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1

Annealing stochastic approximation Monte Carlo algorithm for neural network training  

Microsoft Academic Search

We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC can be regarded as a space annealing version of the stochastic approxi- mation Monte Carlo (SAMC) algorithm. Under mild conditions, we show that ASAMC can converge weakly at a rate of ?(1\\/ ? t) toward a neighboring set (in

Faming Liang

2007-01-01

2

Stochastic Series Expansion Quantum Monte Carlo  

NASA Astrophysics Data System (ADS)

This chapter outlines the fundamental construction of the Stochastic Series Expansion, a highly efficient and easily implementable quantum Monte Carlo method for quantum lattice models. Originally devised as a finite-temperature simulation based on a Taylor expansion of the partition function, the method has recently been recast in the formalism of a zero-temperature projector method, where a large power of the Hamiltonian is applied to a trial wavefunction to project out the groundstate. Although these two methods appear formally quite different, their implementation via non-local loop or cluster algorithms reveals their underlying fundamental similarity. Here, we briefly review the finite- and zero-temperature formalisms, and discuss concrete manifestations of the algorithm for the spin 1/2 Heisenberg and transverse field Ising models.

Melko, Roger G.

3

Optimization of Monte Carlo transport simulations in stochastic media  

SciTech Connect

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

4

Protein folding and phylogenetic tree reconstruction using stochastic approximation Monte Carlo  

E-print Network

Recently, the stochastic approximation Monte Carlo algorithm has been proposed by Liang et al. (2005) as a general-purpose stochastic optimization and simulation algorithm. An annealing version of this algorithm was developed for real small protein...

Cheon, Sooyoung

2007-09-17

5

Monte Carlo Simulations of Stochastic Differential Equations at the Example of the Forced Burgers' Equation  

NASA Astrophysics Data System (ADS)

We investigate the behaviour of stochastic differential equations, especially Burgers' equation, by means of Monte Carlo techniques. By analysis of the produced configurations, we show that direct and often intuitive insight into the fundamentals of the solutions to the underlying equation, like shock wave formation, intermittency and chaotic dynamics, can be obtained. We also demonstrate that very natural constraints for the lattice parameters are sufficient to ensure stable calculations for unlimited numbers of Monte Carlo steps.

Homeier, D.; Jansen, K.; Mesterhazy, D.; Urbach, C.

2008-11-01

6

Stochastic molecular dynamics: A combined Monte Carlo and molecular dynamics technique for isothermal simulations  

E-print Network

Stochastic molecular dynamics: A combined Monte Carlo and molecular dynamics technique for isothermal simulations Phil Attard Ian Wark Research Institute, University of South Australia, Mawson Lakes dynamics technique is developed that gives equations of motion for an isothermal system. Test results

Attard, Phil

7

Monte Carlo Simulations of Stochastic Differential Equations at the Example of the Forced Burgers' Equation  

Microsoft Academic Search

We investigate the behaviour of stochastic differential equations, especially Burgers' equation, by means of Monte Carlo techniques. By analysis of the produced configurations, we show that direct and often intuitive insight into the fundamentals of the solutions to the underlying equation, like shock wave formation, intermittency and chaotic dynamics, can be obtained. We also demonstrate that very natural constraints for

D. Homeier; K. Jansen; D. Mesterhazy; C. Urbach

2008-01-01

8

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

SciTech Connect

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

Monte Carlo Modeling  

NSDL National Science Digital Library

Monte Carlo modeling refers to the solution of mathematical problems with the use of random numbers. This can include both function integration and the modeling of stochastic phenomena using random processes.

Joiner, David; The Shodor Education Foundation, Inc.

10

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

SciTech Connect

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

11

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo  

PubMed Central

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.

2011-01-01

12

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

SciTech Connect

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

13

Quasi-Monte Carlo Sampling to improve the Efficiency of Monte Carlo EM  

E-print Network

Quasi-Monte Carlo Sampling to improve the Efficiency of Monte Carlo EM Wolfgang Jank Department@rhsmith.umd.edu November 17, 2003 Abstract In this paper we investigate an efficient implementation of the Monte Carlo EM al- gorithm based on Quasi-Monte Carlo sampling. The Monte Carlo EM algorithm is a stochastic version

Jank, Wolfgang

14

Monte Carlo methods Sequential Monte Carlo  

E-print Network

Monte Carlo methods Sequential Monte Carlo A. Doucet Carcans Sept. 2011 A. Doucet (MLSS Sept. 2011) Sequential Monte Carlo Sept. 2011 1 / 85 #12;Generic Problem Consider a sequence of probability distributions, Fn = Fn 1 F. A. Doucet (MLSS Sept. 2011) Sequential Monte Carlo Sept. 2011 2 / 85 #12;Generic Problem

Doucet, Arnaud

15

Monte Carlo Sampling Methods  

Microsoft Academic Search

In this chapter we discuss Monte Carlo sampling methods for solving large scale stochastic programming problems. We concentrate on the “exterior” approach where a random sample is generated outside of an optimization procedure, and then the constructed, so-called sample average approximation (SAA), problem is solved by an appropriate deterministic algorithm. We study statistical properties of the obtained SAA estimators. The

Alexander Shapiro

2003-01-01

16

Bayesian and non-bayesian analysis of gamma stochastic frontier models by Markov Chain Monte Carlo methods  

Microsoft Academic Search

Summary  This paper considers simulation-based approaches for the gamma stochastic frontier model. Efficient Markov chain Monte Carlo\\u000a methods are proposed for sampling the posterior distribution of the parameters. Maximum likelihood estimation is also discussed\\u000a based on the stochastic approximation algorithm. The methods are applied to a data set of the U.S. electric utility industry.

Hideo Kozumi; Xingyuan Zhang

2005-01-01

17

Stochastic analyses and Monte Carlo simulations of nonergodic solute transport in three-dimensional heterogeneous and statistically anisotropic aquifers  

Microsoft Academic Search

Stochastic analyses and Monte Carlo simulations were conducted for nonergodic transport of a nonreactive solute plume in three-dimensional heterogeneous and statistically anisotropic aquifers under uniform mean flow along the x axis. The hydraulic conductivity, K(x), is modeled as a random field which is assumed to be lognormally distributed with an anisotropic exponential covariance. The simulation model is validated with good

You-Kuan Zhang; Byong-min Seo

2004-01-01

18

A Comparison of Monte Carlo Particle Transport Algorithms for an Interior Source Binary Stochastic Medium Benchmark Suite  

SciTech Connect

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

19

Combining stochastics and analytics for a fast Monte Carlo decay chain generator  

NASA Astrophysics Data System (ADS)

Various Monte Carlo programs, developed either by small groups or widely available, have been used simulate decays of radioactive chains, from the original parent nucleus to the final stable isotopes. These chains include uranium, thorium, radon, and others, and generally have long-lived parent nuclei. Generating decays within these chains requires a certain amount of computing overhead related to simulating unnecessary decays, time-ordering the final results in post-processing, or both. We present a combination analytic/stochastic algorithm for creating a time-ordered set of decays with position and time correlations, and starting with an arbitrary source age. Thus the simulation costs are greatly reduced, while at the same time avoiding chronological post-processing. We discuss optimization methods within the approach to minimize calculation time, and extension of the algorithm to include various source types.

Kazkaz, K.; Walsh, N.

2011-10-01

20

Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models  

E-print Network

We present an efficient algorithm for the inference of stochastic block models in large networks. The algorithm can be used as an optimized Markov chain Monte Carlo (MCMC) method, with a fast mixing time and a much reduced susceptibility to getting trapped in metastable states, or as a greedy agglomerative heuristic, with an almost linear $O(N\\ln^2N)$ complexity, where $N$ is the number of nodes in the network, independent on the number of blocks being inferred. We show that the heuristic is capable of delivering results which are indistinguishable from the more exact and numerically expensive MCMC method in many artificial and empirical networks, despite being much faster. The method is entirely unbiased towards any specific mixing pattern, and in particular it does not favor assortative community structures.

Peixoto, Tiago P

2014-01-01

21

Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models.  

PubMed

We present an efficient algorithm for the inference of stochastic block models in large networks. The algorithm can be used as an optimized Markov chain Monte Carlo (MCMC) method, with a fast mixing time and a much reduced susceptibility to getting trapped in metastable states, or as a greedy agglomerative heuristic, with an almost linear O(Nln2N) complexity, where N is the number of nodes in the network, independent of the number of blocks being inferred. We show that the heuristic is capable of delivering results which are indistinguishable from the more exact and numerically expensive MCMC method in many artificial and empirical networks, despite being much faster. The method is entirely unbiased towards any specific mixing pattern, and in particular it does not favor assortative community structures. PMID:24580278

Peixoto, Tiago P

2014-01-01

22

Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models  

NASA Astrophysics Data System (ADS)

We present an efficient algorithm for the inference of stochastic block models in large networks. The algorithm can be used as an optimized Markov chain Monte Carlo (MCMC) method, with a fast mixing time and a much reduced susceptibility to getting trapped in metastable states, or as a greedy agglomerative heuristic, with an almost linear O (Nln2N) complexity, where N is the number of nodes in the network, independent of the number of blocks being inferred. We show that the heuristic is capable of delivering results which are indistinguishable from the more exact and numerically expensive MCMC method in many artificial and empirical networks, despite being much faster. The method is entirely unbiased towards any specific mixing pattern, and in particular it does not favor assortative community structures.

Peixoto, Tiago P.

2014-01-01

23

Sequential Monte Carlo simulation for the estimation of small reachability probabilities for stochastic hybrid systems  

E-print Network

Sequential Monte Carlo simulation for the estimation of small reachability probabilities the probability that a system reaches a given set within some time horizon is considered. Standard Monte Carlo methods for reachability probability estimation do not require specific assumptions on the system under

Del Moral , Pierre

24

Reduced Monte Carlo methods for the solution of stochastic groundwater flow problems  

NASA Astrophysics Data System (ADS)

Reduced order modeling is often employed to decrease the computational cost of numerical solutions of parametric Partial Differential Equations. Reduced basis, balanced truncation, projections methods are among the most studied techniques to achieve model reduction. We study the applicability of snapshot-based Proper Orthogonal Decomposition (POD) to Monte Carlo (MC) simulations applied to the solution of the stochastic groundwater flow problem. POD model reduction is obtained by projecting the model equations onto a space generated by a small number of basis functions (principal components). These are obtained upon exploring the solution (probability) space with snapshots, i.e., system states obtained by solving the original process-based equations. The reduced model is then employed to complete the ensemble by adding multiple realizations. We apply this technique to a two dimensional simulation of steady state saturated groundwater flow, and explore the sensitivity of the method to the number of snapshots and associated principal components in terms of accuracy and efficiency of the overall MC procedure. In our preliminary results, we distinguish the problem of heterogeneous recharge, in which the stochastic term is confined to the forcing function (additive stochasticity), from the case of heterogeneous hydraulic conductivity, in which the stochastic term is multiplicative. In the first scenario, the linearity of the problem is fully exploited and the POD approach yields accurate and efficient realizations, leading to substantial speed up of the MC method. The second scenario poses a significant challenge, as the adoption of a few snapshots based on the full model does not provide enough variability in the reduced order replicates, thus leading to poor convergence of the MC method. We find that increasing the number of snapshots improves the convergence of MC but only for large integral scales of the log-conductivity field. The technique is then extended to take full advantage of the solution of moment differential equations of groundwater flow.

Pasetto, D.; Guadagnini, A.; Putti, M.

2012-04-01

25

Graduiertenschule Hybrid Monte Carlo  

E-print Network

Graduiertenschule Hybrid Monte Carlo SS 2005 Heermann - Universit¨at Heidelberg Seite 1 #12;Graduiertenschule · In conventional Monte-Carlo (MC) calculations of condensed matter systems, such as an N probability distribution, unlike Monte-Carlo calculations. · The Hybrid Monte-Carlo (HMC) method combines

Heermann, Dieter W.

