht) is unclear to us. We assume the proportion between Hc and Ht as a random number in the interval from 2.0 to 3.0. De Wit's sphere leaf angle distribution function was used within the canopy for acceleration. Finally, we simulate the open forest albedo using MCRT method. The MCRT algorithm of this study is summarized as follows (1) Initialize the photon with a position (r0), source direction (?0) and intensity (I0), respectively. (2) Simulate the free path (s) of a photon under the condition of (r', ?, I') in the canopy. (3) Calculate the new position of the photon r=r +s?'. (4) Determine the new scattering direction (?)after collision at, r and then calculate the new intensity I = ?L(?L,?'-->?)I'.(5) Accumulate the intensity I of a photon escaping from the top boundary of the 3-D Scene, otherwise redo from step (2), until I is smaller than a threshold. (6) Repeat from step (1), for each photon. We testify the model on four different simulated open forests and the effectiveness of the model is demonstrated in details.

Jin, Shengye; Tamura, Masayuki

2013-10-01

23

Monte Carlo (MC) simulation of most spatially distributed systems is plagued by several problems, namely, execution of one process at a time, large separation of time scales of various processes, and large length scales. Recently, a coarse-grained Monte Carlo (CGMC) method was introduced that can capture large length scales at reasonable computational times. An inherent assumption in this CGMC method revolves around a mean-field closure invoked in each coarse cell that is inaccurate for short-ranged interactions. Two new approaches are explored to improve upon this closure. The first employs the local quasichemical approximation, which is applicable to first nearest-neighbor interactions. The second, termed multiscale CGMC method, employs singular perturbation ideas on multiple grids to capture the entire cluster probability distribution function via short microscopic MC simulations on small, fine-grid lattices by taking advantage of the time scale separation of multiple processes. Computational strategies for coupling the fast process at small length scales (fine grid) with the slow processes at large length scales (coarse grid) are discussed. Finally, the binomial tau-leap method is combined with the multiscale CGMC method to execute multiple processes over the entire lattice and provide additional computational acceleration. Numerical simulations demonstrate that in the presence of fast diffusion and slow adsorption and desorption processes the two new approaches provide more accurate solutions in comparison to the previously introduced CGMC method. PMID:16483199

Chatterjee, Abhijit; Vlachos, Dionisios G

2006-02-14

24

NASA Astrophysics Data System (ADS)

Monte Carlo (MC) simulation of most spatially distributed systems is plagued by several problems, namely, execution of one process at a time, large separation of time scales of various processes, and large length scales. Recently, a coarse-grained Monte Carlo (CGMC) method was introduced that can capture large length scales at reasonable computational times. An inherent assumption in this CGMC method revolves around a mean-field closure invoked in each coarse cell that is inaccurate for short-ranged interactions. Two new approaches are explored to improve upon this closure. The first employs the local quasichemical approximation, which is applicable to first nearest-neighbor interactions. The second, termed multiscale CGMC method, employs singular perturbation ideas on multiple grids to capture the entire cluster probability distribution function via short microscopic MC simulations on small, fine-grid lattices by taking advantage of the time scale separation of multiple processes. Computational strategies for coupling the fast process at small length scales (fine grid) with the slow processes at large length scales (coarse grid) are discussed. Finally, the binomial ?-leap method is combined with the multiscale CGMC method to execute multiple processes over the entire lattice and provide additional computational acceleration. Numerical simulations demonstrate that in the presence of fast diffusion and slow adsorption and desorption processes the two new approaches provide more accurate solutions in comparison to the previously introduced CGMC method.

Chatterjee, Abhijit; Vlachos, Dionisios G.

2006-02-01

25

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.

Brown, F.B.; Sutton, T.M.

1996-02-01

26

Accurate prediction of complex phenomena can be greatly enhanced through the use of data and observations to update simulations. The ability to create these data-driven simulations is limited by error and uncertainty in both the data and the simulation. The stochastic engine project addressed this problem through the development and application of a family of Markov Chain Monte Carlo methods

R E Glaser; G Johannesson; S Sengupta; B Kosovic; S Carle; G A Franz; R D Aines; J J Nitao; W G Hanley; A L Ramirez; R L Newmark; V M Johnson; K M Dyer; K A Henderson; G A Sugiyama; T L Hickling; M E Pasyanos; D A Jones; R J Grimm; R A Levine

2004-01-01

27

NASA Astrophysics Data System (ADS)

Traditional Monte Carlo ray-tracing (MCRT) methods for continuous participating media are not applicable in media represented by point masses (or stochastic particles) frequently encountered in combustion modeling. In the authors previous work several ray models and particle models have been proposed for radiation simulations in such media. In the present paper an efficient emission scheme is developed for MCRT in highly inhomogeneous media represented by particle fields. Ray energies are limited to a narrow range to reduce statistical error, by having particles emit numbers of photons proportional to their emissive power (including combination of weak particles). A method to evaluate the radiative heat source, required by the overall energy equation, is also developed. A particle field representing the highly inhomogeneous medium in a turbulent jet flame is employed to test the proposed methods.

Wang, Anquan; Modest, Michael F.

2007-03-01

28

We present a Monte Carlo algorithm for learning to act in partially observable Markov decision processes (POMDPs) with real-valued state and action spaces. Our approach uses importance sampling for representing beliefs, and Monte Carlo approximation for belief propagation. A reinforcement learning algorithm, value iteration, is employed to learn value functions over belief states. Finally, a sample- based version of nearest

Sebastian Thrun

1999-01-01

29

A stochastic Markov chain approach for tennis: Monte Carlo simulation and modeling

NASA Astrophysics Data System (ADS)

This dissertation describes the computational formulation of probability density functions (pdfs) that facilitate head-to-head match simulations in tennis along with ranking systems developed from their use. A background on the statistical method used to develop the pdfs , the Monte Carlo method, and the resulting rankings are included along with a discussion on ranking methods currently being used both in professional sports and in other applications. Using an analytical theory developed by Newton and Keller in [34] that defines a tennis player's probability of winning a game, set, match and single elimination tournament, a computational simulation has been developed in Matlab that allows further modeling not previously possible with the analytical theory alone. Such experimentation consists of the exploration of non-iid effects, considers the concept the varying importance of points in a match and allows an unlimited number of matches to be simulated between unlikely opponents. The results of these studies have provided pdfs that accurately model an individual tennis player's ability along with a realistic, fair and mathematically sound platform for ranking them.

Aslam, Kamran

30

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.

Cramer, S.N.

1984-01-01

31

Semistochastic projector Monte Carlo method.

We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix multiplication is partially implemented numerically exactly and partially stochastically with respect to expectation values only. Compared to a fully stochastic method, the semistochastic approach significantly reduces the computational time required to obtain the eigenvalue to a specified statistical uncertainty. This is demonstrated by the application of the semistochastic quantum Monte Carlo method to systems with a sign problem: the fermion Hubbard model and the carbon dimer. PMID:23368167

Petruzielo, F R; Holmes, A A; Changlani, Hitesh J; Nightingale, M P; Umrigar, C J

2012-12-01

32

Monte-Carlo simulation of dynamics system with stochastic parameters in the Solar system

In developing models describing possible formation procceses of differemt small bodies in the Solar system, when factors of objective and subjective uncertainties are present, it is reasonable to use the methods of stochastic formalism of a problem. First, stochastic formalism of a problem brings it closer to the real process as the input model in its realization is not substituted

A. V. Myshev; N. V. Kulikova

1997-01-01

33

Monte Carlo radiative transfer

NASA Astrophysics Data System (ADS)

I outline methods for calculating the solution of Monte Carlo Radiative Transfer (MCRT) in scattering, absorption and emission processes of dust and gas, including polarization. I provide a bibliography of relevant papers on methods with astrophysical applications.

Whitney, B. A.

2011-03-01

34

Monte Carlo radiative transfer

NASA Astrophysics Data System (ADS)

I outline methods for calculating the solution of Monte Carlo Radiative Transfer (MCRT) in scattering, absorption and emission processes of dust and gas, including polarization. I provide a bibliography of relevant papers on methods with astrophysical applications.

Whitney, Barbara A.

2011-12-01

35

Monte Carlo algorithms are developed to calculate the ensemble-average particle leakage through the boundaries of a 2-D binary stochastic material. The mixture is specified within a rectangular area and consists of a fixed number of disks of constant radius randomly embedded in a matrix material. The algorithms are extensions of the proposal of Zimmerman et al., using chord-length sampling to eliminate the need to explicitly model the geometry of the mixture. Two variations are considered. The first algorithm uses Chord-Length Sampling (CLS) for both material regions. The second algorithm employs Limited Chord Length Sampling (LCLS), only using chord-length sampling in the matrix material. Ensemble-average leakage results are computed for a range of material interaction coefficients and compared against benchmark results for both accuracy and efficiency. both algorithms are exact for purely absorbing materials and provide decreasing accuracy as scattering is increased in the matrix material. The LCLS algorithm shows a better accuracy than the CLS algorithm for all cases while maintaining an equivalent or better efficiency. Accuracy and efficiency problems with the CLS algorithm are due principally to assumptions made in determining the chord-length distribution within the disks.

T.J. Donovan; Y. Danon

2002-03-15

36

A stochastic model of the resistive switching mechanism in bipolar metal-oxide based resistive random access memory (RRAM)\\u000a is presented. The distribution of electron occupation probabilities obtained is in agreement with previous work. In particular,\\u000a a low occupation region is formed near the cathode. Our simulations of the temperature dependence of the electron occupation\\u000a probability near the anode and the cathode

Alexander Makarov; Viktor Sverdlov; Siegfried Selberherr

2010-01-01

37

Shell model Monte Carlo methods

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.

Koonin, S.E. [California Inst. of Tech., Pasadena, CA (United States). W.K. Kellogg Radiation Lab.; Dean, D.J. [Oak Ridge National Lab., TN (United States)

1996-10-01

38

Stochastic theory of interfacial enzyme kinetics: A kinetic Monte Carlo study

NASA Astrophysics Data System (ADS)

In the spirit of Gillespie's stochastic approach we have formulated a theory to explore the advancement of the interfacial enzyme kinetics at the single enzyme level which is ultimately utilized to obtain the ensemble average macroscopic feature, lag-burst kinetics. We have provided a theory of the transition from the lag phase to the burst phase kinetics by considering the gradual development of electrostatic interaction among the positively charged enzyme and negatively charged product molecules deposited on the phospholipid surface. It is shown that the different diffusion time scales of the enzyme over the fluid and product regions are responsible for the memory effect in the correlation of successive turnover events of the hopping mode in the single trajectory analysis which again is reflected on the non-Gaussian distribution of turnover times on the macroscopic kinetics in the lag phase unlike the burst phase kinetics.

Das, Biswajit; Gangopadhyay, Gautam

2012-01-01

39

Viral load and stochastic mutation in a Monte Carlo simulation of HIV

NASA Astrophysics Data System (ADS)

Viral load is examined, as a function of primary viral growth factor ( Pg) and mutation, through a computer simulation model for HIV immune response. Cell-mediated immune response is considered on a cubic lattice with four cell types: macrophage ( M), helper ( H), cytotoxic ( C), and virus ( V). Rule-based interactions are used with random sequential update of the binary cellular states. The relative viral load (the concentration of virus with respect to helper cells) is found to increase with the primary viral growth factor above a critical value ( Pc), leading to a phase transition from immuno-competent to immuno-deficient state. The critical growth factor ( Pc) seems to depend on mobility and mutation. The stochastic growth due to mutation is found to depend non-monotonically on the relative viral load, with a maximum at a characteristic load which is lower for stronger viral growth.

Ruskin, H. J.; Pandey, R. B.; Liu, Y.

2002-08-01

40

The Monte Carlo method is a well established approach for the statistical solution of the Boltz- mann transport equation in semiconductors (l, 21. As device dimensions are reduced, it is important to account for hot electron effects, responsible for overshoot phenomena and reliability problems like breakdown due to impact ionization, defect generation, and injection into gate oxides. In some cases,

C. H. Lee; U. Ravaioli

41

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.

Dytman, Steven [Department.of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260 (United States)

2011-10-06

42

Monte Carlo valuation of natural gas investments

In this evaluation of energy assets related to natural gas, our particular focus is on a base load natural gas combined cycle power plant and a liquefied natural gas facility in a realistic setting. We also value several American-type investment options following the least squares Monte Carlo approach. We calibrate mean-reverting stochastic processes for gas and electricity prices by using

Luis M. Abadie; José M. Chamorro

2009-01-01

43

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.

Chin, P.W. [Department of Medical Physics, Velindre Cancer Centre, Velindre Road, Cardiff CF14 2TL (United Kingdom)]. E-mail: mary.chin@physics.org

2005-10-15

44

Monte Carlo fluorescence microtomography

Fluorescence microscopy allows real-time monitoring of optical molecular probes for disease characterization, drug development, and tissue regeneration. However, when a biological sample is thicker than 1 mm, intense scattering of light would significantly degrade the spatial resolution of fluorescence microscopy. In this paper, we develop a fluorescence microtomography technique that utilizes the Monte Carlo method to image fluorescence reporters in thick biological samples. This approach is based on an l0-regularized tomography model and provides an excellent solution. Our studies on biomimetic tissue scaffolds have demonstrated that the proposed approach is capable of localizing and quantifying the distribution of optical molecular probe accurately and reliably.

Cong, Alexander X.; Hofmann, Matthias C.; Cong, Wenxiang; Xu, Yong; Wang, Ge

2011-01-01

45

Monte Carlo fluorescence microtomography

NASA Astrophysics Data System (ADS)

Fluorescence microscopy allows real-time monitoring of optical molecular probes for disease characterization, drug development, and tissue regeneration. However, when a biological sample is thicker than 1 mm, intense scattering of light would significantly degrade the spatial resolution of fluorescence microscopy. In this paper, we develop a fluorescence microtomography technique that utilizes the Monte Carlo method to image fluorescence reporters in thick biological samples. This approach is based on an l0-regularized tomography model and provides an excellent solution. Our studies on biomimetic tissue scaffolds have demonstrated that the proposed approach is capable of localizing and quantifying the distribution of optical molecular probe accurately and reliably.

Cong, Alexander X.; Hofmann, Matthias C.; Cong, Wenxiang; Xu, Yong; Wang, Ge

2011-07-01

46

Interacting Electrons in a Quantum Dot: Quantum Monte Carlo Studies.

National Technical Information Service (NTIS)

An efficient optimization method for the quantum Monte Carlo many-body wave functions, called the stochastic gradient approximation (SGA), is presented. Using this method, the states of interacting electrons in a semiconductor quantum dot are studied for ...

A. Harju

1999-01-01

47

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.

Marcus, Ryan C. [Los Alamos National Laboratory

2012-07-25

48

In this paper we want to minimize passengers waiting times at the bus stops by making buses wait at a stop. We compare a simple rule based approach to a Monte- Carlo method for this problem. When allocated enough time, the Monte-Carlo method gives better results. If the passengers arrivals and the bus travel times are known, the best algorithm

Tristan Cazenave; Flavien Balbo; Suzanne Pinson

49

NASA Astrophysics Data System (ADS)

Electrical variations as an aperiodic oscillation were generated across polypyrrole chemically polymerized on polycarbonate membrane filters, separating two electrolyte solutions, one containing an electron donor and the other an electron acceptor. It was found that the aperiodic oscillations were created by stirring of the solutions and were amplified by salt concentration differences across the membrane. Speculation that the aperiodic oscillations reflect the differences in electron and ion transfer rate between reduced and oxidized states of the polypyrrole membranes motivated and guided the simulation portion of this study. The aperiodic oscillation behavior was successfully reproduced by the Monte Carlo simulation of a model based on the propagation mechanism of a conductive zone in conducting polymers.

Sugiyama, Yukihiro; Iseki, Masahiro; Ikematsu, Mineo; Mizukami, Atsuo

50

NASA Astrophysics Data System (ADS)

We study theoretically the possible origin of a double-peak fine structure of Surface Relief Gratings in azo-functionalized poly(etherimide) reported recently in experiments. To improve the statistics of experimental data additional measurements were done. For the theoretical analysis we develop a stochastic Monte Carlo model for photoinduced mass transport in azobenzene-functionalized polymer matrix. The long sought-after transport of polymer chains from bright to dark places of the illumination pattern is demonstrated and characterized, various scenarios for the intertwined processes of build-up of density and SRG gratings are examined. Model predicts that for some azo-functionalized materials double-peak SRG maxima can develop in the permanent, quasi-permanent or transient regimes. Available experimental data are interpreted in terms of model's predictions.

Pawlik, G.; Miniewicz, A.; Sobolewska, A.; Mitus, A. C.

2014-01-01

51

Parallelizing Monte Carlo with PMC

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.

Rathkopf, J.A.; Jones, T.R.; Nessett, D.M.; Stanberry, L.C.

1994-11-01

52

The purpose of the paper is to present the results of application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) data of Mittal Steel Poland (MSP) complex in Kraków, Poland. In order to assess the uncertainty, the software CrystalBallŽ (CB), which is associated with MicrosoftŽ Excel spreadsheet model, is used. The framework of the study was originally carried out for 2005. The total production of steel, coke, pig iron, sinter, slabs from continuous steel casting (CSC), sheets from hot rolling mill (HRM) and blast furnace gas, collected in 2005 from MSP was analyzed and used for MC simulation of the LCI model. In order to describe random nature of all main products used in this study, normal distribution has been applied. The results of the simulation (10,000 trials) performed with the use of CB consist of frequency charts and statistical reports. The results of this study can be used as the first step in performing a full LCA analysis in the steel industry. Further, it is concluded that the stochastic approach is a powerful method for quantifying parameter uncertainty in LCA/LCI studies and it can be applied to any steel industry. The results obtained from this study can help practitioners and decision-makers in the steel production management. PMID:24290145

Bieda, Bogus?aw

2014-05-15

53

QuasiMonte Carlo Constructions

In this chapter and the following one, we discuss the use of low-discrepancy sampling to replace the pure random sampling that forms the backbone of the Monte Carlo method. Using this alternative sampling method\\u000a in the context of multivariate integration is usually referred to as quasiMonte Carlo. A low-discrepancy sample is one whose points are distributed in a way that

Christiane Lemieux

54

Efficient Kinetic Monte Carlo Simulation

This paper concerns Kinetic Monte Carlo (KMC) algorithms that have a single- event execution time independent of the system size. Two methods are presented one that combines the use of inverted-list data structures with rejection Monte Carlo and a second that combines inverted lists with the Marsaglia-Norman-Cannon algorithm. The resulting algorithms apply to models with rates that are determined by

Tim P. Schulze

2007-01-01

55

Efficient kinetic Monte Carlo simulation

This paper concerns kinetic Monte Carlo (KMC) algorithms that have a single-event execution time independent of the system size. Two methods are presentedone that combines the use of inverted-list data structures with rejection Monte Carlo and a second that combines inverted lists with the MarsagliaNormanCannon algorithm. The resulting algorithms apply to models with rates that are determined by the local

Tim P. Schulze

2008-01-01

56

Quantum Monte Carlo simulation of high-field electron transport: An application to silicon dioxide

A new approach to the Monte Carlo simulation of electron transport is presented. The Monte Carlo technique is regarded as a stochastic evaluation of the Green's function expressed as a Feynman path integral. By the proper weighting of the randomly generated trajectories, conventional Monte Carlo simulations can be used to obtain the correct quantum solution. This technique is applied to

Massimo V. Fischetti; D. J. Dimaria

1985-01-01

57

NASA Astrophysics Data System (ADS)

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.

Morokoff, William J.; Caflisch, Russel E.

1995-12-01

58

Proton Upset Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

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.

O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.

2009-01-01

59

Process characterization with Monte Carlo wave functions

NASA Astrophysics Data System (ADS)

We present an efficient method to simulate a quantum process subject to dissipation and noise. To describe the effect on any input state we evolve Monte Carlo wave functions for a principal and ancilla system, prepared initially in an entangled state. In analogy to experimental process tomography, the simulated propagator for the system density matrix is conveniently described by a process ? matrix - directly determined from the stochastic state vectors. Our method significantly reduces the computational complexity compared with standard theoretical characterization methods. It also delivers an upper bound on the trace distance between the ideal and simulated process based on the evolution of only a single wave function of the entangled system.

Gulliksen, J.; Rao, D. D. Bhaktavatsala; Mřlmer, K.

2013-11-01

60

Quantum Monte Carlo with short directed loops

NASA Astrophysics Data System (ADS)

We introduce a new type of directed loop algorithm with short-loop generation for the stochastic series expansion quantum Monte Carlo method[1]. Short-loop algorithms have been shown to greatly improve the dynamics at low temperature in studies of classical spin ice models[2]. We will discuss the framework of this algorithm and make comparisons to the conventional directed loop algorithm in a specific quantum spin model. [1]O.Suljuasen and A. W. Sandvik, Phys. Rev. E66, 046701 (2002). [2]R. Melko et al., Phys. Rev. Lett. 87, 067203 (2001).

Kao, Ying-Jer

2007-03-01

61

Monte Carlo calculations of nuclei

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.

Pieper, S.C. [Argonne National Lab., IL (United States). Physics Div.

1997-10-01

62

Synchronous Parallel Kinetic Monte Carlo

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.

Mart?nez, E; Marian, J; Kalos, M H

2006-12-14

63

Monte Carlo Small-Sample Perturbation Calculations.

National Technical Information Service (NTIS)

Two different Monte Carlo methods have been developed for benchmark computations of small-sample-worths in simplified geometries. The first is basically a standard Monte Carlo perturbation method in which neutrons are steered towards the sample by roulett...

U. Feldman E. Gelbard R. Blomquist

1983-01-01

64

Suitable Candidates for Monte Carlo Solutions.

ERIC Educational Resources Information Center

Discusses Monte Carlo methods, powerful and useful techniques that rely on random numbers to solve deterministic problems whose solutions may be too difficult to obtain using conventional mathematics. Reviews two excellent candidates for the application of Monte Carlo methods. (ASK)

Lewis, Jerome L.

1998-01-01

65

Monte Carlo Experiments: Design and Implementation.

ERIC Educational Resources Information Center

Illustrates the design and planning of Monte Carlo simulations, presenting nine steps in planning and performing a Monte Carlo analysis from developing a theoretically derived question of interest through summarizing the results. Uses a Monte Carlo simulation to illustrate many of the relevant points. (SLD)

Paxton, Pamela; Curran, Patrick J.; Bollen, Kenneth A.; Kirby, Jim; Chen, Feinian

2001-01-01

66

Wavelet formulation of path integral Monte Carlo

A wavelet formulation of path integral Monte Carlo (PIMC) is constructed. Comparison with Fourier path integral Monte Carlo is presented using simple one-dimensional examples. Wavelet path integral Monte Carlo exhibits a few advantages over previous methods for PIMC. The efficiency of the current method is at least comparable to other techniques.

Art E. Cho; J. D. Doll; David L. Freeman

2002-01-01

67

Monte Carlo simulations in SPET and PET

Monte Carlo methods are extensively used in Nuclear Medicine to tackle a variety of problems that are diffi- cult to study by an experimental or analytical approach. A review of the most recent tools allowing application of Monte Carlo methods in single photon emission tomography (SPET) and positron emission tomography (PET) is presented. To help potential Monte Carlo users choose

I. Buvat; I. Castiglioni

2002-01-01

68

NASA Technical Reports Server (NTRS)

An algorithm employing a modified sequential random perturbation, or creeping random search, was applied to the problem of optimizing the parameters of a high-energy beam transport system. The stochastic solution of the mathematical model for first-order magnetic-field expansion allows the inclusion of state-variable constraints, and the inclusion of parameter constraints allowed by the method of algorithm application eliminates the possibility of infeasible solutions. The mathematical model and the algorithm were programmed for a real-time simulation facility; thus, two important features are provided to the beam designer: (1) a strong degree of man-machine communication (even to the extent of bypassing the algorithm and applying analog-matching techniques), and (2) extensive graphics for displaying information concerning both algorithm operation and transport-system behavior. Chromatic aberration was also included in the mathematical model and in the optimization process. Results presented show this method as yielding better solutions (in terms of resolutions) to the particular problem than those of a standard analog program as well as demonstrating flexibility, in terms of elements, constraints, and chromatic aberration, allowed by user interaction with both the algorithm and the stochastic model. Example of slit usage and a limited comparison of predicted results and actual results obtained with a 600 MeV cyclotron are given.

Parrish, R. V.; Dieudonne, J. E.; Filippas, T. A.

1971-01-01

69

NASA Technical Reports Server (NTRS)

Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

1990-01-01

70

Estimates of monthly average rainfall based on satellite observations from a low Earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The authors estimate the size of this error for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). They first examine in detail the statistical description of rainfall on scales from 1 to 10{sup 3} km, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10% of the mean for rainfall averaged over a 500 {times} 500 km{sup 2} area.

Bell, T.L. (NASA Goddard Space Flight Center, Greenbelt, MD (United States)); Abdullah, A.; Martin, R.L. (Applied Research Corp., Landover, MD (United States)); North, G.R. (Texas A and M Univ., College Station (United States))

1990-02-28

71

Accurate prediction of complex phenomena can be greatly enhanced through the use of data and observations to update simulations. The ability to create these data-driven simulations is limited by error and uncertainty in both the data and the simulation. The stochastic engine project addressed this problem through the development and application of a family of Markov Chain Monte Carlo methods utilizing importance sampling driven by forward simulators to minimize time spent search very large state spaces. The stochastic engine rapidly chooses among a very large number of hypothesized states and selects those that are consistent (within error) with all the information at hand. Predicted measurements from the simulator are used to estimate the likelihood of actual measurements, which in turn reduces the uncertainty in the original sample space via a conditional probability method called Bayesian inferencing. This highly efficient, staged Metropolis-type search algorithm allows us to address extremely complex problems and opens the door to solving many data-driven, nonlinear, multidimensional problems. A key challenge has been developing representation methods that integrate the local details of real data with the global physics of the simulations, enabling supercomputers to efficiently solve the problem. Development focused on large-scale problems, and on examining the mathematical robustness of the approach in diverse applications. Multiple data types were combined with large-scale simulations to evaluate systems with {approx}{sup 10}20,000 possible states (detecting underground leaks at the Hanford waste tanks). The probable uses of chemical process facilities were assessed using an evidence-tree representation and in-process updating. Other applications included contaminant flow paths at the Savannah River Site, locating structural flaws in buildings, improving models for seismic travel times systems used to monitor nuclear proliferation, characterizing the source of indistinct atmospheric plumes, and improving flash radiography. In the course of developing these applications, we also developed new methods to cluster and analyze the results of the state-space searches, as well as a number of algorithms to improve the search speed and efficiency. Our generalized solution contributes both a means to make more informed predictions of the behavior of very complex systems, and to improve those predictions as events unfold, using new data in real time.

Glaser, R E; Johannesson, G; Sengupta, S; Kosovic, B; Carle, S; Franz, G A; Aines, R D; Nitao, J J; Hanley, W G; Ramirez, A L; Newmark, R L; Johnson, V M; Dyer, K M; Henderson, K A; Sugiyama, G A; Hickling, T L; Pasyanos, M E; Jones, D A; Grimm, R J; Levine, R A

2004-03-11

72

A contribution Monte Carlo method

A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time.

Aboughantous, C.H. (Louisiana State Univ., Baton Rouge, LA (United States). Nuclear Science Center)

1994-11-01

73

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.

Zimmerman, G.B.

1997-06-24

74

Parallel Monte Carlo reactor neutronics

The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved.

Blomquist, R.N.; Brown, F.B.

1994-03-01

75

Compressible generalized hybrid Monte Carlo

NASA Astrophysics Data System (ADS)

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.

Fang, Youhan; Sanz-Serna, J. M.; Skeel, Robert D.

2014-05-01

76

Grand Canonical Monte Carlo Model

NSDL National Science Digital Library

The Grand Canonical Monte Carlo Model illustrates grand canonical ensemble (ÂľVT) Monte Carlo simulations: the chemical potential, volume and temperature are the system constraints. This means that the system has porous and diabatic walls, exchanging molecules and heat with a reservoir at constant chemical potential and temperature. The molecules interact through the Lennard-Jones. potential and fluid states at densities 0.0025 ? ? ? 0.85 and temperatures T ? 0.70 can be simulated. Although the volume is kept constant, the number of molecules fluctuates and so does the density. The aim is to reach a chemical potential approaching the imposed one. The input fields can be edited to probe different regions of the phase diagram. Chemical potentials, activity coefficients, Helmholtz free energies, entropies and their excess contributions are worked out. The Grand Canonical Monte Carlo Model was developed using the Easy Java Simulations (EJS) modeling tool. It is distributed as a ready-to-run (compiled) Java archive. Double clicking the jar file will run the program if Java is installed. You can modify this simulation if you have EJS installed by right-clicking within the map and selecting "Open Ejs Model" from the pop-up menu item.

Fernandes, Fernando S.

2014-05-21

77

Compressible generalized hybrid Monte Carlo.

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. PMID:24811626

Fang, Youhan; Sanz-Serna, J M; Skeel, Robert D

2014-05-01

78

Wavefunction Monte Carlo for Transport in Open Quantum Systems

NASA Astrophysics Data System (ADS)

The wave function Monte Carlo method is a technique for solving the stochastic differential equation associated with the master equation (Lindblad equation) for transport in an open quantum system. For an anisotropic, spin 1/2, XXZ Heisenberg chain in an external magnetic field, whose ends interact with heat baths, we compute the heat transport through the chain as a function of chain length, temperature difference at the ends, and the anisotropy of the chain's exchange interaction from both a wavefunction Monte Carlo simulation and a deterministic solution of the master equation for the open system's density matrix. Having both solutions creates benchmarks for the more fundamental objective of studying the consequence of replacing a piecewise deterministic step, which is typically part of the wavefunction Monte Carlo method, with a stochastic step. This replacement affords the potential of simulating longer chain lengths.

Gubernatis, James

2013-03-01

79

The Kinetic Monte Carlo method: Foundation, implementation, and application

The Kinetic Monte Carlo method provides a simple yet powerful and flexible tool for exercising the concerted action of fundamental, stochastic, physical mechanisms to create a model of the phenomena that they produce. This manuscript contains an overview of the theory behind the method, some simple examples to illustrate its implementation, and a technologically relevant application of the method to

Corbett C. Battaile

2008-01-01

80

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial ?-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based ?-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where

Abhijit Chatterjee; Dionisios G.. Vlachos

2006-01-01

81

MONT3E: A Monte Carlo electron heat transfer code.

National Technical Information Service (NTIS)

A Monte Carlo code, MONT3E, was written to analyze heat transfer due to electron backscattering. The availability of supercomputers has made large-scale applications of this analysis technique possible. Statistically valid solutions of complicated enginee...

J. D. Maltby B. T. Kornblum

1990-01-01

82

Monte Python: Monte Carlo Code for CLASS in Python

NASA Astrophysics Data System (ADS)

Monte Python is a parameter inference code which combines the flexibility of the python language and the robustness of the cosmological code CLASS into a simple and easy to manipulate Monte Carlo Markov Chain code.

Audren, Benjamin; Lesgourgues, Julien; Benabed, Karim; Prunet, Simon

2013-07-01

83

VERIFICATION OF THE SHIFT MONTE CARLO CODE

Shift is a new hybrid Monte Carlo\\/deterministic radiation transport code being developed at Oak Ridge National Laboratory. At its current stage of development, Shift includes a fully-functional parallel Monte Carlo capability for simulating eigenvalue and fixed-source multigroup transport problems. This paper focuses on recent efforts to verify Shift s Monte Carlo component using the two-dimensional and three-dimensional C5G7 NEA benchmark

Nicholas Sly; Mervin Brenden Mervin; Scott W Mosher; Thomas M Evans; G. Ivan Maldonado

2012-01-01

84

Using QuasiMonte Carlo in Practice

In the preceding chapter, we presented several constructions that can be used for quasiMonte Carlo sampling and discussed\\u000a how to assess their quality. In this chapter, we focus on issues that arise when applying quasiMonte Carlo methods in practice.\\u000a We first discuss randomized quasiMonte Carlo, which, as we mentioned at the end of the previous chapter, is an essential\\u000a tool

Christiane Lemieux

85

Density-matrix quantum Monte Carlo method

NASA Astrophysics Data System (ADS)

We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system at finite temperature. This allows arbitrary reduced density matrix elements and expectation values of complicated nonlocal observables to be evaluated easily. The method resembles full configuration interaction quantum Monte Carlo but works in the space of many-particle operators instead of the space of many-particle wave functions. One simulation provides the density matrix at all temperatures simultaneously, from T =? to T =0, allowing the temperature dependence of expectation values to be studied. The direct sampling of the density matrix also allows the calculation of some previously inaccessible entanglement measures. We explain the theory underlying the method, describe the algorithm, and introduce an importance-sampling procedure to improve the stochastic efficiency. To demonstrate the potential of our approach, the energy and staggered magnetization of the isotropic antiferromagnetic Heisenberg model on small lattices, the concurrence of one-dimensional spin rings, and the Renyi S2 entanglement entropy of various sublattices of the 6×6 Heisenberg model are calculated. The nature of the sign problem in the method is also investigated.

Blunt, N. S.; Rogers, T. W.; Spencer, J. S.; Foulkes, W. M. C.

2014-06-01

86

Chemical application of diffusion quantum Monte Carlo

NASA Astrophysics Data System (ADS)

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.

Reynolds, P. J.; Lester, W. A., Jr.

1983-10-01

87

Chemical application of diffusion quantum Monte Carlo

NASA Technical Reports Server (NTRS)

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.

Reynolds, P. J.; Lester, W. A., Jr.