26

Monte Carlo Simulations to Calibrate and Validate Tank Experiments of Macrodispersion of Density-Dependent Transport in Stochastically Heterogeneous Media  

NASA Astrophysics Data System (ADS)

To calibrate and validate tank experiments of macrodispersion in density-dependent flow within a stochastically heterogeneous medium performed in a 10m long, 1.2m high and 0.1m wide Plexiglas tank at the University of Kassel over the last few years, numerous Monte Carlo simulations using the SUTRA density-dependent flow and transport model have been performed. Objective of this ongoing long-term study is the analysis of the effects of the stochastic properties of the porous medium on the steady-state macrodispersion, particularly, the transversal dispersion. The tank experiments have been set up to mimic density dependent flow under hydrodynamically stable conditions (horizontally stratified flow, whereby saltwater is injected horizontally into freshwater in the lower half of the tank). Numerous experiments with saltwater concentrations ranging from c_0 = 250 (fresh water) to c_0 =100000 ppm and three inflow velocities of u = 1,4 and 8 m/day each are carried out for three stochastic, anisotropically packed sand structures with different mean K_g, variance ?2, and horizontal and vertical correlation lengths ?_x, ?_z for the permeability variations. For each flow and transport experiment carried out in one tankpack, a large number of Monte Carlo simulations with stochastic realizations taken from the corresponding statistical family (with predefined K_g, ?2, ?_x, ?_z) are simulated under steady-state conditions. From moment analyses and laterals widths of the simulated saltwater plume, variances ?_D2 of lateral dispersion are calculated as a function of horizontal distance x from the tank inlet. Using simple square root regression analysis of ?_D2(x), an expectation value for the transversal dispersivity E(A_T) is then computed which should be representative for the particular medium family and the given flow conditions. One issue of particular interest concerns the number N of Monte Carlo simulations reqired to get an asymptotically stable value E(?_D2) or E(A_T). Although this number depends essentially on the variance ?2 of the heterogeneous medium, increasing with the latter, we find out that N = O(100), i.e. an order of magnitude less than what has been found in previously published Monte Carlo simulations of tracer-type macrodispersion in stochastically heterogeneous media. As for the physics of the macrodispersion process retrieved from both the experiments and the Monte Carlo simulations, we find reasonable agreement that, as expected, deterioriates somewhat as the density contrast and the variance of the permeability distribution of the porpus medium increase. Another aspect that will be discussed in detail is the different degree of sensitivity of the lateral macrodispersion to the various parameters describing the flow and the porous medium.

Starke, B.; Koch, M.

2005-12-01

27

Practical Markov Chain Monte Carlo  

Microsoft Academic Search

Markov chain Monte Carlo using the Metropolis-Hastings algorithm is a general method for the simulation of stochastic processes having probability densities known up to a constant of proportionality. Despite recent advances in its theory, the practice has remained controversial. This article makes the case for basing all inference on one long run of the Markov chain and estimating the Monte

Charles J. Geyer

1992-01-01

28

Evaluation of Monte Carlo Electron-Transport Algorithms in the Integrated Tiger Series Codes for Stochastic-Media Simulations  

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

29

Monte Carlo method based radiative transfer simulation of stochastic open forest generated by circle packing application  

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

30

Monte Carlo fundamentals  

SciTech Connect

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

31

STP Monte Carlo Estimation  

NSDL National Science Digital Library

The STP MonteCarloEstimation program estimates the area under the curve given by the square-root of (1-x^2) between 0 and 1 using the Monte Carlo hit and miss method. STP MonteCarloEstimation is part of a suite of Open Source Physics programs that model aspects of Statistical and Thermal Physics (STP). The program is distributed as a ready-to-run (compiled) Java archive. Double clicking the stp_MonteCarloEstimation.jar file will run the program if Java is installed on your computer.

Gould, Harvey; Tobochnik, Jan; Christian, Wolfgang; Cox, Anne

2009-01-26

32

Monte Carlo Planning in RTS Games  

Microsoft Academic Search

Monte Carlo simulations have been success- fully used in classic turn-based games such as backgam- mon, bridge, poker, and Scrabble. In this paper, we ap- ply the ideas to the problem of planning in games with imperfect information, stochasticity, and simultaneous moves. The domain we consider is real-time strategy games. We present a framework — MCPlan — for Monte Carlo

Michael Chung; Michael Buro; Jonathan Schaeffer

2005-01-01

33

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

34

Quantum Monte Carlo for minimum energy structures  

E-print Network

We present an efficient method to find minimum energy structures using energy estimates from accurate quantum Monte Carlo calculations. This method involves a stochastic process formed from the stochastic energy estimates from Monte Carlo that can be averaged to find precise structural minima while using inexpensive calculations with moderate statistical uncertainty. We demonstrate the applicability of the algorithm by minimizing the energy of the H2O-OH- complex and showing that the structural minima from quantum Monte Carlo calculations affect the qualitative behavior of the potential energy surface substantially.

Lucas K. Wagner; Jeffrey C. Grossman

2010-05-03

35

Monte Carlo methods Monte Carlo Principle and MCMC  

E-print Network

Monte Carlo methods Monte Carlo Principle and MCMC A. Doucet Carcans Sept. 2011 A. Doucet (MLSS Sept. 2011) MCMC Sept. 2011 1 / 91 #12;Overview of the Lectures 1 Monte Carlo Principles A. Doucet (MLSS Sept. 2011) MCMC Sept. 2011 2 / 91 #12;Overview of the Lectures 1 Monte Carlo Principles 2 Markov

Doucet, Arnaud

36

An ecien t Markov chain Monte Carlo simulation of a stochastic inverse radiation problem  

Microsoft Academic Search

A novel methodology that combines recent advances in computational statistics and reduced-order modeling is presented to explore the application of Bayesian statistical infer- ence to a stochastic inverse problem in radiative heat transfer. The underlying objective of this work is to reveal the potential of using statistical approaches, mainly Bayesian com- putational statistics and spatial statistics, to solve data-driven stochastic

Jingbo Wang; Nicholas Zabaras

37

Monte Carlo methods: Application to hydrogen gas and hard spheres  

Microsoft Academic Search

Quantum Monte Carlo (QMC) methods are among the most accurate for computing ground state properties of quantum systems. The two major types of QMC we use are Variational Monte Carlo (VMC), which evaluates integrals arising from the variational principle, and Diffusion Monte Carlo (DMC), which stochastically projects to the ground state from a trial wave function. These methods are applied

Mark Douglas Dewing

2001-01-01

38

Application of Monte Carlo Chord-Length Sampling Algorithms to Transport Through a 2-D Binary Stochastic Mixture  

SciTech Connect

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

39

Stochastic Inversion of Electrical Resistivity Changes Using a Markov Chain, Monte Carlo Approach  

Microsoft Academic Search

We describe a stochastic inversion method for mapping subsurface regions where the electrical resistivity is changing. The technique combines prior information, electrical resistance data and forward models to produce subsurface resistivity models that are most consistent with all available data. Bayesian inference and a Metropolis simulation algorithm form the basis for this approach. Attractive features include its ability to: (1)

A Ramirez; J Nitao; W Hanley; R Aines; R Glaser; S Sengupta; K Dyer; T Hickling; W Daily

2004-01-01

40

Stochastic inversion of electrical resistivity changes using a Markov Chain Monte Carlo approach  

Microsoft Academic Search

We describe a stochastic inversion method for mapping subsurface regions where the electrical resistivity is changing. The technique combines prior information, electrical resistance data, and forward models to produce subsurface resistivity models that are most consistent with all available data. Bayesian inference and a Metropolis simulation algorithm form the basis for this approach. Attractive features include its ability (1) to

A. L. Ramirez; J. J. Nitao; W. G. Hanley; R. Aines; R. E. Glaser; S. K. Sengupta; K. M. Dyer; T. L. Hickling; W. D. Daily

2005-01-01

41

Shell model Monte Carlo methods  

SciTech Connect

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

42

Error in Monte Carlo, quasi-error in Quasi-Monte Carlo  

E-print Network

While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of each other and, therefore, fails to account for the error improvement advertised by the Quasi-Monte Carlo method. We advocate the construction of an estimator of stochastic nature, based on the ensemble of pointsets with a particular discrepancy value. We investigate the consequences of this choice and give some first empirical results on the suggested estimators.

R. H. Kleiss; A. Lazopoulos

2005-04-12

43

Quantum Monte Carlo Calculations for Minimum Energy Structures  

E-print Network

We present an efficient method to find minimum energy structures using energy estimates from accurate quantum Monte Carlo calculations. This method involves a stochastic process formed from the stochastic energy estimates ...

Grossman, Jeffrey C.

44

Stochastic Inversion of Electrical Resistivity Changes Using a Markov Chain, Monte Carlo Approach  

SciTech Connect

We describe a stochastic inversion method for mapping subsurface regions where the electrical resistivity is changing. The technique combines prior information, electrical resistance data and forward models to produce subsurface resistivity models that are most consistent with all available data. Bayesian inference and a Metropolis simulation algorithm form the basis for this approach. Attractive features include its ability to: (1) provide quantitative measures of the uncertainty of a generated estimate and, (2) allow alternative model estimates to be identified, compared and ranked. Methods that monitor convergence and summarize important trends of the posterior distribution are introduced. Results from a physical model test and a field experiment were used to assess performance. The stochastic inversions presented provide useful estimates of the most probable location, shape, and volume of the changing region, and the most likely resistivity change. The proposed method is computationally expensive, requiring the use of extensive computational resources to make its application practical.

Ramirez, A; Nitao, J; Hanley, W; Aines, R; Glaser, R; Sengupta, S; Dyer, K; Hickling, T; Daily, W

2004-09-21

45

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

46

Baseball Monte Carlo Style.  

ERIC Educational Resources Information Center

Monte Carlo methods are used to simulate activities in baseball such as a team's "hot streak" and a hitter's "batting slump." Student participation in such simulations is viewed as a useful method of giving pupils a better understanding of the probability concepts involved. (MP)

Houser, Larry L.

1981-01-01

47

Monte Carlo Neutrino Oscillations  

E-print Network

We demonstrate that the effects of matter upon neutrino propagation may be recast as the scattering of the initial neutrino wavefunction. Exchanging the differential, Schrodinger equation for an integral equation for the scattering matrix S permits a Monte Carlo method for the computation of S that removes many of the numerical difficulties associated with direct integration techniques.

James P. Kneller; Gail C. McLaughlin

2005-09-29

48

Monte Carlo neutrino oscillations  

SciTech Connect

We demonstrate that the effects of matter upon neutrino propagation may be recast as the scattering of the initial neutrino wave function. Exchanging the differential, Schrodinger equation for an integral equation for the scattering matrix S permits a Monte Carlo method for the computation of S that removes many of the numerical difficulties associated with direct integration techniques.

Kneller, James P. [Department of Physics, North Carolina State University, Raleigh, North Carolina 27695-8202 (United States); School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455 (United States); McLaughlin, Gail C. [Department of Physics, North Carolina State University, Raleigh, North Carolina 27695-8202 (United States)

2006-03-01

49

Monte-Carlo Go Developments  

Microsoft Academic Search

Abstract Introducing the original ideas of using Monte-Carlo simulation in computer Go. Adding new ideas to pure Monte-Carlo approach for computer Go. • Progressive pruning • All moves as first heuristic • Temperature • Simulated annealing • Depth-2 tree search Conclusion: • With the ever-increasing power of computers, we can add more knowl- edge to the Monte-Carlo approach to get

B. Bouzy; B. Helmstetter; Tsan-sheng Hsu

50

Monte Carlo photon benchmark problems  

SciTech Connect

Photon benchmark calculations have been performed to validate the MCNP Monte Carlo computer code. These are compared to both the COG Monte Carlo computer code and either experimental or analytic results. The calculated solutions indicate that the Monte Carlo method, and MCNP and COG in particular, can accurately model a wide range of physical problems.

Whalen, D.J.; Hollowell, D.E.; Hendricks, J.S.

1991-01-01

51

Monte Carlo photon benchmark problems  

SciTech Connect

Photon benchmark calculations have been performed to validate the MCNP Monte Carlo computer code. These are compared to both the COG Monte Carlo computer code and either experimental or analytic results. The calculated solutions indicate that the Monte Carlo method, and MCNP and COG in particular, can accurately model a wide range of physical problems. 8 refs., 5 figs.