1984-01-01

88

Proceedings of the conference on frontiers of Quantum Monte Carlo

This journal of conference proceedings includes papers on topics such as: computers and science; Quantum Monte Carlo; condensed matter physics (with papers including the statistical error of Green's Function Monte Carlo, a study of Trotter-like approximations, simulations of the Hubbard model, and stochastic simulation of fermions); chemistry (including papers on quantum simulations of aqueous systems, fourier path integral methods, and a study of electron solvation in polar solvents using path integral calculations); atomic molecular and nuclear physics; high-energy physics, and advanced computer designs.

Gubernatis, J.E.

1986-06-01

89

A Monte Carlo model has been developed for optical coherence tomography (OCT). A geometrical optics implementation of the OCT probe with low-coherence interferometric detection was combined with three-dimensional stochastic Monte Carlo modelling of photon propagation in the homogeneous sample medium. Optical properties of the sample were selected to simulate intralipid and blood, representing moderately ( g = 0.7) and highly

Derek J. Smithies; Tore Lindmo; Zhongping Chen; J. Stuart Nelson; Thomas E. Milner

1998-01-01

90

Simulation is often used to predict the response of gamma-ray spectrometers in technology viability and comparative studies for homeland and national security scenarios. Candidate radiation transport methods generally fall into one of two broad categories: stochastic (Monte Carlo) and deterministic. Monte Carlo methods are the most heavily used in the detection community and are particularly effective for calculating pulse-height spectra

Leon E. Smith; Christopher J. Gesh; Richard T. Pagh; Erin A. Miller; Mark W. Shaver; Eric D. Ashbaker; Michael T. Batdorf; J. Edward Ellis; William R. Kaye; Ronald J. McConn; George H. Meriwether; Jennifer J. Ressler; Andrei B. Valsan; Todd A. Wareing

2008-01-01

91

Fission Matrix Capability for MCNP Monte Carlo

In a Monte Carlo criticality calculation, before the tallying of quantities can begin, a converged fission source (the fundamental eigenvector of the fission kernel) is required. Tallies of interest may include powers, absorption rates, leakage rates, or the multiplication factor (the fundamental eigenvalue of the fission kernel, k{sub eff}). Just as in the power iteration method of linear algebra, if the dominance ratio (the ratio of the first and zeroth eigenvalues) is high, many iterations of neutron history simulations are required to isolate the fundamental mode of the problem. Optically large systems have large dominance ratios, and systems containing poor neutron communication between regions are also slow to converge. The fission matrix method, implemented into MCNP[1], addresses these problems. When Monte Carlo random walk from a source is executed, the fission kernel is stochastically applied to the source. Random numbers are used for: distances to collision, reaction types, scattering physics, fission reactions, etc. This method is used because the fission kernel is a complex, 7-dimensional operator that is not explicitly known. Deterministic methods use approximations/discretization in energy, space, and direction to the kernel. Consequently, they are faster. Monte Carlo directly simulates the physics, which necessitates the use of random sampling. Because of this statistical noise, common convergence acceleration methods used in deterministic methods do not work. In the fission matrix method, we are using the random walk information not only to build the next-iteration fission source, but also a spatially-averaged fission kernel. Just like in deterministic methods, this involves approximation and discretization. The approximation is the tallying of the spatially-discretized fission kernel with an incorrect fission source. We address this by making the spatial mesh fine enough that this error is negligible. As a consequence of discretization we get a 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-cycle correlation. We apply this method mainly to four problems: 2D pressurized water reactor (PWR) [6],

Carney, Sean E. [Los Alamos National Laboratory; Brown, Forrest B. [Los Alamos National Laboratory; Kiedrowski, Brian C. [Los Alamos National Laboratory; Martin, William R. [Los Alamos National Laboratory

2012-09-05

92

Optimizing efficiency of perturbative Monte Carlo method

We introduce error weighting functions into the perturbative Monte Carlo method for use with a hybrid ab initio quantum . mechanicsrmolecular mechanics QMrMM potential. The perturbative Monte Carlo approach introduced earlier provides a means to reduce the number of full SCF calculations in simulations using a QMrMM potential by evoking perturbation theory to calculate energy changes due to displacements of

Tom J. Evans; Thanh N. Truong

1998-01-01

93

Monte Carlo Application ToolKit (MCATK)

NASA Astrophysics Data System (ADS)

The Monte Carlo Application ToolKit (MCATK) is a component-based software library designed to build specialized applications and to provide new functionality for existing general purpose Monte Carlo radiation transport codes. We will describe MCATK and its capabilities along with presenting some verification and validations results.

Adams, Terry; Nolen, Steve; Sweezy, Jeremy; Zukaitis, Anthony; Campbell, Joann; Goorley, Tim; Greene, Simon; Aulwes, Rob

2014-06-01

94

Monte Carlo simulation of granular fluids

An overview of recent work on Monte Carlo simulations of a granular binary mixture is presented. The results are obtained numerically solving the Enskog equation for inelastic hard-spheres by means of an extension of the well- known direct Monte Carlo simulation (DSMC) method. The homogeneous cooling state and the stationary state reached using the Gaussian thermostat are considered. The temperature

Jose Mar ´ őa

95

Monte Carlo Simulations of Externally Illuminated Disks

Since Monte Carlo radiative transfer methods provide straightforward numerical modeling of the interaction of light with matter in complex configurations, they are ideal tools for investigating accretion-disk systems. Most previous Monte Carlo treatments of disk scattering have considered the problem of a disk illuminated by a central source (e.g. Wood et al. 1996, Whitney and Hartmann 1992). In this study,

J. L. Hoffman; B. A. Whitney; K. Wood; K. H. Nordsieck

1997-01-01

96

The MC21 Monte Carlo Transport Code

MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities.

Sutton TM, Donovan TJ, Trumbull TH, Dobreff PS, Caro E, Griesheimer DP, Tyburski LJ, Carpenter DC, Joo H

2007-01-09

97

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

98

Monte Carlo approaches to light nuclei

Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.

Carlson, J.

1990-01-01

99

Fixed-lag sequential Monte Carlo data association

NASA Astrophysics Data System (ADS)

The use of multiple scans of data to improve ones ability to improve target tracking performance is widespread in the tracking literature. In this paper, we introduce a novel application of a recent innovation in the SMC literature that uses multiple scans of data to improve the stochastic approximation (and so the data association ability) of a multiple target Sequential Monte Carlo based tracking system. Such an improvement is achieved by resimulating sampled variates over a fixed-lag time window by artificially extending the space of the target distribution. In doing so, the stochastic approximation is improved and so the data association ambiguity is more readily resolved.

Briers, Mark; Doucet, Arnaud; Maskell, Simon R.; Horridge, Paul R.

2006-06-01

100

Monte Carlo Shower Counter Studies

NASA Technical Reports Server (NTRS)

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.

Snyder, H. David

1991-01-01

101

Monte Carlo techniques in statistical physics

NASA Astrophysics Data System (ADS)

In this paper we shall briefly review a few Markov Chain Monte Carlo methods for simulating closed systems described by canonical ensembles. We cover both Boltzmann and non-Boltzmann sampling techniques. The Metropolis algorithm is a typical example of Boltzmann Monte Carlo method. We discuss the time-symmetry of the Markov chain generated by Metropolis like algo- rithms that obey detailed balance. The non-Boltzmann Monte Carlo techniques reviewed include the multicanonical and Wang-Landau sampling. We list what we consider as milestones in the historical development of Monte Carlo methods in statistical physics. We dedicate this article to Prof. Dr. G. Ananthakrishna and wish him the very best in the coming years

Murthy, K. P. N.

2006-11-01

102

Analytical Applications of Monte Carlo Techniques.

ERIC Educational Resources Information Center

Described are analytical applications of the theory of random processes, in particular solutions obtained by using statistical procedures known as Monte Carlo techniques. Supercomputer simulations, sampling, integration, ensemble, annealing, and explicit simulation are discussed. (CW)

Guell, Oscar A.; Holcombe, James A.

1990-01-01

103

Area Estimates by Monte Carlo Simulation

NSDL National Science Digital Library

This demo estimates the area of a circle or triangle using a probability experiment employing the Monte Carlo technique. We also indicate how to use our approach to estimate the area of a polygonal region.

Roberts, Lila F.; Hill, David R.

2001-06-02

104

Frontiers of quantum Monte Carlo workshop: preface

The introductory remarks, table of contents, and list of attendees are presented from the proceedings of the conference, Frontiers of Quantum Monte Carlo, which appeared in the Journal of Statistical Physics. (GHT)

Gubernatis, J.E.

1985-01-01

105

Monte Carlo Approach to Numerical Deconvolution.

National Technical Information Service (NTIS)

A numerical procedure for solving deconvolution problems is presented. The procedure is based on the Monte Carlo method, which statistically estimates each element in the deconvolved excitation. A discrete Fourier transform technique is used to improve th...

M. P. Ekstrom

1976-01-01

106

Robust Monte Carlo Localization for Mobile Robots.

National Technical Information Service (NTIS)

Mobile robot localization is the problem of determining a robot's pose from sensor data. Monte Carlo Localization is a family of algorithms for localization based on particle filters, which are approximate Bayes filters that use random samples for posteri...

S. Thrun D. Fox W. Burgard F. Dellaert

2000-01-01

107

Path integral Monte Carlo simulations of silicates

We investigate the thermal expansion of crystalline SiO2 in the beta-cristobalite and the beta-quartz structure with path integral Monte Carlo (PIMC) techniques. This simulation method allows to treat low-temperature quantum effects properly. At temperatures below the Debye temperature, thermal properties obtained with PIMC agree better with experimental results than those obtained with classical Monte Carlo methods.

Chr. Rickwardt; P. Nielaba; M. H. Müser; K. Binder

2001-01-01

108

Markov Chain Monte Carlo Linkage Analysis Methods

As alluded to in the chapter Linkage Analysis of Qualitative Traits, neither the ElstonSteward algorithm nor the LanderGreen\\u000a approach is amenable to genetic data from large complex pedigrees and a large number of markers. In such cases, Monte Carlo\\u000a estimation methods provide a viable alternative to the exact solutions. Two types of Monte Carlo methods have been developed\\u000a for linkage

Robert P. Igo; Yuqun Luo; Shili Lin

109

IMPROVED ALGORITHMS IN MONTE CARLO DEVICE SIMULATION

Algorithms are presented which advance the state of the art in Monte Carlo device simulation in two ways. Firstly, a method of free-flight time calculation using a new self-scattering algorithm is described. A piecewise linear total scattering rate allows for an efficient reduction of self-scattering events. Secondly, a unique Monte Carlo-Poisson coupling scheme is adopted, which converges faster than presently

H. Kosina; S. Selberherr

110

INTRODUCTION TO THE KINETIC MONTE CARLO METHOD

Monte Carlo refers to a broad class of algorithms that solve problems through the use of random numbers. They .rst emerged\\u000a in the late 1940s and 1950s as electronic computers came into use [1], and the name means just what it sounds like, whimsically\\u000a referring to the random nature of the gambling at Monte Carlo, Monaco. The most famous of

Arthur F. Voter

111

Monte Carlo simulation of granular fluids

An overview of recent work on Monte Carlo simulations of a granular binary\\u000amixture is presented. The results are obtained numerically solving the Enskog\\u000aequation for inelastic hard-spheres by means of an extension of the well-known\\u000adirect Monte Carlo simulation (DSMC) method. The homogeneous cooling state and\\u000athe stationary state reached using the Gaussian thermostat are considered. The\\u000atemperature ratio,

J. M. Montanero

2003-01-01

112

Monte Carlo analysis of inverse problems

Monte Carlo methods have become important in analysis of nonlinear inverse problems where no analytical expression for the forward relation between data and model parameters is available, and where linearization is unsuccessful. In such cases a direct mathematical treatment is impossible, but the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. Monte

Klaus Mosegaard; Malcolm Sambridge

2002-01-01

113

FPGA-driven pseudorandom number generators aimed at accelerating Monte Carlo methods

Hardware acceleration in high performance computing (HPC) context is of growing interest, particularly in the field of Monte Carlo methods where the resort to field programmable gate array (FPGA) technology has been proven as an effective media, capable of enhancing by several orders the speed execution of stochastic processes. The spread-use of reconfigurable hardware for stochastic simulation gathered a significant

Tarek Ould Bachir; Jean-Jules Brault

2009-01-01

114

A hybrid multiscale kinetic Monte Carlo method for simulation of copper electrodeposition

A hybrid multiscale kinetic Monte Carlo (HMKMC) method for speeding up the simulation of copper electrodeposition is presented. The fast diffusion events are simulated deterministically with a heterogeneous diffusion model which considers site-blocking effects of additives. Chemical reactions are simulated by an accelerated (tau-leaping) method for discrete stochastic simulation which adaptively selects exact discrete stochastic simulation for the appropriate reaction

Zheming Zheng; Ryan M. Stephens; Richard D. Braatz; Richard C. Alkire; Linda R. Petzold

2008-01-01

115

Novel Quantum Monte Carlo Approaches for Quantum Liquids

NASA Astrophysics Data System (ADS)

Quantum Monte Carlo methods are a powerful suite of techniques for solving the quantum many-body problem. By using random numbers to stochastically sample quantum properties, QMC methods are capable of studying low-temperature quantum systems well beyond the reach of conventional deterministic techniques. QMC techniques have likewise been indispensible tools for augmenting our current knowledge of superfluidity and superconductivity. In this thesis, I present two new quantum Monte Carlo techniques, the Monte Carlo Power Method and Bose-Fermi Auxiliary-Field Quantum Monte Carlo, and apply previously developed Path Integral Monte Carlo methods to explore two new phases of quantum hard spheres and hydrogen. I lay the foundation for a subsequent description of my research by first reviewing the physics of quantum liquids in Chapter One and the mathematics behind Quantum Monte Carlo algorithms in Chapter Two. I then discuss the Monte Carlo Power Method, a stochastic way of computing the first several extremal eigenvalues of a matrix too memory-intensive to be stored and therefore diagonalized. As an illustration of the technique, I demonstrate how it can be used to determine the second eigenvalues of the transition matrices of several popular Monte Carlo algorithms. This information may be used to quantify how rapidly a Monte Carlo algorithm is converging to the equilibrium probability distribution it is sampling. I next present the Bose-Fermi Auxiliary-Field Quantum Monte Carlo algorithm. This algorithm generalizes the well-known Auxiliary-Field Quantum Monte Carlo algorithm for fermions to bosons and Bose-Fermi mixtures. Despite some shortcomings, the Bose-Fermi Auxiliary-Field Quantum Monte Carlo algorithm represents the first exact technique capable of studying Bose-Fermi mixtures of any size in any dimension. In Chapter Six, I describe a new Constant Stress Path Integral Monte Carlo algorithm for the study of quantum mechanical systems under high pressures. While 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(5):053606, November 2012.

Rubenstein, Brenda M.

116

Exponential distributed time-delay nonlinear models: Monte Carlo simulations

NASA Astrophysics Data System (ADS)

The stochastic dynamics toward the final attractor in an exponential distributed time-delay nonlinear model is studied, in the small noise approximation. The passage time statistic for this non-Markovian type of system has been worked out using Monte Carlo simulations. We report the mean first passage time

Cáceres, Manuel O.; Rojas R., Christian D.

2014-09-01

117

Diagrammatic Monte Carlo and Worm Algorithm Techniques

NASA Astrophysics Data System (ADS)

This chapter reviews basic principles of Diagrammatic Monte Carlo and Worm Algorithm techniques. Diagrammatic Monte Carlo establishes generic rules for unbiased sampling of well defined configuration spaces when the only source of errors is of statistical origin due to finite sampling time, no matter whether configuration parameters involve discrete, as in the Ising model, or continuous, as in Feynman diagrams or lattice path integrals, variables. Worm Algorithms allow one to sample efficiently configuration spaces with complex topology and non-local constraints which cause severe problems for Monte Carlo schemes based on local updates. They achieve this goal by working with the enlarged configuration space which includes configurations violating constraints present in the original formulation.

Prokof'ev, Nikolay

118

Spatial Correlations in Monte Carlo Criticality Simulations

NASA Astrophysics Data System (ADS)

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.

Dumonteil, E.; Malvagi, F.; Zoia, A.; Mazzolo, A.; Artusio, D.; Dieudonné, C.; De Mulatier, C.

2014-06-01

119

Quantum Monte Carlo calculations of light nuclei.

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.

Pieper, S. C.

1998-08-25

120

The Geant4 Virtual Monte Carlo

NASA Astrophysics Data System (ADS)

The Virtual Monte Carlo (VMC) [1] provides the abstract interface to the Monte Carlo transport codes: GEANT 3.21 [2], Geant4 [3], and FLUKA [4]. The user VMC based application, independent from the specific Monte Carlo codes, can be then run with all supported simulation programs. VMC has been developed by the ALICE Offline Project and it has drawn attention in other experimental frameworks. Since its first release in 2002, the implementation of the VMC for Geant4 (Geant4 VMC) has been continuously maintained and developed, driven by the evolution of Geant4 on one side and the requirements from users on the other side. In this paper we report on new features in this tool, we present its development multi-threading version based on the Geant4 MT prototype [5] as well as the time comparisons of equivalent native Geant4 and VMC test applications.

H?ivná?ová, I.

2012-12-01

121

A Monte Carlo model has been developed for optical coherence tomography (OCT). A geometrical optics implementation of the OCT probe with low-coherence interferometric detection was combined with three-dimensional stochastic Monte Carlo modelling of photon propagation in the homogeneous sample medium. Optical properties of the sample were selected to simulate intralipid and blood, representing moderately (g D 0:7) and highly (g

Derek J Smithies; Tore Lindmoyz; Zhongping Chen; Thomas E Milner

1998-01-01

122

Order N cluster Monte Carlo method for spin systems with long-range interactions

An efficient O(N) cluster Monte Carlo method for Ising models with long-range interactions is presented. Our novel algorithm does not introduce any cutoff for interaction range and thus it strictly fulfills the detailed balance. The realized stochastic dynamics is equivalent to that of the conventional SwendsenWang algorithm, which requires O(N2) operations per Monte Carlo sweep if applied to long-range interacting

Kouki Fukui; Synge Todo

2009-01-01

123

Current State of Monte Carlo Visualization Tools

The purpose of a Monte Carlo visualization tool is to aid in the generation of the input file while enabling the user to efficiently debug the input file and to optionally allow the user to display output information including random walks. This paper will provide an overview of three different aspects of Monte Carlo code visualization: (1) input file creation; (2) geometry visualization; and (3) output visualization. A brief description of some of the tools available in each area will be presented. However, the focus will be on the capabilities of the MCNP Visual Editor because it is the code most familiar to the authors.

Schwarz, Randolph A. (BATTELLE (PACIFIC NW LAB)); Carter, Lee (Carter M.C. Analysis, Inc.); Kling, A., et al.

2001-01-01

124

Fast Monte Carlo Localization for Mobile Robot

NASA Astrophysics Data System (ADS)

For the issue of increased computational complexity to improve the positioning accuracy of robots leaving in the mobile robot localization method, this paper propose a new Monte Carlo localization algorithm. This method combinated the traditional particle filter algorithm with unscented Kalman filter, markovian Monte Carlo and reduced complexities level through dynamically updating the number of particles in particle collection and ensuring the accuracy of mobile robot localization. Simulation results show that the algorithm can not only inhibit the particle degradation and improve the positioning accuracy of the robot, but also in terms of computational complexity has increased significantly.

Chen, Liang; Sun, Peixin; Zhang, Guohua; Niu, Jie; Zhang, Xiaodong

125

Monte Carlo inversion of seismic data

NASA Technical Reports Server (NTRS)

The analytic solution to the linear inverse problem provides estimates of the uncertainty of the solution in terms of standard deviations of corrections to a particular solution, resolution of parameter adjustments, and information distribution among the observations. It is shown that Monte Carlo inversion, when properly executed, can provide all the same kinds of information for nonlinear problems. Proper execution requires a relatively uniform sampling of all possible models. The expense of performing Monte Carlo inversion generally requires strategies to improve the probability of finding passing models. Such strategies can lead to a very strong bias in the distribution of models examined unless great care is taken in their application.

Wiggins, R. A.

1972-01-01

126

A new Monte Carlo atmospheric radiative transfer model is presented which is designed to support the interpretation of UV\\/vis\\/near-IR spectroscopic measurements of scattered Sun light in the atmosphere. The integro differential equation describing the underlying transport process and its formal solution are discussed. A stochastic approach to solve the differential equation, the Monte Carlo method, is deduced and its application

Tim Deutschmann; Steffen Beirle; Udo Frieß; Michael Grzegorski; Christoph Kern; Lena Kritten; Ulrich Platt; Cristina Prados-Román; Thomas Wagner; Bodo Werner; Klaus Pfeilsticker

2011-01-01

127

Monte Carlo simulation of scenario probability distributions

Suppose a scenario of interest can be represented as a series of events. A final result R may be viewed then as the intersection of three events, A, B, and C. The probability of the result P(R) in this case is the product P(R) = P(A) P(B {vert_bar} A) P(C {vert_bar} A {intersection} B). An expert may be reluctant to estimate P(R) as a whole yet agree to supply his notions of the component probabilities in the form of prior distributions. Each component prior distribution may be viewed as the stochastic characterization of the expert`s uncertainty regarding the true value of the component probability. Mathematically, the component probabilities are treated as independent random variables and P(R) as their product; the induced prior distribution for P(R) is determined which characterizes the expert`s uncertainty regarding P(R). It may be both convenient and adequate to approximate the desired distribution by Monte Carlo simulation. Software has been written for this task that allows a variety of component priors that experts with good engineering judgment might feel comfortable with. The priors are mostly based on so-called likelihood classes. The software permits an expert to choose for a given component event probability one of six types of prior distributions, and the expert specifies the parameter value(s) for that prior. Each prior is unimodal. The expert essentially decides where the mode is, how the probability is distributed in the vicinity of the mode, and how rapidly it attenuates away. Limiting and degenerate applications allow the expert to be vague or precise.

Glaser, R.

1996-10-23

128

National Technical Information Service (NTIS)

This report describes the technical development of Monte Carlo techniques for isotopic inventory analysis. The primary motivation for this solution methodology is the ability to model systems of DGowing material being exposed to varying and stochastically...

P. P. H. Wilson

2005-01-01

129

Monte Carlo Wave Packet Theory of Dissociative Double Ionization

NASA Astrophysics Data System (ADS)

Nuclear dynamics in strong-field double ionization processes is predicted using a stochastic Monte Carlo wave packet technique. Using input from electronic structure calculations and strong-field electron dynamics the description allows for field-dressed dynamics within a given molecule as well as transitions between several different charge states. The description is computationally efficient and applicable to a wide range of systems. As a proof of principle, theoretical nuclear kinetic energy release spectra for H2 (D2) in strong near-infrared laser pulses of 40 fs duration are compared to experiments and very good agreement is obtained.

Leth, Henriette Astrup; Madsen, Lars Bojer; Mřlmer, Klaus

2009-10-01

130

Monte Carlo simulation and random number generation

Methods of generating pseudorandom number sequences that might have predetermined spectral and probability distribution functions are discussed. Such sequences are of potential value in Monte Carlo simulation of communication, radar, and allied systems. The methods described are particularly suited to implementation on microcomputers, are machine portable, and have been subjected to exhaustive investigation by means of both statistical and theoretical

RODNEY F. W. COATES; GARETH J. JANACEK; KENNETH V. LEVER

1988-01-01

131

A quasi-Monte Carlo Metropolis algorithm

This work presents a version of the MetropolisHastings 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 MetropolisHastings sampling.

Owen, Art B.; Tribble, Seth D.

2005-01-01

132

Monte Carlo Modeling of Luminescent Solar Concentrators

Luminescent Solar Concentrators (LSCs) offer an inexpensive alternative for solar power generation. A LSC is a flat, translucent plate that absorbs sunlight through embedded, highly fluorescent molecules. The emitted light is concentrated via total internal reflection at the edges of the LSC, where photovoltaic cells covert it into electricity. We've developed a Monte Carlo model that predicts the properties of

Alex Mooney; Paul Fontecchio; Bruce Wittmershaus

2006-01-01

133

Improved Monte Carlo Renormalization Group Method

An extensive program to analyse 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. 9 refs.

Gupta, R.; Wilson, K.G.; Umrigar, C.

1985-01-01

134

MCMAC: Monte Carlo Merger Analysis Code

NASA Astrophysics Data System (ADS)

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).

Dawson, William A.

2014-07-01

135

A Monte Carlo based radiotherapy simulator

This paper presents a Monte Carlo based simulator of the radiotherapy treatment chain. The high energy simulation module (HESM) incorporates components for beam generation, irradiation set up, radiation transport modeling and dose distribution calculation. The beam is defined by means of particle charge, energy, direction and position. Comprehensive modeling of photon and electron interactions in the radiotherapy energy range has

K. Bliznakova; Z. Kolitsi; N. Pallikarakis

2004-01-01

136

An Introduction to Monte Carlo Methods

ERIC Educational Resources Information Center

Reviews the principles of Monte Carlo calculation and random number generation in an attempt to introduce the direct and the rejection method of sampling techniques as well as the variance-reduction procedures. Indicates that the increasing availability of computers makes it possible for a wider audience to learn about these powerful methods. (CC)

Raeside, D. E.

1974-01-01

137

Generalized directed loops for quantum Monte Carlo

Efficient quantum Monte Carlo update schemes called directed loops have recently been proposed, which improve the efficiency of simulations of quantum lattice models. We propose to generalize such schemes using additional weight factors that account for the weight of open world-line segments (\\

Fabien Alet; Stefan Wessel; Matthias Troyer

2004-01-01

138

Monte Carlo studies of ARA detector optimization

NASA Astrophysics Data System (ADS)

The Askaryan Radio Array (ARA) is a neutrino detector deployed in the Antarctic ice sheet near the South Pole. The array is designed to detect ultra high energy neutrinos in the range of 0.1-10 EeV. Detector optimization is studied using Monte Carlo simulations.

Stockham, Jessica

2013-04-01

139

Monte Carlo Simulation of Single Event Effects

In this paper, we describe a Monte Carlo approach for estimating the frequency and character of single event effects based on a combination of physical modeling of discrete radiation events, device simulations to estimate charge transport and collection, and circuit simulations to determine the effect of the collected charge. A mathematical analysis of the procedure reveals it to be closely

Robert A. Weller; Marcus H. Mendenhall; Robert A. Reed; Ronald D. Schrimpf; Kevin M. Warren; Brian D. Sierawski; Lloyd W. Massengill

2010-01-01

140

Monte Carlo simulation of nonrelativistic electron scattering

A Monte Carlo calculation is described for the scattering and absorption of nonrelativistic electrons moving through a slab of uniformly distributed material of given atomic number, density, and thickness. We give an elementary discussion of the basic physics necessary for developing a computer simulation of the movement of electrons through the material. A basic program was written for microprocessors which

Williamson W. Jr; G. C. Duncan

1986-01-01

141

Monte Carlo Simulation Of Silicon Devices

The Monte Carlo method is a well established approach for the statistical solution of the Boltzmann transport equation in semiconductors [l, 21. As device dimensions are reduced, it is important to account for hot electron effects, responsible for overshoot phenomena and reliability problems like breakdown due to impact ionization, defect generation, and injection into gate oxides. In some cases, hot

C. H. Lee; U. Ravaioli

1993-01-01

142

Coded aperture optimization using Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.

Martineau, A.; Rocchisani, J. M.; Moretti, J. L.

2010-04-01

143

Kinetic Monte Carlo simulations of heteroepitaxial growth

We introduce an algorithm for off-lattice kinetic Monte Carlo simulations of heteroepitaxial crystal growth. In heteroepitaxy a mismatch of the lattice constants in adsorbate and substrate can lead to a variety of phenomena already within the first monolayers of growth. This includes the appearance of misfit dislocations or the formation of self-assembled islands. In order to gain general insight into

M. Biehl; M. Ahr; W. Kinzel

2003-01-01

144

Structural Reliability and Monte Carlo Simulation.

ERIC Educational Resources Information Center

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)

Laumakis, P. J.; Harlow, G.

2002-01-01

145

Monte Carlo approaches to effective field theories.

National Technical Information Service (NTIS)

In this paper, we explore the application of continuum Monte Carlo methods to effective field theory models. Effective field theories, in this context, are those in which a Fock space decomposition of the state is useful. These problems arise both in nucl...

J. Carlson K. E. Schmidt

1991-01-01

146

Monte Carlo method in computer holography

A method based on the Monte Carlo procedure is suggested to simulate the reconstruction of non-Fourier-type computer- generated holograms (CGHs). The cases of amplitude holograms (CGAHs) and phase holograms (CGPHs), or `kinoform lenses,' are investigated. A method to model the finite pixel size of the hologram is suggested. An importance sampling method is proposed to simulate the reconstruction of CGAHs.

Nandor Bokor; Zsolt Papp

1997-01-01

147

Monte Carlo simulation of linearly polarized photons

The collision routine actually used in computer codes for Monte Carlo simulation of (partially) linearly polarized photons follows essentially one intuitive approach which simulates the unpolarized fraction of the beam by generating many polarized photons with their electric field vectors randomly oriented on the polarization plane. Clearly, this approach is more inefficient for simulating unpolarized than polarized radiation, and produces

J. E. Fernández

1997-01-01

148

Monte Carlo simulation in molecular gas dynamics

In the Monte Carlo simulation in the molecular gas dynamics, the behaviors of molecules are probabilistically simulated based on the Boltzmann equation assumptions, i.e., binary molecular collisions, molecular chaos, and vanishingly short time and small physical space for molecular collisions; the simulated molecules are probabilistically followed using random numbers on a computer through the molecular motions the molecular collisions, and

K. Koura

1983-01-01

149

Monte Carlo computer simulation of ion sputtering

Using the sputtering version of the Monte-Carlo (MC) computer code TRIRS (TRansport of Ions and Recoils in Solid) we studied the collision sputtering processes under ion bombardment of a structureless target. Basically, the TRIRS calculation procedure is similar to the one used in the well known TRIM code. The important feature of the TRIRS with respect to other similar MC

E. E. Zhurkin; D. P. Ivanov

1998-01-01

150

A combined Monte Carlo diode simulation code

A collisional Monte Carlo electron transport model has been combined with an existing relativistic electron beam diode simulation code to investigate the effect of electron material interactions on diode performance. The effects of electron scattering and deposition in various anode materials on the electron beam profile are detailed. Simulations of two enhanced electron deposition experiments are described.

J. P. Quintenz; M. M. Widner

1980-01-01

151

Robust Monte Carlo localization for mobile robots

Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples), which approximate the posterior under a common Bayesian formulation of the localization problem. Building on the basic MCL

Sebastian Thrun; Dieter Fox; Wolfram Burgard; Frank Dellaert

2001-01-01

152

TYCHE, A MONTE CARLO SLOWING DOWN CODE

TYCHE is a Monte Carlo code designed to find the second, fourth, and ; sixth moments of the neutron slowing down density distribution in an infinite ; homogeneous medium. Analytic techniques are used to reduce the number of random ; variables and recursive relations to generate the moments. The code was written ; in the FORTRAN language for the IBM-7090

Blaine

1962-01-01

153

Monte Carlo Simulations of Star Clusters

A revision of Stodól Kiewicz's Monte Carlo code is used to simulate evolution of large star clusters. The new method treats each superstar as a single star and follows the evolution and motion of all individual stellar objects. The first calculations, for multi-mass systems influenced by the tidal field of a parent galaxy and with stellar evolution are presented. The

Mirek Giersz

2000-01-01

154

Monte Carlo simulations of muon production

Muon production requirements for a muon collider are presented. Production of muons from pion decay is studied. Lithium lenses and solenoids are considered for focussing pions from a target, and for matching the pions into a decay channel. Pion decay channels of alternating quadrupoles and long solenoids are compared. Monte Carlo simulations are presented for production of pi-->mu by protons

Robert B. Palmer; Juan C. Gallardo; Richard C. Fernow; David Neuffer; David Winn

1996-01-01

155

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation.

National Technical Information Service (NTIS)

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resourc...

C. Restrepo J. E. Hurtado

2011-01-01

156

Benchmark Monte Carlo simulations of positive column discharges

A null-collision Monte Carlo algorithm is being used to simulate electron transport in positive column discharges. The use of a piecewise harmonic radial potential makes the electron motion completely analytic and makes the Monte Carlo code very efficient. The Monte Carlo code is partially self-consistent in that the axial electric field and sheath potential are adjusted to satisfy ionization balance

J. E. Lawler; U. Kortshagen; G. J. Parker

1996-01-01

157

Distributional monte carlo methods for the boltzmann equation

NASA Astrophysics Data System (ADS)

Stochastic particle methods (SPMs) for the Boltzmann equation, such as the Direct Simulation Monte Carlo (DSMC) technique, have gained popularity for the prediction of flows in which the assumptions behind the continuum equations of fluid mechanics break down; however, there are still a number of issues that make SPMs computationally challenging for practical use. In traditional SPMs, simulated particles may possess only a single velocity vector, even though they may represent an extremely large collection of actual particles. This limits the method to converge only in law to the Boltzmann solution. This document details the development of new SPMs that allow the velocity of each simulated particle to be distributed. This approach has been termed Distributional Monte Carlo (DMC). A technique is described which applies kernel density estimation to Nanbu's DSMC algorithm. It is then proven that the method converges not just in law, but also in solution for Linfinity(R 3) solutions of the space homogeneous Boltzmann equation. This provides for direct evaluation of the velocity density function. The derivation of a general Distributional Monte Carlo method is given which treats collision interactions between simulated particles as a relaxation problem. The framework is proven to converge in law to the solution of the space homogeneous Boltzmann equation, as well as in solution for Linfinity(R3) solutions. An approach based on the BGK simplification is presented which computes collision outcomes deterministically. Each technique is applied to the well-studied Bobylev-Krook-Wu solution as a numerical test case. Accuracy and variance of the solutions are examined as functions of various simulation parameters. Significantly improved accuracy and reduced variance are observed in the normalized moments for the Distributional Monte Carlo technique employing discrete BGK collision modeling.