Whalen, D.J. (Brigham Young Univ., Provo, UT (USA)); Hollowell, D.E.; Hendricks, J.S. (Los Alamos National Lab., NM (USA))

1990-01-01

52

Quantum Monte Carlo Helsinki 2011  

E-print Network

Quantum Monte Carlo Helsinki 2011 Marius Lewerenz MSME/CT, UMR 8208 CNRS, Universit´e Paris Est? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 What is a Monte Carlo method? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3 What are Monte Carlo methods good for? . . . . . . . . . . . . . . . . . . . . . . . 5 1

Boyer, Edmond

53

Monte-Carlo Tests Diplomarbeit  

E-print Network

Monte-Carlo Tests Diplomarbeit Wiebke Werft Mathematisches Institut der Heinrich.2 Suffizienz und Vollständigkeit . . . . . . . . . . . . . . . . . . . . 5 2 Monte-Carlo Tests 8 2.1 Formulierung des Testproblems . . . . . . . . . . . . . . . . . . . 8 2.2 Definition des Monte-Carlo Tests

54

Experiments with Monte Carlo Othello  

Microsoft Academic Search

In this paper, we report on our experiments with using Monte Carlo simulation (specifically the UCT algorithm) as the basis for an Othello playing program. Monte Carlo methods have been used for other games in the past, most recently and notably in successful Go playing programs. We show that Monte Carlo-based players have potential for Othello, and that evolutionary algorithms

Philip Hingston; Martin Masek

2007-01-01

55

Monte Carlo Event Generators  

NASA Astrophysics Data System (ADS)

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

2011-10-01

56

Diffusion Monte Carlo Method on Curved Manifolds  

Microsoft Academic Search

We present a stochastic approach to solving the many-body Schrödinger equation on curved manifolds with general metric. The method is based on the Diffusion Monte Carlo (DMC) technique, modified to include `quantum corrections' into the propagator which appear due to the curvature. As an illustration of our method we apply it to the quantum Hall effect, using the spherical geometry

V. Melik-Alaverdian; N. E. Bonesteel; G. Ortiz

1997-01-01

57

Reflexive Monte-Carlo Search  

Microsoft Academic Search

Reflexive Monte-Carlo search uses the Monte-Carlo search of a given level to improve the search of the upper level. We describe the application to Morpion Solitaire. For the non touching version, reflexive M onte-Carlo search breaks the current record and establishes a new record of 78 moves.

Tristan Cazenave

58

Monte Carlo Event Generators  

E-print Network

Monte Carlo event generators are essential components of almost all experimental analyses and are also widely used by theorists and experiments to make predictions and preparations for future experiments. They are all too often used as "black boxes", without sufficient consideration of their component models or their reliability. In this set of three lectures we hope to open the box and explain the physical bases behind the models they use. We focus primarily on the general features of parton showers, hadronization and underlying event generation.

Michael H. Seymour; Marilyn Marx

2013-04-24

59

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

60

Multicanonical Multigrid Monte Carlo  

E-print Network

To further improve the performance of Monte Carlo simulations of first-order phase transitions we propose to combine the multicanonical approach with multigrid techniques. We report tests of this proposition for the $d$-dimensional $\\Phi^4$ field theory in two different situations. First, we study quantum tunneling for $d = 1$ in the continuum limit, and second, we investigate first-order phase transitions for $d = 2$ in the infinite volume limit. Compared with standard multicanonical simulations we obtain improvement factors of several resp. of about one order of magnitude.

W. Janke; T. Sauer

1993-05-20

61

Quantum Gibbs ensemble Monte Carlo  

NASA Astrophysics Data System (ADS)

We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs ensemble Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs ensemble Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of 4He in two dimensions.

Fantoni, Riccardo; Moroni, Saverio

2014-09-01

62

MONTE CARLO EXTENSION OF QUASIMONTE CARLO Art B. Owen  

E-print Network

MONTE CARLO EXTENSION OF QUASI­MONTE CARLO Art B. Owen Department of Statistics Stanford University Stanford CA 94305, U.S.A. ABSTRACT This paper surveys recent research on using Monte Carlo techniques to improve quasi­Monte Carlo tech­ niques. Randomized quasi­Monte Carlo methods pro­ vide a basis for error

Owen, Art

63

Secondproofs Monte Carlo and Quasi-Monte Carlo Methods 2008  

E-print Network

Pierre L'Ecuyer r Art B. Owen Editors Monte Carlo and Quasi-Monte Carlo Methods 2008 #12;Secondproofs lecuyer@iro.umontreal.ca Art B. Owen Department of Statistics Stanford University Sequoia Hall Stanford, CA 94305 USA owen@stanford.edu ISBN 978-3-642-04106-8 DOI 10.1007/978-3-642-04107-5 e-ISBN978

L'Ecuyer, Pierre

64

Monte Carlo and Quasi-Monte Carlo algorithms for the Barker-Ferry equation with low  

E-print Network

Monte Carlo and Quasi-Monte Carlo algorithms for the Barker-Ferry equation with low complexity ? T. The quasi-Monte Carlo (QMC) solutions obtained by QRNs are compared with the Monte Carlo (MC) solutions) converges [3] and the solution can be evaluated by a MC estimator. 2 Monte Carlo and Quasi-Monte Carlo

Whitlock, Paula

65

DEVELOPMENTS ON MONTE CARLO GO  

Microsoft Academic Search

We have developed two go programs, Olga and Oleg, using a Monte Carlo ap- proach, simpler than Bruegmann's (Bruegmann, 1993), and based on (Abramson, 1990). We have set up experiments to assess ideas such as progressive pruning, transpositions, temperature, simulated annealing and depth-two tree search within the Monte Carlo framework. We have shown that progressive pruning alone gives better results

Bruno Bouzy; Bernard Helmstetter

66

MCMini: Monte Carlo on GPGPU  

SciTech Connect

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

67

Efficient Scores, Variance Decompositions and Monte Carlo Swindles.  

National Technical Information Service (NTIS)

Monte Carlo swindles or variance reduction techniques exploit the experimenter's knowledge of the stochastic structure governing the simulated data to construct more precise estimates of unknown parameters. Alternatively, one can reduce the number of repl...

I. Johnstone, P. Velleman

1984-01-01

68

Fermion Monte Carlo  

SciTech Connect

We review the fundamental challenge of fermion Monte Carlo for continuous systems, the "sign problem". We seek that eigenfunction of the many-body Schriodinger equation that is antisymmetric under interchange of the coordinates of pairs of particles. We describe methods that depend upon the use of correlated dynamics for pairs of correlated walkers that carry opposite signs. There is an algorithmic symmetry between such walkers that must be broken to create a method that is both exact and as effective as for symmetric functions, In our new method, it is broken by using different "guiding" functions for walkers of opposite signs, and a geometric correlation between steps of their walks, With a specific process of cancellation of the walkers, overlaps with antisymmetric test functions are preserved. Finally, we describe the progress in treating free-fermion systems and a fermion fluid with 14 3He atoms.

Kalos, M. H.; Pederiva, F.

1998-12-01

69

Parallelizing Monte Carlo with PMC  

SciTech Connect

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

70

Generic stochastic Monte Carlo model of the photoinduced mass transport in azo-polymers and fine structure of Surface Relief Gratings  

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

71

ORIE 5582: Monte Carlo Methods in Financial Engineering This course covers the principles of derivative pricing, generation of sample paths and  

E-print Network

ORIE 5582: Monte Carlo Methods in Financial Engineering This course covers the principles, 2009 Prerequisites ORIE 5581 (Monte Carlo Simulation) ORIE 5600 (Stochastic calculus) Instructor Peter books may prove helpful. Monte Carlo Methods in Financial Engineering. P. Glasserman. Springer

Keinan, Alon

72

Monte-Carlo Go Developments  

Microsoft Academic Search

We describe two Go programs, and , developed by a Monte-Carlo approach that is simpler than Bruegmann's (1993) approach. Our method is based on Abramson (1990). We performed experiments to assess ideas on (1) progressive pruning, (2) all moves as first heuristic, (3) temperature, (4) simu- lated annealing, and (5) depth-two tree search within the Monte-Carlo frame- work. Progressive pruning

Bruno Bouzy; Bernard Helmstetter

2003-01-01

73

Monte Carlo Methods for Inference and Learning  

E-print Network

Monte Carlo Methods for Inference and Learning Guest Lecturer: Ryan Adams CSC 2535 http://www.cs.toronto.edu/~rpa #12;Overview ·Monte Carlo basics ·Rejection and Importance sampling ·Markov chain Monte Carlo ·Metropolis-Hastings and Gibbs sampling ·Slice sampling ·Hamiltonian Monte Carlo #12;Computing Expectations We

Hinton, Geoffrey E.

74

Monte Carlo and Quasi-Monte Carlo for Art B. Owen  

E-print Network

Monte Carlo and Quasi-Monte Carlo for Statistics Art B. Owen Abstract This article reports Monte Carlo methods can be used. There was a special emphasis on areas where Quasi-Monte Carlo ideas This survey is aimed at exposing good problems in statistics to researchers in Quasi- Monte Carlo. It has

Owen, Art

75

Monte Carlo Methods for Computation and Optimization (048715) Winter 2013/4  

E-print Network

Monte Carlo Methods for Computation and Optimization (048715) Winter 2013/4 Lecture Notes Nahum Shimkin i #12;PREFACE These lecture notes are intended for a first, graduate-level, course on Monte-Carlo, Simulation and the Monte Carlo Method, Wiley, 2008. (2) S. Asmussen and P. Glynn, Stochastic Simulation

Shimkin, Nahum

76

Quantum Monte Carlo simulation of thin magnetic films P. Henelius,1,  

E-print Network

Quantum Monte Carlo simulation of thin magnetic films P. Henelius,1, * P. Fro¨brich,2,3 P. J. Kuntz Received 30 April 2002; published 6 September 2002 The stochastic series expansion quantum Monte Carlo theoretical approaches above differ significantly from each other, and the Monte Carlo method is free

von Oppen, Felix

77

Application of Monte Carlo Chord-Length Sampling Algorithms to Transport Through a Two-Dimensional Binary Stochastic Mixture  

E-print Network

-Dimensional Binary Stochastic Mixture Timothy J. Donovan* Lockheed Martin Corporation P.O. Box 1072, Schenectady, New through the boundaries of a two-dimensional binary stochastic material. The mixture is specified within (CLS) to eliminate the need to explicitly model the geometry of the mixture. Two variations

Danon, Yaron

78

Monte Carlo Simulation of Interacting Electron Models  

E-print Network

Monte Carlo Simulation of Interacting Electron Models by a New Determinant Approach by Mucheng discusses the calculation of determinants and Monte Carlo simulation of Hub- bard models by a new and a Monte Carlo summation algorithm to evaluate the relevant diagram determinant sums. Index words: Monte

Robinson, Robert W.

79

Monte-Carlo Proof-Number Search for Computer Go  

Microsoft Academic Search

In the last decade, proof-number search and Monte-Carlo methods have successfully been applied to the combinatorial-games do- main. Proof-number search is a reliable algorithm. It requires a well defined goal to prove. This can be seen as a disadvantage. In contrast to proof-number search, Monte-Carlo evaluation is a flexible stochastic evaluation for game-tree search. In order to improve the efficiency

Jahn-takeshi Saito; Guillaume Chaslot; Jos W. H. M. Uiterwijk; H. Jaap Van Den Herik

2006-01-01

80

Monte Carlo integration on GPU  

E-print Network

We use a graphics processing unit (GPU) for fast computations of Monte Carlo integrations. Two widely used Monte Carlo integration programs, VEGAS and BASES, are parallelized on GPU. By using $W^{+}$ plus multi-gluon production processes at LHC, we test integrated cross sections and execution time for programs in FORTRAN and C on CPU and those on GPU. Integrated results agree with each other within statistical errors. Execution time of programs on GPU run about 50 times faster than those in C, and more than 60 times faster than the original FORTRAN programs.