Schrock, Christopher R.

158

Improved diffusion Monte Carlo and the Brownian fan

NASA Astrophysics Data System (ADS)

Diffusion Monte Carlo (DMC) is a workhorse of stochastic computing. It was invented forty years ago as the central component in a Monte Carlo technique for estimating various characteristics of quantum mechanical systems. Since then it has been used in applied in a huge number of fields, often as a central component in sequential Monte Carlo techniques (e.g. the particle filter). DMC computes averages of some underlying stochastic dynamics weighted by a functional of the path of the process. The weight functional could represent the potential term in a Feynman-Kac representation of a partial differential equation (as in quantum Monte Carlo) or it could represent the likelihood of a sequence of noisy observations of the underlying system (as in particle filtering). DMC alternates between an evolution step in which a collection of samples of the underlying system are evolved for some short time interval, and a branching step in which, according to the weight functional, some samples are copied and some samples are eliminated. Unfortunately for certain choices of the weight functional DMC fails to have a meaningful limit as one decreases the evolution time interval between branching steps. We propose a modification of the standard DMC algorithm. The new algorithm has a lower variance per workload, regardless of the regime considered. In particular, it makes it feasible to use DMC in situations where the ``naive'' generalization of the standard algorithm would be impractical, due to an exponential explosion of its variance. We numerically demonstrate the effectiveness of the new algorithm on a standard rare event simulation problem (probability of an unlikely transition in a Lennard-Jones cluster), as well as a high-frequency data assimilation problem. We then provide a detailed heuristic explanation of why, in the case of rare event simulation, the new algorithm is expected to converge to a limiting process as the underlying stepsize goes to 0. This is shown rigorously in the simplest possible situation of a random walk, biased by a linear potential. The resulting limiting object, which we call the ``Brownian fan'', is a very natural new mathematical object of independent interest.The reconstruction (dotted lines) of a trajectory of stochastic Lorenz 63 (solid lines) by DMC (the standard particle filter). The reconstruction by the modified DMC algorithm.

Weare, J.; Hairer, M.

2012-12-01

159

Fission Matrix Capability for MCNP Monte Carlo

NASA Astrophysics Data System (ADS)

We describe recent experience and results from implementing a fission matrix capability into the MCNP Monte Carlo code. The fission matrix can be used to provide estimates of the fundamental mode fission distribution, the dominance ratio, the eigenvalue spectrum, and higher mode forward and adjoint eigenfunctions of the fission neutron source distribution. It can also be used to accelerate the convergence of the power method iterations and to provide basis functions for higher-order perturbation theory. The higher-mode fission sources can be used in MCNP to determine higher-mode forward fluxes and tallies, and work is underway to provide higher-mode adjoint-weighted fluxes and tallies. Past difficulties and limitations of the fission matrix approach are overcome with a new sparse representation of the matrix, permitting much larger and more accurate fission matrix representations. The new fission matrix capabilities provide a significant advance in the state-of-the-art for Monte Carlo criticality calculations.

Brown, Forrest; Carney, Sean; Kiedrowski, Brian; Martin, William

2014-06-01

160

Status of Monte Carlo at Los Alamos

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.

Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.

1980-05-01

161

Status of Monte Carlo at Los Alamos

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.

Thompson, W.L.; Cashwell, E.D.

1980-01-01

162

Quantum Monte Carlo by message passing

We summarize results of quantum Monte Carlo simulations of the degenerate single-impurity Anderson model using the impurity algorithm of Hirsch and Fye. Using methods of Bayesian statistical inference, coupled with the principle of maximum entropy, we extracted the single-particle spectral density from the imaginary-time Green`s function. The variations of resulting spectral densities with model parameters agree qualitatively with the spectral densities predicted by NCA calculations. All the simulations were performed on a cluster of 16 IBM R6000/560 workstations under the control of the message-passing software PVM. We described the trivial parallelization of our quantum Monte Carlo code both for the cluster and the CM-5 computer. Other issues for effective parallelization of the impurity algorithm are also discussed.

Bonca, J.; Gubernatis, J.E.

1993-05-01

163

Quantum Monte Carlo by message passing

We summarize results of quantum Monte Carlo simulations of the degenerate single-impurity Anderson model using the impurity algorithm of Hirsch and Fye. Using methods of Bayesian statistical inference, coupled with the principle of maximum entropy, we extracted the single-particle spectral density from the imaginary-time Green's function. The variations of resulting spectral densities with model parameters agree qualitatively with the spectral densities predicted by NCA calculations. All the simulations were performed on a cluster of 16 IBM R6000/560 workstations under the control of the message-passing software PVM. We described the trivial parallelization of our quantum Monte Carlo code both for the cluster and the CM-5 computer. Other issues for effective parallelization of the impurity algorithm are also discussed.

Bonca, J.; Gubernatis, J.E.

1993-01-01

164

Monte Carlo simulation of gas Cerenkov detectors

Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier.

Mack, J.M.; Jain, M.; Jordan, T.M.

1984-01-01

165

Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy

NASA Astrophysics Data System (ADS)

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.

Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James

2012-02-01

166

Coded aperture optimization using Monte Carlo simulations

Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The

A. Martineau; J. M. Rocchisani; J. L. Moretti

2010-01-01

167

Coded aperture optimization using Monte Carlo simulations

Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood ExpectationMaximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The

A. Martineau; J. M. Rocchisani; J. L. Moretti

2010-01-01

168

Monte Carlo simulations of muon production

Muon production requirements for a muon collider are presented. Production of muons from pion decay is studied. Lithium lenses and solenoids are considered for focusing pions from a target, and for matching the pions into a decay channel. Pion decay channels of alternating quadrupoles and long solenoids are compared. Monte Carlo simulations are presented for production of {pi} {yields} {mu} by protons over a wide energy range, and criteria for choosing the best proton energy are discussed.

Palmer, R.B.; Gallardo, J.C.; Fernow, R.C.; Torun, Y. [Brookhaven National Lab., Upton, NY (United States); Neuffer, D. [CEBAF, Newport News, VA (United States); Winn, D. [Fairfield Univ., CT (United States)

1995-03-01

169

Polaron effective mass from Monte Carlo simulations

A new Monte Carlo algorithm for calculating polaron effective mass is\\u000aproposed. It is based on the path-integral representation of a partial\\u000apartition function with fixed total quasi-momentum. Phonon degrees of freedom\\u000aare integrated out analytically resulting in a single-electron system with\\u000aretarded self-interaction and open boundary conditions in imaginary time. The\\u000aeffective mass is inversely proportional to the covariance

P. E. Kornilovitch; E. R. Pike

1997-01-01

170

Overview of Monte Carlo radiation transport codes

The Radiation Safety Information Computational Center (RSICC) is the designated central repository of the United States Department of Energy (DOE) for nuclear software in radiation transport, safety, and shielding. Since the center was established in the early 60's, there have been several Monte Carlo particle transport (MC) computer codes contributed by scientists from various countries. An overview of the neutron transport computer codes in the RSICC collection is presented.

Kirk, Bernadette Lugue [ORNL

2010-01-01

171

Polaron effective mass from Monte Carlo simulations

A Monte Carlo algorithm for calculating polaron effective mass is proposed. It is based on the path-integral representation of a partial partition function with fixed total quasimomentum. Phonon degrees of freedom are integrated out analytically resulting in a single-electron system with retarded self-interaction and open boundary conditions in imaginary time. The effective mass is inversely proportional to the covariance of

P. E. Kornilovitch; E. R. Pike

1997-01-01

172

Monte-Carlo Simulations - First Results

A revision of Stodol kiewicz's Monte--Carlo code is used to simulate evolution of star clusters. The new method treats each superstar as a single star and follows the evolution and motion of all individual stellar objects. The first calculations, for isolated, equal--mass N--body systems with three--body energy generation according to Spitzer's formulae, show good agreement with direct N--body calculations for

M. Giersz

1997-01-01

173

Monte Carlo simulation of low density flows

The necessity for adopting a kinetic-theoretical approach to obtain aerodynamic characteristics in low density flow past space\\u000a vehicles is highlighted in this paper; it is shown how long-standing difficulties in theoretically handling such flows can\\u000a be circumvented by adopting a Monte Carlo technique. The principles underlying the technique are briefly described, and are\\u000a first illustrated by applying the technique to

S. M. Deshpande; P. V. Subba Raju; N. Ramani; R. Narasimha

1978-01-01

174

Monte Carlo simulations of muon production

Muon production requirements for a muon collider are presented. Production of muons from pion decay is studied. Lithium lenses and solenoids are considered for focusing pions from a target, and for matching the pions into a decay channel. Pion decay channels of alternating quadrupoles and long solenoids are compared. Monte Carlo simulations are presented for production of pi --> {mu} by protons over a wide energy range, and criteria for choosing the best proton energy are discussed.

Robert B. Palmer; Juan C. Gallardo; Richard C. Fernow; Yagmur Torun; David Neuffer; David Winn

1994-11-01

175

Introduction to Cluster Monte Carlo Algorithms

This chapter provides an introduction to cluster Monte Carlo algorithms for classical statistical-mechanical systems. A brief\\u000a review of the conventional Metropolis algorithm is given, followed by a detailed discussion of the lattice cluster algorithm\\u000a developed by Swendsen and Wang and the single-cluster variant introduced by Wolff. For continuum systems, the geometric cluster\\u000a algorithm of Dress and Krauth is described. It

E. Luijten; Frederick Seitz

2006-01-01

176

Monte Carlo modeling of eye iris color

NASA Astrophysics Data System (ADS)

Based on the presented two-layer eye iris model, the iris diffuse reflectance has been calculated by Monte Carlo technique in the spectral range 400-800 nm. The diffuse reflectance spectra have been recalculated in L*a*b* color coordinate system. Obtained results demonstrated that the iris color coordinates (hue and chroma) can be used for estimation of melanin content in the range of small melanin concentrations, i.e. for estimation of melanin content in blue and green eyes.

Koblova, Ekaterina V.; Bashkatov, Alexey N.; Dolotov, Leonid E.; Sinichkin, Yuri P.; Kamenskikh, Tatyana G.; Genina, Elina A.; Tuchin, Valery V.

2007-06-01

177

Monte Carlo dose mapping on deforming anatomy

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 voxels 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 patients IMRT treatment plan, EBDI and TDI differed from EMCM by 1.96% and 7.3% in the lung patients 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.

Zhong, Hualiang; Siebers, Jeffrey V

2010-01-01

178

Chemical Potentials by Monte Carlo Simulations Model

NSDL National Science Digital Library

The Chemical Potentials by Monte Carlo Simulations Model performs canonical (NVT) and isothermal-isobaric (NPT) Monte Carlo simulations focusing the calculation of chemical potentials, for the fluid phases of the Lennard-Jones system, by using the virtual particle insertion method of Widom. Although it can not determine phase-equilibrium directly, the gas-liquid line can be approached as illustrated in the included case study. The model paves the way to uVT and Gibbs Ensemble simulations, and shows the limitation of Widom's method at high fluid densities. The Chemical Potentials by Monte Carlo Simulations Model was developed using the Easy Java Simulations (EJS) modeling tool. It is distributed as a ready-to-run (compiled) Java archive. Double clicking the jar file will run the program if Java is installed. You can modify this simulation if you have EJS installed by right-clicking within the map and selecting "Open Ejs Model" from the pop-up menu item.

Fernandes, Fernando S.

2013-10-30

179

A hybrid multiscale kinetic Monte Carlo method for simulation of copper electrodeposition

A hybrid multiscale kinetic Monte Carlo (HMKMC) method for speeding up the simulation of copper electrodeposition is presented. The fast diffusion events are simulated deterministically with a heterogeneous diffusion model which considers site-blocking effects of additives. Chemical reactions are simulated by an accelerated (tau-leaping) method for discrete stochastic simulation which adaptively selects exact discrete stochastic simulation for the appropriate reaction whenever that is necessary. The HMKMC method is seen to be accurate and highly efficient.

Zheng Zheming [Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106 (United States); Stephens, Ryan M.; Braatz, Richard D.; Alkire, Richard C. [Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 (United States); Petzold, Linda R. [Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106 (United States)], E-mail: petzold@cs.ucsb.edu

2008-05-01

180

The reflection spectra of a multilayer random medium - the human skin - strongly scattering and absorbing light are numerically simulated. The propagation of light in the medium and the absorption spectra are simulated by the stochastic Monte Carlo method, which combines schemes for calculations of real photon trajectories and the statistical weight method. The model takes into account the

Meglinskii

2001-01-01

181

Monte Carlo computation of power generation production costs under operating constraints

This paper highlights the need for considering the stochastic processes associated with the frequency and duration of generating unit outages for assessing the mean and variance of production costs under operating constraints. A numerical example based on a Markov model is given to show that Monte Carlo estimates of these quantities may be incorrect if only the forced outage rates

Jorge Valenzuela; Mainak Mazumdar

2001-01-01

182

Monte Carlo computation of power generation production cost under unit commitment constraints

A highly efficient Monte Carlo procedure for estimating the mean and variance of electric power production cost under unit commitment constraints is proposed. Such estimates are useful in making near-term operational decisions. The authors show that, for this purpose, it is essential to consider the stochastic processes associated with generation unit outages. When unit commitment constraints are taken into account

J. Valenzuela; M. Mazumdar

2000-01-01

183

Reliability of nonlinear vibrating systems under stochastic excitations is investi- gated using a two-stage Monte Carlo simulation strategy. For systems with white noise excitation, the governing equations of motion are interpreted as a set of Ito stochastic differential equations. It is assumed that the probability distribution of the maximum in the steady state response belongs to the basin of attraction

B Radhika; S S Panda; C S Manohar

2009-01-01

184

NSDL National Science Digital Library

The HS-WCA-LJ Monte Carlo Model performs simultaneous canonical Monte Carlo (MC) simulations of 108, 256 or 500 particles interacting through the hard sphere (HS), the Weeks, Chandler and Andersen (WCA) and the Lennard-Jones (LJ) pair potentials. It was inspired by the review of Chandler, Weeks and Anderson on WCA theory, illustrating that "the attractive interactions help fix the volume of the system, but the arrangements and motions of molecules within that volume are determined primarily by the local packing and steric effects produced by the repulsive forces". The radial distribution functions for the three systems are plotted after every MC cycle, at densities and temperatures chosen by the user, and the data Tables display thermodynamic results from the LJ and WCA potentials. The thermodynamics of the HS system was addressed to another application cataloged at Open Source Physics. The objective of this application is: (i) to illustrate the canonical MC method with three different systems;(ii) to probe the densities and temperatures at which the HS and WCA potentials approach the structure(defined by the radial distribution functions) of the LJ system, regarding their use in perturbation theory. The HS-WCA-LJ Monte Carlo Model was developed using the Easy Java Simulations (EJS) modeling tool. It is distributed as a ready-to-run (compiled) Java archive. Double clicking the jar file will run the program if Java is installed. You can modify this simulation if you have EJS installed by right-clicking within the map and selecting "Open Ejs Model" from the pop-up menu item.

Fernandes, Fernando S.

2013-03-12

185

Quantum Monte Carlo for vibrating molecules

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.

Brown, W.R. [Univ. of California, Berkeley, CA (United States). Chemistry Dept.]|[Lawrence Berkeley National Lab., CA (United States). Chemical Sciences Div.

1996-08-01

186

Dynamic weighting in Monte Carlo and optimization

Dynamic importance weighting is proposed as a Monte Carlo method that has the capability to sample relevant parts of the configuration space even in the presence of many steep energy minima. The method relies on an additional dynamic variable (the importance weight) to help the system overcome steep barriers. A non-Metropolis theory is developed for the construction of such weighted samplers. Algorithms based on this method are designed for simulation and global optimization tasks arising from multimodal sampling, neural network training, and the traveling salesman problem. Numerical tests on these problems confirm the effectiveness of the method.

Wong, Wing Hung; Liang, Faming

1997-01-01

187

Spectral functions from Quantum Monte Carlo

In his review, D. Scalapino identified two serious limitations on the application of Quantum Monte Carlo (QMC) methods to the models of interest in High {Tc} Superconductivity (HTS). One is the sign problem''. The other is the analytic continuation problem'', which is how to extract electron spectral functions from QMC calculations of the imaginary time Green's functions. Through-out this Symposium on HTS, the spectral functions have been the focus for the discussion of normal state properties including the applicability of band theory, Fermi liquid theory, marginal Fermi liquids, and novel non-perturbative states. 5 refs., 1 fig.

Silver, R.N.

1989-01-01

188

Monte Carlo radiation transport¶llelism

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.

Cox, L. J. (Lawrence J.); Post, S. E. (Susan E.)

2002-01-01

189

Monte Carlo study of disorder in HMTA

NASA Astrophysics Data System (ADS)

We investigate disordered solids by automated fitting of a Monte Carlo simulation of a crystal to observed single-crystal diffuse X-ray scattering. This method has been extended to the study of crystals of relatively large organic molecules by using a z-matrix to describe the molecules. This allows exploration of motions within molecules. We refer to the correlated thermal motion observed in benzil, and to the occupational and thermal disorder in the 1:1 adduct of hexamethylenetetramine and azelaic acid, HMTA. The technique is capable of giving insight into modes of vibration within molecules and correlated motions between molecules.

Goossens, D. J.; Welberry, T. R.

2001-12-01

190

Vanadium oxide compounds with quantum Monte Carlo.

Calculations with the diffusion quantum Monte Carlo method are presented for vanadium oxide molecules VO0/+0(n) with n = 1-4 and for V2O5. Atomization and ionization energies are calculated as well as oxygen abstraction energies. The fixed-node approximation is compared for guide functions with orbitals from B3LYP and BP86 calculations and higher accuracy was obtained with the latter orbitals. Additionally, all-electron and pseudopotential calculations are compared for the oxygen atom. The overall accuracy is found to be comparable to CCSD(T) calculations where experimental data is available. PMID:18535719

Bande, Annika; Lüchow, Arne

2008-06-21

191

Monte Carlo procedure for protein design

NASA Astrophysics Data System (ADS)

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.

Irbäck, Anders; Peterson, Carsten; Potthast, Frank; Sandelin, Erik

1998-11-01

192

Quantum Monte Carlo calculations for light nuclei

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 30 different (j{sup {prime}}, 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.

Wiringa, R.B.

1998-08-01

193

SATMC: SED Analysis Through Monte Carlo

NASA Astrophysics Data System (ADS)

SATMC is a general purpose, MCMC-based SED fitting code written for IDL and Python. Following Bayesian statistics and Monte Carlo Markov Chain algorithms, SATMC derives the best fit parameter values and returns the sampling of parameter space used to construct confidence intervals and parameter-parameter confidence contours. The fitting may cover any range of wavelengths. The code is designed to incorporate any models (and potential priors) of the user's choice. The user's guide list all the relevant details for including observations, models and usage under both IDL and Python.

Johnson, Seth

2013-09-01

194

Diffusion quantum Monte Carlo for molecules

A quantum mechanical Monte Carlo method has been used for the treatment of molecular problems. The imaginary-time Schroedinger equation written with a shift in zero energy (E/sub T/ - V(R)) can be interpreted as a generalized diffusion equation with a position-dependent rate or branching term. Since diffusion is the continuum limit of a random walk, one may simulate the Schroedinger equation with a function psi (note, not psi/sup 2/) as a density of ''walks.'' The walks undergo an exponential birth and death as given by the rate term. 16 refs., 2 tabs.

Lester, W.A. Jr.

1986-07-01

195

Score Bounded Monte-Carlo Tree Search

NASA Astrophysics Data System (ADS)

Monte-Carlo Tree Search (MCTS) is a successful algorithm used in many state of the art game engines. We propose to improve a MCTS solver when a game has more than two outcomes. It is for example the case in games that can end in draw positions. In this case it improves significantly a MCTS solver to take into account bounds on the possible scores of a node in order to select the nodes to explore. We apply our algorithm to solving Seki in the game of Go and to Connect Four.

Cazenave, Tristan; Saffidine, Abdallah

196

MBR Monte Carlo Simulation in PYTHIA8

NASA Astrophysics Data System (ADS)

We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.

Ciesielski, R.

197

A Monte Carlo algorithm for degenerate plasmas

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 FermiDirac distribution function, and scattering is via a Pauli blocked binary collision approximation. The algorithm is tested against degenerate electronion 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.

Turrell, A.E., E-mail: a.turrell09@imperial.ac.uk; Sherlock, M.; Rose, S.J.

2013-09-15

198

Monte Carlo simulations of muon production

Muon production requirements for a muon collider are presented. Production of muons from pion decay is studied. Lithium lenses and solenoids are considered for focussing pions from a target, and for matching the pions into a decay channel. Pion decay channels of alternating quadrupoles and long solenoids are compared. Monte Carlo simulations are presented for production of {pi}{r_arrow}{mu} by protons over a wide energy range, and criteria for choosing the best proton energy are discussed. {copyright} {ital 1995 American Institute of Physics.}

Palmer, R.B.; Gallardo, J.C.; Fernow, R.C.; Torun, Y. [Brookhaven National Laboratory, P.O. Box 5000, Upton, New York 11973-5000 (United States); Neuffer, D. [CEBAF, Newport News, Virginia 23606 (United States); Winn, D. [Fairfield University, Fairfield, Connecticut 06430-5195 (United States)

1996-01-01

199

Introduction to Cluster Monte Carlo Algorithms

NASA Astrophysics Data System (ADS)

This chapter provides an introduction to cluster Monte Carlo algorithms for classical statistical-mechanical systems. A brief review of the conventional Metropolis algorithm is given, followed by a detailed discussion of the lattice cluster algorithm developed by Swendsen and Wang and the single-cluster variant introduced by Wolff. For continuum systems, the geometric cluster algorithm of Dress and Krauth is described. It is shown how their geometric approach can be generalized to incorporate particle interactions beyond hardcore repulsions, thus forging a connection between the lattice and continuum approaches. Several illustrative examples are discussed.

Luijten, E.

200

Monte Carlo learning/biasing experiment with intelligent random numbers

A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs.

Booth, T.E.

1985-01-01

201

Monte Carlo simulations in emission tomography and GATE: An overview

Monte Carlo simulations are nowadays an essential tool in emission tomography (Single-Photon Emission Computed TomographySPECT and Positron Emission TomographyPET), for assisting system design and optimizing imaging and processing protocols. Several Monte Carlo simulation software are currently available for modeling SPECT and PET configurations.This paper presents an overview of current trends concerning Monte Carlo simulations in SPECT and PET. The evolution

Irčne Buvat; Delphine Lazaro

2006-01-01

202

MECA: a multiprocessor concept specialized to Monte Carlo

Discrete-ordinates and Monte Carlo techniques are compared for solving integrodifferential equations and compare their relative adaptability to vector processors. The author discusses the utility of multiprocessors for Monte Carlo calculations and describes a simple architecture (the monodirectional edge-coupled array or MECA) that seems ideally suited to Monte Carlo and overcomes many of the packaging problems associated with more general multiprocessors. 18 refs., 3 figs., 1 tab.

Solem, J.C.

1985-01-01

203

Monte Carlo modeling of spatial coherence: free-space diffraction.

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

Fischer, David G; Prahl, Scott A; Duncan, Donald D

2008-10-01

204

Monte Carlo modeling of spatial coherence: free-space diffraction

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.

Fischer, David G.; Prahl, Scott A.; Duncan, Donald D.

2008-01-01

205

Lagged average forecasting, an alternative to Monte Carlo forecasting

NASA Technical Reports Server (NTRS)

A 'lagged average forecast' (LAF) model is developed for stochastic dynamic weather forecasting and used for predictions in comparison with the results of a Monte Carlo forecast (MCF). The technique involves the calculation of sample statistics from an ensemble of forecasts, with each ensemble member being an ordinary dynamical forecast (ODF). Initial conditions at a time lagging the start of the forecast period are used, with varying amounts of time for the lags. Forcing by asymmetric Newtonian heating of the lower layer is used in a two-layer, f-plane, highly truncated spectral model in a test forecasting run. Both the LAF and MCF are found to be more accurate than the ODF due to ensemble averaging with the MCF and the LAF. When a regression filter is introduced, all models become more accurate, with the LAF model giving the best results. The possibility of generating monthly or seasonal forecasts with the LAF is discussed.

Hoffman, R. N.; Kalnay, E.

1983-01-01

206

Efficient quantum monte carlo energies for molecular dynamics simulations.

A method is presented to treat electrons within the many-body quantum Monte Carlo (QMC) approach "on-the-fly" throughout a molecular dynamics (MD) simulation. Our approach leverages the large (10-100) ratio of the QMC electron to MD ion motion to couple the stochastic, imaginary-time electronic and real-time ionic trajectories. This continuous evolution of the QMC electrons results in highly accurate total energies for the full dynamical trajectory at a fraction of the cost of conventional, discrete sampling. We show that this can be achieved efficiently for both ground and excited states with only a modest overhead to an ab initio MD method. The accuracy of this dynamical QMC approach is demonstrated for a variety of systems, phases, and properties, including optical gaps of hot silicon quantum dots, dissociation energy of a single water molecule, and heat of vaporization of liquid water. PMID:15783668

Grossman, Jeffrey C; Mitas, Lubos

2005-02-11

207

Monte Carlo modeling for perfusion monitoring

NASA Astrophysics Data System (ADS)

A Monte Carlo method was developed to model light transport through multi-layered tissue with the application focused on the development of an implantable perfusion monitor. The model was developed and then verified experimentally with a micro perfusion phantom. The program modeled a three-layer (tissue, capillary bed, tissue) scenario to investigate the source-detector separation effects for an implantable sensor. The Monte Carlo code was used specifically to model the effects of absorption and scattering properties of the surrounding tissue, the hemoglobin concentration in the middle layer, the ratio of thickness of the capillary layer to the first layer, and the probe-source separation distance on the propagation of the light through the tissue. The model was verified experimentally, using a simple in vitro system with optical source and detector fibers separated at various distances. The model was also used to investigate fluctuations in luminance as a result of hemoglobin concentrations and the response of the system to various wavelengths. The model was helpful for an ongoing project to develop an implantable perfusion monitor for transplanted organs or skin flaps.

Dixon, Brandon; Ibey, Bennett L.; Ericson, M. Nance; Wilson, Mark A.; Cote, Gerard L.

2003-07-01

208

Simple Monte Carlo model for crowd dynamics

NASA Astrophysics Data System (ADS)

In this paper, we introduce a simple Monte Carlo method for simulating the dynamics of a crowd. Within our model a collection of hard-disk agents is subjected to a series of two-stage steps, implying (i) the displacement of one specific agent followed by (ii) a rearrangement of the rest of the group through a Monte Carlo dynamics. The rules for the combined steps are determined by the specific setting of the granular flow, so that our scheme should be easily adapted to describe crowd dynamics issues of many sorts, from stampedes in panic scenarios to organized flow around obstacles or through bottlenecks. We validate our scheme by computing the serving times statistics of a group of agents crowding to be served around a desk. In the case of a size homogeneous crowd, we recover intuitive results prompted by physical sense. However, as a further illustration of our theoretical framework, we show that heterogeneous systems display a less obvious behavior, as smaller agents feature shorter serving times. Finally, we analyze our results in the light of known properties of nonequilibrium hard-disk fluids and discuss general implications of our model.

Piazza, Francesco

2010-08-01

209

THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE

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.

WATERS, LAURIE S. [Los Alamos National Laboratory; MCKINNEY, GREGG W. [Los Alamos National Laboratory; DURKEE, JOE W. [Los Alamos National Laboratory; FENSIN, MICHAEL L. [Los Alamos National Laboratory; JAMES, MICHAEL R. [Los Alamos National Laboratory; JOHNS, RUSSELL C. [Los Alamos National Laboratory; PELOWITZ, DENISE B. [Los Alamos National Laboratory

2007-01-10

210

Discrete range clustering using Monte Carlo methods

NASA Technical Reports Server (NTRS)

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.

Chatterji, G. B.; Sridhar, B.

1993-01-01

211

Monte Carlo simulation of large electron fields

NASA Astrophysics Data System (ADS)

Accurate simulation of large electron fields may lead to improved accuracy in Monte Carlo treatment planning while simplifying the commissioning procedure. We have used measurements made with wide-open jaws and no electron applicator to adjust simulation parameters. Central axis depth dose curves and profiles of 6-21 MeV electron beams measured in this geometry were used to estimate source and geometry parameters, including those that affect beam symmetry: incident beam direction and offset of the secondary scattering foil and monitor chamber from the beam axis. Parameter estimation relied on a comprehensive analysis of the sensitivity of the measured quantities, in the large field, to source and geometry parameters. Results demonstrate that the EGS4 Monte Carlo system is capable of matching dose distributions in the largest electron field to the least restrictive of 1 cGy or 1 mm, with Dmax of 100 cGy, over the full energy range. This match results in an underestimation of the bremsstrahlung dose of 10-20% at 15-21 MeV, exceeding the combined experimental and calculational uncertainty in this quantity of 3%. The simulation of electron scattering at energies of 15-21 MeV in EGS4 may be in error. The recently released EGSnrc/BEAMnrc system may provide a better match to measurement.

Faddegon, B.; Schreiber, E.; Ding, X.

2005-03-01

212

Phylogenetic Inference via Sequential Monte Carlo

Bayesian inference provides an appealing general framework for phylogenetic analysis, able to incorporate a wide variety of modeling assumptions and to provide a coherent treatment of uncertainty. Existing computational approaches to Bayesian inference based on Markov chain Monte Carlo (MCMC) have not, however, kept pace with the scale of the data analysis problems in phylogenetics, and this has hindered the adoption of Bayesian methods. In this paper, we present an alternative to MCMC based on Sequential Monte Carlo (SMC). We develop an extension of classical SMC based on partially ordered sets and show how to apply this frameworkwhich we refer to as PosetSMCto phylogenetic analysis. We provide a theoretical treatment of PosetSMC and also present experimental evaluation of PosetSMC on both synthetic and real data. The empirical results demonstrate that PosetSMC is a very promising alternative to MCMC, providing up to two orders of magnitude faster convergence. We discuss other factors favorable to the adoption of PosetSMC in phylogenetics, including its ability to estimate marginal likelihoods, its ready implementability on parallel and distributed computing platforms, and the possibility of combining with MCMC in hybrid MCMCSMC schemes. Software for PosetSMC is available at http://www.stat.ubc.ca/ bouchard/PosetSMC.

Sankararaman, Sriram; Jordan, Michael I.

2012-01-01

213

Calculating Pi Using the Monte Carlo Method

NASA Astrophysics Data System (ADS)

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.1 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.

Williamson, Timothy

2013-11-01

214

Geometrical Monte Carlo simulation of atmospheric turbulence

NASA Astrophysics Data System (ADS)

Atmospheric turbulence has a significant impact on the quality of a laser beam propagating through the atmosphere over long distances. Turbulence causes intensity scintillation and beam wander from propagation through turbulent eddies of varying sizes and refractive index. This can severely impair the operation of target designation and Free-Space Optical (FSO) communications systems. In addition, experimenting on an FSO communication system is rather tedious and difficult. The interferences of plentiful elements affect the result and cause the experimental outcomes to have bigger error variance margins than they are supposed to have. Especially when we go into the stronger turbulence regimes the simulation and analysis of the turbulence induced beams require delicate attention. We propose a new geometrical model to assess the phase shift of a laser beam propagating through turbulence. The atmosphere along the laser beam propagation path will be modeled as a spatial distribution of spherical bubbles with refractive index discontinuity calculated from a Gaussian distribution with the mean value being the index of air. For each statistical representation of the atmosphere, the path of rays will be analyzed using geometrical optics. These Monte Carlo techniques will assess the phase shift as a summation of the phases that arrive at the same point at the receiver. Accordingly, there would be dark and bright spots at the receiver that give an idea regarding the intensity pattern without having to solve the wave equation. The Monte Carlo analysis will be compared with the predictions of wave theory.

Yuksel, Demet; Yuksel, Heba

2013-09-01

215

Reverse Monte Carlo modeling in confined systems.

An extension of the well established Reverse Monte Carlo (RMC) method for modeling systems under close confinement has been developed. The method overcomes limitations induced by close confinement in systems such as fluids adsorbed in microporous materials. As a test of the method, we investigate a model system of (36)Ar adsorbed into two zeolites with significantly different pore sizes: Silicalite-I (a pure silica form of ZSM-5 zeolite, characterized by relatively narrow channels forming a 3D network) at partial and full loadings and siliceous Faujasite (which exhibits relatively wide channels and large cavities). The model systems are simulated using grand canonical Monte Carlo and, in each case, its structure factor is used as input for the proposed method, which shows a rapid convergence and yields an adsorbate microscopic structure in good agreement with that of the model system, even to the level of three body correlations, when these are induced by the confining media. The application to experimental systems is straightforward incorporating factors such as the experimental resolution and appropriate q-sampling, along the lines of previous experiences of RMC modeling of powder diffraction data including Bragg and diffuse scattering. PMID:24437893

Sánchez-Gil, V; Noya, E G; Lomba, E

2014-01-14

216

Reverse Monte Carlo modeling in confined systems

NASA Astrophysics Data System (ADS)

An extension of the well established Reverse Monte Carlo (RMC) method for modeling systems under close confinement has been developed. The method overcomes limitations induced by close confinement in systems such as fluids adsorbed in microporous materials. As a test of the method, we investigate a model system of 36Ar adsorbed into two zeolites with significantly different pore sizes: Silicalite-I (a pure silica form of ZSM-5 zeolite, characterized by relatively narrow channels forming a 3D network) at partial and full loadings and siliceous Faujasite (which exhibits relatively wide channels and large cavities). The model systems are simulated using grand canonical Monte Carlo and, in each case, its structure factor is used as input for the proposed method, which shows a rapid convergence and yields an adsorbate microscopic structure in good agreement with that of the model system, even to the level of three body correlations, when these are induced by the confining media. The application to experimental systems is straightforward incorporating factors such as the experimental resolution and appropriate q-sampling, along the lines of previous experiences of RMC modeling of powder diffraction data including Bragg and diffuse scattering.