J. Kanzaki

2010-10-11

81

First principles quantum Monte Carlo  

E-print Network

Present quantum Monte Carlo codes use statistical techniques adapted to find the amplitude of a quantum system or the associated eigenvalues. Thus, they do not use a true physical random source. It is demonstrated that, in fact, quantum probability admits a description based on a specific class of random process at least for the single particle case. Then a first principle Monte Carlo code that exactly simulates quantum dynamics can be constructed. The subtle question concerning how to map random choices in amplitude interferences is explained. Possible advantages of this code in simulating single hit experiments are discussed.

J. M. A. Figueiredo

2005-10-06

82

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

83

A Monte Carlo approach to water management  

NASA Astrophysics Data System (ADS)

Common methods for making optimal decisions in water management problems are insufficient. Linear programming methods are inappropriate because hydrosystems are nonlinear with respect to their dynamics, operation constraints and objectives. Dynamic programming methods are inappropriate because water management problems cannot be divided into sequential stages. Also, these deterministic methods cannot properly deal with the uncertainty of future conditions (inflows, demands, etc.). Even stochastic extensions of these methods (e.g. linear-quadratic-Gaussian control) necessitate such drastic oversimplifications of hydrosystems that may make the obtained results irrelevant to the real world problems. However, a Monte Carlo approach is feasible and can form a general methodology applicable to any type of hydrosystem. This methodology uses stochastic simulation to generate system inputs, either unconditional or conditioned on a prediction, if available, and represents the operation of the entire system through a simulation model as faithful as possible, without demanding a specific mathematical form that would imply oversimplifications. Such representation fully respects the physical constraints, while at the same time it evaluates the system operation constraints and objectives in probabilistic terms, and derives their distribution functions and statistics through Monte Carlo simulation. As the performance criteria of a hydrosystem operation will generally be highly nonlinear and highly nonconvex functions of the control variables, a second Monte Carlo procedure, implementing stochastic optimization, is necessary to optimize system performance and evaluate the control variables of the system. The latter is facilitated if the entire representation is parsimonious, i.e. if the number of control variables is kept at a minimum by involving a suitable system parameterization. The approach is illustrated through three examples for (a) a hypothetical system of two reservoirs performing a variety of functions, (b) the water resource system of Athens comprising four reservoirs and many aqueducts, and (c) a human-modified inadequately measured basin in which the parameter fitting of a hydrological model is sought.

Koutsoyiannis, D.

2012-04-01

84

Monte Carlo calculations of nuclei  

SciTech Connect

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

85

Heuristics in Monte Carlo Go  

Microsoft Academic Search

Writing programs to play the classical Asian game of Go is considered one of the grand challenges of artifi- cial intelligence. Traditional game tree search methods have failed to conquer Go because the search space is so vast and because static evaluation of board posi- tions is extremely difficult. There has been consider- able progress recently in using Monte Carlo

Peter Drake; Steve Uurtamo

2007-01-01

86

Monte Carlo for the LHC  

E-print Network

I review the status of the general-purpose Monte Carlo event generators for the LHC, with emphasis on areas of recent physics developments. There has been great progress, especially in multi-jet simulation, but I mention some question marks that have recently arisen.

Michael H. Seymour

2010-08-17

87

Monte Carlo Estimation for Pi  

NSDL National Science Digital Library

This is the description and instructions for the Monte Carlo Estimation of Pi applet. It is a simulation of throwing darts at a figure of a circle inscribed in a square. It shows the relationship between the geometry of the figure and the statistical outcome of throwing the darts.

Mcgath, Gary; Trunfio, Paul

1996-01-01

88

Is Monte Carlo embarrassingly parallel?  

SciTech Connect

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)

2012-07-01

89

Jet evolution and Monte Carlo  

E-print Network

In this lecture I discuss jet-shape distributions and describe how from jet evolution one may design Monte Carlo simulations which are used in the analysis of short distance distributions in $\\ee$-annihilation, lepton-hadron and hadron-hadron collisions

Giuseppe Marchesini

2005-01-24

90

Monte Carlo techniques for real-time quantum dynamics  

E-print Network

The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the "weight", and its magnitude is related to the importance of the stochastic trajectory. We investigate the use of Monte Carlo algorithms to improve the sampling of the weighted trajectories and thus reduce sampling error in a simulation of quantum dynamics. The method can be applied to calculations in real time, as well as imaginary time for which Monte Carlo algorithms are more-commonly used. The method is applicable when the weight is guaranteed to be real, and we demonstrate how to ensure this is the case. Examples are given for the anharmonic oscillator, where large improvements over stochastic sampling are observed.

Mark R. Dowling; Matthew J. Davis; Peter D. Drummond; Joel F. Corney

2005-07-01

91

Monte-Carlo Exploration for Deterministic Planning  

Microsoft Academic Search

Search methods based on Monte-Carlo simulation have recently led to breakthrough performance im- provements in difficult game-playing domains such as Go and General Game Playing. Monte-Carlo Random Walk (MRW) planning applies Monte- Carlo ideas to deterministic classical planning. In the forward chaining planner ARVAND, Monte- Carlo random walks are used to explore the local neighborhood of a search state for

Hootan Nakhost; Martin Müller

2009-01-01

92

Population Monte Carlo Methods/OFPR/CREST/May 5, 2003 1 Population Monte Carlo Methods  

E-print Network

Population Monte Carlo Methods/OFPR/CREST/May 5, 2003 1 Population Monte Carlo Methods Christian P. Robert Universit´e Paris Dauphine #12;Population Monte Carlo Methods/OFPR/CREST/May 5, 2003 2 1 A Benchmark example #12;Population Monte Carlo Methods/OFPR/CREST/May 5, 2003 3 Even simple models may lead

Robert, Christian P.

93

Towards Monte Carlo Simulations on Large Nuclei August 2014 Towards Monte Carlo Simulations on Large Nuclei  

E-print Network

Towards Monte Carlo Simulations on Large Nuclei � August 2014 Towards Monte Carlo Simulations published method to compute properties on neutron matter using variational Monte Carlo simulations published a method of performing variational Monte Carlo calculations on neutron matter comprised of up

Washington at Seattle, University of - Department of Physics, Electroweak Interaction Research Group

94

Parallel Monte Carlo Simulation for control system design  

NASA Technical Reports Server (NTRS)

The research during the 1993/94 academic year addressed the design of parallel algorithms for stochastic robustness synthesis (SRS). SRS uses Monte Carlo simulation to compute probabilities of system instability and other design-metric violations. The probabilities form a cost function which is used by a genetic algorithm (GA). The GA searches for the stochastic optimal controller. The existing sequential algorithm was analyzed and modified to execute in a distributed environment. For this, parallel approaches to Monte Carlo simulation and genetic algorithms were investigated. Initial empirical results are available for the KSR1.

Schubert, Wolfgang M.

1995-01-01

95

Advanced Monte Carlo Methods: American Options  

E-print Network

doesn't fit well with Monte Carlo methods which go forwards in time American options ­ p. 4 #12;ProblemAdvanced Monte Carlo Methods: American Options Prof. Mike Giles mike.giles@maths.ox.ac.uk Oxford for Monte Carlo methods is the accurate and efficient pricing of options with optional early exercise

Giles, Mike

96

Monte-Carlo Game Tree Search  

Microsoft Academic Search

Abstract Introducing the original ideas of using Monte-Carlo simulation in computer Go. Adding new ideas to pure Monte-Carlo approach for computer Go. • Progressive pruning • All moves as first heuristic • Temperature • Simulated annealing • Depth-2 tree search Parallel Monte-Carlo tree search Conclusion: • With the ever-increasing power of computers, we can add more knowl- edge to the

Tsan-sheng Hsu

97

Monte Carlo simulations in SPET and PET  

Microsoft Academic Search

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

98

Advanced Monte Carlo Methods: American Options  

E-print Network

backwards in time doesn't fit well with Monte Carlo methods which go forwards in time American options ­ pAdvanced Monte Carlo Methods: American Options Prof. Mike Giles mike.giles@maths.ox.ac.uk Oxford for Monte Carlo methods is the accurate and efficient pricing of options with optional early exercise

Giles, Mike

99

Monte Carlo Go Using Previous Simulation Results  

Microsoft Academic Search

The researches on Go using Monte Carlo method are treated as hot topics in these years. In particular, Monte Carlo Tree Search algorithm such as UCT made great contributions to the development of computer Go. When Monte Carlo method was used for Go, the previous simulation results were not usually stored. In this paper, we suggest a new idea of

Takuma TOYODA; Yoshiyuki KOTANI

2010-01-01

100

Monte Carlo Simulations of Model Nonionic Surfactants  

E-print Network

Monte Carlo Simulations of Model Nonionic Surfactants A.P. Chatterjee and A.Z. Panagiotopoulos was studied by histogram reweight- ing grand canonical Monte Carlo simulations. Two di erent sets of site volume fractions using lattice Monte Carlo simulations performed in the canonical constant NV T ensemble

101

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

102

A Monte Carlo Study of Titrating Polyelectrolytes  

E-print Network

A Monte Carlo Study of Titrating Polyelectrolytes Magnus Ullnery and Bo Jonssonz Physical Chemistry Journal of Chemical Physics 104, 3048-3057 (1996) Monte Carlo simulations have been used to study three di the conformations towards more extended structures. In the Monte Carlo simulations presented here, focus

Peterson, Carsten

103

A Monte Carlo Study of Titrating Polyelectrolytes  

E-print Network

A Monte Carlo Study of Titrating Polyelectrolytes Magnus Ullner y and Bo J¨onsson z Physical, Sweden Journal of Chemical Physics 104, 3048­3057 (1996) Monte Carlo simulations have been used to study of the polymer more difficult and biases the conformations towards more extended structures. In the Monte Carlo

Peterson, Carsten

104

Monte Carlo Methods in Statistics Christian Robert  

E-print Network

Monte Carlo Methods in Statistics Christian Robert Universit´e Paris Dauphine and CREST, INSEE September 2, 2009 Monte Carlo methods are now an essential part of the statistician's toolbox, to the point! We recall in this note some of the advances made in the design of Monte Carlo techniques towards

Boyer, Edmond

105

Monte Carlo Integration Lecture 2 The Problem  

E-print Network

Monte Carlo Integration Lecture 2 The Problem Let be a probability measure over the Borel -field X S and h(x) = 0 otherwise. #12;Monte Carlo Integration Lecture 2 When the problem appears to be intractable, Press et al (1992) and reference therein). For high dimensional problems, Monte Carlo methods have

Liang, Faming

106

MONTE CARLO METHOD AND SENSITIVITY ESTIMATIONS  

E-print Network

MONTE CARLO METHOD AND SENSITIVITY ESTIMATIONS A. de Lataillade a;#3; , S. Blanco b , Y. Clergent b on a formal basis and simple radiative transfer examples are used for illustration. Key words: Monte Carlo submitted to Elsevier Science 18 February 2002 #12; 1 Introduction Monte Carlo methods are commonly used

Dufresne, Jean-Louis

107

The monte carlo newton-raphson algorithm  

Microsoft Academic Search

It is shown that the Monte Carlo Newton-Raphson algorithm is a viable alternative to the Monte Carlo EM algorithm for finding maximum likelihood estimates based on incomplete data. Both Monte Carlo procedures require simulations from the conditional distribution of the missing data given the observed data with the aid of methods like Gibbs sampling and rejective sampling. The Newton-Raphson algorithm

Anthony Y. C. Kuk; Yuk W. Cheng

1997-01-01

108

Thermodynamic Scaling Gibbs Ensemble Monte Carlo  

E-print Network

Thermodynamic Scaling Gibbs Ensemble Monte Carlo: A new method for determination of phase for correspondence. E­mail:azp2@cornell.edu #12; We combine Valleau's thermodynamic scaling Monte Carlo concept Monte Carlo simulations. There has been significant recent progress in molecular simulation method

109

Comparative Monte Carlo Efficiency by Monte Carlo Analysis  

E-print Network

We propose a modified power method for computing the subdominant eigenvalue $\\lambda_2$ of a matrix or continuous operator. Here we focus on defining simple Monte Carlo methods for its application. The methods presented use random walkers of mixed signs to represent the subdominant eigenfuction. Accordingly, the methods must cancel these signs properly in order to sample this eigenfunction faithfully. We present a simple procedure to solve this sign problem and then test our Monte Carlo methods by computing the $\\lambda_2$ of various Markov chain transition matrices. We first computed ${\\lambda_2}$ for several one and two dimensional Ising models, which have a discrete phase space, and compared the relative efficiencies of the Metropolis and heat-bath algorithms as a function of temperature and applied magnetic field. Next, we computed $\\lambda_2$ for a model of an interacting gas trapped by a harmonic potential, which has a mutidimensional continuous phase space, and studied the efficiency of the Metropolis ...

Rubenstein, B M; Doll, J D

2010-01-01

110

Application of Monte Carlo techniques to optimization of high-energy beam transport in a stochastic environment  

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

111

Estimation and Inferencevia Bayesian Simulation: An Introduction to Markov Chain Monte Carlo  

E-print Network

Estimation and Inferencevia Bayesian Simulation: An Introduction to Markov Chain Monte Carlo Simon manifestations of paranoia. Things have changed. ... P. Clifford (1993,53) arkov Chain Monte Carlo (MCMC) methods a class of methods for estimation and inference via stochastic simulation known as Markov Chain Monte

Gribble, Paul

112

Electronic structure quantum Monte Carlo  

NASA Astrophysics Data System (ADS)

Quantum Monte Carlo (QMC) is an advanced simulation methodology for studies of manybody quantum systems. The QMC approaches combine analytical insights with stochastic computational techniques for efficient solution of several classes of important many-body problems such as the stationary Schrödinger equation. QMC methods of various flavors have been applied to a great variety of systems spanning continuous and lattice quantum models, molecular and condensed systems, BEC-BCS ultracold condensates, nuclei, etc. In this review, we focus on the electronic structure QMC, i.e., methods relevant for systems described by the electron-ion Hamiltonians. Some of the key QMC achievements include direct treatment of electron correlation, accuracy in predicting energy differences and favorable scaling in the system size. Calculations of atoms, molecules, clusters and solids have demonstrated QMC applicability to real systems with hundreds of electrons while providing 90-95% of the correlation energy and energy differences typically within a few percent of experiments. Advances in accuracy beyond these limits are hampered by the so-called fixed-node approximation which is used to circumvent the notorious fermion sign problem. Many-body nodes of fermion states and their properties have therefore become one of the important topics for further progress in predictive power and efficiency of QMC calculations. Some of our recent results on the wave function nodes and related nodal domain topologies will be briefly reviewed. This includes analysis of few-electron systems and descriptions of exact and approximate nodes using transformations and projections of the highly-dimensional nodal hypersurfaces into the 3D space. Studies of fermion nodes offer new insights into topological properties of eigenstates such as explicit demonstrations that generic fermionic ground states exhibit the minimal number of two nodal domains. Recently proposed trial wave functions based on Pfaffians with pairing orbitals are presented and their nodal properties are tested in calculations of first row atoms and molecules. Finally, backflow "dressed" coordinates are introduced as another possibility for capturing correlation effects and for decreasing the fixed-node bias.

Bajdich, Michal; Mitas, Lubos

2009-04-01

113

Kinematics of Multigrid Monte Carlo  

E-print Network

We study the kinematics of multigrid Monte Carlo algorithms by means of acceptance rates for nonlocal Metropolis update proposals. An approximation formula for acceptance rates is derived. We present a comparison of different coarse-to-fine interpolation schemes in free field theory, where the formula is exact. The predictions of the approximation formula for several interacting models are well confirmed by Monte Carlo simulations. The following rule is found: For a critical model with fundamental Hamiltonian H(phi), absence of critical slowing down can only be expected if the expansion of in terms of the shift psi contains no relevant (mass) term. We also introduce a multigrid update procedure for nonabelian lattice gauge theory and study the acceptance rates for gauge group SU(2) in four dimensions.

M. Grabenstein; K. Pinn

1992-07-03

114

Bacteria Allocation Using Monte Carlo  

NSDL National Science Digital Library

This applet, created by David Hill and Lila Roberts, uses the Monte Carlo technique to simulate a count of bacteria that are present as a result of a certain sampling process. This simulation could be modified to perform other experiments. This experiment is geared towards high school calculus students or probability courses for mathematics majors in college. Students must possess a basic understanding of probability concepts before performing this experiment. Overall, it is a nice activity for a mathematics classroom.

Hill, David R.; Roberts, Lila F.

2009-11-24

115

Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model  

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

116

Monte Carlo methods for the solution of nonlinear partial differential equations  

NASA Astrophysics Data System (ADS)

Stochastic models for the solution of nonlinear partial differential equations are discussed. They consist of a discretized version of these equations and Monte Carlo techniques. The Markov transitions are based on a priori estimates of the solution. To improve the efficiency of stochastic smoothers a Monte Carlo multigrid method is presented. The numerical results presented show the convergence of these methods. Some directions for the parallelization of the Monte Carlo algorithms presented are outlined. The techniques introduced make possible the extension of Monte Carlo methods to nonlinear problems, offering a new approach with an analytic potential for a wide range of problems in computational physics.

Marshall, Guillermo

1989-11-01

117

Numerical Simulation of Lightning Location Based on Monte Carlo Method  

Microsoft Academic Search

Currently, lightning location system (LLS) is one of the important bases for urban lightning protection. A key factor of the TDOA technology prevalently adopted in LLS is the time error of detection stations. According to the stochastic property of the time error measured by detection stations, the lightning information containing error is simulated using Monte Carlo method. The location error

Z. X. Hu; Y. P. Wen; W. G. Zhao; H. P. Zhu; S. L. Liu

2009-01-01

118

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

119

Fermion Monte Carlo without fixed nodes: A Game of Life, death and annihilation in Slater Determinant space  

E-print Network

Fermion Monte Carlo without fixed nodes: A Game of Life, death and annihilation in Slater Monte Carlo method for the simulation of correlated many- electron systems in Full Configuration of many- electron systems via stochastic methods such as Diffusion quantum Monte Carlo (DMC) [1

Alavi, Ali

120

Multivariate Monte Carlo Model Fitting  

NASA Astrophysics Data System (ADS)

We present a new method for analyzing multi-dimensional data. The method uses an astrophysical and instrument response Monte Carlo to simulate photons and then iteratively analyze the data. The simulated photons are then compared directly with the measured values for the data with a new multivariate generalization of the Cramér-von Mises and Kolmogorov-Smirnov statistic. Techniques for model fitting, error estimation, and deconvolution using this method are discussed. Examples of this approach using Chandra observations of X-ray clusters of galaxies and XMM-Newton Reflection Grating Spectrometer data are presented.

Peterson, J. R.; Jernigan, J. G.; Kahn, S. M.

2000-05-01

121

A Chance at Monte Carlo  

NSDL National Science Digital Library

At its core, the LEGO® MINDSTORMS® NXT product provides a programmable microprocessor. Students use the NXT processor to simulate an experiment involving thousands of uniformly random points placed within a unit square. Using the underlying geometry of the experimental model, as well as the geometric definition of the constant Ï (pi), students form an empirical ratio of areas to estimate a numerical value of Ï. Although typically used for numerical integration of irregular shapes, in this activity, students use a Monte Carlo simulation to estimate a common but rather complex analytical formâthe numerical value of the most famous irrational number, Ï.

AMPS GK-12 Program,

122

Monte Carlo approach to turbulence  

E-print Network

The behavior of the one-dimensional random-force-driven Burgers equation is investigated in the path integral formalism on a discrete space-time lattice. We show that by means of Monte Carlo methods one may evaluate observables, such as structure functions, as ensemble averages over different field realizations. The regularization of shock solutions to the zero-viscosity limit (Hopf-equation) eventually leads to constraints on lattice parameters required for the stability of the simulations. Insight into the formation of localized structures (shocks) and their dynamics is obtained.

Düben, P; Jansen, K; Mesterhazy, D; Münster, G

2009-01-01

123

Monte Carlo approach to turbulence  

E-print Network

The behavior of the one-dimensional random-force-driven Burgers equation is investigated in the path integral formalism on a discrete space-time lattice. We show that by means of Monte Carlo methods one may evaluate observables, such as structure functions, as ensemble averages over different field realizations. The regularization of shock solutions to the zero-viscosity limit (Hopf-equation) eventually leads to constraints on lattice parameters required for the stability of the simulations. Insight into the formation of localized structures (shocks) and their dynamics is obtained.

P. Düben; D. Homeier; K. Jansen; D. Mesterhazy; G. Münster

2009-11-03

124

The PHOBOS Glauber Monte Carlo  

E-print Network

``Glauber'' models are used to calculate geometric quantities in the initial state of heavy ion collisions, such as impact parameter, number of participating nucleons and initial eccentricity. The four RHIC experiments have different methods for Glauber Model calculations, leading to similar results for various geometric observables. In this document, we describe an implementation of the Monte Carlo based Glauber Model calculation used by the PHOBOS experiment. The assumptions that go in the calculation are described. A user's guide is provided for running various calculations.

B. Alver; M. Baker; C. Loizides; P. Steinberg

2008-05-28

125

Monte-Carlo Go Reinforcement Learning Experiments  

Microsoft Academic Search

Abstractó This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture. Currently, Monte-Carlo is a popular technique for computer Go. In a previous study, Monte-Carlo was associated with domain-dependent knowledge in the Go-playing program Indigo. In 2003, a 3x3 pattern database was built manually. This paper explores the possibility

Bruno Bouzy; Guillaume Chaslot

2006-01-01

126

Monte Carlo One-dimension Integration Model  

NSDL National Science Digital Library

The Monte Carlo One-dimension Integration Model illustrates the Monte Carlo integration algorithm to compute the integral of a function f(x). The simulation allows you to select the number of random points, to make an automatic fit to the function graph in the Y axis (thus improving the accuracy of the estimation), and to display the points or not. The simulation computes the actual value of the integral using a Romberg algorithm to test the Monte Carlo integral approximation.

Franciscouembre

2012-02-08

127

1-D EQUILIBRIUM DISCRETE DIFFUSION MONTE CARLO  

SciTech Connect

We present a new hybrid Monte Carlo method for 1-D equilibrium diffusion problems in which the radiation field coexists with matter in local thermodynamic equilibrium. This method, the Equilibrium Discrete Diffusion Monte Carlo (EqDDMC) method, combines Monte Carlo particles with spatially discrete diffusion solutions. We verify the EqDDMC method with computational results from three slab problems. The EqDDMC method represents an incremental step toward applying this hybrid methodology to non-equilibrium diffusion, where it could be simultaneously coupled to Monte Carlo transport.

T. EVANS; ET AL

2000-08-01

128

Monte Carlo surface flux tallies  

SciTech Connect

Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.

Favorite, Jeffrey A [Los Alamos National Laboratory

2010-11-19

129

Fission Matrix Capability for MCNP Monte Carlo  

SciTech Connect

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

130

The Monte-Carlo Approach in Amazons  

Microsoft Academic Search

The game of the Amazons is a quite new game whose rules stand between the game of Go and Chess. Its main diculty in terms of game programming is the huge branching factor. Monte-Carlo is a method used in game programming which allows us to overcome easily this problem. This paper presents how the Monte-Carlo method can be best adapted

Julien Kloetzer; Hiroyuki Iida; Bruno Bouzy

131

Monte-Carlo Strategies for Computer Go  

Microsoft Academic Search

The game of Go is one of the games that still withstand classical Articial Intelligence approaches. Hence, it is a good testbed for new AI methods. Amongst them, Monte-Carlo led to promising results. This method consists of building an evaluation function by averaging the outcome of several randomized games. The paper introduces a new strategy, which we call Objective Monte-Carlo,

Guillaume Chaslot; Jos W. H. M. Uiterwijk; Bruno Bouzy; H. Jaap van den Herik

132

Monte Carlo techniques in medical radiation physics  

Microsoft Academic Search

The author's main purpose is to review the techniques and applications of the Monte Carlo method in medical radiation physics since Raeside's review article in 1976. Emphasis is given to applications where proton and\\/or electron transport in matter is simulated. Some practical aspects of Monte Carlo practice, mainly related to random numbers and other computational details, are discussed in connection

P. Andreo

1991-01-01

133

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

134

Monte Carlo Simulations for Radiobiology  

NASA Astrophysics Data System (ADS)

The relationship between tumor response and radiation is currently modeled as dose, quantified on the mm or cm scale through measurement or simulation. This does not take into account modern knowledge of cancer, including tissue heterogeneities and repair mechanisms. We perform Monte Carlo simulations utilizing Geant4 to model radiation treatment on a cellular scale. Biological measurements are correlated to simulated results, primarily the energy deposit in nuclear volumes. One application is modeling dose enhancement through the use of high-Z materials, such gold nanoparticles. The model matches in vitro data and predicts dose enhancement ratios for a variety of in vivo scenarios. This model shows promise for both treatment design and furthering our understanding of radiobiology.