Sánchez-Gil, V.; Noya, E. G.; Lomba, E.

2014-01-01

217

Monte Carlo generators in ATLAS software

NASA Astrophysics Data System (ADS)

This document describes how Monte Carlo (MC) generators can be used in the ATLAS software framework (Athena). The framework is written in C++ using Python scripts for job configuration. Monte Carlo generators that provide the four-vectors describing the results of LHC collisions are written in general by third parties and are not part of Athena. These libraries are linked from the LCG Generator Services (GENSER) distribution. Generators are run from within Athena and the generated event output is put into a transient store, in HepMC format, using StoreGate. A common interface, implemented via inheritance of a GeneratorModule class, guarantees common functionality for the basic generation steps. The generator information can be accessed and manipulated by helper packages like TruthHelper. The ATLAS detector simulation as well access the truth information from StoreGate1. Steering is done through specific interfaces to allow for flexible configuration using ATLAS Python scripts. Interfaces to most general purpose generators, including: Pythia6, Pythia8, Herwig, Herwig++ and Sherpa are provided, as well as to more specialized packages, for example Phojet and Cascade. A second type of interface exist for the so called Matrix Element generators that only generate the particles produced in the hard scattering process and write events in the Les Houches event format. A generic interface to pass these events to Pythia6 and Herwig for parton showering and hadronisation has been written.

Ay, C.; Buckley, A.; Butterworth, J.; Ferland, J.; Hinchliffe, I.; Jinnouchi, O.; Katzy, J.; Kersevan, B.; Lobodzinska, E.; Monk, J.; Qin, Z.; Savinov, V.; Schumacher, J.

2010-04-01

218

Quantum Monte Carlo Endstation for Petascale Computing

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 published papers, 15 invited talks and lectures nationally and internationally. My former graduate student and postdoc Dr. Michal Bajdich, who was supported byt this grant, is currently a postdoc with ORNL in the group of Dr. F. Reboredo and Dr. P. Kent and is using the developed tools in a number of DOE projects. The QWalk package has become a truly important research tool used by the electronic structure community and has attracted several new developers in other research groups. Our tools use several types of correlated wavefunction approaches, variational, diffusion and reptation methods, large-scale optimization methods for wavefunctions and enables to calculate energy differences such as cohesion, electronic gaps, but also densities and other properties, using multiple runs one can obtain equations of state for given structures and beyond. Our codes use efficient numerical and Monte Carlo strategies (high accuracy numerical orbitals, multi-reference wave functions, highly accurate correlation factors, pairing orbitals, force biased and correlated sampling Monte Carlo), are robustly parallelized and enable to run on tens of thousands cores very efficiently. Our demonstration applications were focused on the challenging research problems in several fields of materials science such as transition metal solids. We note that our study of FeO solid was the first QMC calculation of transition metal oxides at high pressures.

Lubos Mitas

2011-01-26

219

Ultraviolet filtering of lattice configurations and applications to Monte Carlo dynamics

NASA Astrophysics Data System (ADS)

We present a detailed study of a filtering method based upon Dirac quasi-zeromodes in the adjoint representation. The procedure induces no distortions on configurations which are solutions of the euclidean classical equations of motion. On the other hand, it is very effective in reducing the short-wavelength stochastic noise present in Monte-Carlo generated configurations. After testing the performance of the method in various situations, we apply it successfully to study the effect of Monte-Carlo dynamics on topological structures like instantons.

Pérez, Margarita García; González-Arroyo, Antonio; Sastre, Alfonso

2011-07-01

220

A comprehensive study of the two-dimensional (2D) compass model on the square lattice is performed for classical and quantum spin degrees of freedom using Monte Carlo and quantum Monte Carlo methods. We employ state-of-the-art implementations using Metropolis, stochastic series expansion, and parallel tempering techniques to obtain the critical ordering temperatures and critical exponents. In a preinvestigation we reconsider the classical

Sandro Wenzel; Wolfhard Janke

2008-01-01

221

Monte Carlo simulations of protein folding

NASA Astrophysics Data System (ADS)

Monte Carlo simulations are employed to study how a protein folds from a random coil to its native state. In Part I, we investigate the kinetics and thermodynamics of a polypeptide modeled as a chain of 125 beads restricted to a lattice. The behavior of the model is found to be more complex than that of smaller systems. The diverse trajectories that lead to the native state can be classified into a small number of average pathways: a ``fast track'' in which the chain forms a stable core that folds directly to the native state and several ``slow tracks'' in which particular contacts form before the core is complete and direct the chain to misfolded intermediates. Rearrangement to the native state is slow because it requires breaking stable contacts that involve primarily surface residues. Increases in temperature destabilize the intermediates and shift the transition state in a Hammond manner. The mechanism is mapped to two coordinates that are based on a comparison of folding and non-folding trajectories. The free energy in terms of those variables is in good agreement with the observed kinetics, which indicates that they provide an adequate description of the folding reaction. The generality of the results is confirmed by statistical analysis of a 200 sequence database. In Part II, the study is extended to higher resolution (all-atom) models. We generalize a procedure for local deformation of a polymer by concerted rotation of several sequential rotatable main chain dihedral angles and evaluate its usefulness as an elementary move. A Monte Carlo module that includes this move is implemented for the program CHARMM and is applied to sampling the accessible configuration space of a 16-residue peptide that has been shown experimentally to adopt a hairpin structure in solution. A non-canonical weighting scheme is employed to accelerate the escape from local free energy minima. Overall, there is only a relatively small number of distinct conformations. The results suggest that Monte Carlo methods will be capable of finding the native states not only of peptides but also of proteins in the relatively near future.

Dinner, Aaron Reuven

222

A Primer in Monte Carlo Integration Using Mathcad

ERIC Educational Resources Information Center

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

Hoyer, Chad E.; Kegerreis, Jeb S.

2013-01-01

223

Path Integral Monte Carlo Calculation of Interatomic Forces

The calculation of electronic forces with quantum Monte Carlo has, for many years, been an outstanding problem. One can calculate interatomic forces with Path Integral Monte Carlo(PIMC) as the coordinate derivatives of the partition function. Advantages of using PIMC are that effects of thermal electronic excitations and correlations are included, no trial functions are involved and the force estimator is

Fenghua Zong; David Ceperley

1997-01-01

224

Green's function analysis of path integral Monte Carlo molecular simulations

We demonstrate the direct determination of molecular properties from path integral Monte Carlo simulations. By sampling Matsubura Green's functions, we have calculated several linear response properties of the hydrogen molecule (H2) directly from quantum Monte Carlo. We show that the vibration frequency of H2 as calculated directly from the phonon temperature Green's function is in very good agreement with the

Daejin Shin; John Shumway

2006-01-01

225

Monte Carlo modeling of spatial coherence: free-space diffraction

We present a Monte Carlo method for propagating partially coherent fields through complex deterministic op- tical 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

David G. Fischer; Scott A. Prahl; Donald D. Duncan

2008-01-01

226

PARALLELIZATION OF THE PENELOPE MONTE CARLO PARTICLE TRANSPORT SIMULATION PACKAGE

We have parallelized the PENELOPE Monte Carlo particle transport simulation package (1). The motivation is to increase efficiency of Monte Carlo simulations for medical applications. Our parallelization is based on the standard MPI message passing interface. The parallel code is especially suitable for a distributed memory environment, and has been run on up to 256 processors on the Indiana University

R. B. Cruise; R. W. Sheppard; V. P. Moskvin

2003-01-01

227

Monte Carlo simulation in PET and SPECT instrumentation using GATE

Monte Carlo simulation is an essential tool to assist in the design of new medical imaging devices for emission tomography. On one hand, dedicated Monte Carlo codes have been developed for PET and SPECT. However, they suffer from a variety of drawbacks and limitations in terms of validation, accuracy, and\\/or support. On the other hand, accurate and versatile simulation codes

Karine Assié; Vincent Breton; Irčne Buvat; Claude Comtat; Sébastien Jan; Magalie Krieguer; Delphine Lazaro; Christian Morel; Martin Rey; Giovanni Santin; Luc Simon; Steven Staelens; Daniel Strul; Jean-Marc Vieira; Rik Van de Walle

2004-01-01

228

Optimally combining sampling techniques for Monte Carlo rendering

Monte Carlo integration is a powerful technique for the evaluation of difficult integrals. Applications in rendering include distribution ray tracing, Monte Carlo path tracing, and form-factor computation for radiosity methods. In these cases variance can often be signifi- cantly reduced by drawing samples from several distributions, each designed to sample well some difficult aspect of the integrand. Nor- mally this

Eric Veach; Leonidas J. Guibas

1995-01-01

229

Bayesian Inference in Econometric Models Using Monte Carlo Integration

Methods for the systematic application of Monte Carlo integration with importance sampling to Bayesian inference are developed. Conditions under which the numerical approximation converges almost surely to the true value with the number of Monte Carlo replications, and its numerical accuracy may be assessed reliably, are given. Importance sampling densities are derived from multivariate normal or student approximations to the

John Geweke

1989-01-01

230

Cool walking: A new Markov chain Monte Carlo sampling method

Effective relaxation processes for difficult systems like proteins or spin glasses require special simulation techniques that permit barrier crossing to ensure ergodic sampling. Numerous adaptations of the venerable Metropolis Monte Carlo (MMC) algorithm have been proposed to improve its sampling efficiency, including various hybrid Monte Carlo (HMC) schemes, and methods designed specifically for overcoming quasi-ergodicity problems such as Jump Walking

Scott Brown; Teresa Head-gordon

2003-01-01

231

Monte Carlo isotopic inventory analysis for complex nuclear systems

Monte Carlo Inventory Simulation Engine (MCise) is a newly developed method for calculating isotopic inventory of materials. It offers the promise of modeling materials with complex processes and irradiation histories, which pose challenges for current, deterministic tools, and has strong analogies to Monte Carlo (MC) neutral particle transport. The analog method, including considerations for simple, complex and loop flows, is

Phiphat Phruksarojanakun

2007-01-01

232

Monte Carlo simulation of noncubic symmetry semiconducting materials and devices

In this paper, we discuss the complexities that arise in Monte Carlo based modeling of noncubic symmetry semiconductors and their related devices. We have identified three general issues, band structure, scattering mechanisms, and band intersections that require some modification of the Monte Carlo simulator from that for cubic symmetry. Owing to the increased size and number of atoms per unit

Kevin F. Brennan; Enrico Bellotti; Maziar Farahmand; Hans-Erik Nilsson; P. Paul Ruden; Yumin Zhang

2000-01-01

233

A macro Monte Carlo method for electron beam dose calculations

The macro Monte Carlo (MMC) method is a fast Monte Carlo (MC) algorithm for high energy electron transport in an absorbing medium. Incident electrons are transported in large-scale macroscopic steps through the absorber. Electron parameters after each step are calculated from probability distributions. Transport of secondary electrons and bremsstrahlung photons is taken into account. For electron beam dose calculations, the

H. Neuenschwander; E. J. Born

1992-01-01

234

Kinetic Monte Carlo studies of hydrogen abstraction from graphite

We present Monte Carlo simulations on Eley-Rideal abstraction reactions of atomic hydrogen chemisorbed on graphite. The results are obtained via a hybrid approach where energy barriers derived from density functional theory calculations are used as input to Monte Carlo simulations. By comparing with experimental data, we discriminate between contributions from different Eley-Rideal mechanisms. A combination of two different mechanisms yields

H. M. Cuppen; L. Hornekćr

2008-01-01

235

Quantum ice: a quantum Monte Carlo study.

Ice states, in which frustrated interactions lead to a macroscopic ground-state degeneracy, occur in water ice, in problems of frustrated charge order on the pyrochlore lattice, and in the family of rare-earth magnets collectively known as spin ice. Of particular interest at the moment are "quantum spin-ice" materials, where large quantum fluctuations may permit tunnelling between a macroscopic number of different classical ground states. Here we use zero-temperature quantum Monte Carlo simulations to show how such tunnelling can lift the degeneracy of a spin or charge ice, stabilizing a unique "quantum-ice" ground state-a quantum liquid with excitations described by the Maxwell action of (3+1)-dimensional quantum electrodynamics. We further identify a competing ordered squiggle state, and show how both squiggle and quantum-ice states might be distinguished in neutron scattering experiments on a spin-ice material. PMID:22401117

Shannon, Nic; Sikora, Olga; Pollmann, Frank; Penc, Karlo; Fulde, Peter

2012-02-10

236

Population size bias in diffusion Monte Carlo.

The size of the population of random walkers required to obtain converged estimates in diffusion Monte Carlo (DMC) increases dramatically with system size. We illustrate this by comparing ground state energies of small clusters of parahydrogen (up to 48 molecules) computed by DMC and path integral ground state (PIGS) techniques. We contend that the bias associated with a finite population of walkers is the most likely cause of quantitative numerical discrepancies between PIGS and DMC energy estimates reported in the literature, for this few-body Bose system. We discuss the viability of DMC as a general-purpose ground state technique, and argue that PIGS, and even finite temperature methods, enjoy more favorable scaling, and are therefore a superior option for systems of large size. PMID:23214911

Boninsegni, Massimo; Moroni, Saverio

2012-11-01

237

Monte Carlo Modeling of Luminescent Solar Concentrators

NASA Astrophysics Data System (ADS)

Luminescent Solar Concentrators (LSCs) offer an inexpensive alternative for solar power generation. A LSC is a flat, translucent plate that absorbs sunlight through embedded, highly fluorescent molecules. The emitted light is concentrated via total internal reflection at the edges of the LSC, where photovoltaic cells covert it into electricity. We've developed a Monte Carlo model that predicts the properties of LSCs by tracing individual light rays. The user controls the plate's geometry and spectral properties, along with the spectral profile of the excitation source. The user can include a specular or diffuse reflective background under the LSC. We've demonstrated the ability to predict the output of a LSC as a function of its optical density. Reabsorption distorts the profile of fluorescence as light propagates through a LSC, and the program can accurately reproduce the effect. The goal is to use the model as a predictive tool for improving the design of LSCs.

Mooney, Alex; Fontecchio, Paul; Wittmershaus, Bruce

2006-03-01

238

Monte Carlo simulation of radiating reentry flows

NASA Technical Reports Server (NTRS)

The Direct Simulation Monte Carlo (DSMC) method is applied to a radiating, hypersonic, axisymmetric flow over a blunt body in the near continuum regime. The ability of the method to predict the flowfield radiation and the radiative heating is investigated for flow over the Project Fire II configuration at 11.36 kilometers per second at an altitude of 76.42 kilometers. Two methods that differ in the manner in which they treat ionization and estimate electronic excitation are employed. The calculated results are presented and compared with both experimental data and solutions where radiation effects were not included. Differences in the results are discussed. Both methods ignore self absorption and, as a result, overpredict measured radiative heating.

Taylor, Jeff C.; Carlson, Ann B.; Hassan, H. A.

1993-01-01

239

Resist develop prediction by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

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.

Sohn, Dong-Soo; Jeon, Kyoung-Ah; Sohn, Young-Soo; Oh, Hye-Keun

2002-07-01

240

MORSE Monte Carlo radiation transport code system

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)

Emmett, M.B.

1983-02-01

241

Monte Carlo study of semiflexible living polymers

NASA Astrophysics Data System (ADS)

We study the order-disorder phase transition and the cluster-size distribution of ``living polymers'' in a lattice-hole model of a polydisperse system of semiflexible chain macromolecules by Monte Carlo simulation. In two dimensions we find that the transition line in T-? space (temperature-chemical potential) contains a tricritical point and that the values of the critical exponents along the second-order portion of the phase boundary belong to the Ising universality class. In three dimensions a finite-size scaling analysis suggests that the phase transition is always first order. In both cases the chain lengths of the polymers follow an exponential probability distribution although the dependence of the mean chain length on density and temperature deviates from predictions of analytical theory. (c) 1995 The American Physical Society

Milchev, Andrey; Landau, D. P.

1995-12-01

242

Monte Carlo simulation of neutron scattering instruments

A code package consisting of the Monte Carlo Library MCLIB, the executing code MC{_}RUN, the web application MC{_}Web, and various ancillary codes is proposed as an open standard for simulation of neutron scattering instruments. The architecture of the package includes structures to define surfaces, regions, and optical elements contained in regions. A particle is defined by its vector position and velocity, its time of flight, its mass and charge, and a polarization vector. The MC{_}RUN code handles neutron transport and bookkeeping, while the action on the neutron within any region is computed using algorithms that may be deterministic, probabilistic, or a combination. Complete versatility is possible because the existing library may be supplemented by any procedures a user is able to code. Some examples are shown.

Seeger, P.A.; Daemen, L.L.; Hjelm, R.P. Jr.

1998-12-01

243

Monte Carlo modeling and meteor showers

NASA Technical Reports Server (NTRS)

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.

Kulikova, N. V.

1987-01-01

244

Variational Monte Carlo studies of gossamer superconductivity

NASA Astrophysics Data System (ADS)

We use a partially Gutzwiller projected BCS d -wave wave function with an antiferromagnetic-weighting factor to study the ground-state phase diagram of a half-filled Hubbard-Heisenberg model in a square lattice with nearest-neighbor hopping t and a diagonal hopping t' . The calculations are carried out by using variational Monte Carlo method which treats the Gutzwiller projection explicitly. At large on-site Coulomb interaction U , the ground state is antiferromagnetic. As U decreases, the ground state becomes superconducting and eventually metallic. The phase diagram is obtained by extensive calculations. As compared to the strong effect of U/t , the phase boundaries turn out to be less sensitive to t'/t . The result is consistent with the phase diagram in layered organic conductors and is compared to the earlier mean-field result based on the Gutzwiller approximation.

Guertler, Siegfried; Wang, Qiang-Hua; Zhang, Fu-Chun

2009-04-01

245

Minimum energy pathways via quantum Monte Carlo.

We perform quantum Monte Carlo (QMC) calculations to determine minimum energy pathways of simple chemical reactions, and compare the computed geometries and reaction barriers with those obtained with density functional theory (DFT) and quantum chemistry methods. We find that QMC performs in general significantly better than DFT, being also able to treat cases in which DFT is inaccurate or even unable to locate the transition state. Since the wave function form employed here is particularly simple and can be transferred to larger systems, we suggest that a QMC approach is both viable and useful for reactions difficult to address by DFT and system sizes too large for high level quantum chemistry methods. PMID:23464142

Saccani, S; Filippi, C; Moroni, S

2013-02-28

246

Monte Carlo modeling of lunar megaregolith development

NASA Technical Reports Server (NTRS)

A Monte Carlo model of lunar megaregolith development is proposed. Minimum megaregolith depths are obtained in the preliminary model. The model impacts a gridded, initially flat surface area randomly, with points not constrained to grid intersections. Information is recorded at grid points on evolving topography, deepest depth impacted to, and number of hits at that location. Two types of lunar surfaces ar simulated, maria and highlands. Crater production functions are after run to densities that are multiples of observed lunar crater densities for craters of 8 km in diameter and larger. all craters are considered to have formed in a gravity scaled regime. Edge effect problems are corrected in this model by allowing craters forming outside the grid area or along its edges to effect the gridded area.

Cashore, J.; Woronow, A.

1985-01-01

247

Monte Carlo Simulation of Endlinking Oligomers

NASA Technical Reports Server (NTRS)

This report describes initial efforts to model the endlinking reaction of phenylethynyl-terminated oligomers. Several different molecular weights were simulated using the Bond Fluctuation Monte Carlo technique on a 20 x 20 x 20 unit lattice with periodic boundary conditions. After a monodisperse "melt" was equilibrated, chain ends were linked whenever they came within the allowed bond distance. Ends remained reactive throughout, so that multiple links were permitted. Even under these very liberal crosslinking assumptions, geometrical factors limited the degree of crosslinking. Average crosslink functionalities were 2.3 to 2.6; surprisingly, they did not depend strongly on the chain length. These results agreed well with the degrees of crosslinking inferred from experiment in a cured phenylethynyl-terminated polyimide oligomer.

Hinkley, Jeffrey A.; Young, Jennifer A.

1998-01-01

248

Generalized directed loops for quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Efficient quantum Monte Carlo update schemes called directed loops have recently been proposed, which improve the efficiency of simulations of quantum lattice models. We propose to generalize such schemes using additional weight factors that account for the weight of open world-line segments ("worms"). Employing linear programming techniques in order to solve these equations, we obtain optimal construction schemes for directed loops. The resulting algorithms are bounce-free in larger regions of parameter space than the original directed loop algorithm. This generalized directed loop method is applied to the magnetization process of spin chains in order to compare its efficiency to that of previous directed loops. We find that minimizing bounces does not necessarily guarantee more efficient algorithms in terms of autocorrelations.

Alet, Fabien; Wessel, Stefan; Troyer, Matthias

2004-03-01

249

Monte Carlo Sampling in Fractal Landscapes

NASA Astrophysics Data System (ADS)

We design a random walk to explore fractal landscapes such as those describing chaotic transients in dynamical systems. We show that the random walk moves efficiently only when its step length depends on the height of the landscape via the largest Lyapunov exponent of the chaotic system. We propose a generalization of the Wang-Landau algorithm which constructs not only the density of states (transient time distribution) but also the correct step length. As a result, we obtain a flat-histogram Monte Carlo method which samples fractal landscapes in polynomial time, a dramatic improvement over the exponential scaling of traditional uniform-sampling methods. Our results are not limited by the dimensionality of the landscape and are confirmed numerically in chaotic systems with up to 30 dimensions.

Leităo, Jorge C.; Lopes, J. M. Viana Parente; Altmann, Eduardo G.

2013-05-01

250

Parallel implicit Monte Carlo in C++

The authors are developing a parallel C++ Implicit Monte Carlo code in the Draco framework. As a background and motivation for the parallelization strategy, they first present three basic parallelization schemes. They use three hypothetical examples, mimicking the memory constraints of the real world, to examine characteristics of the basic schemes. Next, they present a two-step scheme proposed by Lawrence Livermore National Laboratory (LLNL). The two-step parallelization scheme they develop is based upon LLNL`s two-step scheme. The two-step scheme appears to have greater potential compared to the basic schemes and LLNL`s two-step scheme. Lastly, they explain the code design and describe how the functionality of C++ and the Draco framework assist the development of a parallel code.

Urbatsch, T.J.; Evans, T.M.

1998-12-31

251

Accuracy control in Monte Carlo radiative calculations

NASA Technical Reports Server (NTRS)

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.

Almazan, P. Planas

1993-01-01

252

Monte Carlo Exploration of Warped Higgsless Models

We have performed a detailed Monte Carlo exploration of the parameter space for a warped Higgsless model of electroweak symmetry breaking in 5 dimensions. This model is based on the SU(2)L x SU(2){sub R} x U(1){sub B-L} gauge group in an AdS{sub 5} bulk with arbitrary gauge kinetic terms on both the Planck and TeV branes. Constraints arising from precision electroweak measurements and collider data are found to be relatively easy to satisfy. We show, however, that the additional requirement of perturbative unitarity up to the cut-off, {approx} 10 TeV, in W{sub L}{sup +}W{sub L}{sup -} elastic scattering in the absence of dangerous tachyons eliminates all models. If successful models of this class exist, they must be highly fine-tuned.

Hewett, J

2004-07-06

253

Entanglement spectroscopy using quantum Monte Carlo

NASA Astrophysics Data System (ADS)

We present a numerical scheme to reconstruct a subset of the entanglement spectrum of quantum many body systems using quantum Monte Carlo. The approach builds on the replica trick to evaluate particle number resolved traces of the first n of powers of a reduced density matrix. From this information we reconstruct n entanglement spectrum levels using a polynomial root solver. We illustrate the power and limitations of the method by an application to the extended Bose-Hubbard model in one dimension where we are able to resolve the quasidegeneracy of the entanglement spectrum in the Haldane-insulator phase. In general, the method is able to reconstruct the largest few eigenvalues in each symmetry sector and typically performs better when the eigenvalues are not too different.

Chung, Chia-Min; Bonnes, Lars; Chen, Pochung; Läuchli, Andreas M.

2014-05-01

254

Methods for Monte Carlo simulations of biomacromolecules

The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies.

Vitalis, Andreas; Pappu, Rohit V.

2010-01-01

255

Green's function Monte Carlo in nuclear physics

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.

Carlson, J.

1990-01-01

256

Vectorization of Monte Carlo particle transport

Fully vectorized versions of the Los Alamos National Laboratory benchmark code Gamteb, a Monte Carlo photon transport algorithm, were developed for the Cyber 205/ETA-10 and Cray X-MP/Y-MP architectures. Single-processor performance measurements of the vector and scalar implementations were modeled in a modified Amdahl's Law that accounts for additional data motion in the vector code. The performance and implementation strategy of the vector codes are related to architectural features of each machine. Speedups between fifteen and eighteen for Cyber 205/ETA-10 architectures, and about nine for CRAY X-MP/Y-MP architectures are observed. The best single processor execution time for the problem was 0.33 seconds on the ETA-10G, and 0.42 seconds on the CRAY Y-MP. 32 refs., 12 figs., 1 tab.

Burns, P.J.; Christon, M.; Schweitzer, R.; Lubeck, O.M.; Wasserman, H.J.; Simmons, M.L.; Pryor, D.V. (Colorado State Univ., Fort Collins, CO (USA). Computer Center; Los Alamos National Lab., NM (USA); Supercomputing Research Center, Bowie, MD (USA))

1989-01-01

257

Lunar Regolith Albedos Using Monte Carlos

NASA Technical Reports Server (NTRS)

The analysis of planetary regoliths for their backscatter albedos produced by cosmic rays (CRs) is important for space exploration and its potential contributions to science investigations in fundamental physics and astrophysics. Albedos affect all such experiments and the personnel that operate them. Groups have analyzed the production rates of various particles and elemental species by planetary surfaces when bombarded with Galactic CR fluxes, both theoretically and by means of various transport codes, some of which have emphasized neutrons. Here we report on the preliminary results of our current Monte Carlo investigation into the production of charged particles, neutrons, and neutrinos by the lunar surface using FLUKA. In contrast to previous work, the effects of charm are now included.

Wilson, T. L.; Andersen, V.; Pinsky, L. S.

2003-01-01

258

Monte Carlo scatter correction for SPECT

NASA Astrophysics Data System (ADS)

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.

Liu, Zemei

259

Quantum Monte Carlo studies on small molecules

NASA Astrophysics Data System (ADS)

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.

Galek, Peter T. A.; Handy, Nicholas C.; Lester, William A., Jr.

260

Monte Carlo modelling of TRIGA research reactor

NASA Astrophysics Data System (ADS)

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( ?, ?) 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.

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

261

Monte Carlo approaches to effective field theories

NASA Astrophysics Data System (ADS)

In this paper, we explore the application of continuum Monte Carlo methods to effective field theory models. Effective field theories, in this context, are those in which a Fock space decomposition of the state is useful. These problems arise both in nuclear and condensed matter physics. In nuclear physics, much work has been done on effective field theories of mesons and baryons. While the theories are not fundamental, they should be able to describe nuclear properties at low energy and momentum scales. After describing the methods, we solve two simple scalar field theory problems; the polaron and two nucleons interacting through scalar meson exchange. The methods presented here are rather straightforward extensions of methods used to solve quantum mechanics problems. Monte Carlo methods are used to avoid the truncation inherent in a Tamm-Dancoff approach and its associated difficulties. Nevertheless, the methods will be most valuable when the Fock space decomposition of the states is useful. Hence, while they are not intended for ab initio studies of QCD, they may prove valuable in studies of light nuclei, or for systems of interacting electrons and phonons. In these problems, a Fock space decomposition can be used to reduce the number of degrees of freedom and to retain the rotational symmetries exactly. The problems we address here are comparatively simple, but offer useful initial tests of the method. We present results for the polaron and two non-relativistic nucleons interacting through scalar meson exchange. In each case, it is possible to integrate out the boson degrees of freedom exactly, and obtain a retarded form of the action that depends only upon the fermion paths. Here we keep the explicit bosons, though, since we would like to retain information about the boson components of the states and it will be necessary to keep these components in order to treat non-scalar of interacting bosonic fields.

Carlson, J.; Schmidt, K. E.

262

Recent advances and future prospects for Monte Carlo

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.

Brown, Forrest B [Los Alamos National Laboratory

2010-01-01

263

Continuous-time quantum Monte Carlo impurity solvers

NASA Astrophysics Data System (ADS)

Continuous-time quantum Monte Carlo impurity solvers are algorithms that sample the partition function of an impurity model using diagrammatic Monte Carlo techniques. The present paper describes codes that implement the interaction expansion algorithm originally developed by Rubtsov, Savkin, and Lichtenstein, as well as the hybridization expansion method developed by Werner, Millis, Troyer, et al. These impurity solvers are part of the ALPS-DMFT application package and are accompanied by an implementation of dynamical mean-field self-consistency equations for (single orbital single site) dynamical mean-field problems with arbitrary densities of states. Program summaryProgram title: dmft Catalogue identifier: AEIL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: ALPS LIBRARY LICENSE version 1.1 No. of lines in distributed program, including test data, etc.: 899 806 No. of bytes in distributed program, including test data, etc.: 32 153 916 Distribution format: tar.gz Programming language: C++ Operating system: The ALPS libraries have been tested on the following platforms and compilers: Linux with GNU Compiler Collection (g++ version 3.1 and higher), and Intel C++ Compiler (icc version 7.0 and higher) MacOS X with GNU Compiler (g++ Apple-version 3.1, 3.3 and 4.0) IBM AIX with Visual Age C++ (xlC version 6.0) and GNU (g++ version 3.1 and higher) compilers Compaq Tru64 UNIX with Compq C++ Compiler (cxx) SGI IRIX with MIPSpro C++ Compiler (CC) HP-UX with HP C++ Compiler (aCC) Windows with Cygwin or coLinux platforms and GNU Compiler Collection (g++ version 3.1 and higher) RAM: 10 MB-1 GB Classification: 7.3 External routines: ALPS [1], BLAS/LAPACK, HDF5 Nature of problem: (See [2].) Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as representations of quantum dots and molecular conductors and play an increasingly important role in the theory of "correlated electron" materials as auxiliary problems whose solution gives the "dynamical mean field" approximation to the self-energy and local correlation functions. Solution method: Quantum impurity models require a method of solution which provides access to both high and low energy scales and is effective for wide classes of physically realistic models. The continuous-time quantum Monte Carlo algorithms for which we present implementations here meet this challenge. Continuous-time quantum impurity methods are based on partition function expansions of quantum impurity models that are stochastically sampled to all orders using diagrammatic quantum Monte Carlo techniques. For a review of quantum impurity models and their applications and of continuous-time quantum Monte Carlo methods for impurity models we refer the reader to [2]. Additional comments: Use of dmft requires citation of this paper. Use of any ALPS program requires citation of the ALPS [1] paper. Running time: 60 s-8 h per iteration.

Gull, Emanuel; Werner, Philipp; Fuchs, Sebastian; Surer, Brigitte; Pruschke, Thomas; Troyer, Matthias

2011-04-01

264

NASA Technical Reports Server (NTRS)

A realization of a stochastic atmosphere model for use in simulations is presented. The model provides pressure, density, temperature, and wind velocity as a function of latitude, longitude, and altitude, and is implemented in a three degree of freedom simulation package. This implementation is used in the Monte Carlo simulation of an aeroassisted orbital transfer maneuver and results are compared to those of a more traditional approach.

Queen, Eric M.; Omara, Thomas M.

1990-01-01

265

Noise-induced instability in self-consistent Monte Carlo calculations

NASA Astrophysics Data System (ADS)

We identify, analyze, and propose remedies for a numerical instability responsible for the growth or decay of sums that should be conserved in Monte Carlo simulations of stochastically interacting particles. ``Noisy'' sums with fluctuations proportional to 1/ ?n , where n is the number of particles in the simulation, provide feedback that drives the instability. Numerical illustrations of an energy loss or ``cooling'' instability in an Ornstein-Uhlenbeck process support our analysis. (c) 1995 The American Physical Society

Lemons, D. S.; Lackman, J.; Jones, M. E.; Winske, D.

1995-12-01

266

An Efficient Monte-Carlo Method for Calculating Free Energy in Long-Range Interacting Systems

We present an efficient Monte-Carlo method for long-range interacting systems to calculate free energy as a function of an order parameter. In this method, a variant of the Wang--Landau method regarding the order parameter is combined with the stochastic cutoff method, which has recently been developed for long-range interacting systems. This method enables us to calculate free energy in long-range

Kazuya Watanabe; Munetaka Sasaki

2011-01-01

267

Coupling kinetic Monte-Carlo and continuum models with application to epitaxial growth

We present a hybrid method for simulating epitaxial growth that combines kinetic Monte-Carlo (KMC) simulations with the BurtonCabreraFrank model for crystal growth. This involves partitioning the computational domain into KMC regions and regions where we time-step a discretized diffusion equation. Computational speed and accuracy are discussed. We find that the method is significantly faster than KMC while accounting for stochastic

Tim P. Schulze; Peter Smereka; Weinan E

2003-01-01

268

Accurate rotational barrier calculations with diffusion quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Accurate quantum Monte Carlo, MP2, coupled cluster, and DFT calculations of rotational barriers of several small molecules are presented. With the diffusion quantum Monte Carlo method (DMC) excellent agreement with experimental barriers is obtained except for the gauche-gauche barriers of n-butane and ethylmethylether. It is argued that these two experimental values might be erroneous. Additionally, barriers calculated with the more efficient variational quantum Monte Carlo method (VMC) are presented. The VMC barriers are less accurate than the DMC results, but it is demonstrated that accurate barriers can be obtained with sophisticated Jastrow correlation functions.

Klahm, Sebastian; Lüchow, Arne

269

Bold diagrammatic Monte Carlo study of ?4 theory

NASA Astrophysics Data System (ADS)

By incorporating renormalization procedure into bold diagrammatic Monte Carlo, we propose a method for studying quantum field theories in the strong coupling regime. Bold diagrammatic Monte Carlo essentially samples Feynman diagrams using local Metropolis-type updates. Applying the method to three-dimensional ?4 theory, we analyze the strong coupling limit of the theory and confirm the existence of a nontrivial IR fixed point in agreement with prior studies. Interestingly, we find that working with bold correlation functions as building blocks of the Monte Carlo procedure renders the scheme convergent, and no further resummation method is needed.

Davody, Ali

2013-12-01

270

Fast Monte Carlo Full Spectrum Scene Simulation

NASA Astrophysics Data System (ADS)

This paper discusses the formulation and implementation of an acceleration approach for the MCScene code, a high fidelity model for full optical spectrum (UV to LWIR) hyperspectral image (HSI) simulation. The MCScene simulation is based on a Direct Simulation Monte Carlo approach for modeling 3D atmospheric radiative transport, as well as spatially inhomogeneous surfaces including surface BRDF effects. The model includes treatment of land and ocean surfaces, 3D terrain, 3D surface objects, and effects of finite clouds with surface shadowing. This paper will review an acceleration algorithm that exploits spectral redundancies in hyperspectral images. In this algorithm, the full scene is determined for a subset of spectral channels, and then this multispectral scene is unmixed into spectral end members and end member abundance maps. Next, pure end member pixels are determined at their full hyperspectral resolution, and the full hyperspectral scene is reconstructed from the hyperspectral end member spectra and the multispectral abundance maps. This algorithm effectively performs a hyperspectral simulation while requiring only the computational time of a multispectral simulation. The acceleration algorithm will be demonstrated, and errors associated with the algorithm will be analyzed.

Richtsmeier, Steven; Sundberg, Robert; Clark, Frank O.

2009-03-01

271

La modélisation par Reverse Monte Carlo (RMC)

NASA Astrophysics Data System (ADS)

La technique de modélisation par Reverse Monte Carlo (RMC) est une méthode générale de modélisation structurale ŕ partir d'un ensemble de données expérimentales. Cette méthode étant trčs souple, elle peut s'appliquer ŕ de nombreux types de données. Jusqu'ŕ présent ces applications comprennent : la diffraction des neutrons (y compris la substitution isotopique), la diffraction des rayons X (y compris la diffusion anomale), la diffraction des électrons, la RMN (les techniques d'angle magique et de 2čme moment) et l'EXAFS. Les systčmes étudiés sont également d'une grande variété : liquides, verres, polymčres, cristaux et matériaux magnétiques, par exemple. Ce cours présente les bases de la méthode RMC en signalant certaines des idées fausses répandues. L'accent sera mis sur le fait que les modčles structuraux obtenus par RMC ne sont ni'uniques' ni 'exacts' ; cependant ils sont souvent utiles ŕ la compréhension soit de la structure du systčme, soit des relations entre structure et autres propriétés physiques.

McGreevy, R. L.

2003-09-01

272

Monte Carlo study of nanowire magnetic properties

NASA Astrophysics Data System (ADS)

In this work, we use Monte Carlo simulations to study the magnetic properties of a nanowire system based on a honeycomb lattice, in the absence as well as in the presence of both an external magnetic field and crystal field. The system is formed with NL layers having spins that can take the values ? = ą1/2 and S = ą1,0. The blocking temperature is deduced, for each spin configuration, depending on the crystal field ?. The effect of the exchange interaction coupling Jp between the spin configurations ? and S is studied for different values of temperature at fixed crystal field. The established ground-state phase diagram, in the plane (Jp, ?), shows that the only stable configurations are: (1/2, 0), (1/2, +1), and (1/2, -1). The thermal magnetization and susceptibility are investigated for the two spin configurations, in the absence as well as in the presence of a crystal field. Finally, we establish the hysteresis cycle for different temperature values, showing that there is almost no remaining magnetization in the absence of the external magnetic field, and that the studied system exhibits a super-paramagnetic behavior.

Masrour, R.; Bahmad, L.; Benyoussef, A.

2013-05-01

273

Quantum Ice : A Quantum Monte Carlo Study

NASA Astrophysics Data System (ADS)

The magnetic ``ice'' state found in spin ice materials has recently generated great excitement for its magnetic monopole excitations. However the deconfined nature of these monopoles depends crucially on the macroscopic degeneracy of the classical ice ground state. And at very low temperatures we might expect this degeneracy to be lifted by quantum tunneling between different ice configurations. Here we present the results of large-scale Green's function Monte Carlo simulation of ice-type models which include quantum tunneling. We find compelling evidence of an extended quantum U(1)-liquid ground state with deconfined monopole excitations in both the quantum dimer model [1,2] and the quantum ice model on the diamond lattice [3]. This quantum U(1) liquid proves to be remarkably robust against the inclusion of long range dipolar interactions. [0pt] [1] O. Sikora et al., Phys. Rev. Lett. 103, 247001 (2009) [2] O. Sikora et al., Phys. Rev. B 84, 115129 (2011) [3] N. Shannon et al., arXiv:1105.4196

Sikora, Olga; Benton, Owen; Shannon, Nic; Penc, Karlo; McClarty, Paul; Pollmann, Frank; Moessner, Roderich; Fulde, Peter

2012-02-01

274

Classical Trajectory and Monte Carlo Techniques

NASA Astrophysics Data System (ADS)

The classical trajectory Monte Carlo (CTMC) method originated with Hirschfelder, who studied the H + D2 exchange reaction using a mechanical calculator [58.1]. With the availability of computers, the CTMC method was actively applied to a large number of chemical systems to determine reaction rates, and final state vibrational and rotational populations (see, e.g., Karplus et al. [58.2]). For atomic physics problems, a major step was introduced by Abrines and Percival [58.3] who employed Kepler's equations and the Bohr-Sommerfield model for atomic hydrogen to investigate electron capture and ionization for intermediate velocity collisions of H+ + H. An excellent description is given by Percival and Richards [58.4]. The CTMC method has a wide range of applicability to strongly-coupled systems, such as collisions by multiply-charged ions [58.5]. In such systems, perturbation methods fail, and basis set limitations of coupled-channel molecular- and atomic-orbital techniques have difficulty in representing the multitude of activeexcitation, electron capture, and ionization channels. Vector- and parallel-processors now allow increasingly detailed study of the dynamics of the heavy projectile and target, along with the active electrons.

Olson, Ronald

275

Monte Carlo simulation with tensor network states

NASA Astrophysics Data System (ADS)

We demonstrate that Monte Carlo sampling can be used to efficiently extract the expectation value of projected entangled pair states with a large virtual bond dimension. We use the simple update rule introduced by H. C. Jiang [Phys. Rev. LettPRLTAO0031-900710.1103/PhysRevLett.101.090603 101, 090603 (2008)] to obtain the tensors describing the ground state wave function of the antiferromagnetic Heisenberg model and evaluate the finite size energy and staggered magnetization for square lattices with periodic boundary conditions of linear sizes up to L=16 and virtual bond dimensions up to D=16. The finite size magnetization errors are 0.003(2) and 0.013(2) at D=16 for a system of size L=8,16, respectively. Finite D extrapolation provides exact finite size magnetization for L=8, and reduces the magnetization error to 0.005(3) for L=16, significantly improving the previous state-of-the-art results.

Wang, Ling; Piorn, Iztok; Verstraete, Frank

2011-04-01

276

A Local Superbasin Kinetic Monte Carlo Method

NASA Astrophysics Data System (ADS)

A ubiquitous problem in atomic-scale simulation of materials is the small-barrier problem, in which the free-energy landscape presents ``superbasins'' with low intra-basin energy barriers relative to the inter-basin barriers. Rare-event simulation methods, such as kinetic Monte Carlo (KMC) and accelerated molecular dynamics, are inefficient for such systems because considerable effort is spent simulating short-time, intra-basin motion without evolving the system significantly. We developed an adaptive local-superbasin KMC algorithm (LSKMC) for treating fast, intra-basin motion using a Master-equation / Markov-chain approach and long-time evolution using KMC. Our algorithm is designed to identify local superbasins in an on-the-fly search during conventional KMC, construct the rate matrix, compute the mean exit time and its distribution, obtain the probability to exit to each of the superbasin border (absorbing) states, and integrate superbasin exits with non-superbasin moves. We demonstrate various aspects of the method in several examples, which also highlight the efficiency of the method.

Fichthorn, Kristen; Lin, Yangzheng

2013-03-01

277

Monte Carlo computer simulation of ion sputtering

NASA Astrophysics Data System (ADS)

Using the sputtering version of the Monte-Carlo (MC) computer code TRIRS (TRansport of Ions and Recoils in Solid) we studied the collision sputtering processes under ion bombardment of a structureless target. Basically, the TRIRS calculation procedure is similar to the one used in the well known TRIM code. The important feature of the TRIRS with respect to other similar MC codes is the elaborate design of the particles trajectories, i.e., the scattering angle is calculated exactly using a scattering integral; the asymptotic trajectories of particles are computed taking into account a `time integral' for the specific interatomic potential used in calculation; during low energy events not only binary collisions, but also many-bode interaction may be taken into account. Comparing the calculation results and experimental data, we can see that TRIRS code is more realistic than TRIM in modeling the low-energy interatomic collisions, which dominate in sputtering processes. The special dynamic version of TRIRS code (DYTRIRS) was used to study the sputtering in the course of high-fluence irradiation when the target may be modified during irradiation. The high-fluence effects in preferential sputtering have also been discussed.

Zhurkin, Evgeni E.; Ivanov, Dmitrij P.

1998-01-01

278

Monte Carlo shower counter studies. Progress report

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.

Snyder, H.D.

1991-01-01

279

The GENIE neutrino Monte Carlo generator

NASA Astrophysics Data System (ADS)

GENIE [1] is a new neutrino event generator for the experimental neutrino physics community. The goal of the project is to develop a 'canonical' neutrino interaction physics Monte Carlo whose validity extends to all nuclear targets and neutrino flavors from MeV to PeV energy scales. Currently, emphasis is on the few-GeV energy range, the challenging boundary between the non-perturbative and perturbative regimes, which is relevant for the current and near future long-baseline precision neutrino experiments using accelerator-made beams. The design of the package addresses many challenges unique to neutrino simulations and supports the full life-cycle of simulation and generator-related analysis tasks. GENIE is a large-scale software system, consisting of 120000 lines of C++ code, featuring a modern object-oriented design and extensively validated physics content. The first official physics release of GENIE was made available in August 2007, and at the time of the writing of this article, the latest available version was v2.4.4.

Andreopoulos, C.; Bell, A.; Bhattacharya, D.; Cavanna, F.; Dobson, J.; Dytman, S.; Gallagher, H.; Guzowski, P.; Hatcher, R.; Kehayias, P.; Meregaglia, A.; Naples, D.; Pearce, G.; Rubbia, A.; Whalley, M.; Yang, T.

2010-02-01

280

Path Integral Quantum Monte Carlo Benchmarks for Molecules and Plasmas

NASA Astrophysics Data System (ADS)

Path integral quantum Monte Carlo is used to simulate hot dense plasmas and other systems where quantum and thermal fluctuations are important. The fixed node approximation---ubiquitous in ab initio ground state Quantum Monte Carlo---is more complicated at finite temperatures, with many unanswered questions. In this talk I discuss the current state of fermionic path integral quantum Monte Carlo, with an emphasis on molecular systems where good benchmark data exists. We look at two ways of formulating the fixed node constraint and strategies for constructing finite-temperature nodal surfaces. We compare different the free energies of different nodal choices by sampling an ensemble of nodal models within a Monte Carlo simulation. We also present data on imaginary-time correlation fluctuations, which can be surprisingly accurate for molecular vibrations and polarizabilty.

Shumway, John

2013-03-01

281

Path-Integral Monte Carlo Methods for Ultrasmall Device Modeling

Monte Carlo methods based on the Feynman path -integral (FPI) formulation of quantum mechanics are developed for modeling ultrasmall device structures. A brief introduction to pertinent aspects of the FPI formalism is given. A practical \\

Leonard Franklin Register II

1990-01-01

282

Monte Carlo Simulations of Arterial Imaging with Optical Coherence Tomography.

National Technical Information Service (NTIS)

The laser-tissue interaction code LATIS is used to analyze photon scattering histories representative of optical coherence tomography (OCT) experiments performed at Lawrence Livermore National Laboratory. Monte Carlo photonics with Henyey-Greenstein aniso...

P. Amendt K. Estabrook M. Everett R. A. London D. Maitland G. Zimmerman B. Colston L. da Silva U. Sathnyam

2000-01-01

283

Overview of the NCC Spray/Monte-Carlo-PDF Computations.

National Technical Information Service (NTIS)

This paper advances the state-of-the-art in spray computations with some of our recent contributions involving scalar Monte Carlo PDF (Probability Density Function), unstructured grids and parallel computing. It provides a complete overview of the scalar ...

M. S. Raju

2000-01-01

284

A Monte Carlo Simulation of Air Shower Cores.

National Technical Information Service (NTIS)

The electromagnetic and strongly interacting particle distributions falling on the Sydney 64 scintillator array for a variety of primary particles (from protons to iron) of a given incident total energy have been simulated using Monte Carlo and analytic m...

C. B. A. McCusker L. S. Peak M. H. Rathgeber

1967-01-01

285

Towards a Revised Monte Carlo Neutral Particle Surface Interaction Model.

National Technical Information Service (NTIS)

The components of the neutral- and plasma-surface interaction model used in the Monte Carlo neutral transport code DEGAS 2 are reviewed. The idealized surfaces and processes handled by that model are inadequate for accurately simulating neutral transport ...

D. P. Stotler

2005-01-01

286

Vector Computers, Monte Carlo Simulation, and Regression Analysis: An Introduction.

National Technical Information Service (NTIS)

Vector computers provide a new tool for management scientists. The application of that tool requires thinking in vector mode. The mode is examined in the context of Monte Carlo experiments with regression models; these regression models serve as metamodel...

J. P. C. Kleijnen B. Annink

1989-01-01

287

Molecular Physics and Chemistry Applications of Quantum Monte Carlo.

National Technical Information Service (NTIS)

We discuss recent work with the diffusion quantum Monte Carlo (QMC) method in its application to molecular systems. The formal correspondence of the imaginary time Schroedinger equation to a diffusion equation allows one to calculate quantum mechanical ex...

P. J. Reynolds R. N. Barnett B. L. Hammond W. A. Lester

1985-01-01

288

Modeling and Computer Simulation: Molecular Dynamics and Kinetic Monte Carlo.

National Technical Information Service (NTIS)

This article describes the atomistic modeling techniques of molecular dynamics (MD) and kinetic Monte Carlo (KMC), and an example of their application to radiation damage production and accumulation in metals. It is important to note at the outset that th...

B. D. Wirth M. J. Caturla T. Diaz de la Rubia

2000-01-01

289

Monte Carlo Modeling of Electron Transport in Repeated Overshoot Structures,

National Technical Information Service (NTIS)

Repeated velocity overshoot has been proposed as a way of obtaining high average velocities over significant distances in semiconductor devices. The potential of this concept is examined using a fully self-consistent particle-field Monte Carlo simulation....

G. I. Haddad T. L. Crandle J. R. East P. A. Blakey

1989-01-01

290

Vectorized Monte Carlo Methods for Reactor Lattice Analysis.

National Technical Information Service (NTIS)

This report details some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-energy Monte Carlo code for use on the CYBER-205 computer. While the principal applicatio...

F. B. Brown

1982-01-01

291

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...

292

Monte Carlo Heat Conduction Using the Transport Equation Approximation.

National Technical Information Service (NTIS)

The use of Monte Carlo radiation transport codes to solve heat conduction problems was shown to be applicable to steady state and time dependent multi-media problems. An improved method for treating problems with given surface temperature distributions is...

S. K. Fraley

1977-01-01

293

Monte Carlo Calculation of the Radiation Field at Aircraft Altitudes.

National Technical Information Service (NTIS)

Energy spectra of secondary cosmic rays are calculated for aircraft altitudes and a discrete set of solar modulation parameters and rigidity cutoff values covering all possible conditions. The calculations are based on the Monte Carlo code FLUKA and on th...

S. Roesler

2001-01-01

294

Green's function Monte Carlo calculations of /sup 4/He

Green's Function Monte Carlo methods have been developed to study the ground state properties of light nuclei. These methods are shown to reproduce results of Faddeev calculations for A = 3, and are then used to calculate ground state energies, one- and two-body distribution functions, and the D-state probability for the alpha particle. Results are compared to variational Monte Carlo calculations for several nuclear interaction models. 31 refs.

Carlson, J.A.

1988-01-01

295

Path Integral Monte Carlo Simulation of Isotopic Liquid Helium Mixtures

We report results of a path integral Monte Carlo simulation of a liquid 3He- 4He mixture at low temperature. In the limit of low 3He concentration, a kinetic energy of 17 K is found for the 3He atoms; the 3He effective mass is m* = 2.3m. The restricted path integral Monte Carlo method was utilized to investigate the separation of

Massimo Boninsegni; David M. Ceperley

1995-01-01

296

MOS2: an efficient MOnte Carlo Simulator for MOS devices

An efficient Monte Carlo device simulator has been developed as a postprocessor of a two-dimensional numerical analyzer based on the drift-diffusion model. The Monte Carlo package analyzes real VLSI MOSFETs in a minicomputer environment, overcoming some existing theoretical and practical problems. In particular, the particle free-flight time distribution is obtained by a new algorithm, leading to a CPU time saving

Enrico Sangiorgi; Bruno Riccň; Franco Venturi

1988-01-01

297

Monte Carlo methods and applications in nuclear physics

Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.

Carlson, J.

1990-01-01

298

A Particle Population Control Method for Dynamic Monte Carlo

NASA Astrophysics Data System (ADS)

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.

Sweezy, Jeremy; Nolen, Steve; Adams, Terry; Zukaitis, Anthony

2014-06-01

299

Fast Off-Lattice Monte Carlo Simulations with Soft Potentials

Fast off-lattice Monte Carlo simulations with soft repulsive potentials that allow particle overlapping give orders of magnitude faster\\/better sampling of the configurational space than conventional molecular simulations with hard-core repulsions (such as the hard-sphere or Lennard-Jones repulsion). ootnotetextQ. Wang and Y. Yin, J. Chem. Phys., 130, 104903 (2009). Here we present our fast off-lattice Monte Carlo simulations ranging from small-molecule

Jing Zong; Delian Yang; Yuhua Yin; Xinghua Zhang

2011-01-01

300

Development of Monte Carlo Capability for Orion Parachute Simulations

NASA Technical Reports Server (NTRS)

Parachute test programs employ Monte Carlo simulation techniques to plan testing and make critical decisions related to parachute loads, rate-of-descent, or other parameters. This paper describes the development and use of a MATLAB-based Monte Carlo tool for three parachute drop test simulations currently used by NASA. The Decelerator System Simulation (DSS) is a legacy 6 Degree-of-Freedom (DOF) simulation used to predict parachute loads and descent trajectories. The Decelerator System Simulation Application (DSSA) is a 6-DOF simulation that is well suited for modeling aircraft extraction and descent of pallet-like test vehicles. The Drop Test Vehicle Simulation (DTVSim) is a 2-DOF trajectory simulation that is convenient for quick turn-around analysis tasks. These three tools have significantly different software architectures and do not share common input files or output data structures. Separate Monte Carlo tools were initially developed for each simulation. A recently-developed simulation output structure enables the use of the more sophisticated DSSA Monte Carlo tool with any of the core-simulations. The task of configuring the inputs for the nominal simulation is left to the existing tools. Once the nominal simulation is configured, the Monte Carlo tool perturbs the input set according to dispersion rules created by the analyst. These rules define the statistical distribution and parameters to be applied to each simulation input. Individual dispersed parameters are combined to create a dispersed set of simulation inputs. The Monte Carlo tool repeatedly executes the core-simulation with the dispersed inputs and stores the results for analysis. The analyst may define conditions on one or more output parameters at which to collect data slices. The tool provides a versatile interface for reviewing output of large Monte Carlo data sets while preserving the capability for detailed examination of individual dispersed trajectories. The Monte Carlo tool described in this paper has proven useful in planning several Crew Exploration Vehicle parachute tests.

Moore, James W.

2011-01-01

301

Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms

IntroductionThe goal of these lectures is to give an introduction to current research on MonteCarlo methods in statistical mechanics and quantum field theory, with an emphasis on:1) the conceptual foundations of the method, including the possible dangers andmisuses, and the correct use of statistical error analysis; and2) new Monte Carlo algorithms for problems in critical phenomena and quantumfield theory, aimed

Alan D. Sokal

1996-01-01

302

Monte Carlo simulations of the transport of sputtered particles

NASA Astrophysics Data System (ADS)

Program SPATS models the transport of neutral particles during magnetron sputtering deposition. The 3D Monte Carlo simulation provides information about spatial distribution of the fluxes, density of the sputtered particles in the chamber glow discharge area, and kinetic energy distribution of the arrival flux. Collision events are modelled by scattering in Biersack's potential, Lennard-Jones potential, or by binary hard sphere collision approximation. The code has an interface for Monte Carlo TRIM simulated results of the sputtered particles.

Macŕk, Karol; Macŕk, Peter; Helmersson, Ulf

1999-08-01

303

Perturbation Monte Carlo methods for tissue structure alterations

This paper describes an extension of the perturbation Monte Carlo method to model light transport when the phase function is arbitrarily perturbed. Current perturbation Monte Carlo methods allow perturbation of both the scattering and absorption coefficients, however, the phase function can not be varied. The more complex method we develop and test here is not limited in this way. We derive a rigorous perturbation Monte Carlo extension that can be applied to a large family of important biomedical light transport problems and demonstrate its greater computational efficiency compared with using conventional Monte Carlo simulations to produce forward transport problem solutions. The gains of the perturbation method occur because only a single baseline Monte Carlo simulation is needed to obtain forward solutions to other closely related problems whose input is described by perturbing one or more parameters from the input of the baseline problem. The new perturbation Monte Carlo methods are tested using tissue light scattering parameters relevant to epithelia where many tumors originate. The tissue model has parameters for the number density and average size of three classes of scatterers; whole nuclei, organelles such as lysosomes and mitochondria, and small particles such as ribosomes or large protein complexes. When these parameters or the wavelength is varied the scattering coefficient and the phase function vary. Perturbation calculations give accurate results over variations of ?1525% of the scattering parameters.

Nguyen, Jennifer; Hayakawa, Carole K.; Mourant, Judith R.; Spanier, Jerome

2013-01-01

304

Monte Carlo shell model calculations for medium-mass nuclei

The formulation and recent applications of the Monte Carlo shell model based upon the Quantum Monte Carlo diagonalization (QMCD) method are reported. The QMCD has been proposed for solving the quantum many-body interacting systems. By the Monte Carlo shell model calculations, the level structure of low-lying states can be studied with realistic interactions, providing a useful tool for nuclear spectroscopy. Some examples of such calculations are presented. We report that the doubly closed shell probability of a proton-rich unstable nucleus {sup 56}Ni is shown to be only 49% in a full pf shell calculation, in contrast to the corresponding probability of {sup 48}Ca which reaches 86%. The Monte Carlo shell model calculation based on the QMCD method is extended so that the structure of non-yrast states can be described as well as yrast states, and it is applied again to {sup 56}Ni but on an excited rotational band. This band is nicely described in a good agreement to recent experimental observation. Thus, the Monte Carlo shell model calculation is shown to be quite feasible for the spectroscopic study of nuclei. The Monte Carlo shell model is applied also to the study of unstable nuclei: the level scheme and E2 transition probabilities of neutron-rich nuclei around {sup 32}Mg are discussed.

Otsuka, Takaharu [Department of Physics, University of Tokyo, Hongo, Tokyo 113-0033 (Japan); RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Mizusaki, Takahiro; Utsuno, Yutaka [Department of Physics, University of Tokyo, Hongo, Tokyo 113-0033 (Japan); Honma, Michio [Center for Mathematical Sciences, University of Aizu, Tsuruga, Ikki-machi Aizu-Wakamatsu, Fukushima 965 (Japan)

1999-09-02

305

Perturbation Monte Carlo methods for tissue structure alterations.

This paper describes an extension of the perturbation Monte Carlo method to model light transport when the phase function is arbitrarily perturbed. Current perturbation Monte Carlo methods allow perturbation of both the scattering and absorption coefficients, however, the phase function can not be varied. The more complex method we develop and test here is not limited in this way. We derive a rigorous perturbation Monte Carlo extension that can be applied to a large family of important biomedical light transport problems and demonstrate its greater computational efficiency compared with using conventional Monte Carlo simulations to produce forward transport problem solutions. The gains of the perturbation method occur because only a single baseline Monte Carlo simulation is needed to obtain forward solutions to other closely related problems whose input is described by perturbing one or more parameters from the input of the baseline problem. The new perturbation Monte Carlo methods are tested using tissue light scattering parameters relevant to epithelia where many tumors originate. The tissue model has parameters for the number density and average size of three classes of scatterers; whole nuclei, organelles such as lysosomes and mitochondria, and small particles such as ribosomes or large protein complexes. When these parameters or the wavelength is varied the scattering coefficient and the phase function vary. Perturbation calculations give accurate results over variations of ?15-25% of the scattering parameters. PMID:24156056

Nguyen, Jennifer; Hayakawa, Carole K; Mourant, Judith R; Spanier, Jerome

2013-01-01

306

Quantum Monte Carlo: Towards Real Materials

NASA Astrophysics Data System (ADS)

Quantum Monte Carlo (QMC) methods form a general approach to simulation of interacting systems of many particles. Variational approaches can test the accuracy of physically-motivated approximate wavefunctions, whereas Greens Function or diffusion methods can in principle provide exact properties in the ground state or thermal equilibrium. The difficulty in describing "real materials" is due to the famous sign problem, which so far has prevented exact simulations of large numbers of electrons, and the accuracy required to find interesting differences in energy that are much smaller than the total energy. The latter effect is especially problematic for atoms with cores. This has led to two approaches: 1) reduce the problem to "realistic" models that can be solved by QMC, and 2) develop ever more efficient algorithms to treat the "real" problem. In this talk I will review a small part of the work done using both approaches, including calculations on C_60 materials represented by a degenerate Hubbard model with realistic parameters( E. Koch, O. E. Gunnarsson, and R. M. Martin, Phys. Rev. Lett. 83, 620 (1999).); simulations of hydrogen at high pressure including the real Coulomb interactions and treating both electrons and protons as quantum particles( V. Natoli, R. M. Martin and D. M. Ceperley, Phys. Rev. Lett. 74, 1601 (1995).); and calculations on many real molecules and some solids( See, e.g., R. Q. Hood, et al., Phys. Rev. Lett. 78, 3350 (1997), and the review in preparation by W. M. C. Foulkes, L. Mitas, R. J. Needs, and G. Rajagopal.) such as structures of nitrogen, graphite and diamond carbon, and crystalline Si.

Martin, Richard M.

2000-03-01

307

Monte Carlo simulation of large electron fields.

Two Monte Carlo systems, EGSnrc and Geant4, the latter with two different 'physics lists,' were used to calculate dose distributions in large electron fields used in radiotherapy. Source and geometry parameters were adjusted to match calculated results to measurement. Both codes were capable of accurately reproducing the measured dose distributions of the six electron beams available on the accelerator. Depth penetration matched the average measured with a diode and parallel-plate chamber to 0.04 cm or better. Calculated depth dose curves agreed to 2% with diode measurements in the build-up region, although for the lower beam energies there was a discrepancy of up to 5% in this region when calculated results are compared to parallel-plate measurements. Dose profiles at the depth of maximum dose matched to 2-3% in the central 25 cm of the field, corresponding to the field size of the largest applicator. A 4% match was obtained outside the central region. The discrepancy observed in the bremsstrahlung tail in published results that used EGS4 is no longer evident. Simulations with the different codes and physics lists used different source energies, incident beam angles, thicknesses of the primary foils, and distance between the primary and secondary foil. The true source and geometry parameters were not known with sufficient accuracy to determine which parameter set, including the energy of the source, was closest to the truth. These results underscore the requirement for experimental benchmarks of depth penetration and electron scatter for beam energies and foils relevant to radiotherapy. PMID:18296775

Faddegon, Bruce A; Perl, Joseph; Asai, Makoto

2008-03-01

308

kmos: A lattice kinetic Monte Carlo framework

NASA Astrophysics Data System (ADS)

Kinetic Monte Carlo (kMC) simulations have emerged as a key tool for microkinetic modeling in heterogeneous catalysis and other materials applications. Systems, where site-specificity of all elementary reactions allows a mapping onto a lattice of discrete active sites, can be addressed within the particularly efficient lattice kMC approach. To this end we describe the versatile kmos software package, which offers a most user-friendly implementation, execution, and evaluation of lattice kMC models of arbitrary complexity in one- to three-dimensional lattice systems, involving multiple active sites in periodic or aperiodic arrangements, as well as site-resolved pairwise and higher-order lateral interactions. Conceptually, kmos achieves a maximum runtime performance which is essentially independent of lattice size by generating code for the efficiency-determining local update of available events that is optimized for a defined kMC model. For this model definition and the control of all runtime and evaluation aspects kmos offers a high-level application programming interface. Usage proceeds interactively, via scripts, or a graphical user interface, which visualizes the model geometry, the lattice occupations and rates of selected elementary reactions, while allowing on-the-fly changes of simulation parameters. We demonstrate the performance and scaling of kmos with the application to kMC models for surface catalytic processes, where for given operation conditions (temperature and partial pressures of all reactants) central simulation outcomes are catalytic activity and selectivities, surface composition, and mechanistic insight into the occurrence of individual elementary processes in the reaction network.

Hoffmann, Max J.; Matera, Sebastian; Reuter, Karsten

2014-07-01

309

MGGPOD Monte Carlo suite (Weidenspointner+, 2005)

NASA Astrophysics Data System (ADS)

Intense and complex instrumental backgrounds, against which the much smaller signals from celestial sources have to be discerned, are a notorious problem for low- and intermediate-energy {gamma}-ray astronomy (~50keV-10MeV). Therefore, a detailed qualitative and quantitative understanding of instrumental line and continuum backgrounds is crucial for most stages of {gamma}-ray astronomy missions, ranging from the design and development of new instrumentation through performance prediction to data reduction. We have developed MGGPOD, a user-friendly suite of Monte Carlo codes built around the widely used GEANT (ver. 3.21) package, to simulate ab initio the physical processes relevant for the production of instrumental backgrounds. These include the build-up and delayed decay of radioactive isotopes as well as the prompt de-excitation of excited nuclei, both of which give rise to a plethora of instrumental {gamma}-ray background lines in addition to continuum backgrounds. The MGGPOD package and documentation are publicly available online (http://sigma-2.cesr.fr/spi/MGGPOD/). We demonstrate the capabilities of the MGGPOD suite by modeling high-resolution {gamma}-ray spectra recorded by the Transient Gamma-Ray Spectrometer (TGRS) on board Wind during 1995. The TGRS is a Ge spectrometer operating in the 40keV-8MeV range. Because of its fine energy resolution, these spectra reveal the complex instrumental background in formidable detail, particularly the many prompt and delayed {gamma}-ray lines. We evaluate the successes and failures of the MGGPOD package in reproducing TGRS data and provide identifications for the numerous instrumental lines. (2 data files).

Weidenspointner, G.; Harris, M. J.; Sturner, S.; Teegarden, B. J.; Ferguson, C.

2005-06-01

310

Quantum Monte Carlo calculations on positronium compounds

NASA Astrophysics Data System (ADS)

The stability of compounds containing one or more positrons in addition to electrons and nuclei has been the focus of extensive scientific investigations. Interest in these compounds stems from the important role they play in the process of positron annihilation, which has become a useful technique in material science studies. Knowledge of these compounds comes mostly from calculations which are presently less difficult than laboratory experiments. Owing to the small binding energies of these compounds, quantum chemistry methods beyond the molecular orbital approximation must be used. Among them, the quantum Monte Carlo (QMC) method is most appealing because it is easy to implement, gives exact results within the fixed nodes approximation, and makes good use of existing approximate wavefunctions. Applying QMC to small systems like PsH for binding energy calculation is straightforward. To apply it to systems with heavier atoms, to systems for which the center-of-mass motion needs to be separated, and to calculate annihilation rates, special techniques must be developed. In this project a detailed study and several advancements to the QMC method are carried out. Positronium compounds PsH, Ps2, PsO, and Ps2O are studied with algorithms we developed. Results for PsH and Ps2 agree with the best accepted to date. Results for PsO confirm the stability of this compound, and are in fair agreement with an earlier calculation. Results for Ps2O establish the stability of this compound and give an approximate annihilation rate for the first time. Discussions will include an introduction to QMC methods, an in-depth discussion on the QMC formalism, presentation of new algorithms developed in this study, and procedures and results of QMC calculations on the above mentioned positronium compounds.