Ackerman, Nicole; Bazalova, Magdalena; Chang, Kevin; Graves, Edward

2012-02-01

135

MONTE CARLO METHODS IN GEOPHYSICAL INVERSE Malcolm Sambridge  

E-print Network

MONTE CARLO METHODS IN GEOPHYSICAL INVERSE PROBLEMS Malcolm Sambridge Research School Earth 27 2000; revised 15 December 2001; accepted 9 September published 5 December Monte Carlo inversion encountered in exploration seismology. traces development application Monte Carlo methods inverse problems

Sambridge, Malcolm

136

Fluctuating hydrodynamics and direct simulation Monte Carlo  

NASA Astrophysics Data System (ADS)

Thermodynamic fluctuations are significant at microscopic scales even when hydrodynamic transport models (i.e., Navier-Stokes equations) are still accurate; a well-known example is Rayleigh scattering, which makes the sky blue. Interesting phenomena also appear in non-equilibrium systems, such as the enhancement of diffusion during mixing due to the correlation of velocity and concentration fluctuations. Direct Simulation Monte Carlo (DSMC) simulations are useful in the study of hydrodynamic fluctuations due to their computational efficiency and ability to model molecular detail, such as internal energy and chemical reactions. More recently, finite volume schemes based on the fluctuating hydrodynamic equations of Landau and Lifshitz have been formulated and validated by comparisons with DSMC simulations. This paper discusses some of the relevant numerical issues and physical effects investigated using DSMC and stochastic Navier-Stokes simulations. This paper also presents the multi-component fluctuating hydrodynamic equations, including chemical reactions, and illustrates their numerical solutions in the study of Turing patterns. We find that behind a propagating reaction front, labyrinth patterns are produced due to the coupling of reactions and species diffusion. In general, fluctuations accelerate the propagation speed of the leading front but differences are observed in the Turing patterns depending on the origin of the fluctuations (stochastic hydrodynamic fluxes versus Langevin chemistry).

Balakrishnan, Kaushik; Bell, John B.; Donev, Aleksandar; Garcia, Alejandro L.

2012-11-01

137

Deterministic theory of Monte Carlo variance  

SciTech Connect

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validate this theory.

Ueki, T.; Larsen, E.W. [Univ. of Michigan, Ann Arbor, MI (United States)

1996-12-31

138

Competition between subdiffusion and Lévy flights: a Monte Carlo approach.  

PubMed

In this paper we answer positively a question raised by Metzler and Klafter [Phys. Rep. 339, 1 (2000)]: can one see a competition between subdiffusion and Lévy flights in the framework of the fractional Fokker-Planck dynamics? Our method of Monte Carlo simulations demonstrates the competition on the level of realizations as well as on the level of probability density functions of the anomalous diffusion process. The simulation algorithm is based on a stochastic representation of the above dynamics. PMID:17677193

Magdziarz, Marcin; Weron, Aleksander

2007-05-01

139

Frontiers of quantum Monte Carlo workshop: preface  

SciTech Connect

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

140

Quantum Monte Carlo Calculations of Light Nuclei  

E-print Network

During the last 15 years, there has been much progress in defining the nuclear Hamiltonian and applying quantum Monte Carlo methods to the calculation of light nuclei. I describe both aspects of this work and some recent results.

Steven C. Pieper

2007-11-09

141

Monte Carlo Tree Search in Hex  

Microsoft Academic Search

Hex, the classic board game invented by Piet Hein in 1942 and independently by John Nash in 1948, has been a domain of AI research since Claude Shannon's seminal work in the 1950s. Until the Monte Carlo Go revolution a few years ago, the best computer Hex players used knowledge-intensive alpha-beta search. Since that time, strong Monte Carlo Hex players

Broderick Arneson; Ryan B. Hayward; Philip Henderson

2010-01-01

142

Dynamic Randomization Enhances Monte-Carlo Go  

Microsoft Academic Search

This paper proposes two dynamic randomization techniques for Monte-Carlo Go that uses Monte-Carlo tree search with UCT algorithm. First, during the in-tree phase of a simulation game, the parameters are randomized in selected ranges before each simulation move. Second, during the playout phase, the order of simulation move generators are hierarchically randomized before each playout move. Both dynamic randomization techniques

Keh-Hsun Chen

2010-01-01

143

Bandit based Monte-Carlo Planning  

Microsoft Academic Search

For large state-space Markovian Decision Problems Monte- Carlo planning is one of the few viable approaches to flnd near-optimal solutions. In this paper we introduce a new algorithm, UCT, that ap- plies bandit ideas to guide Monte-Carlo planning. In flnite-horizon or discounted MDPs the algorithm is shown to be consistent and flnite sample bounds are derived on the estimation error

Levente Kocsis; Csaba Szepesvari

2006-01-01

144

Monte Carlo Go Has a Way to Go  

Microsoft Academic Search

Monte Carlo Go is a promising method to improve the perfor- mance of computer Go programs. This approach determines the next move to play based on many Monte Carlo samples. This paper examines the relative advantages of additional samples and enhancements for Monte Carlo Go. By par- allelizing Monte Carlo Go, we could increase sample sizes by two orders of

Haruhiro Yoshimoto; Kazuki Yoshizoe; Tomoyuki Kaneko; Akihiro Kishimoto; Kenjiro Taura

2006-01-01

145

Monte-Carlo Planning: Basic Principles and Recent Progress  

E-print Network

/ Video games Go / RTS In many cases Monte-Carlo techniques yield state-of-the-art performance. Even1 Monte-Carlo Planning: Basic Principles and Recent Progress Alan Fern School of EECS Oregon State University #12;2 Outline Preliminaries: Markov Decision Processes What is Monte-Carlo Planning? Uniform Monte-Carlo

146

Monte-Carlo Go Reinforcement Learning Experiments Bruno Bouzy  

E-print Network

Monte-Carlo Go Reinforcement Learning Experiments Bruno Bouzy Universit´e Ren´e Descartes UFR de during simulations performed in a Monte-Carlo Go archi- tecture. Currently, Monte-Carlo is a popular technique for computer Go. In a previous study, Monte-Carlo was associated with domain-dependent knowledge

Bouzy, Bruno

147

Monte-Carlo vs. Bulk Conductivity Modeling of RF  

E-print Network

Monte-Carlo vs. Bulk Conductivity Modeling of RF Breakdown of Helium* Carsten Thoma, Thomas Hughes distribution function can be quite non-Maxwellian #12;2 approaches to simulating weakly- ionized plasma · Monte-Carlo with He at STP. #12;Monte Carlo Scattering Algorithm* · Implemented a Monte Carlo scattering algorithm

Kaganovich, Igor

148

Monte Carlo data association for multiple target tracking Rickard Karlsson  

E-print Network

Monte Carlo data association for multiple target tracking Rickard Karlsson Dept. of Electrical, these estimation methods may lead to non­optimal solutions. The sequential Monte Carlo methods, or particle filters chose the number of particles. 2 Sequential Monte Carlo methods Monte Carlo techniques have been

Gustafsson, Fredrik

149

The Monte-Carlo Revolution in Go Remi Coulom  

E-print Network

The Monte-Carlo Revolution in Go R´emi Coulom Universit´e Charles de Gaulle, INRIA, CNRS, Lille, France January, 2009 JFFoS'2008: Japanese-French Frontiers of Science Symposium #12;Introduction Monte-Carlo configurations R´emi Coulom The Monte Carlo Revolution in Go 2 / 12 #12;Introduction Monte-Carlo Tree Search

Coulom, Rémi - Groupe de Recherche sur l'Apprentissage Automatique, Université Charles de Gaulle

150

A Monte Carlo method for solving unsteady adjoint equations  

E-print Network

A Monte Carlo method for solving unsteady adjoint equations Qiqi Wang a,*, David Gleich a , Amin on this technique and uses a Monte Carlo linear solver. The Monte Carlo solver yields a forward-time algorithm' equation, the Monte Carlo approach is faster for a large class of problems while preserving sufficient

Wang, Qiqi

151

Monte Carlo data association for multiple target tracking Rickard Karlsson  

E-print Network

Monte Carlo data association for multiple target tracking Rickard Karlsson Dept. of Electrical, these estimation methods may lead to non-optimal solutions. The sequential Monte Carlo methods, or particle filters chose the number of particles. 2 Sequential Monte Carlo methods Monte Carlo techniques have been

Gustafsson, Fredrik

152

Monte Carlo methods for fissured porous media: gridless approaches  

E-print Network

Monte Carlo methods for fissured porous media: gridless approaches Antoine Lejay1, -- Projet OMEGA (INRIA / Institut ´Elie Cartan, Nancy) Abstract: In this article, we present two Monte Carlo methods) Published in Monte Carlo Methods and Applications. Proc. of the IV IMACS Seminar on Monte Carlo Methods

Paris-Sud XI, Université de

153

The Monte Carlo Method and Software Reliability Theory  

E-print Network

1 The Monte Carlo Method and Software Reliability Theory Brian Korver1 briank@cs.pdx.edu TR 94-1. February 18, 1994 1.0 Abstract The Monte Carlo method of reliability prediction is useful when system for valid, nontrivial input data and an external oracle. 2.0 The Monte Carlo Method The Monte Carlo method

Pratt, Vaughan

154

Monte Carlo Methods in Reactor Physics  

SciTech Connect

Two approaches exist for particle transport simulation in reactor physics, deterministic and statistical Monte Carlo. The Monte Carlo and deterministic approaches are compared, and their advantages and disadvantages are discussed. Then different issues related to Monte Carlo simulations for solving different types of problems are described, along with methods to resolve some of the issues; these include variance-reduction techniques, automated variance techniques, and parallel computing. Then a few sample examples for real-life problems are presented. In the author's opinion, there are effective variance-reduction techniques and automation tools for the fixed-source simulations. This, however, is not true for the Monte Carlo eigenvalue calculations. The needs in this area are development of methods for determination of a ''good'' starting source and variance-reduction methods for effective sampling of source energies and regions. This is especially important because of emerging new applications including Monte Carlo depletion in general; Generation VI reactor design, which may involve irregular geometries and novel concepts; design and analyses for plutonium disposition; spent-fuel storage; radioactive waste disposal; and criticality safety evaluation of nuclear material handling facilities. The author believe that to make the Monte Carlo methods more effective and reliable, the use of deterministic methods is a must.