Jiang, Nan

311

Quantum Monte Carlo Endstation for Petascale Computing

The major achievements enabled by QMC Endstation grant include * Performance improvement on clusters of x86 multi-core systems, especially on Cray XT systems * New and improved methods for the wavefunction optimizations * New forms of trial wavefunctions * Implementation of the full application on NVIDIA GPUs using CUDA The scaling studies of QMCPACK on large-scale systems show excellent parallel efficiency up to 216K cores on Jaguarpf (Cray XT5). The GPU implementation shows speedups of 10-15x over the CPU implementation on older generation of x86. We have implemented hybrid OpenMP/MPI scheme in QMC to take advantage of multi-core shared memory processors of petascale systems. Our hybrid scheme has several advantages over the standard MPI-only scheme. * Memory optimized: large read-only data to store one-body orbitals and other shared properties to represent the trial wave function and many-body Hamiltonian can be shared among threads, which reduces the memory footprint of a large-scale problem. * Cache optimized: the data associated with an active Walker are in cache during the compute-intensive drift-diffusion process and the operations on an Walker are optimized for cache reuse. Thread-local objects are used to ensure the data affinity to a thread. * Load balanced: Walkers in an ensemble are evenly distributed among threads and MPI tasks. The two-level parallelism reduces the population imbalance among MPI tasks and reduces the number of point-to-point communications of large messages (serialized objects) for the Walker exchange. * Communication optimized: the communication overhead, especially for the collective operations necessary to determine ET and measure the properties of an ensemble, is significantly lowered by using less MPI tasks. The multiple forms of parallelism afforded by QMC algorithms make them ideal candidates for acceleration in the many-core paradigm. We presented the results of our effort to port the QMCPACK simulation code to the NVIDIA 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 hydrogen on Ti(1,2)ethylene-nH2 using Diffusion Monte Carlo. This work has been started and is o

David Ceperley

2011-03-02

312

Monte Carlo role in radiobiological modelling of radiotherapy outcomes.

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy. PMID:22571871

El Naqa, Issam; Pater, Piotr; Seuntjens, Jan

2012-06-01

313

Prediction of Protein-DNA binding by Monte Carlo method

NASA Astrophysics Data System (ADS)

We present an analysis and prediction of protein-DNA binding specificity based on the hydrogen bonding between DNA, protein, and auxillary clusters of water molecules. Zif268, glucocorticoid receptor, ?-repressor mutant, HIN-recombinase, and tramtrack protein-DNA complexes are studied. Hydrogen bonds are approximated by the Lennard-Jones potential with a cutoff distance between the hydrogen and the acceptor atoms set to 3.2 Ĺand an angular component based on a dipole-dipole interaction. We use a three-stage docking algorithm: geometric hashing that matches pairs of hydrogen bonding sites; (2) least-squares minimization of pairwise distances to filter out insignificant matches; and (3) Monte Carlo stochastic search to minimize the energy of the system. More information can be obtained from our first paper on this subject [Y.Deng et all, J.Computational Chemistry (1995)]. Results show that the biologically correct base pair is selected preferentially when there are two or more strong hydrogen bonds (with LJ potential lower than -0.20) that bind it to the protein. Predicted sequences are less stable in the case of weaker bonding sites. In general the inclusion of water bridges does increase the number of base pairs for which correct specificity is predicted.

Deng, Yuefan; Eisenberg, Moises; Korobka, Alex

1997-08-01

314

Advances in quantum Monte Carlo for quantum critical systems

NASA Astrophysics Data System (ADS)

During the past few years, there has been significant progress in efficient quantum Monte Carlo methods for certain classes of spin systems and other lattice many-body problems. Cluster updates have been developed that speed up the sampling by several orders of magnitude, and schemes to avoid the systematic errors of the traditionally used Trotter decomposition have been deviced. Thanks to these developments, quantum critical phenomena (for systems where there are no sign problems) can now be investigated to a level of accuracy approaching classical simulation studies. I will discuss an approach to quantum simulations which is particularly efficient for (unfrustrated) S=1/2 Heisenberg models; the stochastic series expansion (SSE) method incorporating a cluster update for sampling the power series expansion of exp(-? H) to all contributing orders [A. W. Sandvik, Phys. Rev. B 59 R14157 (1999)]. I will also discuss high-precision calculations using the SSE algorithm for the Heisenberg antiferromagnet on a bilayer. This model can be tuned through a quantum critical point by varying the ratio of the inter-plane (J_?) to in-plane interaction (J), and has been very useful for testing predictions for quantum critical behavior in two-dimensional antiferromagnets. I will discuss finite-size scaling of ground state data, as well as the finite-temperature quantum critical behavior.

Sandvik, Anders

2000-03-01

315

Monte Carlo role in radiobiological modelling of radiotherapy outcomes

NASA Astrophysics Data System (ADS)

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.

El Naqa, Issam; Pater, Piotr; Seuntjens, Jan

2012-06-01

316

Radiation transport modeling methods used in the radiation detection community fall into one of two broad categories: stochastic (Monte Carlo) and deterministic. Monte Carlo methods are typically the tool of choice for simulating gamma-ray spectrometers operating in homeland and national security settings (e.g. portal monitoring of vehicles or isotope identification using handheld devices), but deterministic codes that discretize the linear Boltzmann transport equation in space, angle, and energy offer potential advantages in computational efficiency for many complex radiation detection problems. This paper describes the development of a scenario simulation framework based on deterministic algorithms. Key challenges include: formulating methods to automatically define an energy group structure that can support modeling of gamma-ray spectrometers ranging from low to high resolution; combining deterministic transport algorithms (e.g. ray-tracing and discrete ordinates) to mitigate ray effects for a wide range of problem types; and developing efficient and accurate methods to calculate gamma-ray spectrometer response functions from the deterministic angular flux solutions. The software framework aimed at addressing these challenges is described and results from test problems that compare coupled deterministic-Monte Carlo methods and purely Monte Carlo approaches are provided.

Smith, Leon E.; Gesh, Christopher J.; Pagh, Richard T.; Miller, Erin A.; Shaver, Mark W.; Ashbaker, Eric D.; Batdorf, Michael T.; Ellis, J. E.; Kaye, William R.; McConn, Ronald J.; Meriwether, George H.; Ressler, Jennifer J.; Valsan, Andrei B.; Wareing, Todd A.

2008-10-31

317

Electron energy loss modelling in small volumes: A Monte Carlo study

NASA Astrophysics Data System (ADS)

In thin target and sub-volumes, electronic energy losses in single collisions vary considerably for individual charged particles. These fluctuations resulting from the stochastic nature of the interactions can be described through a simulation with Monte Carlo calculations. Models used in the present simulations to describe the electron scattering processes are derived from quantum mechanics. The resulting cross sections for energies up to 200 keV are shown for both processes, i.e. elastic and inelastic interactions. Influence of the Monte Carlo strategy adopted to calculate energy loss spectra (straggling functions) is discussed. Straggling functions calculated from the general purpose Monte Carlo code Penelope and the convolution method of Bichsel are included for comparisons. The results are new. In fact, disagreements have been found in the calculated energy spectra when using different strategies. These deviations are explained in the present study by investigating the thickness dependence on the electron energy. As a central result, energy deposition in silicon detectors can be described accurately when event by event Monte Carlo strategy is used.

Chaoui, Zine-El-Abidine

2008-12-01

318

Finding organic vapors - a Monte Carlo approach

NASA Astrophysics Data System (ADS)

Aerosols have an important role in regulating the climate both directly by absorbing and scattering solar radiation, as well as indirectly by acting as cloud condensation nuclei. While it is known that their net effect on radiative forcing is negative, several key aspects remain mysterious. There exist plenty of known primary sources of particles due to both natural and man-made origin - for example desert dust, volcanic activity and tire debris. On the other hand, it has been shown that the formation of secondary particles, by nucleation from precursor vapors, is a frequent, global phenomenon. However, the very earliest steps in new particle formation - nucleation and early growth by condensation - have many big question marks on them. While several studies have indicated the importance of a sufficient concentration of sulphuric acid vapor for the process, it has also been noted that this is usually not enough. Heads have therefore turned to organic vapors, which in their multitude could explain various observed characteristics of new particle formation. But alas, the vast number of organic compounds, their complex chemistry and properties that make them difficult to measure, have complicated the quantifying task. Nevertheless, evidence of organic contribution in particles of all size classes has been found. In particular, a significant organic constituent in the very finest particles suggests the presence of a high concentration of very low-volatile organic vapors. In this study, new particle formation in the boreal forest environment of Hyytiälä, Finland, is investigated in a process model. Our goal is to quantify the concentration, to find the diurnal profile and to get hints of the identity of some organic vapors taking part in new particle formation. Previous studies on the subject have relied on data analysis of the growth rate of the observed particles. However, due to the coarse nature of the methods used to calculate growth rates, this approach has its drawbacks in accuracy, the inability to find diurnal variation and the lack of size resolution. Here, we aim to shed some light onto the problem by applying an ad hoc Monte Carlo algorithm to a well established aerosol dynamical model, the University of Helsinki Multicomponent Aerosol model (UHMA). By performing a side-by-side comparison with measurement data within the algorithm, this approach has the significant advantage of decreasing the amount of manual labor. But more importantly, by basing the comparison on particle number size distribution data - a quantity that can be quite reliably measured - the accuracy of the results is good.

Vuollekoski, Henri; Boy, Michael; Kerminen, Veli-Matti; Kulmala, Markku

2010-05-01

319

NASA Astrophysics Data System (ADS)

We describe a subspace Monte Carlo (SSMC) technique that reduces the burden of calibration-constrained Monte Carlo when undertaken with highly parameterized models. When Monte Carlo methods are used to evaluate the uncertainty in model outputs, ensuring that parameter realizations reproduce the calibration data requires many model runs to condition each realization. In the new SSMC approach, the model is first calibrated using a subspace regularization method, ideally the hybrid Tikhonov-TSVD "superparameter" approach described by Tonkin and Doherty (2005). Sensitivities calculated with the calibrated model are used to define the calibration null-space, which is spanned by parameter combinations that have no effect on simulated equivalents to available observations. Next, a stochastic parameter generator is used to produce parameter realizations, and for each a difference is formed between the stochastic parameters and the calibrated parameters. This difference is projected onto the calibration null-space and added to the calibrated parameters. If the model is no longer calibrated, parameter combinations that span the calibration solution space are reestimated while retaining the null-space projected parameter differences as additive values. The recalibration can often be undertaken using existing sensitivities, so that conditioning requires only a small number of model runs. Using synthetic and real-world model applications we demonstrate that the SSMC approach is general (it is not limited to any particular model or any particular parameterization scheme) and that it can rapidly produce a large number of conditioned parameter sets.

Tonkin, Matthew; Doherty, John

2009-12-01

320

Evaluation of expectation values in full configuration interaction quantum Monte Carlo

NASA Astrophysics Data System (ADS)

The full configuration interaction quantum Monte Carlo (FCIQMC) method[1-3] provides access to the exact ground state energy. However, like diffusion Monte Carlo, it is hard to precisely calculate expectation values of operators which do not commute with the Hamiltonian due to the stochastic representation of the wavefunction. Following related work on diffusion Monte Carlo[4], we have formulated an approach to stochastically sample additional operators in FCIQMC by using the Hellmann-Feynman theorem and sampling pumped equations of motion coupled to the standard equation of motion used to evolve the wavefunction. Our approach requires only minor modifications to existing FCIQMC programs and can be used to evaluate expectation values of arbitrary operators. We will present example calculations on the Hubbard model and molecular systems. [1pt] [1] G.H. Booth, A.J.W. Thom, A. Alavi, J. Chem. Phys. 131, 054106 (2009). [2] D. Cleland, G.H. Booth, A. Alavi, J. Chem. Phys. 132, 041103 (2010). [3] J.S. Spencer, N.S. Blunt, W.M.C. Foulkes, J. Chem. Phys. 136, 054110 (2012). [4] R. Gaudoin, J.M. Pitarke, Phys. Rev. Lett. 99, 126406 (2007).

Spencer, J. S.; Foulkes, W. M. C.

2013-03-01

321

REVIEW: Fifty years of Monte Carlo simulations for medical physics

NASA Astrophysics Data System (ADS)

Monte Carlo techniques have become ubiquitous in medical physics over the last 50 years with a doubling of papers on the subject every 5 years between the first PMB paper in 1967 and 2000 when the numbers levelled off. While recognizing the many other roles that Monte Carlo techniques have played in medical physics, this review emphasizes techniques for electron-photon transport simulations. The broad range of codes available is mentioned but there is special emphasis on the EGS4/EGSnrc code system which the author has helped develop for 25 years. The importance of the 1987 Erice Summer School on Monte Carlo techniques is highlighted. As an illustrative example of the role Monte Carlo techniques have played, the history of the correction for wall attenuation and scatter in an ion chamber is presented as it demonstrates the interplay between a specific problem and the development of tools to solve the problem which in turn leads to applications in other areas. This paper is dedicated to W Ralph Nelson and to the memory of Martin J Berger, two men who have left indelible marks on the field of Monte Carlo simulation of electron-photon transport.

Rogers, D. W. O.

2006-07-01

322

A new method to assess Monte Carlo convergence

The central limit theorem can be applied to a Monte Carlo solution if the following two requirements are satisfied: (1) the random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these are satisfied, a confidence interval based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the type of Monte Carlo tally being used. The Monte Carlo practitioner has only a limited number of marginally quantifiable methods that use sampled values to assess the fulfillment of the second requirement; e.g., statistical error reduction proportional to 1{radical}N with error magnitude guidelines. No consideration is given to what has not yet been sampled. A new method is presented here to assess the convergence of Monte Carlo solutions by analyzing the shape of the empirical probability density function (PDF) of history scores, f(x), where the random variable x is the score from one particle history and {integral}{sub {minus}{infinity}}{sup {infinity}} f(x) dx = 1. Since f(x) is seldom known explicitly, Monte Carlo particle random walks sample f(x) implicitly. Unless there is a largest possible history score, the empirical f(x) must eventually decrease more steeply than l/x{sup 3} for the second moment ({integral}{sub {minus}{infinity}}{sup {infinity}} x{sup 2}f(x) dx) to exist.

Forster, R.A.; Booth, T.E.; Pederson, S.P.

1993-05-01

323

NASA Astrophysics Data System (ADS)

Variational wave functions used in the variational Monte Carlo (VMC) method are extensively improved to overcome the biases coming from the assumed variational form of the wave functions. We construct a highly generalized variational form by introducing a large number of variational parameters to the Gutzwiller-Jastrow factor as well as to the one-body part. Moreover, the projection operator to restore the symmetry of the wave function is introduced. These improvements enable to treat fluctuations with long-ranged as well as short-ranged correlations. A highly generalized wave function is implemented by the Pfaffians introduced by Bouchaud et al., together with the stochastic reconfiguration method introduced by Sorella for the parameter optimization. Our framework offers much higher accuracy for strongly correlated electron systems than the conventional variational Monte Carlo methods.

Tahara, Daisuke; Imada, Masatoshi

2008-11-01

324

Order-N cluster Monte Carlo method for spin systems with long-range interactions

An efficient O(N) cluster Monte Carlo method for Ising models with long-range interactions is presented. Our novel algorithm does not introduce any cutoff for interaction range and thus it strictly fulfills the detailed balance. The realized stochastic dynamics is equivalent to that of the conventional Swendsen-Wang algorithm, which requires O(N{sup 2}) operations per Monte Carlo sweep if applied to long-range interacting models. In addition, it is shown that the total energy and the specific heat can also be measured in O(N) time. We demonstrate the efficiency of our algorithm over the conventional method and the O(NlogN) algorithm by Luijten and Bloete. We also apply our algorithm to the classical and quantum Ising chains with inverse-square ferromagnetic interactions, and confirm in a high accuracy that a Kosterlitz-Thouless phase transition, associated with a universal jump in the magnetization, occurs in both cases.

Fukui, Kouki [Department of Applied Physics, University of Tokyo, 7-3-1 Hongo, Tokyo 113-8656 (Japan); Todo, Synge [Department of Applied Physics, University of Tokyo, 7-3-1 Hongo, Tokyo 113-8656 (Japan); CREST, Japan Science and Technology Agency, Kawaguchi 332-0012 (Japan)], E-mail: wistaria@ap.t.u-tokyo.ac.jp

2009-04-20

325

Quantum Monte Carlo calculation of entanglement Rényi entropies for generic quantum systems

NASA Astrophysics Data System (ADS)

We present a general scheme for the calculation of the Rényi entropy of a subsystem in quantum many-body models that can be efficiently simulated via quantum Monte Carlo. When the simulation is performed at very low temperature, the above approach delivers the entanglement Rényi entropy of the subsystem, and it allows us to explore the crossover to the thermal Rényi entropy as the temperature is increased. We implement this scheme explicitly within the stochastic series expansion as well as within path-integral Monte Carlo, and apply it to quantum spin and quantum rotor models. In the case of quantum spins, we show that relevant models in two dimensions with reduced symmetry (XX model or hard-core bosons, transverse-field Ising model at the quantum critical point) exhibit an area law for the scaling of the entanglement entropy.

Humeniuk, Stephan; Roscilde, Tommaso

2012-12-01

326

Monte Carlo Simulations for Mine Detection

During January, 1998, collaboration between LLNL, UCI and Exdet, Ltd. arranged for the testing and evaluation of a Russian developed antitank mine detection system at the Buried Objects Detection Facility (BODF) located at the Nevada Test Site. BODF is a secured 30-acre facility with approximately 300 live antitank mines that were buried in 1993 and 1994. The burial depths range from a few cm to 15 cm and the various metal- and plastic-case antitank mines each contain 6-12 kg of high explosive. Contractors who have tested their mine detection equipment at BODF include: SAIC, SRI, ERIM, MIT/Lincoln Laboratory and Loral Defense Systems. In addition LLNL researchers have used BODF to test antitank mine detection systems based on: dual-band infrared imaging, hyper-spectral imaging, synthetic aperture impulse radar and micro-impulse radar. In a blind test the Russian operated system obtained the highest score of any technology tested to date at BODF. The system is based on combining information from two separate sensors; one to detect anomalous concentrations of hydrogen and the other to detect if such anomalies also have the correct nitrogen to carbon ratio for high explosives. The detection sensitivity is set by the geometry and type of neutron moderator and filters surrounding the neutron source and detectors. Detection of hydrogen anomalies is a rapid process based on neutron scattering. The handheld instrument on the end of a wand could scan a large area at a rate of 4-5 square meters per minute. Once the hydrogen anomalies were located a second sensor was used to measure the thermal neutron excited gamma-ray spectrum at each hydrogen anomaly to determine whether that location in addition contained high concentrations of nitrogen. The second process was slower, taking up to 5 minutes for each location. The information from both sensors were then examined by the operator and a declaration was made as to whether or not the anomaly was a buried antitank mine. Although the system worked extremely well on all classes of anti-tank mines, the Russian hardware components were inferior to those that are commercially available in the United States, i.e. the NaI(Tl) crystals had significantly higher background levels and poorer resolution than their U.S. counterparts, the electronics appeared to be decades old and the photomultiplier tubes were noisy and lacked gain stabilization circuitry. During the evaluation of this technology, the question that came to mind was: could state-of-the-art sensors and electronics and improved software algorithms lead to a neutron based system that could reliably detect much smaller buried mines; namely antipersonnel mines containing 30-40 grams of high explosive? Our goal in this study was to conduct Monte Carlo simulations to gain better understanding of both phases of the mine detection system and to develop an understanding for the system's overall capabilities and limitations. In addition, we examined possible extensions of this technology to see whether or not state-of-the-art improvements could lead to a reliable anti-personnel mine detection system.

Toor, A.; Marchetti, A.A.

2000-03-14

327

Monte Carlo Simulations of Ly? Line Profiles

NASA Astrophysics Data System (ADS)

In this paper, a code of simulations of Ly? line profiles via Monte Carlo methods is introduced. This code is developed based on the ideas of Anne Verhamme, Daniel Schaerer and Antonella Maselli, combining with the methods of Matthew Hansen and S. Peng Oh. The simulation of one Ly? photon starts when the photon is created and ends when the photon escapes from the medium or is absorbed by the dust. The Ly? photon is created at the isotropic source, which can be monochromatic or non-monochromatic. After being created, the photon walks in the medium. It moves from one position, where it interacts with the medium, to the next, until it moves out of the medium or absorbed by the dust. The direction and the frequency of the photon will be changed after it interacts with the H atom. The photon has probability to interact with the dust, which may absorb or scatter the photon. When a simulation of one photon is completed, the photon will be recorded and the simulation of another photon begins. After all of the photons are simulated, the line profile will be calculated. In 2006, Verhamme, Schaerer and Maselli developed a general code for 3D Ly? radiation transfer in galaxies. As they did, in this paper, three kinds of model are used. The first one is slab, which is made by three infinite parallel planes. The middle one of the three planes is the source, and the other two are the edges, between which is the medium. Although this model is simple, many kinds of line profiles, such as symmetric double peaks, redshifted/blueshifted single peak and damped profile, can be obtained by changing the conditions of the source and the medium. The profile of the static dust free slab is similar with the analytic solutions of Neufeld (1990). The second model is halo, which is a ball of medium. The source can be in the center of the ball or be spread in the medium. Symmetric double peaks, redshifted/blueshifted single peak and P-Cygni profile can be obtained by changing the conditions. The third one is the expanding shell, a shell of medium. If the source is monochromatic, the profile is made of many peaks which are redshifted by nVexp. The height of each peak and the distance between two neighboring peaks are determined by the conditions of the shell. This is different with the result of Verhamme. However, the two results both have a peak which is redshifted by 2Vexp. Different kinds of distribution of the velocity and mass of the medium are discussed in this paper. However, no new profile is discovered. The similar profiles can be obtained by changing the conditions of the slab, halo or shell.

Wang, Y.

2009-04-01

328

Photon beam description in PEREGRINE for Monte Carlo dose calculations

Goal of PEREGRINE is to provide capability for accurate, fast Monte Carlo calculation of radiation therapy dose distributions for routine clinical use and for research into efficacy of improved dose calculation. An accurate, efficient method of describing and sampling radiation sources is needed, and a simple, flexible solution is provided. The teletherapy source package for PEREGRINE, coupled with state-of-the-art Monte Carlo simulations of treatment heads, makes it possible to describe any teletherapy photon beam to the precision needed for highly accurate Monte Carlo dose calculations in complex clinical configurations that use standard patient modifiers such as collimator jaws, wedges, blocks, and/or multi-leaf collimators. Generic beam descriptions for a class of treatment machines can readily be adjusted to yield dose calculation to match specific clinical sites.

Cox, L. J., LLNL

1997-03-04

329

Vectorizing and macrotasking Monte Carlo neutral particle algorithms

Monte Carlo algorithms for computing neutral particle transport in plasmas have been vectorized and macrotasked. The techniques used are directly applicable to Monte Carlo calculations of neutron and photon transport, and Monte Carlo integration schemes in general. A highly vectorized code was achieved by calculating test flight trajectories in loops over arrays of flight data, isolating the conditional branches to as few a number of loops as possible. A number of solutions are discussed to the problem of gaps appearing in the arrays due to completed flights, which impede vectorization. A simple and effective implementation of macrotasking is achieved by dividing the calculation of the test flight profile among several processors. A tree of random numbers is used to ensure reproducible results. The additional memory required for each task may preclude using a larger number of tasks. In future machines, the limit of macrotasking may be possible, with each test flight, and split test flight, being a separate task.

Heifetz, D.B.

1987-04-01

330

Magnitude of bias in Monte Carlo eigenvalue calculations

Most Monte Carlo eigenvalue calculations are based on power iteration methods, like those used in analytical algorithms. But if N/sub H/, the number of histories in each generation is fixed, then such Monte Carlo calculations will be biased. Various arguments lead to the conclusion that eigenvalue and shape biases are both proportional to 1/N/sub H/, but little more is known about their magnitudes. Numerical experiments on simple matrices suggest that the biases are small, but information more relevant to real reactor calculations is very sparse. In fact to determine the bias in real reactor calculations is quite expensive. It seems worthwhile, therefore, to try to understand the Monte Carlo biases in systems more realistic than arbitrary matrices, but simpler than real reactors. For this reason biases in simple one-group model problems have been computed.

Bowsher, H.; Gelbard, E.M.; Gemmel, P.; Pack, G.

1983-01-01

331

Two proposed convergence criteria for Monte Carlo solutions

The central limit theorem (CLT) can be applied to a Monte Carlo solution if two requirements are satisfied: (1) The random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these two conditions are satisfied, a confidence interval (CI) based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the Monte Carlo tally being used. The Monte Carlo practitioner has a limited number of marginal methods to assess the fulfillment of the second requirement, such as statistical error reduction proportional to 1/[radical]N with error magnitude guidelines. Two proposed methods are discussed in this paper to assist in deciding if N is large enough: estimating the relative variance of the variance (VOV) and examining the empirical history score probability density function (pdf).

Forster, R.A.; Pederson, S.P.; Booth, T.E. (Los Alamos National Lab., NM (United States))

1992-01-01

332

A Multivariate Time Series Method for Monte Carlo Reactor Analysis

A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor.

Taro Ueki

2008-08-14

333

Implementation of Monte Carlo Simulations for the Gamma Knife System

NASA Astrophysics Data System (ADS)

Currently the Gamma Knife system is accompanied with a treatment planning system, Leksell GammaPlan (LGP) which is a standard, computer-based treatment planning system for Gamma Knife radiosurgery. In LGP, the dose calculation algorithm does not consider the scatter dose contributions and the inhomogeneity effect due to the skull and air cavities. To improve the dose calculation accuracy, Monte Carlo simulations have been implemented for the Gamma Knife planning system. In this work, the 201 Cobalt-60 sources in the Gamma Knife unit are considered to have the same activity. Each Cobalt-60 source is contained in a cylindric stainless steel capsule. The particle phase space information is stored in four beam data files, which are collected in the inner sides of the 4 treatment helmets, after the Cobalt beam passes through the stationary and helmet collimators. Patient geometries are rebuilt from patient CT data. Twenty two Patients are included in the Monte Carlo simulation for this study. The dose is calculated using Monte Carlo in both homogenous and inhomogeneous geometries with identical beam parameters. To investigate the attenuation effect of the skull bone the dose in a 16cm diameter spherical QA phantom is measured with and without a 1.5mm Lead-covering and also simulated using Monte Carlo. The dose ratios with and without the 1.5mm Lead-covering are 89.8% based on measurements and 89.2% according to Monte Carlo for a 18mm-collimator Helmet. For patient geometries, the Monte Carlo results show that although the relative isodose lines remain almost the same with and without inhomogeneity corrections, the difference in the absolute dose is clinically significant. The average inhomogeneity correction is (3.9 ą 0.90) % for the 22 patients investigated. These results suggest that the inhomogeneity effect should be considered in the dose calculation for Gamma Knife treatment planning.

Xiong, W.; Huang, D.; Lee, L.; Feng, J.; Morris, K.; Calugaru, E.; Burman, C.; Li, J.; Ma, C.-M.

2007-06-01

334

Bold Diagrammatic Monte Carlo for Fermionic and Fermionized Systems

NASA Astrophysics Data System (ADS)

In three different fermionic cases---repulsive Hubbard model, resonant fermions, and fermionized spins-1/2 (on triangular lattice)---we observe the phenomenon of sign blessing: Feynman diagrammatic series features finite convergence radius despite factorial growth of the number of diagrams with diagram order. Bold diagrammatic Monte Carlo technique allows us to sample millions of skeleton Feynman diagrams. With the universal fermionization trick we can fermionize essentially any (bosonic, spin, mixed, etc.) lattice system. The combination of fermionization and Bold diagrammatic Monte Carlo yields a universal first-principle approach to strongly correlated lattice systems, provided the sign blessing is a generic fermionic phenomenon.

Svistunov, Boris

2013-03-01

335

Iterative Monte Carlo formulation of real-time correlation functions.

We present an iterative Monte Carlo path integral methodology for evaluating thermally averaged real-time correlation functions. Standard path integral Monte Carlo methods are used to sample paths along the imaginary time contour. Propagation of the density matrix is performed iteratively on a grid composed of the end points of the sampled paths. Minimally oscillatory propagators are constructed using energy filtering techniques. A single propagation yields the values of the correlation function at all intermediate time points. Model calculations suggest that the method yields accurate results over several oscillation periods and the statistical error grows slowly with increasing propagation time. PMID:21033771

Baltaretu, Cristian O; Makri, Nancy

2010-10-28

336

Modelling cerebral blood oxygenation using Monte Carlo XYZ-PA

NASA Astrophysics Data System (ADS)

Continuous monitoring of cerebral blood oxygenation is critically important for the management of many lifethreatening conditions. Non-invasive monitoring of cerebral blood oxygenation with a photoacoustic technique offers advantages over current invasive and non-invasive methods. We introduce a Monte Carlo XYZ-PA to model the energy deposition in 3D and the time-resolved pressures and velocity potential based on the energy absorbed by the biological tissue. This paper outlines the benefits of using Monte Carlo XYZ-PA for optimization of photoacoustic measurement and imaging. To the best of our knowledge this is the first fully integrated tool for photoacoustic modelling.

Zam, Azhar; Jacques, Steven L.; Alexandrov, Sergey; Li, Youzhi; Leahy, Martin J.

2013-02-01

337

Anomalous Behavior of Monte Carlo Uncertainties near Reflecting Boundaries

NASA Astrophysics Data System (ADS)

It has been observed that statistical uncertainties on tallies in Monte Carlo iterated-fission-source calculations tend to be larger for tally regions near reflective boundaries than for similar tally regions far from such boundaries. Using a theoretical methodology developed by Brissenden and Garlick, the cause of this behavior was found to be a greater correlation between fission generations in the regions near the reflective boundaries. The theory was found to be in qualitative agreement with Monte Carlo results for a simple test problem. It is also shown that applying the coarse mesh finite difference method eliminates the anomalous behavior.

Sutton, Thomas M.

2014-06-01

338

Overview of the MCU Monte Carlo Software Package

NASA Astrophysics Data System (ADS)

MCU (Monte Carlo Universal) is a project on development and practical use of a universal computer code for simulation of particle transport (neutrons, photons, electrons, positrons) in three-dimensional systems by means of the Monte Carlo method. This paper provides the information on the current state of the project. The developed libraries of constants are briefly described, and the potentialities of the MCU-5 package modules and the executable codes compiled from them are characterized. Examples of important problems of reactor physics solved with the code are presented.

Kalugin, M. A.; Oleynik, D. S.; Shkarovsky, D. A.

2014-06-01

339

Precise Monte Carlo simulation of single-photon detectors

NASA Astrophysics Data System (ADS)

We demonstrate the importance and utility of Monte Carlo simulation of single-photon detectors. Devising an optimal simulation is strongly influenced by the particular application because of the complexity of modern, avalanche-diode based single-photon detectors. Using a simple yet very demanding example of random number generation via detection of Poissonian photons exiting a beam splitter, we present a Monte Carlo simulation that faithfully reproduces the serial autocorrelation of random bits as a function of detection frequency over four orders of magnitude of the incident photon flux. We conjecture that this simulation approach can be easily modified for use in many other applications.

Stip?evi?, Mario; Gauthier, Daniel J.

2013-05-01

340

Markov chain Monte Carlo linkage analysis of complex quantitative phenotypes.

We report a Markov chain Monte Carlo analysis of the five simulated quantitative traits in Genetic Analysis Workshop 12 using the Loki software. Our objectives were to determine the efficacy of the Markov chain Monte Carlo method and to test a new scoring technique. Our initial blind analysis, on replicate 42 (the "best replicate") successfully detected four out of the five disease loci and found no false positives. A power analysis shows that the software could usually detect 4 of the 10 trait/gene combinations at an empirical point-wise p-value of 1.5 x 10(-4). PMID:11793758

Hinrichs, A; Reich, T

2001-01-01

341

Monte Carlo implementation of density-functional theory

NASA Astrophysics Data System (ADS)

We propose a conceptually easy and relatively straigthforward numerical method for calculating the ground-state properties of many-particle systems based on the Hohenberg-Kohn theorems. In this density-functional Monte Carlo method a direct numerical minimization of the energy functional is performed by a Monte Carlo algorithm in which the density is simulated by a distribution of Bernoulli walkers. The total number of particles is conserved by construction, unlike for other implementations of density-functional theory. The feasibility of the method is illustrated by applying it to a nanoshell.

Putteneers, K.; Brosens, F.

2012-08-01

342

Monte Carlo calculation of monitor unit for electron arc therapy

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 for electron arc therapy. Since Monte Carlo simulations can generate a precalculated database of ROF, SSD offset, and DF for the MU calculation, with a reduction in human effort and linac beam-on time, it is recommended that Monte Carlo simulations be partially or completely integrated into the commissioning of electron arc therapy.

Chow, James C. L.; Jiang Runqing [Radiation Medicine Program, Princess Margaret Hospital, University Health Network, Toronto, Ontario M5G 2M9 (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5G 2M9 (Canada) and Department of Physics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada); Department of Medical Physics, Grand River Regional Cancer Center, Kitchener, Ontario N2G 1G3 (Canada)

2010-04-15

343

Monte Carlo Methods for Neutrino Transport in Core Collapse Supernovae

NASA Astrophysics Data System (ADS)

Core-collapse supernovae are among the most powerful events in Nature. Despite decades of effort, the details of the explosion mechanism remain uncertain. Recent studies indicate that the neutrino-driven explosion mechanism is a fundamentally three-dimensional phenomenon, implying that it is necessary to model such an event in three dimensions using large parallel supercomputers. Monte Carlo methods for radiation transport have been known for their simplicity and ease of parallel implementation. In this talk, I will present results of our explorations of Monte Carlo methods for neutrino transport in core-collapse supernovae.

Abdikamalov, Ernazar; Burrows, Adam; Loeffler, Frank; Ott, Christian D.; Schnetter, E.; Diener, Peter

2011-04-01

344

Collective translational and rotational Monte Carlo moves for attractive particles.

Virtual move Monte Carlo is a Monte Carlo (MC) cluster algorithm forming clusters via local energy gradients and approximating the collective kinetic or dynamic motion of attractive colloidal particles. We carefully describe, analyze, and test the algorithm. To formally validate the algorithm through highlighting its symmetries, we present alternative and compact ways of selecting and accepting clusters which illustrate the formal use of abstract concepts in the design of biased MC techniques: the superdetailed balance and the early rejection scheme. A brief and comprehensive summary of the algorithms is presented, which makes them accessible without needing to understand the details of the derivation. PMID:24730967

R?i?ka, St?pán; Allen, Michael P

2014-03-01

345

Multiscale Kinetic Monte-Carlo for Simulating Epitaxial Growth

We present a fast Monte-Carlo algorithm for simulating epitaxial surface\\u000agrowth, based on the continuous-time Monte-Carlo algorithm of Bortz, Kalos and\\u000aLebowitz. When simulating realistic growth regimes, much computational time is\\u000aconsumed by the relatively fast dynamics of the adatoms. Continuum and\\u000acontinuum-discrete hybrid methods have been developed to approach this issue;\\u000ahowever in many situations, the density of adatoms

Jason P. DeVita; Leonard M. Sander; Peter Smereka

2005-01-01

346

Optix: A Monte Carlo scintillation light transport code

NASA Astrophysics Data System (ADS)

The paper reports on the capabilities of Monte Carlo scintillation light transport code Optix, which is an extended version of previously introduced code Optics. Optix provides the user a variety of both numerical and graphical outputs with a very simple and user-friendly input structure. A benchmarking strategy has been adopted based on the comparison with experimental results, semi-analytical solutions, and other Monte Carlo simulation codes to verify various aspects of the developed code. Besides, some extensive comparisons have been made against the tracking abilities of general-purpose MCNPX and FLUKA codes. The presented benchmark results for the Optix code exhibit promising agreements.

Safari, M. J.; Afarideh, H.; Ghal-Eh, N.; Davani, F. Abbasi

2014-02-01

347

Directed loop algorithm for quantum Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Loop algorithms [1] have dramatically improved the performance of world-line quantum Monte Carlo simulations of a wide range of models. However, the method is restricted to certain regions of parameter space. In particular, the presence of external fields (chemical potential or magnetic field) can typically not be taken into account in the loop construction. Two other methods were developed that do not have this restriction; the worm algorithm [2] for world-lines in continuous imaginary time and the operator-loop algorithm for stochastic series expansion [3]. Here there is a greater freedom in the loop-building process (the loops can be self-intersecting and also, in some cases, back-tracking) and all interactions can therefore be taken into account. Recently a framework was developed [4] within which these more general algorithms emerge as natural generalizations of the original loop algorithm. In this "directed loop" approach, the detailed balance condition leads to a set of coupled equations for the probabilities of the various loop-building steps. The directed loop equations often have an infinite number of solutions, and the probabilities should hence be optimized for the most efficient simulations. I will discuss an algorithm for the S=1/2 XXZ model [4], where the optimization criterion is the minimization of the back-tracking probability. [1] H. G. Evertz, G. Lana, and M. Marcu, Phys. Rev. Lett. 70, 875 (1993). [2] N. V. Prokofev, B. V. Svistunov, and I. S. Tupitsyn, Phys. Lett A238, 253 (1998). [3] A. W. Sandvik, Phys. Rev. B59, R14157 (1999). [4] O.Suljuasen and A. W. Sandvik, Phys. Rev. E66, 046701 (2002).

Sandvik, Anders

2003-03-01

348

ITER Neutronics Modeling Using Hybrid Monte Carlo/Deterministic and CAD-Based Monte Carlo Methods

The immense size and complex geometry of the ITER experimental fusion reactor require the development of special techniques that can accurately and efficiently perform neutronics simulations with minimal human effort. This paper shows the effect of the hybrid Monte Carlo (MC)/deterministic techniques - Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) - in enhancing the efficiency of the neutronics modeling of ITER and demonstrates the applicability of coupling these methods with computer-aided-design-based MC. Three quantities were calculated in this analysis: the total nuclear heating in the inboard leg of the toroidal field coils (TFCs), the prompt dose outside the biological shield, and the total neutron and gamma fluxes over a mesh tally covering the entire reactor. The use of FW-CADIS in estimating the nuclear heating in the inboard TFCs resulted in a factor of ~ 275 increase in the MC figure of merit (FOM) compared with analog MC and a factor of ~ 9 compared with the traditional methods of variance reduction. By providing a factor of ~ 21 000 increase in the MC FOM, the radiation dose calculation showed how the CADIS method can be effectively used in the simulation of problems that are practically impossible using analog MC. The total flux calculation demonstrated the ability of FW-CADIS to simultaneously enhance the MC statistical precision throughout the entire ITER geometry. Collectively, these calculations demonstrate the ability of the hybrid techniques to accurately model very challenging shielding problems in reasonable execution times.

Ibrahim, A. [University of Wisconsin; Mosher, Scott W [ORNL; Evans, Thomas M [ORNL; Peplow, Douglas E. [ORNL; Sawan, M. [University of Wisconsin; Wilson, P. [University of Wisconsin; Wagner, John C [ORNL; Heltemes, Thad [University of Wisconsin, Madison

2011-01-01

349

Monte Carlo simulation-based approach to model the size distribution of metastatic tumors.

The size distribution of metastatic tumors and its time evolution are traditionally described by integrodifferential equations and stochastic models. Here we develop a simple Monte Carlo approach in which each event of metastasis is treated as a chance event through random-number generation. We demonstrate the accuracy of this approach on a specific growth and metastasis model by showing that it quantitatively reproduces the size distribution and the total number of tumors as a function of time. The approach also yields statistical distribution of patient-to-patient variations, and has the flexibility to incorporate many real-life complexities. PMID:22400608

Maiti, Esha

2012-01-01

350

Monte Carlo simulation-based approach to model the size distribution of metastatic tumors

NASA Astrophysics Data System (ADS)

The size distribution of metastatic tumors and its time evolution are traditionally described by integrodifferential equations and stochastic models. Here we develop a simple Monte Carlo approach in which each event of metastasis is treated as a chance event through random-number generation. We demonstrate the accuracy of this approach on a specific growth and metastasis model by showing that it quantitatively reproduces the size distribution and the total number of tumors as a function of time. The approach also yields statistical distribution of patient-to-patient variations, and has the flexibility to incorporate many real-life complexities.

Maiti, Esha

2012-01-01

351

SCOUT: A Fast Monte-Carlo Modeling Tool of Scintillation Camera Output

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools.

Hunter, William C. J.; Barrett, Harrison H.; Lewellen, Thomas K.; Miyaoka, Robert S.; Muzi, John P.; Li, Xiaoli; McDougald, Wendy; MacDonald, Lawrence R.

2011-01-01

352

Calculating coherent pair production with Monte Carlo methods

We discuss calculations of the coherent electromagnetic pair production in ultra-relativistic hadron collisions. This type of production, in lowest order, is obtained from three diagrams which contain two virtual photons. We discuss simple Monte Carlo methods for evaluating these classes of diagrams without recourse to involved algebraic reduction schemes. 19 refs., 11 figs.

Bottcher, C.; Strayer, M.R.

1989-01-01

353

Force induced melting of DNA hairpin: A Monte Carlo study

NASA Astrophysics Data System (ADS)

In this paper we present the thermodynamic properties of DNA hairpin studied by using non-Boltzmann Monte Carlo methods. The force-temperature phase diagram and Landau free energy near and at critical temperatures are obtained. From free energy curves it is observed that the transition from closed loop state to open state is of first order.

Kalyan, M. Suman; Murthy, K. P. N.

2013-02-01

354

Monte Carlo Results from a Computer Program for Tailored Testing.

ERIC Educational Resources Information Center

INTERTAIL, the computer program which implements an approach to tailored testing outlined by Cliff (1975), was examined with errorless data in several Monte Carlo studies. Three replications of each cell of a 3 x 3 table with 10, 20 and 40 items and persons were analyzed. Mean rank correlation coefficients between the true order, specified by

Cudeck, Robert A.; And Others

355

Path Integral Monte Carlo Simulation of Hot, Dense Hydrogen

Path integral Monte Carlo simulations have been applied to study the hot, dense hydrogen at Mega-bar pressures corresponding to the density and temperature range of 1 < rs < 14 and 5000 K < T < 1000000 K. We determine the equation of state and study the phase diagram including the molecular, atomic and plasma regime. We discuss the effects

Burkhard Militzer

2001-01-01

356

Pairing Hamiltonian by a path integral Monte Carlo procedure.

National Technical Information Service (NTIS)

A Monte Carlo approach is presented for the treatment of the pairing force in nuclear systems. This method is computationally efficient and very simple to implement. Numerical results are given and compared to an exact calculation and to the predictions o...

N. Cerf O. Martin

1992-01-01

357

Path integral Monte Carlo for dissipative many-body systems

We address the possibility of performing numerical Monte Carlo simulations for the thermodynamics of quantum dissipative systems. Dissipation is considered within the Caldeira-Leggett formulation, which describes the system in the path-integral formalism through the inclusion of an influence action that is bilocal and quadratic in the system's coordinates. At a first sight the usual direct approach of discretizing the path

Luca Capriotti; Alessandro Cuccoli; Andrea Fubini; Valerio Tognetti; Ruggero Vaia

2003-01-01

358

a Path Integral Monte Carlo Method for the Quasielastic Response

We formulate the quasielastic response of a non -relativistic many-body system at zero temperature in terms of ground state density matrix elements and real time path integrals that embody the final state interactions. While the former provide the weight for a conventional Monte Carlo calculation, the latter require a more sophisticated treatment. We argue that the recently developed Stationary Phase

Carlo Carraro

1990-01-01

359

Global Optimization: Quantum Thermal Annealing with Path Integral Monte Carlo

We investigate a new method (QTA-PIMC) for global optimization on complex potential energy surfaces which combines the path integral Monte Carlo method with quantum and thermal annealing. This method is applied to the BLN protein model (Honeycutt, J. D.; Thirumalai, D. Biopolymers 1992, 32, 695). We show that this new approach outperforms simulated (thermal) annealing (SA) and that in fact

Yong-Han Lee; B. J. Berne

2000-01-01

360

Path integral Monte Carlo simulations of hot dense hydrogen

Path integral Monte Carlo (PIMC) simulations are a powerful computational method to study interacting quantum systems at finite temperature. In this work, PIMC has been applied to study the equilibrium properties of hot, dense hydrogen in the temperature and density range of 5000 <= T <= 10 6K and 10--3 <= p <= 2.7gcm --3. We determine the equation of

Burkhard Militzer

2000-01-01

361

Numerical Pricing of Derivative Claims: Path Integral Monte Carlo Approach

We propose a path integral Monte Carlo method for pricing of derivative securities. Metropolisalgorithm is used to sample probability distribution of histories (paths) of the underlying security.The advantage of path integral approach is that complete information about the derivative security,including its parameter sensitivities is obtained in a single simulation. It is also possible to obtainresults for multiple values of parameters

Miloje S. Makivic

1994-01-01

362

On Monte Carlo Methods and Applications in Geoscience

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

Zhan Zhang; J. Blais

2009-01-01

363

Monte Carlo Simulation for Gamma Knife Radiosurgery using the Grid

Gamma Knife radiosurgery is an established technique for the treatment of intracranial lesions and vascular malformations in the brain. In this study, dose distributions in a phantom calculated by GammaPlan have been compared with dose distributions computed by a Monte Carlo code (RAPT) assuming the phantom as a homogenous medium. Comparisons have Considered both single shot plans and treatment plans.

V. Ganesan; R. Mehrem; J. Fenner; L. Walton

2006-01-01

364

Implementation of Monte Carlo Simulations for the Gamma Knife System

Currently the Gamma Knife system is accompanied with a treatment planning system, Leksell GammaPlan (LGP) which is a standard, computer-based treatment planning system for Gamma Knife radiosurgery. In LGP, the dose calculation algorithm does not consider the scatter dose contributions and the inhomogeneity effect due to the skull and air cavities. To improve the dose calculation accuracy, Monte Carlo simulations

W Xiong; D Huang; L Lee; J Feng; K Morris; E Calugaru; C Burman; J Li; C-M Ma

2007-01-01

365

Monte Carlo Planning Technique for Renewable Energy Sources

Distributed power generation provides electric power at a site closer to customers. This paper, formulates the problem of optimal utilization of renewable energy options to meet the peak load demand. A Monte Carlo apportioning technique of solar photovoltaic, co-generation, wind power, and small hydro, which considers specific techno-economic constraints, such as capital cost and generation cost constraints, and carbon dioxide

C. S. Indulkar

2008-01-01

366

CMS Monte Carlo production operations in a distributed computing environment

Monte Carlo production for the CMS experiment is carried out in a distributed computing environment; the goal of producing 30M simulated events per month in the first half of 2007 has been reached. A brief overview of the production operations and statistics is presented.

Mohapatra, A.; Lazaridis, C.; /Wisconsin U., Madison; Hernandez, J.M.; Caballero, J.; /Madrid, CIEMAT; Hof, C.; Kalinin, S.; /Aachen, Tech. Hochsch.; Flossdorf, A.; /DESY; Abbrescia, M.; De Filippis, N.; Donvito, G.; Maggi, G.; /Bari U. /INFN, Bari /INFN, Pisa /Vrije U., Brussels /Brussels U. /Imperial Coll., London /CERN /Princeton U. /Fermilab

2008-01-01

367

A separable shadow Hamiltonian hybrid Monte Carlo method.

Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc). PMID:19894997

Sweet, Christopher R; Hampton, Scott S; Skeel, Robert D; Izaguirre, Jesús A

2009-11-01

368

A separable shadow Hamiltonian hybrid Monte Carlo method

NASA Astrophysics Data System (ADS)

Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).

Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.

2009-11-01

369

Beating the Verlet integrator in Monte Carlo simulations

NASA Astrophysics Data System (ADS)

We propose a new methodology for constructing integrators to simulate Hamiltonian dynamics within Hybrid Monte Carlo and related algorithms. The algorithms based on the new approach are minor modifications of the standard Verlet integrator that nevertheless provide very substantial savings in computational cost.

Blanes, S.; Casas, F.; Sanz-Serna, J. M.

2013-10-01

370

Present Status and Extensions of the Monte Carlo Performance Benchmark

NASA Astrophysics Data System (ADS)

The NEA Monte Carlo Performance benchmark started in 2011 aiming to monitor over the years the abilities to perform a full-size Monte Carlo reactor core calculation with a detailed power production for each fuel pin with axial distribution. This paper gives an overview of the contributed results thus far. It shows that reaching a statistical accuracy of 1 % for most of the small fuel zones requires about 100 billion neutron histories. The efficiency of parallel execution of Monte Carlo codes on a large number of processor cores shows clear limitations for computer clusters with common type computer nodes. However, using true supercomputers the speedup of parallel calculations is increasing up to large numbers of processor cores. More experience is needed from calculations on true supercomputers using large numbers of processors in order to predict if the requested calculations can be done in a short time. As the specifications of the reactor geometry for this benchmark test are well suited for further investigations of full-core Monte Carlo calculations and a need is felt for testing other issues than its computational performance, proposals are presented for extending the benchmark to a suite of benchmark problems for evaluating fission source convergence for a system with a high dominance ratio, for coupling with thermal-hydraulics calculations to evaluate the use of different temperatures and coolant densities and to study the correctness and effectiveness of burnup calculations. Moreover, other contemporary proposals for a full-core calculation with realistic geometry and material composition will be discussed.

Hoogenboom, J. Eduard; Petrovic, Bojan; Martin, William R.

2014-06-01

371

Neutron stimulated emission computed tomography: a Monte Carlo simulation approach

A Monte Carlo simulation has been developed for neutron stimulated emission computed tomography (NSECT) using the GEANT4 toolkit. NSECT is a new approach to biomedical imaging that allows spectral analysis of the elements present within the sample. In NSECT, a beam of high-energy neutrons interrogates a sample and the nuclei in the sample are stimulated to an excited state by

A. C. Sharma; B. P. Harrawood; J. E. Bender; G. D. Tourassi; A. J. Kapadia

2007-01-01

372

Validation maps for bias correction in Monte Carlo denoising

A fundamental prerequisite of computer aided radiotherapy treatment is the accurate estimation of the dose distributions so as to deliver a high homogeneous dose volume to the tumor without causing unnecessary side effects for the patient. The Monte Carlo (MC) method is considered the most effective dose distribution computational technique. However, it is too slow and contaminated with noisy degradations

Joseph O. Deasy; Issam El Naqa; Milos Vicic

2003-01-01

373

Retrospective Monte Carlo dose calculations with limited beam weight information

An important unresolved issue in outcomes analysis for lung complications is the effect of poor or completely lacking heterogeneity corrections in previously archived treatment plans. To estimate this effect, we developed a novel method based on Monte Carlo (MC) dose calculations which can be applied retrospectively to RTOG\\/AAPM-style archived treatment plans (ATP). We applied this method to 218 archived nonsmall

Patricia E. Lindsay; Issam El Naqa; Andrew J. Hope; Milos Vicic; Cui Jing; Jeffrey D. Bradley; Joseph O. Deasy

2007-01-01

374

Optimized Monte Carlo Path Generation using Genetic Algorithms

In this technical report we present a new method for optimizing the generation of paths in Monte Carlo global illumination rendering algorithms. Ray tracing, particle tracing, and bidirectional ray tracing all use random walks to estimate various fluxes in the scene. The probability density functions neces- sary to generate these random walks are optimized using a genetic algorithm, such that

F. Suykens; Y. D. Willems

375

Adaptive Markov chain Monte Carlo for Bayesian Variable Selection

We describe adaptive Markov chain Monte Carlo (MCMC) methods for sampling posterior distributions arising from Bayesian variable selection problems. Point mass mixture priors are commonly used in Bayesian variable selection problems in regres- sion. However, for generalized linear and nonlinear models where the conditional den- sities cannot be obtained directly, the resulting mixture posterior may be difficult to sample using

Chunlin Ji; Scott C. Schmidler

376

Monte Carlo simulation of DNMR spectra of coupled spin systems

A new program MC-DNMR is presented for the simulation of dynamic nuclear magnetic resonance spectra. The algorithm is a Monte Carlo type method based on the extension of single spin vector model to coupled spin systems. This extension is explained in detail and the theory is justified by examples. The main advantage of this program is the significantly smaller sizes

Zsófia Szalay; János Rohonczy

2008-01-01

377

Use of the GATE Monte Carlo package for dosimetry applications

One of the roles for Monte Carlo (MC) simulation studies is in the area of dosimetry. A number of different codes dedicated to dosimetry applications are available and widely used today, such as MCNP, EGSnrc and PTRAN. However, such codes do not easily facilitate the description of complicated 3D sources or emission tomography systems and associated data flow, which may

D. Visvikis; M. Bardies; S. Chiavassa; C. Danford; A. Kirov; F. Lamare; L. Maigne; S. Staelens; R. Taschereau

2006-01-01

378

Markov chain Monte-Carlo orbit computation for binary asteroids

NASA Astrophysics Data System (ADS)

We present a novel orbit comutation method for resolved binary asteroids. The method relays on Markov chain Monte Carlo sampling of orbital period and three observations, the parameters used in the Thiele-Innes method. We threat the orbit computation problem as an inverse problem and apply Baysien statistical methods to solve for the maximum likelihood orbit and confidence regions.

Oszkiewicz, D.; Hestroffer, D.; Davis, P.

2013-09-01

379

Study of Certain Monte Carlo Search and Optimisation Methods.

National Technical Information Service (NTIS)

Studies are described which might lead to the development of a search and optimisation facility for the Monte Carlo criticality code MONK. The facility envisaged could be used to maximise a function of k-effective with respect to certain parameters of the...

C. Budd

1984-01-01

380

Time-resolved polarization imaging: Monte Carlo simulation

Monte Carlo method was used to simulate time resolved polarization imaging in turbid media. Mie theory was used to calculate the Meuller matrix of a single scattering event. In the simulation, the Stokes vector of each incident photon package was traced. The summation of the Stokes vectors of the traced photon packages gave the total output Stokes vector. The time

Gang Yao; Lihong V. Wang

2001-01-01

381

Monte Carlo data association for multiple target tracking

The data association problem occurs for multiple target tracking applications. Since non-linear and non-Gaussian estimation problems are solved approxi- mately in an optimal way using recursive Monte Carlo methods or particle lters, the association step will be crucial for the overall performance. We introduce a Bayesian data association method based on the par- ticle lter idea and the joint probabilistic

Rickard Karlsson; Fredrik Gustafsson

2001-01-01

382

Weight Window/Importance Generator for Monte Carlo Streaming Problems.

National Technical Information Service (NTIS)

A Monte Carlo method for solving highly angle dependent streaming problems is described. The method uses a DXTRAN-like angle biasing scheme, a space-angle weight window to reduce weight fluctuations introduced by the angle biasing, and a space-angle impor...

T. E. Booth

1983-01-01

383

Direct calculation of bubble points by Monte Carlo simulation

The calculation of bubble points, i.e. the conditions in which a liquid starts to form a vapour phase, is a problem of industrial interest in petroleum and chemical engineering. Phase equilibrium at specified global composition, temperature and volume or pressure can be computed by the Gibbs Ensemble Monte Carlo method (GEMC). However it is not directly applicable to bubble points,

Philippe Ungerer; Anne Boutin; Alain H. Fuchs

1999-01-01

384

A multilayer Monte Carlo method with free phase function choice

NASA Astrophysics Data System (ADS)

This paper presents an adaptation of the widely accepted Monte Carlo method for Multi-layered media (MCML). Its original Henyey-Greenstein phase function is an interesting approach for describing how light scattering inside biological tissues occurs. It has the important advantage of generating deflection angles in an efficient - and therefore computationally fast- manner. However, in order to allow the fast generation of the phase function, the MCML code generates a distribution for the cosine of the deflection angle instead of generating a distribution for the deflection angle, causing a bias in the phase function. Moreover, other, more elaborate phase functions are not available in the MCML code. To overcome these limitations of MCML, it was adapted to allow the use of any discretized phase function. An additional tool allows generating a numerical approximation for the phase function for every layer. This could either be a discretized version of (1) the Henyey-Greenstein phase function, (2) a modified Henyey-Greenstein phase function or (3) a phase function generated from the Mie theory. These discretized phase functions are then stored in a look-up table, which can be used by the adapted Monte Carlo code. The Monte Carlo code with flexible phase function choice (fpf-MC) was compared and validated with the original MCML code. The novelty of the developed program is the generation of a user-friendly algorithm, which allows several types of phase functions to be generated and applied into a Monte Carlo method, without compromising the computational performance.

Watté, R.; Aernouts, B.; Saeys, W.

2012-05-01

385

Credit Risk Modelling using Hardware Accelerated Monte-Carlo Simulation

The recent turmoil in global credit markets has demon- strated the need for advanced modelling of credit risk, which can take into account the effects of changing eco- nomic conditions on portfolios of loans. Such models are most easily described as Monte-Carlo simulations, but take too long to converge in software based simula- tors. This paper describes a hardware implementation

David B. Thomas; Wayne Luk

2008-01-01

386

Clinical implementation of proton Monte Carlo dose calculation.

NASA Astrophysics Data System (ADS)

Goal was the clinical implementation of Monte Carlo dose calculation for use in parallel to a commercial planning system. Treatment heads were modeled in detail. To describe the patient anatomy, Hounsfield Units were converted into materials with explicit element composition and density. We developed a method to dynamically assign the mass density to the materials during particle transport. Memory for CT voxels is assigned dynamically. A software link was created between the commercial planning system, the treatment machine control system and the Monte Carlo program. The prescribed range and modulation are automatically translated into the corresponding settings of the treatment head. For broad beam modulation treatment, the Monte Carlo code simulates apertures and compensators based on the milling machine files. Treatment information, like prescribed dose per field, size of the air gap, couch angle and gantry angle, is read from the departmental patient database. For absolute dosimetry, the dose delivered to the patient per monitor unit is calculated based on the simulation of the reading of a segmented transmission ionization chamber. Dose calculations are done on the CT grid resolution and have been performed for various treatment sites. Monte Carlo results can be imported into the planning system.

Paganetti, Harald; Jiang, Hongyu; Kollipara, Shashidhar; Kooy, Hanne

2006-03-01

387

Monte Carlo simulations of environmental degradation on polymer coatings

The degradation of a polymer coating and predicting the coating lifetime, based on physica properties and distribution within the coating of the polymer binder, pigments, and fillers, are economically very important. As technologies advance, allowing control of coatings at the nanoscale level, methods such as Monte Carlo can be used not only to predict the behavior of a nanodesigned coating

Brian Hinderliter; Stuart Croll

2003-01-01

388

Monte Carlo simulations of environmental degradation on polymer coatings

NASA Astrophysics Data System (ADS)

The degradation of a polymer coating and predicting the coating lifetime, based on physica properties and distribution within the coating of the polymer binder, pigments, and fillers, are economically very important. As technologies advance, allowing control of coatings at the nanoscale level, methods such as Monte Carlo can be used not only to predict the behavior of a nanodesigned coating with time but also to design coatings, such as optimizing pigment particle distributions or optimum hard and soft phase distributions of the binders in multiphase systems for maintaining the desired property with time. Erosion of the coating surface was simulated using Monte Carlo techniques where terrestrial solar flux is the initiator for polymer segment cleavage and removal. The impact on the sensitivity of the polymer adjacent to the detached polymer segment can be increased or decreased in the model based on the chemistry and surface energy of the remaining polymer matrix. Multiple phases with varying sensitivity to degradation can be modeled. The Monte Carlo generates a statistically similar surface topography and chemistry of the coating. The results of the Monte Carlo model are compared to measurable properties; such as gloss, fracture toughness, and wetting contact angle, using various published correlations of the property to the surface topology. The simulated properties change through the lifetime of the coating in ways that are consistent with observed behavior. Apparently, complicated changes in many properties can be described by the repeated application of simple, random processes.

Hinderliter, Brian; Croll, Stuart

2003-07-01

389

Epitaxial growth of metals: Experimental results and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Layer-by-layer growth of epitaxial systems has been studied with Monte Carlo (MC) simulations, and the results have been compared with those of thermal energy atom scattering (TEAS). This technique has proved to be purely kinematical and sensitive only to defects in the outermost layers, thus allowing for a direct comparison with MC results.

Ferrón, J.; Gallego, J. M.; Cebollada, A.; De Miguel, J. J.; Ferrer, S.

1989-04-01

390

Markov Chain Monte Carlo Analysis of Correlated Count Data

This article is concerned with the analysis of correlated count data. A class of models is proposed in which the correlation among the counts is represented by correlated latent effects. Special cases of the model are discussed and a tuned and efficient Markov chain Monte Carlo algorithm is developed to estimate the model under both multivariate normal and multivariate-t assumptions

Siddhartha Chib; Rainer Winkelmann

2001-01-01

391

Monte Carlo variance reduction using finite element adjoint weight windows

The use of Monte Carlo variance reduction techniques is unavoidable on present day computers in obtaining numerical solutions in complex shielding, deep penetration or other radiation transport problems such as nuclear well logging and ex-core reactor core modeling etc. A deterministic variance reduction technique based on the finite element adjoint weight window (FEAWW) scheme is developed and applied in the well-known and widely used Monte Carlo radiation transport code MCNP. The scheme involves generating importance maps from the adjoint deterministic EVENT transport calculations which are then extracted and used as 'weight window lower bounds' suitable for acceleration of the forward Monte Carlo radiation transport calculations. The 'holy grail' of an automatic variance reduction technique is to provide a single method which provides systematic or nearly systematic ways to eliminate much of the user's intervention. The proposed method employs the adjoint solutions to the problem of interest which has been folded into the MCNP weight window scheme. The FEAWW method is tested on a number of complex deep penetration and neutron streaming problems and compared against the standard Monte Carlo generated variance reduction techniques with encouraging results. (authors)

Shahdatullah, M. S. [Applied Modelling and Computation Group AMCG, Imperial College of Science, Technology and Medicine, Dept. of Earth Science and Engineering, London, SW7 2AZ (United Kingdom); Ziver, K. [Applied Modelling and Computation Group AMCG, Imperial College of Science, Technology and Medicine, Dept. of Earth Science and Engineering, London, SW7 2AZ (United Kingdom); AMCG Group (United Kingdom); RM Consultants Ltd. Abingdon, Oxfordshire (United Kingdom); Eaton, M. D.; Pain, C. C.; Goddard, A. J. H. [Applied Modelling and Computation Group AMCG, Imperial College of Science, Technology and Medicine, Dept. of Earth Science and Engineering, London, SW7 2AZ (United Kingdom)

2006-07-01

392

Time-Dependent Tracking in the Monte Carlo Application Toolkit

NASA Astrophysics Data System (ADS)

The Monte Carlo Application Toolkit (MCATK) provides solution options for problems with time varying properties in mesh geometries and simple solid bodies. The paper describes the toolkit's mechanism for handling time varying problems focusing on managing the particle population. The included results show the robustness of this approach for systems with varying degrees of criticality without user intervention.

Nolen, Steven; Adams, Terry; Sweezy, Jeremy; Zukaitis, Anthony

2014-06-01

393

GEANT Monte Carlo simulations for the GREAT spectrometer

NASA Astrophysics Data System (ADS)

GEANT Monte Carlo simulations for the recently developed GREAT spectrometer are presented. Some novel applications of the spectrometer for ?-ray, conversion-electron and ?-decay spectroscopy are discussed. The conversion-electron spectroscopy of heavy nuclei with strongly converted transitions and the extension of the recoil decay tagging method to ?-decaying nuclei are considered in detail.

Andreyev, A. N.; Butler, P. A.; Page, R. D.; Appelbe, D. E.; Jones, G. D.; Joss, D. T.; Herzberg, R.-D.; Regan, P. H.; Simpson, J.; Wadsworth, R.

394

Monte Carlo renormalization-group analysis of percolation.

We describe a Monte Carlo renormalization group approach to the calculation of critical behavior for percolation models. This approach can be utilized to determine the renormalized bond probabilities and the values of the critical exponents. We illustrate the method for two-dimensional bond percolation, but the method is also applicable to other percolation models and other dimensions. PMID:24229304

Brown, Albert; Edelman, Alexander; Rocks, Jason; Coniglio, Antonio; Swendsen, Robert H

2013-10-01

395

First-passage Monte Carlo for simulations of alloy microstructure

We unveil a principally new Monte Carlo algorithm for simulations of multiple diffusing particles of finite dimensions that coalesce or annihilate on collisions. The algorithm is derived from the theory of first-passage processes and a time-dependent Green's function formalism. The new method circumvents the need for long and tedious diffusion hops by which the particles find each other in space.

Aleksandar Donev; Vasily Bulatov; Tomas Oppelstrup; Malvin Kalos; George Gilmer; Babak Sadigh

2007-01-01

396

Monte Carlo Simulations of the Phase Behavior of Surfactant Solutions

Phase diagrams are determined by Monte Carlo lattice simulations for idealized symmetric and asymmetric surfactant molecules mixed with single-site ``oil'' and ``water'' molecules. At high concentrations (above 20%) of surfactant, the simulations show the self assembly of liquid crystalline phases, including smectic, hexagonal, BCC sphere packings, and Ia3d gyroid cubic phases. The locations of the phases on the diagram for

R. G. Larson

1996-01-01

397

Monte Carlo Capabilities of the SCALE Code System

NASA Astrophysics Data System (ADS)

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a "plug-and-play" framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE's graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2, to be released in 2014, will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.

Rearden, B. T.; Petrie, L. M.; Peplow, D. E.; Bekar, K. B.; Wiarda, D.; Celik, C.; Perfetti, C. M.; Ibrahim, A. M.; Hart, S. W. D.; Dunn, M. E.

2014-06-01

398

Monte Carlo simulation of ions in a magnetron plasma

A simulation of ion dynamics in a planar magnetron discharge is performed using separate three-dimensional Monte Carlo codes for the electrons and ions. First, to predict the ionization sites, the orbits of energetic electrons are simulated for prescribed DC electric and magnetic fields, subject to collision with neutrals at random intervals. In the second code the predicted sites are used

Matthew J. Goeckner; John A. Goree; Terrence E. Sheridan

1991-01-01

399

Monte Carlo Simulation of Directivity of Interplanetary Radio Bursts

We have developed a Monte Carlo simulation code to study the effects of refraction due to spatial variation of the solar wind density and scattering due to random density fluctuations on directivities, time profiles, and sizes and positions of the apparent sources of the interplanetary type II and type III radio bursts excited at the fundamental (F) and second harmonic

G. Thejappa; R. J. MacDowall; M. L. Kaiser

2007-01-01

400

Monte Carlo simulations of phonon transport in silicon

In this paper, the development of a computational procedure to simulate thermal transport in small semiconductor structures was described. On a microscopic scale, heat transport can be described mathematically using a Boltzmann equation for phonons. Direct numerical solution of this equation is difficult, without extensive approximation, because of the quantity and complexity of the anharmonic phonon-phonon interactions. Therefore, Monte Carlo

A. Asokan; R. W. Kelsall

2004-01-01

401

Classical Trajectory Monte Carlo Simulations for Charge Transfer Processes

I have calculated electron transfer cross sections for slow, highly charged ion-atomic hydrogen collisions by using the classical trajectory Monte Carlo method. Similar calculations for alkaline metal targets are also carried out using a simple one-electron model. I compare the results to predictions by the extended classical over barrier model and available experimental data. The calculated cross sections are in

YAMADA Ichihiro

2004-01-01

402

Monte Carlo Simulations on Scattering of Bombarded Ions in Solids

By taking account of not only an elastic scattering but also an inelastic scattering, the Monte Carlo technique based on a single scattering model is applied to a simulation of the behavior of ion beam in the amorphous target. The calculations are carried out for the light ion beam mainly and the results show a fairly good agreement with the

Tohru Ishitani; Ryuichi Shimizu; Kenji Murata

1972-01-01

403

Monte Carlo simulation of electron beam lithography on topographical substrates

A Monte Carlo program suite MOCASEL has been developed for 3-D simulation of e-beam lithography over a flat or a topographical substrate. A new electron cloud scheme is introduced to reduce the number of electrons used in the simulation, which results in a considerable reduction of computation time. Electron trajectories over substrate topography of single or composite materials are presented.