Haghighat, Alireza

2001-06-17

155

Ada Numerica (1998), pp. 1-49 Cambridge University Press, 1998 Monte Carlo and quasi-Monte Carlo  

E-print Network

Ada Numerica (1998), pp. 1-49 © Cambridge University Press, 1998 Monte Carlo and quasi-Monte Carlo-mail: caiflisch@math.ucla.edu Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~1 ^2 ), is independent of dimension, which shows Monte Carlo to be very robust but also

Li, Tiejun

156

Monte Carlo Integration This chapter gives an introduction to Monte Carlo integration. The main goals are to review  

E-print Network

Chapter 2 Monte Carlo Integration This chapter gives an introduction to Monte Carlo integration useful in computer graphics. Good references on Monte Carlo methods include Kalos & Whitlock [1986 for Monte Carlo applications to neutron transport problems; Lewis & Miller [1984] is a good source

Stanford University

157

Applied Probability Trust (25 February 2008) MONTE CARLO METHODS FOR SENSITIVITY ANALYSIS OF  

E-print Network

separable metric space M. Under the probability measure P, the intensity of the Poisson point process Poisson processes, with respect to the intensity of the process. As our main result, we provide Monte in stochastic geometry and insurance. Keywords: Importance sampling, Marked Poisson processes, Monte Carlo

Bordenave, Charles

158

Monte Carlo Shielding Analysis Capabilities with MAVRIC  

SciTech Connect

Monte Carlo shielding analysis capabilities in SCALE 6 are centered on the CADIS methodology Consistent Adjoint Driven Importance Sampling. CADIS is used to create an importance map for space/energy weight windows as well as a biased source distribution. New to SCALE 6 are the Monaco functional module, a multi-group fixed-source Monte Carlo transport code, and the MAVRIC sequence (Monaco with Automated Variance Reduction Using Importance Calculations). MAVRIC uses the Denovo code (also new to SCALE 6) to compute coarse-mesh discrete ordinates solutions which are used by CADIS to form an importance map and biased source distribution for the Monaco Monte Carlo code. MAVRIC allows the user to optimize the Monaco calculation for a specify tally using the CADIS method with little extra input compared to a standard Monte Carlo calculation. When computing several tallies at once or a mesh tally over a large volume of space, an extension of the CADIS method called FW-CADIS can be used to help the Monte Carlo simulation spread particles over phase space to get more uniform relative uncertainties.

Peplow, Douglas E. [ORNL

2011-01-01

159

Advanced interacting sequential Monte Carlo sampling for inverse scattering  

NASA Astrophysics Data System (ADS)

The following electromagnetism (EM) inverse problem is addressed. It consists in estimating the local radioelectric properties of materials recovering an object from global EM scattering measurements, at various incidences and wave frequencies. This large scale ill-posed inverse problem is explored by an intensive exploitation of an efficient 2D Maxwell solver, distributed on high performance computing machines. Applied to a large training data set, a statistical analysis reduces the problem to a simpler probabilistic metamodel, from which Bayesian inference can be performed. Considering the radioelectric properties as a hidden dynamic stochastic process that evolves according to the frequency, it is shown how advanced Markov chain Monte Carlo methods—called sequential Monte Carlo or interacting particles—can take benefit of the structure and provide local EM property estimates.

Giraud, F.; Minvielle, P.; Del Moral, P.

2013-09-01

160

Exploring Various Monte Carlo Simulations for Geoscience Applications  

NASA Astrophysics Data System (ADS)

Computer simulations are increasingly important in geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN), or chaotic random number (CRN) generators. Equidistributed quasi-random numbers (QRNs) can also be used in Monte Carlo simulations. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as Importance Sampling and Stratified Sampling can be implemented to significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on examples of geodetic applications of gravimetric terrain corrections and gravity inversion, conclusions and recommendations concerning their performance and general applicability are included.

Blais, R.

2010-12-01

161

Exploring pseudo- and chaotic random Monte Carlo simulations  

NASA Astrophysics Data System (ADS)

Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer-generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as importance sampling and stratified sampling can be applied in most Monte Carlo simulations and significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on some practical examples of geodetic direct and inverse problems, conclusions and recommendations concerning their performance and general applicability are included.

Blais, J. A. Rod; Zhang, Zhan

2011-07-01

162

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

163

Monte Carlo-based inverse treatment planning.  

PubMed

A Monte Carlo based inverse treatment planning system (MCI) has been developed which combines arguably the most accurate dose calculation method (Monte Carlo particle transport) with a 'guaranteed' optimization method (simulated annealing). A distribution of photons is specified in the tumour volume; they are transported using an adjoint calculation method to outside the patient surface to build up an intensity distribution. This intensity distribution is used as the initial input into an optimization algorithm. The dose distribution from each beam element from a number of fields is pre-calculated using Monte Carlo transport. Simulated annealing optimization is then used to find the weighting of each beam element, to yield the optimal dose distribution for the given criteria and constraints. MCI plans have been generated in various theoretical phantoms and patient geometries. These plans show conformation of the dose to the target volume and avoidance of critical structures. To verify the code, an experiment was performed on an anthropomorphic phantom. PMID:10473202

Jeraj, R; Keall, P

1999-08-01

164

Shell model the Monte Carlo way  

SciTech Connect

The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.

Ormand, W.E.

1995-03-01

165

Geodesic Monte Carlo on Embedded Manifolds  

PubMed Central

Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices.

Byrne, Simon; Girolami, Mark

2013-01-01

166

The Rational Hybrid Monte Carlo Algorithm  

E-print Network

The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.

M. A. Clark

2006-10-06

167

Monte Carlo evaluation of thermal desorption rates  

SciTech Connect

The recently reported method for computing thermal desorption rates via a Monte Carlo evaluation of the appropriate transition state theory expression (J. E. Adams and J. D. Doll, J. Chem. Phys. 74, 1467 (1980)) is extended, by the use of importance sampling, so as to generate the complete temperature dependence in a single calculation. We also describe a straightforward means of calculating the activation energy for the desorption process within the same Monte Carlo framework. The result obtained in this way represents, for the case of a simple desorptive event, an upper bound to the true value.

Adams, J.E.; Doll, J.D.

1981-05-01

168

Monte Carlo Renormalization Group: a review  

SciTech Connect

The logic and the methods of Monte Carlo Renormalization Group (MCRG) are reviewed. A status report of results for 4-dimensional lattice gauge theories derived using MCRG is presented. Existing methods for calculating the improved action are reviewed and evaluated. The Gupta-Cordery improved MCRG method is described and compared with the standard one. 71 refs., 8 figs.

Gupta, R.

1985-01-01

169

Dosimetry, scattering theory, and Monte Carlo simulation  

E-print Network

The purpose of this paper is to provide an introduction to the physics of scattering theory, to define the dosimetric concept of linear energy transfer in terms of scattering theory, and to provide an introduction to the concepts underlying Monte Carlo simulations.

Gordon McCabe

2008-06-28

170

MONTE CARLO GO CAPTURING TACTIC SEARCH  

Microsoft Academic Search

This paper is an extended version of the authors' paper12 presented at JCIS 2007. Standard Monte Carlo UCT tree search algorithm is modified and extended to provide an efficient Go capturing problem solver. Experimental results show that this method outperforms traditional tree search methods to solve capturing problems in Go.

PEIGANG ZHANG; KEH-HSUN CHEN

2008-01-01

171

Overview of Monte Carlo radiation transport codes  

Microsoft Academic Search

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 (MC) particle transport computer codes contributed by scientists from various countries. An overview of the neutron

B. L. Kirk; Bernadette Lugue

2010-01-01

172

Computational Physics Resources: Basic Monte Carlo Methods  

NSDL National Science Digital Library

This website contains a set of 7 simulations and accompanying worksheets that introduce a number of basic Monte Carlo techniques (e.g. generating and testing random sequences, simulating random walks and radioactive decay, and sampling according to a given distribution).

Wheaton, Spencer

2014-01-18

173

Fast Monte Carlo full spectrum scene simulation  

Microsoft Academic Search

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

Steven Richtsmeier; Robert Sundberg; Raymond Haren; Frank O. Clark

2006-01-01

174

Fast Monte Carlo Full Spectrum Scene Simulation  

Microsoft Academic Search

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

Steven Richtsmeier; Robert Sundberg; Frank O. Clark

2009-01-01

175

Monte Carlo approach to Dark Matter Mapping  

Microsoft Academic Search

We present an an analysis method of constructing dark matter maps based on weak lensing using a Markov Chain Monte Carlo technique. The dark matter in a cluster can be modeled as a collection of massive blobs that bend light according to gravitational lensing. We move these dark matter blobs in RA, Dec and redshift and as a result perturb

Suzanne Lorenz; J. R. Peterson

2011-01-01

176

Monte Carlo analysis of CLAS data  

E-print Network

We present a fit of the virtual-photon scattering asymmetry of polarized Deep Inelastic Scattering which combines a Monte Carlo technique with the use of a redundant parametrization based on Neural Networks. We apply the result to the analysis of CLAS data on a polarized proton target.

L. Del Debbio; A. Guffanti; A. Piccione

2008-06-30

177

Lexical Frequency Profiles: A Monte Carlo Analysis  

ERIC Educational Resources Information Center

This paper reports a set of Monte Carlo simulations designed to evaluate the main claims made by Laufer and Nation about the Lexical Frequency Profile (LFP). Laufer and Nation claim that the LFP is a sensitive and reliable tool for assessing productive vocabulary in L2 speakers, and they suggest it might have a serious role to play in diagnostic…

Meara, Paul

2005-01-01

178

Monte Carlo simulation for radiative kaon decays  

E-print Network

For high precision measurements of K decays, the presence of radiated photons cannot be neglected. The Monte Carlo simulations must include the radiative corrections in order to compute the correct event counting and efficiency calculations. In this paper we briefly describe a method for simulating such decays.

C. Gatti

2005-07-25

179

Nonuniversal critical dynamics in Monte Carlo simulations  

Microsoft Academic Search

A new approach to Monte Carlo simulations is presented, giving a highly efficient method of simulation for large systems near criticality. The algorithm violates dynamic universality at second-order phase transitions, producing unusually small values of the dynamical critical exponent.

Robert H. Swendsen; Jian-Sheng Wang

1987-01-01

180

Monte Carlo Tools for Jet Quenching  

E-print Network

A thorough understanding of jet quenching on the basis of multi-particle final states and jet observables requires new theoretical tools. This talk summarises the status and propects of the theoretical description of jet quenching in terms of Monte Carlo generators.

Korinna Zapp

2011-09-07

181

Monte Carlo correction programme for PC  

Microsoft Academic Search

A Monte Carlo correction program for quantitative microanalysis on PC computer is introduced in this paper. The elastic scattering is described by the screened Rutherford cross section. Instead of computing the energy loss according to the actual path between two scatterings we have defined the “Bethe inelastic cross section” determined by the Bethe-slowing-down approximation. It is assumed that it causes

Ondrej Gedeon; Vaclav Hulinsky

1994-01-01

182

On Markov Chain Monte Carlo Acceleration  

Microsoft Academic Search

Markov chain Monte Carlo (MCMC) methods are currently enjoying a surge of interest within the statistical community. The goal of this work is to formalize and support two distinct adaptive strategies that typically accelerate the convergence of an MCMC algorithm. One approach is through resampling; the other incorporates adaptive switching of the transition kernel. Support is both by analytic arguments

Alan E. Gelfand; Sujit K. Sahu

1994-01-01

183

Adaptive Markov Chain Monte Carlo through Regeneration  

Microsoft Academic Search

Markov chain Monte Carlo (MCMC) is used for evaluating expectations of functions of interest under a target distribution ?. This is done by calculating averages over the sample path of a Markov chain having ? as its stationary distribution. For computational efficiency, the Markov chain should be rapidly mixing. This sometimes can be achieved only by careful design of the

Walter R. Gilks; Gareth O. Roberts; Sujit K. Sahu

1998-01-01

184

Parallel processing Monte Carlo radiation transport codes  

SciTech Connect

Issues related to distributed-memory multiprocessing as applied to Monte Carlo radiation transport are discussed. Measurements of communication overhead are presented for the radiation transport code MCNP which employs the communication software package PVM, and average efficiency curves are provided for a homogeneous virtual machine.

McKinney, G.W.

1994-02-01

185

Non-Hermitian Polynomial Hybrid Monte Carlo  

E-print Network

We report on a new variant of the hybrid Monte Carlo algorithm employing a polynomial approximation of the inverse of the non-Hermitian Dirac-Wilson operator. Our approximation relies on simple and stable recurrence relations of complex Chebyshev polynomials. First performance figures are presented.

Oliver Witzel

2008-09-05

186

MIMO detection employing Markov Chain Monte Carlo  

E-print Network

We propose a soft-output detection scheme for Multiple-Input-Multiple-Output (MIMO) systems. The detector employs Markov Chain Monte Carlo method to compute bit reliabilities from the signals received and is thus suited for coded MIMO systems. It offers a good trade-off between achievable performance and algorithmic complexity.

V. Sundaram; K. P. N. Murthy

2007-05-05

187

Monte Carlo Simulation of Counting Experiments.  