Zheng Cui

1998-01-01

404

Quantum Monte Carlo Simulation of Tunneling Devices Using Bohm Trajectories

A generalization of the classical Monte Carlo (MC) device simulation technique is proposed to simultaneously deal with quantum-mechanical phase-coherence effects and scattering interactions in tunneling devices. The proposed method restricts the quantum treatment of transport to the regions of the device where the potential profile significantly changes in distances of the order of the de Broglie wavelength of the carriers

X. Oriols; J. J. García-García; F. Martín; J. Suńé; T. González; J. Mateos; D. Pardo

1997-01-01

405

A new method to assess Monte Carlo convergence

The central limit theorem can be applied to a Monte Carlo solution if the following two requirements are satisfied: (1) the random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these are satisfied, a confidence interval based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the type of Monte Carlo tally being used. The Monte Carlo practitioner has only a limited number of marginally quantifiable methods that use sampled values to assess the fulfillment of the second requirement; e.g., statistical error reduction proportional to 1[radical]N with error magnitude guidelines. No consideration is given to what has not yet been sampled. A new method is presented here to assess the convergence of Monte Carlo solutions by analyzing the shape of the empirical probability density function (PDF) of history scores, f(x), where the random variable x is the score from one particle history and [integral][sub [minus][infinity

Forster, R.A.; Booth, T.E.; Pederson, S.P.

1993-01-01

406

Mechanical Properties of Gold Nanocontacts Studied by Monte Carlo Simulation

The Monte Carlo method has been applied to the study on the size dependence of mechanical properties in gold nanocontacts. Using the Metropolis method, thermal-equilibrium atomic configurations in model nanocontacts have been followed during elongation of the contacts. The Morse potential has been used as an interatomic interaction. The relation between the tensile force and strain, the change in atomic

Souichirou Tanimori; Shuji Shimamura

2002-01-01

407

Conditions for Captive Insurer Value: A Monte Carlo Simulation

We construct two potential scenarios to depict the cash flows from the operation of a captive insurer. We then use Monte Carlo simulation to identify conditions that are sustainable in practice and under which captives have a high probability of creating positive shareholder value. We use realistic value ranges for both a class 1 Bermuda captive and a British Virgin

Nicos A. Scordis; James Barrese; Masakazu Yokoyama

2007-01-01

408

Monte Carlo spreadsheet modeling of stable isotope biosynthesis

Metabolic physiologists often introduce stable isotopes, atoms containing additional neutrons, into molecules during biosynthesis. This tags the newly synthesized material by altering its mass. Monte Carlo analysis is implemented on a popular spreadsheet to analyze this process. An example is provided where acetoacetate is synthesized by condensation of two acetate moieties. The precursor acetate is present as a mixture of

Thomas M. Masterson; Joanne K. Kelleher

1996-01-01

409

SABRINA: an interactive solid geometry modeling program for Monte Carlo

SABRINA is a fully interactive three-dimensional geometry modeling program for MCNP. In SABRINA, a user interactively constructs either body geometry, or surface geometry models, and interactively debugs spatial descriptions for the resulting objects. This enhanced capability significantly reduces the effort in constructing and debugging complicated three-dimensional geometry models for Monte Carlo Analysis.

West, J.T.

1985-01-01

410

Kinetic Monte Carlo Simulations of dislocations in heteroepitaxial growth

We determine the critical layer thickness for the appearance of misfit dislocations as a function of the misfit between the lattice constants of the substrate and the adsorbate from Kinetic Monte Carlo (KMC) simulations of heteroepitaxial growth. To this end, an algorithm is introduced which allows the off-lattice simulation of various phenomena observed in heteroepitaxial growth including critical layer thickness

F. Much M. Ahr; M. Biehl; W. Kinzel

2001-01-01

411

Kinetic Monte Carlo simulation of nucleation on patterned substrates

The effects of a patterned substrate on island nucleation are investigated using kinetic Monte Carlo simulations. Two different models are formulated by incorporating an inhomogeneous energy surface into the basic solid-on-solid model of epitaxial growth to describe surface diffusion and consequent island nucleation on a patterned substrate. These models are related to two examples of real systems in which preferential

L. Nurminen; A. Kuronen; K. Kaski

2001-01-01

412

Kinetic Monte Carlo simulations of the growth of polymer crystals

Based upon kinetic Monte Carlo simulations of crystallization in a simple polymer model we present a new picture of the mechanism by which the thickness of lamellar polymer crystals is constrained to a value close to the minimum thermodynamically stable thickness, lmin. The free energetic costs of the polymer extending beyond the edges of the previous crystalline layer and of

Jonathan P. K. Doye; Daan Frenkel

1999-01-01

413

Kinetic Monte Carlo method for dislocation glide in silicon

A kinetic Monte Carlo (KMC) approach to the mesoscale simulation of dislocation glide via the kink mechanism is developed. In this paper we present the details of the KMC methodology, highlighting three features: (1) inclusion of dislocation dissociation; (2) efficient method of sampling the double-kink nucleation process; and (3) exact calculation of dislocation segment interactions.

V ASILY V. BULATOV

1999-01-01

414

Kinetic Monte Carlo simulation of Cu thin film growth

A three-dimensional kinetic Monte Carlo technique has been developed for simulating the growth of thin Cu films. The model involves incident atom attachment, surface diffusion of the atoms on the growing surface and atom detachment from the growing surface. A significant improvement in calculation of activation barriers for the surface atom diffusion on the growing film was made. The related

Peifeng Zhang; Xiaoping Zheng; Suoping Wu; Jun Liu; Deyan He

2004-01-01

415

Kinetic Monte Carlo simulation of heterometal epitaxial deposition

Vapor deposited multilayers consisting of alternating ferromagnetic and nonferrous metals are being used for magnetic sensing and data storage devices. Their performance is dependent upon interface morphology which is a sensitive function of deposition condition such as the deposition rate, deposition temperature, and flux angle of incidence. A two-dimensional kinetic Monte Carlo method has been developed and used to explore

Y. G Yang; R. A Johnson; H. N. G Wadley

2002-01-01

416

Optimization of Kinoform Lenses with the Monte Carlo Method

For the optimization of non-Fourier-type computer-generated phase holograms (kinoform lenses), a method based on the Monte Carlo procedure is suggested. This method can be regarded as analogous to the iterative Fourier transform algorithm method that is widely used for the optimization of Fourier-type computer-generated phase holograms (kinoforms).

Nandor Bokor; Zsolt Papp

1998-01-01

417

Border Sampling through Coupling Markov Chain Monte Carlo

Recently, progressive border sampling (PBS) was proposed for sample selection in supervised learning by progressively learning an augmented full border from small labeled datasets. However, this quadratic learning algorithm is inapplicable to large datasets. In this paper, we incorporate the PBS to a state of the art technique called coupling Markov chain Monte Carlo (CMCMC) in an attempt to scale

Guichong Li; Nathalie Japkowicz; Trevor J. Stocki; R. Kurt Ungar

2008-01-01

418

Capacity evaluation of MIMO systems by Monte-Carlo methods

In order to form the theoretical information foundation of multiple input and multiple output channel techniques and its applications, the analysis and simulations of the capacity of MIMO based on Monte-Carlo are presented in this paper. We can get a conclusion that with a circularly symmetric Gaussian transmit vector, the extremely high capacity of the Rayleigh fading MIMO channel can

Wang Chao; Wu Shunjun; Zhang Linrang; Tao Xiaoyan

2003-01-01

419

Stellar collisions in accreting protoclusters: a Monte Carlo dynamical study

We explore the behaviour of accreting protoclusters with a Monte Carlo dynamical code in order to evaluate the relative roles of accretion, two-body relaxation and stellar collisions in the cluster evolution. We corroborate the suggestion of Clarke and Bonnell that the number of stellar collisions should scale as (independent of other cluster parameters, where N is the number of stars

O. Davis; C. J. Clarke; M. Freitag

2010-01-01

420

Modifications to the TRIM Monte Carlo simulation program

Extensive modifications were made to the TRIM (TRansport of Ions in Matter) Monte Carlo computer code which simulates the ion irradiation of amorphous solids. The original FORTRAN code was translated into BASIC for use on minicomputers with 32 K words of memory. Versions have been written to simulate very low-energy irradiations and the irradiation of binary alloys. Furthermore, a version

Macrander

1979-01-01

421

Benchmark calculations for Monte Carlo simulations of electron transport

Benchmark calculations have been performed for electron transport coefficients with an aim to produce a body of data required to verify the codes used in plasma modeling. The present code for the time resolved Monte Carlo simulation (MCS) was shown to represent properly DC transport coefficients in a purely electric field, in crossed electric and magnetic fields, and in the

Z. M. Raspopovic; S. Sakadzic; S. A. Bzenic; Z. Lj. Petrovic

1999-01-01

422

Monte Carlo simulations of the transport of sputtered particles

Program SPATS models the transport of neutral particles during magnetron sputtering deposition. The 3D Monte Carlo simulation provides information about spatial distribution of the fluxes, density of the sputtered particles in the chamber glow discharge area, and kinetic energy distribution of the arrival flux. Collision events are modelled by scattering in Biersack's potential, Lennard-Jones potential, or by binary hard sphere

Karol Macŕk; Peter Macŕk; Ulf Helmersson

1999-01-01

423

Nonlinear Acoustics in Diatomic Gases Using Direct Simulation Monte Carlo

The Direct Simulation Monte Carlo (DSMC) method has been very successful for the study of many problems in rarefied gas dynamics and hypersonic flow. The extension to applications such as acoustics will provide a useful tool for capturing all physical properties of interest for nonlinear acoustic problems, such as dispersion, attenuation, harmonic generation and nonequilibrium effects. The validity of DSMC

Amanda L. Danforth; Lyle N. Long

2005-01-01

424

A Variational Monte Carlo Approach to Atomic Structure

ERIC Educational Resources Information Center

The practicality and usefulness of variational Monte Carlo calculations to atomic structure are demonstrated. It is found to succeed in quantitatively illustrating electron shielding, effective nuclear charge, l-dependence of the orbital energies, and singlet-tripetenergy splitting and ionization energy trends in atomic structure theory.

Davis, Stephen L.

2007-01-01

425

Monte Carlo simulation of the shape space model of immunology

NASA Astrophysics Data System (ADS)

The shape space model of de Boer, Segel and Perelson for the immune system is studied with a probabilistic updating rule by Monte Carlo simulation. A suitable mathematical form is chosen for the probability of increase of B-cell concentration depending on the concentration around the mirror image site. The results obtained agree reasonably with the results obtained by deterministic cellular automata.

Dasgupta, Subinay

1992-11-01

426

Efficient cosmological parameter estimation with Hamiltonian Monte Carlo technique

Traditional Markov Chain Monte Carlo methods suffer from low acceptance rate, slow mixing, and low efficiency in high dimensions. Hamiltonian Monte Carlo resolves this issue by avoiding the random walk. Hamiltonian Monte Carlo (HMC) is a Markov Chain Monte Carlo (MCMC) technique built upon the basic principle of Hamiltonian mechanics. Hamiltonian dynamics allows the chain to move along trajectories of constant energy, taking large jumps in the parameter space with relatively inexpensive computations. This new technique improves the acceptance rate by a factor of 4 while reducing the correlations and boosts up the efficiency by almost a factor of D in a D-dimensional parameter space. Therefore shorter chains will be needed for a reliable parameter estimation comparing to a traditional MCMC chain yielding the same performance. Besides that, the HMC is well suited for sampling from non-Gaussian and curved distributions which are very hard to sample from using the traditional MCMC methods. The method is very simple to code and can be easily plugged into standard parameter estimation codes such as CosmoMC. In this paper we demonstrate how the HMC can be efficiently used in cosmological parameter estimation. Also we discuss possible ways of getting good estimates of the derivatives of (the log of) posterior which is needed for HMC.

Hajian, Amir [Department of Physics, Jadwin Hall, Princeton University, P.O. Box 708, Princeton, New Jersey 08542 (United States); Department of Astrophysical Sciences, Peyton Hall, Princeton University, Princeton, New Jersey 08544 (United States)

2007-04-15

427

CO2 Clathrate Hydrate Structure: A Monte Carlo Approach

Monte Carlo simulations have been carried out for the structure of CO2 hydrate in the NPT ensemble using SPC intermolecular potential model of water. A mixture of water and CO2 placed arbitrarily in a cubic cell has been used as a model system to simulate the CO2 clathrate hydrate at a temperature 260 (K) and pressure 4 (MPa). The comparison

M. FERDOWS; MASAHIRO OTA

2005-01-01

428

On the monte carlo simulation of optical MEMS components

A statistical Monte Carlo technique for the performance estimation of optical MEMS components is presented in this paper. The developed technique is applied on the 2x2 moving mirror optical MEMS switch as a typical example to study its performance under realistic passive alignment conditions. The obtained results enable to evaluate the assembly process capability and to analyze the performance sensitivity

Tarek Badreldin; Tamer Saad; D. Khalil

2004-01-01

429

Multiple scattering in reflection nebulae. I. A Monte Carlo approach

A method is described which permits the calculation of the surface brightness distribution on a plane-parallel reflection nebula of uniform density, illuminated by a single star located in front of, behind, or arbitrarily inside the nebula. The multiple scattering problem is solved by the Monte Carlo technique in a three-dimensional simulation. The models are completely parametrized by describing particle properties

A. N. Witt

1977-01-01

430

Development of a New Monte Carlo Reactor Physics Code.

National Technical Information Service (NTIS)

A major part of this work deals with the on-going development of the PSG Monte Carlo reactor physics code. The work described in this thesis was started in September 2004 and carried out until the summer of 2006 at the VTT Technical Research Centre of Fin...

J. Leppaenen

2009-01-01

431

A Monte Carlo simulation of the Bernoulli principle

Effusion of an ideal gas through a small orifice when a drifting gas exists past the orifice, as well as the reverse process, are investigated through extensive two-dimensional Monte Carlo simulations. It is found that a net transport of particles takes place toward the side containing the drifting gas. Based on the model used, however, this transport of particles is

Pirooz Mohazzabi; Mark D. Bernhardt

1996-01-01

432

Criticality accident detector coverage analysis using the Monte Carlo Method.

National Technical Information Service (NTIS)

As a result of the need for a more accurate computational methodology, the Los Alamos developed Monte Carlo code MCNP is used to show the implementation of a more advanced and accurate methodology in criticality accident detector analysis. This paper will...

J. F. Zino K. C. Okafor

1993-01-01

433

Verification of the Shift Monte Carlo Code with the C5G7 Reactor Benchmark.

National Technical Information Service (NTIS)

Shift is a new hybrid Monte Carlo/deterministic radiation transport code being developed at Oak Ridge National Laboratory. At its current stage of development, Shift includes a parallel Monte Carlo capability for simulating eigenvalue and fixed-source mul...

B. T. Mervin G. I. Maldonado J. C. Wagner N. C. Sly S. W. Mosher T. M. Evans

2012-01-01

434

Variance Reduction Methods Applied to Deep-Penetration Monte Carlo Problems.

National Technical Information Service (NTIS)

A review of standard variance reduction methods for deep-penetration Monte Carlo calculations is presented. Comparisons and contrasts are made with methods for nonpenetration and reactor core problems. Difficulties and limitations of the Monte Carlo metho...

S. N. Cramer J. S. Tang

1986-01-01

435

Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

Global sensitivity indices for rather complex mathematical models can be efficiently computed by Monte Carlo (or quasi-Monte Carlo) methods. These indices are used for estimating the influence of individual variables or groups of variables on the model output.

2001-01-01

436

Unified Monte Carlo interpretation of particle simulations and applications to nonneutral plasmas.

National Technical Information Service (NTIS)

Using a ''Monte Carlo interpretation'' a particle simulations, a general description of low-noise techniques is developed in terms well-known Monte Carlo variance reduction methods. Some of these techniques then are applied to linear and nonlinear studies...

A. Y. Aydemir

1993-01-01

437

Sequential Monte Carlo Method for Real-time Tracking of Multiple Targets.

National Technical Information Service (NTIS)

In this project, a Monte Carlo approach to tracking was developed for tracking in cluttered environments and across multiple scales. The Monte Carlo approach was compared with an active contour approach. Specifically, we developed a novel deterministic ap...

B. Li S. T. Acton

2010-01-01

438

Comparative Dosimetric Estimates of a 25 KeV Electron Microbeam with Three Monte Carlo Codes.

National Technical Information Service (NTIS)

The calculations presented compare the different performances of the three Monte Carlo codes: PENetration and Energy LOss of Positrons and Electrons code (PENELOPE-1999), Monte Carlo N-Particle transport code system (MCNP-4C), Positive Ion Track Structure...

E. Mainardi R. J. Donahue E. A. Blakely

2002-01-01

439

Design, Implementation and Optimization of a Parallel Monte Carlo Particle Transport Code.

National Technical Information Service (NTIS)

The design, implementation and optimization of a parallel, Monte Carlo particle transport code is presented. MERCURY is a modern Monte Carlo code being developed at the Lawrence Livermore National Laboratory (LLNL). It is capable of modeling the transport...

2004-01-01

440

Direct aperture optimization for IMRT using Monte Carlo generated beamlets

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 2.5x5.0 mm{sup 2} 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 {approx}33% compared to fluence-based optimization methods.

Bergman, Alanah M.; Bush, Karl; Milette, Marie-Pierre; Popescu, I. Antoniu; Otto, Karl; Duzenli, Cheryl [Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia (Canada); Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia (Canada); Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia (Canada); Medical Physics, BC Cancer Agency-Vancouver Centre, Vancouver, British Columbia (Canada)

2006-10-15

441

Reconstruction of Human Monte Carlo Geometry from Segmented Images

NASA Astrophysics Data System (ADS)

Human computational phantoms have been used extensively for scientific experimental analysis and experimental simulation. This article presented a method for human geometry reconstruction from a series of segmented images of a Chinese visible human dataset. The phantom geometry could actually describe detailed structure of an organ and could be converted into the input file of the Monte Carlo codes for dose calculation. A whole-body computational phantom of Chinese adult female has been established by FDS Team which is named Rad-HUMAN with about 28.8 billion voxel number. For being processed conveniently, different organs on images were segmented with different RGB colors and the voxels were assigned with positions of the dataset. For refinement, the positions were first sampled. Secondly, the large sums of voxels inside the organ were three-dimensional adjacent, however, there were not thoroughly mergence methods to reduce the cell amounts for the description of the organ. In this study, the voxels on the organ surface were taken into consideration of the mergence which could produce fewer cells for the organs. At the same time, an indexed based sorting algorithm was put forward for enhancing the mergence speed. Finally, the Rad-HUMAN which included a total of 46 organs and tissues was described by the cuboids into the Monte Carlo Monte Carlo Geometry for the simulation. The Monte Carlo geometry was constructed directly from the segmented images and the voxels was merged exhaustively. Each organ geometry model was constructed without ambiguity and self-crossing, its geometry information could represent the accuracy appearance and precise interior structure of the organs. The constructed geometry largely retaining the original shape of organs could easily be described into different Monte Carlo codes input file such as MCNP. Its universal property was testified and high-performance was experimentally verified

Zhao, Kai; Cheng, Mengyun; Fan, Yanchang; Wang, Wen; Long, Pengcheng; Wu, Yican

2014-06-01

442

Monte Carlo (MC) simulations in positron emission tomography (PET) play an important role in detector modeling and algorithm testing. Nowadays, these simulation are also increasingly used for scatter correction during reconstruction. This can be done ideally by using MC simulations to calculate the system matrix including scatter (full matrix approach). Another approach to incorporate MC simulations into the reconstruction is

Niklas Rehfeld; Markus Alber

2007-01-01

443

Validation of the Monte Carlo simulator GATE for indium-111 imaging

Monte Carlo simulations are useful for optimizing and assessing single photon emission computed tomography (SPECT) protocols, especially when aiming at measuring quantitative parameters from SPECT images. Before Monte Carlo simulated data can be trusted, the simulation model must be validated. The purpose of this work was to validate the use of GATE, a new Monte Carlo simulation platform based on

K. Assié; I. Gardin; P. Véra; I. Buvat

2005-01-01

444

MCNP-REN: a Monte Carlo tool for neutron detector design

The development of neutron detectors makes extensive use of the predictions of detector response through the use of Monte Carlo techniques in conjunction with the point reactor model. Unfortunately, the point reactor model fails to accurately predict detector response in common applications. For this reason, the general Monte Carlo code developed at Los Alamos National Laboratory, Monte Carlo N-Particle (MCNP),

Mark E. Abhold; Michael C. Baker

2002-01-01

445

Monte Carlo simulation of the scattered radiation distribution in diagnostic radiology

Monte Carlo techniques were employed to evaluate the point spread function (PSF) of scattered radiation in diagnostic radiology. The Monte Carlo procedure is described and shown to compare well with Monte Carlo scatter analysis of other authors. The intensity and distribution of the PSF are described independently. The effects of object thickness, air gap, and beam spectra are examined. An

John M. Boone; J. A. Seibert

1988-01-01

446

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and BuckleyLeverett transport in random heterogeneous porous media. The performance of MLMC is compared to MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.

Müller, Florian, E-mail: florian.mueller@sam.math.ethz.ch; Jenny, Patrick, E-mail: jenny@ifd.mavt.ethz.ch; Meyer, Daniel W., E-mail: meyerda@ethz.ch

2013-10-01

447

NASA Astrophysics Data System (ADS)

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley-Leverett transport in random heterogeneous porous media. The performance of MLMC is compared to MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.

Müller, Florian; Jenny, Patrick; Meyer, Daniel W.

2013-10-01

448

Monte Carlo and analytical dose calculations for ocular proton therapy

NASA Astrophysics Data System (ADS)

Uveal melanoma is a rare but life-threatening form of ocular cancer. Contemporary treatment techniques include proton therapy, which enables conservation of the eye and its useful vision. Dose to the proximal structures is widely believed to play a role in treatment side effects, therefore, reliable dose estimates are required for properly evaluating the therapeutic value and complication risk of treatment plans. Unfortunately, current simplistic dose calculation algorithms can result in errors of up to 30% in the proximal region. In addition, they lack predictive methods for absolute dose per monitor unit (D/MU) values. To facilitate more accurate dose predictions, a Monte Carlo model of an ocular proton nozzle was created and benchmarked against measured dose profiles to within +/-3% or +/-0.5 mm and D/MU values to within +/-3%. The benchmarked Monte Carlo model was used to develop and validate a new broad beam dose algorithm that included the influence of edgescattered protons on the cross-field intensity profile, the effect of energy straggling in the distal portion of poly-energetic beams, and the proton fluence loss as a function of residual range. Generally, the analytical algorithm predicted relative dose distributions that were within +/-3% or +/-0.5 mm and absolute D/MU values that were within +/-3% of Monte Carlo calculations. Slightly larger dose differences were observed at depths less than 7 mm, an effect attributed to the dose contributions of edge-scattered protons. Additional comparisons of Monte Carlo and broad beam dose predictions were made in a detailed eye model developed in this work, with generally similar findings. Monte Carlo was shown to be an excellent predictor of the measured dose profiles and D/MU values and a valuable tool for developing and validating a broad beam dose algorithm for ocular proton therapy. The more detailed physics modeling by the Monte Carlo and broad beam dose algorithms represent an improvement in the accuracy of relative dose predictions over current techniques, and they provide absolute dose predictions. It is anticipated these improvements can be used to develop treatment strategies that reduce the incidence or severity of treatment complications by sparing normal tissue.

Koch, Nicholas Corey

449

NASA Astrophysics Data System (ADS)

To a large extent, the flow and transport behaviour within a subsurface reservoir is governed by its permeability. Typically, permeability measurements of a subsurface reservoir are affordable at few spatial locations only. Due to this lack of information, permeability fields are preferably described by stochastic models rather than deterministically. A stochastic method is needed to asses the transition of the input uncertainty in permeability through the system of partial differential equations describing flow and transport to the output quantity of interest. Monte Carlo (MC) is an established method for quantifying uncertainty arising in subsurface flow and transport problems. Although robust and easy to implement, MC suffers from slow statistical convergence. To reduce the computational cost of MC, the multilevel Monte Carlo (MLMC) method was introduced. Instead of sampling a random output quantity of interest on the finest affordable grid as in case of MC, MLMC operates on a hierarchy of grids. If parts of the sampling process are successfully delegated to coarser grids where sampling is inexpensive, MLMC can dramatically outperform MC. MLMC has proven to accelerate MC for several applications including integration problems, stochastic ordinary differential equations in finance as well as stochastic elliptic and hyperbolic partial differential equations. In this study, MLMC is combined with a reservoir simulator to assess uncertain two phase (water/oil) flow and transport within a random permeability field. The performance of MLMC is compared to MC for a two-dimensional reservoir with a multi-point Gaussian logarithmic permeability field. It is found that MLMC yields significant speed-ups with respect to MC while providing results of essentially equal accuracy. This finding holds true not only for one specific Gaussian logarithmic permeability model but for a range of correlation lengths and variances.

Müller, Florian; Jenny, Patrick; Daniel, Meyer

2014-05-01

450

Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations.

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-"coupled"- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz-Kalos-Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB source code. PMID:24697425

Arampatzis, Georgios; Katsoulakis, Markos A

2014-03-28

451

Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-"coupled"- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz-Kalos-Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB source code.

Arampatzis, Georgios; Katsoulakis, Markos A.

2014-03-01

452

NASA Technical Reports Server (NTRS)

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

Ponomarev, Artem; Cucinotta, F.

2011-01-01

453

COMET-PE as an Alternative to Monte Carlo for Photon and Electron Transport

NASA Astrophysics Data System (ADS)

Monte Carlo methods are a central component of radiotherapy treatment planning, shielding design, detector modeling, and other applications. Long calculation times, however, can limit the usefulness of these purely stochastic methods. The coarse mesh method for photon and electron transport (COMET-PE) provides an attractive alternative. By combining stochastic pre-computation with a deterministic solver, COMET-PE achieves accuracy comparable to Monte Carlo methods in only a fraction of the time. The method's implementation has been extended to 3D, and in this work, it is validated by comparison to DOSXYZnrc using a photon radiotherapy benchmark. The comparison demonstrates excellent agreement; of the voxels that received more than 10% of the maximum dose, over 97.3% pass a 2% / 2mm acceptance test and over 99.7% pass a 3% / 3mm test. Furthermore, the method is over an order of magnitude faster than DOSXYZnrc and is able to take advantage of both distributed-memory and shared-memory parallel architectures for increased performance.

Hayward, Robert M.; Rahnema, Farzad

2014-06-01

454

An overview of spatial microscopic and accelerated kinetic Monte Carlo methods

NASA Astrophysics Data System (ADS)

The microscopic spatial kinetic Monte Carlo (KMC) method has been employed extensively in materials modeling. In this review paper, we focus on different traditional and multiscale KMC algorithms, challenges associated with their implementation, and methods developed to overcome these challenges. In the first part of the paper, we compare the implementation and computational cost of the null-event and rejection-free microscopic KMC algorithms. A firmer and more general foundation of the null-event KMC algorithm is presented. Statistical equivalence between the null-event and rejection-free KMC algorithms is also demonstrated. Implementation and efficiency of various search and update algorithms, which are at the heart of all spatial KMC simulations, are outlined and compared via numerical examples. In the second half of the paper, we review various spatial and temporal multiscale KMC methods, namely, the coarse-grained Monte Carlo (CGMC), the stochastic singular perturbation approximation, and the ?-leap methods, introduced recently to overcome the disparity of length and time scales and the one-at-a time execution of events. The concepts of the CGMC and the ?-leap methods, stochastic closures, multigrid methods, error associated with coarse-graining, a posteriori error estimates for generating spatially adaptive coarse-grained lattices, and computational speed-up upon coarse-graining are illustrated through simple examples from crystal growth, defect dynamics, adsorption desorption, surface diffusion, and phase transitions.

Chatterjee, Abhijit; Vlachos, Dionisios G.

2007-07-01

455

Analytic results and weighted Monte Carlo simulations for CDO pricing

NASA Astrophysics Data System (ADS)

We explore the possibilities of importance sampling in the Monte Carlo pricing of a structured credit derivative referred to as Collateralized Debt Obligation (CDO). Modeling a CDO contract is challenging, since it depends on a pool of (typically 100) assets, Monte Carlo simulations are often the only feasible approach to pricing. Variance reduction techniques are therefore of great importance. This paper presents an exact analytic solution using Laplace-transform and MC importance sampling results for an easily tractable intensity-based model of the CDO, namely the compound Poissonian. Furthermore analytic formulas are derived for the reweighting efficiency. The computational gain is appealing, nevertheless, even in this basic scheme, a phase transition can be found, rendering some parameter regimes out of reach. A model-independent transform approach is also presented for CDO pricing.

Stippinger, M.; Rácz, É.; Vet?, B.; Bihary, Zs.

2012-02-01

456

Statistical Analysis for Quantum Adiabatic Computations: Quantum Monte Carlo Annealing

NASA Astrophysics Data System (ADS)

Quantum adiabatic computations are designed to determine the ground state configurations of an classical problem Hamiltonian H3SAT within quantum theory and at imaginary time allow statistical mechanics studies for the computational e_ciency of the ground state search. We mention a recent determination of the quantum complexity, i.e. the mass-gap _mGAP for a specific ensemble of three-satisfiability (3SAT) problems with a unique satisfiability assignment, which shows an exponential increase of the gap correlation length _GAP with _GAP = 1=_mGAP. In 3SAT we present numerical data for the behavior of quantum Monte Carlo annealing cycles in search for the ground state. The findings show, that for the specific set of realizations quantum Monte Carlo searches in 3SAT fail above a sharp cut-o_ Kcut in the complexity K, which exemplifies the intractable nature of 3SAT.

Neuhaus, T.

457

Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

NASA Astrophysics Data System (ADS)

A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.

Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.

2012-11-01

458

Monte Carlo simulations of fermion systems: the determinant method

Described are the details for performing Monte Carlo simulations on systems of fermions at finite temperatures by use of a technique called the Determinant Method. This method is based on a functional integral formulation of the fermion problem (Blankenbecler et al., Phys. Rev D 24, 2278 (1981)) in which the quartic fermion-fermion interactions that exist for certain models are transformed into bilinear ones by the introduction (J. Hirsch, Phys. Rev. B 28, 4059 (1983)) of Ising-like variables and an additional finite dimension. It is on the transformed problem the Monte Carlo simulations are performed. A brief summary of research on two such model problems, the spinless fermion lattice gas and the Anderson impurity problem, is also given.

Gubernatis, J.E.

1985-01-01

459

Efficient, automated Monte Carlo methods for radiation transport

Monte Carlo simulations provide an indispensible model for solving radiative transport problems, but their slow convergence inhibits their use as an everyday computational tool. In this paper, we present two new ideas for accelerating the convergence of Monte Carlo algorithms based upon an efficient algorithm that couples simulations of forward and adjoint transport equations. Forward random walks are first processed in stages, each using a fixed sample size, and information from stage k is used to alter the sampling and weighting procedure in stage k+1. This produces rapid geometric convergence and accounts for dramatic gains in the efficiency of the forward computation. In case still greater accuracy is required in the forward solution, information from an adjoint simulation can be added to extend the geometric learning of the forward solution. The resulting new approach should find widespread use when fast, accurate simulations of the transport equation are needed.

Kong Rong; Ambrose, Martin [Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711 (United States); Spanier, Jerome [Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711 (United States); Beckman Laser Institute and Medical Clinic, University of California, 1002 Health Science Road E., Irvine, CA 92612 (United States)], E-mail: jspanier@uci.edu

2008-11-20

460

Large-cell Monte Carlo renormalization of irreversible growth processes

NASA Technical Reports Server (NTRS)

Monte Carlo sampling is applied to a recently formulated direct-cell renormalization method for irreversible, disorderly growth processes. Large-cell Monte Carlo renormalization is carried out for various nonequilibrium problems based on the formulation dealing with relative probabilities. Specifically, the method is demonstrated by application to the 'true' self-avoiding walk and the Eden model of growing animals for d = 2, 3, and 4 and to the invasion percolation problem for d = 2 and 3. The results are asymptotically in agreement with expectations; however, unexpected complications arise, suggesting the possibility of crossovers, and in any case, demonstrating the danger of using small cells alone, because of the very slow convergence as the cell size b is extrapolated to infinity. The difficulty of applying the present method to the diffusion-limited-aggregation model, is commented on.

Nakanishi, H.; Family, F.

1985-01-01