ERIC Educational Resources Information Center

A computer program to perform a Monte Carlo simulation of counting experiments was written. The program was based on a mathematical derivation which started with counts in a time interval. The time interval was subdivided to form a binomial distribution with no two counts in the same subinterval. Then the number of subintervals was extended to…

Ogden, Philip M.

188

Optimizing Efficiency of Perturbative Monte Carlo Method  

E-print Network

-- --Efficiency of Perturbative Monte Carlo Method TOM J. EVANS, THANH N. TRUONG approach introduced earlier provides a means to reduce the number of full SCF calculations in simulations displacements to occur between the performance of the full self-consistent field calculations. This will allow

Truong, Thanh N.

189

Robust Monte Carlo localization for mobile robots  

Microsoft Academic Search

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

190

Non-Linear Monte-Carlo Search in Civilization II  

E-print Network

This paper presents a new Monte-Carlo search algorithm for very large sequential decision-making problems. Our approach builds on the recent success of Monte-Carlo tree search algorithms, which estimate the value of states ...

Branavan, Satchuthanan R.

191

Monte Carlo event reconstruction implemented with artificial neural networks  

E-print Network

I implemented event reconstruction of a Monte Carlo simulation using neural networks. The OLYMPUS Collaboration is using a Monte Carlo simulation of the OLYMPUS particle detector to evaluate systematics and reconstruct ...

Tolley, Emma Elizabeth

2011-01-01

192

Parallel Monte-Carlo Tree Search with Simulation Servers  

Microsoft Academic Search

Monte-Carlo tree search is a new best-first tree search algorithm that triggered a revolution in the computer Go world. Developing good parallel Monte-Carlo tree search algorithms is importan because single processor's performance cannot be expected to increase as used to. A novel parallel Monte-Carlo tree search algorithm is proposed. A tree searcher runs on a client computer and multiple Monte-Carlo

Hideki Kato; Ikuo Takeuchi

2010-01-01

193

A Comparison of Monte-Carlo Methods for Phantom Go  

Microsoft Academic Search

Throughout recent years, Monte-Carlo methods have considerably improved computer Go pro- grams. In particular, Monte-Carlo Tree Search algorithms such as UCT have enabled significant advances in this domain. Phantom Go is a variant of Go which is complicated by the condi- tion of imperfect information. This article compares four Monte-Carlo methods for Phantom Go in a self-play experiment: (1) Monte-Carlo

Joris Borsboom; Jahn-Takeshi Saito; Guillaume Chaslot; Jos W. H. M. Uiterwijk

194

Extension of the fully coupled Monte Carlo/S sub N response matrix method to problems including upscatter and fission  

SciTech Connect

The neutron transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S{sub N}) and stochastic (Monte Carlo) methods are applied. Unlike previous hybrid methods, the Monte Carlo and S{sub N} regions are fully coupled in the sense that no assumption is made about geometrical separation of decoupling. The fully coupled Monte Carlo/S{sub N} technique consists of defining spatial and/or energy regions of a problem in which either a Monte Carlo calculation or an S{sub N} calculation is to be performed. The Monte Carlo and S{sub N} regions are then connected through the common angular boundary fluxes, which are determined iteratively using the response matrix technique, and group sources. The hybrid method provides a new method of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor S{sub N} is well suited for by itself. The fully coupled Monte Carlo/S{sub N} method has been implemented in the S{sub N} code TWODANT by adding special-purpose Monte Carlo subroutines to calculate the response matrices and group sources, and linkage subroutines to carry out the interface flux iterations. The common angular boundary fluxes are included in the S{sub N} code as interior boundary sources, leaving the logic for the solution of the transport flux unchanged, while, with minor modifications, the diffusion synthetic accelerator remains effective in accelerating the S{sub N} calculations. The Monte Carlo routines have been successfully vectorized, with approximately a factor of five increases in speed over the nonvectorized version. The hybrid method is capable of solving forward, inhomogeneous source problems in X-Y and R-Z geometries. This capability now includes mulitigroup problems involving upscatter and fission in non-highly multiplying systems. 8 refs., 8 figs., 1 tab.

Baker, R.S.; Filippone, W.F. (Arizona Univ., Tucson, AZ (USA). Dept. of Nuclear and Energy Engineering); Alcouffe, R.E. (Los Alamos National Lab., NM (USA))

1991-01-01

195

Criticality: a Monte-Carlo Heuristic for Go Remi Coulom  

E-print Network

Criticality: a Monte-Carlo Heuristic for Go Programs R´emi Coulom Universit´e Charles de Gaulle, Peter Drake, and Yung-Pin Chen, in Localizing Search in Monte-Carlo Go Using Statistical Covariance (in Introduction: Principle of Monte-Carlo Evaluation Root Position MC Evaluation + + = Random Playouts R

Coulom, Rémi - Groupe de Recherche sur l'Apprentissage Automatique, Université Charles de Gaulle

196

Advanced Monte Carlo Methods: IV Prof. Mike Giles  

E-print Network

which go forwards in time Advanced Monte Carlo Methods: IV ­ p. 4 #12;Problem Formulation FollowingAdvanced Monte Carlo Methods: IV Prof. Mike Giles mike.giles@maths.ox.ac.uk Oxford University Mathematical Institute Advanced Monte Carlo Methods: IV ­ p. 1 #12;Early Exercise Perhaps the biggest challenge

Giles, Mike

197

Exploration exploitation in Go: UCT for Monte-Carlo Go  

E-print Network

Exploration exploitation in Go: UCT for Monte-Carlo Go Sylvain Gelly(*) and Yizao Wang(*,**) (*)TAO works for minimax tree search. We have developed a Monte-Carlo program, MoGo, which is the first and 13x13) on the international Kiseido Go Server2 . Our approach is based on the Monte-Carlo Go

Paris-Sud XI, Université de

198

MONTE CARLO EXPLORATIONS OF POLYGONAL KNOT SPACES KENNETH C. MILLETT  

E-print Network

1 MONTE CARLO EXPLORATIONS OF POLYGONAL KNOT SPACES KENNETH C. MILLETT Department of Mathematics Monte Carlo explorations, is provided. Keywords: Monte Carlo, polygonal knots, energy, thickness, HOMFLY of n sides into three­dimensional Euclidean space such that the edges go to line segments connecting

Bigelow, Stephen

199

Biasing Monte-Carlo Simulations through RAVE Arpad Rimmel1  

E-print Network

applications: the game of Havannah and the game of Go. 1 Introduction Monte-Carlo Tree Search (MCTS) [5, 6, 10Biasing Monte-Carlo Simulations through RAVE Values Arpad Rimmel1 , Fabien Teytaud2 , and Olivier. The Monte-Carlo Tree Search algorithm has been success- fully applied in various domains. However, its

Paris-Sud XI, Université de

200

MCMs: Early History and The Basics Monte Carlo Methods  

E-print Network

The Name: Ulam's uncle would borrow money from the family by saying that "I just have to go to Monte CarloMCMs: Early History and The Basics Monte Carlo Methods: Early History and The Basics Prof. Michael of Probability Theory and Monte Carlo Methods Early History of Probability Theory The Stars Align at Los Alamos

Mascagni, Michael

201

Sequential Monte Carlo Methods for Statistical Analysis of Tables  

E-print Network

Sequential Monte Carlo Methods for Statistical Analysis of Tables Yuguo CHEN, Persi DIACONIS, Susan- butions. Our method produces Monte Carlo samples that are remarkably close to the uniform distribution. Our method compares favorably with other existing Monte Carlo- based algorithms, and sometimes

Liu, Jun

202

FPGA-based Monte Carlo simulation for fault tree analysis  

Microsoft Academic Search

The reliability analysis of critical systems is often performed using fault-tree analysis. Fault trees are analyzed using analytic approaches or Monte Carlo simulation. The usage of the analytic approaches is limited in few models and certain kinds of distributions. In contrast to the analytic approaches, Monte Carlo simulation can be broadly used. However, Monte Carlo simulation is time-consuming because of

Alireza Ejlali; Seyed Ghassem Miremadi

2004-01-01

203

A Monte Carlo Approach for Finding More than One Eigenpair  

E-print Network

A Monte Carlo Approach for Finding More than One Eigenpair Michael Mascagni1 and Aneta Karaivanova1. 25A, 1113 Sofia, Bulgaria, aneta@csit.fsu.edu, http://parallel.bas.bg/anet/ Abstract. The Monte Carlo) eigenvalues of matrices. In this paper we study computing eigenvectors as well with the Monte Carlo approach

Karaivanova, Aneta

204

Monte Carlo Methods: A Computational Pattern for Our Pattern Language  

E-print Network

Monte Carlo Methods: A Computational Pattern for Our Pattern Language Jike Chong University@eecs.berkeley.edu Kurt Keutzer University of California, Berkeley keutzer@eecs.berkeley.edu ABSTRACT The Monte Carlo for a particular data working set. This paper presents the Monte Carlo Methods software pro- gramming pattern

California at Berkeley, University of

205

MONTE CARLO LIKELIHOOD INFERENCE FOR MISSING DATA MODELS  

E-print Network

MONTE CARLO LIKELIHOOD INFERENCE FOR MISSING DATA MODELS By Yun Ju Sung and Charles J. Geyer University of Washington and University of Minnesota Abbreviated title: Monte Carlo Likelihood Asymptotics We describe a Monte Carlo method to approximate the maximum likeli- hood estimate (MLE), when

Jiang, Tiefeng

206

MONTE CARLO SIMULATION FOR AMERICAN Russel E. Caflisch  

E-print Network

#12;Chapter 1 MONTE CARLO SIMULATION FOR AMERICAN OPTIONS Russel E. Caflisch Mathematics Department This paper reviews the basic properties of American options and the difficulties of applying Monte Carlo of Monte Carlo to American options is described including the following: Branching processes have been con

Caflisch, Russel

207

Monte Carlo modeling of optical coherence tomography systems  

E-print Network

Monte Carlo modeling of optical coherence tomography systems Peter E. Andersen Optics and Fluid 2003 Outline · Motivation · Monte Carlo OCT ­ use MC to model interference? · Results ­ comparison Dynamics Department SFM'03 ­ 7-10 October 2003 Motivation · Monte Carlo (MC) modeling of light propagation

208

Monte Carlo Ray Tracing Siggraph 2003 Course 44  

E-print Network

Monte Carlo Ray Tracing Siggraph 2003 Course 44 Tuesday, July 29, 2003 Organizer Henrik Wann Jensen;Abstract This full day course will provide a detailed overview of state of the art in Monte Carlo ray tracing. Recent advances in algorithms and available compute power have made Monte Carlo ray tracing based

Li, Yaohang

209

Monte Carlo Algorithms for the Partition Function and Information Rates  

E-print Network

1 Monte Carlo Algorithms for the Partition Function and Information Rates of Two Monte Carlo algorithms for the computation of the information rate of two-dimensional source / channel, of such channels has so far remained largely unsolved. Both problems can be reduced to computing a Monte Carlo

Loeliger, Hans-Andrea

210

MONTE CARLO ANALYSIS: ESTIMATING GPP WITH THE CANOPY CONDUCTANCE METHOD  

E-print Network

MONTE CARLO ANALYSIS: ESTIMATING GPP WITH THE CANOPY CONDUCTANCE METHOD 1. Overview A novel method performed a Monte Carlo Analysis to investigate the power of our statistical approach: i.e. what and Assumptions The Monte Carlo Analysis was performed as follows: · Natural variation. The only study to date

DeLucia, Evan H.

211

MONTE CARLO METHODS IN GEOPHYSICAL INVERSE Malcolm Sambridge  

E-print Network

MONTE CARLO METHODS IN GEOPHYSICAL INVERSE PROBLEMS Malcolm Sambridge Research School of Earth 2002. [1] Monte Carlo inversion techniques were first used by Earth scientists more than 30 years ago in exploration seismology. This pa- per traces the development and application of Monte Carlo methods for inverse

Sambridge, Malcolm

212

Monte Carlo procedure for protein design Anders Irback,* Carsten Peterson,  

E-print Network

Monte Carlo procedure for protein design Anders Irba¨ck,* Carsten Peterson, Frank Potthast functions, is based upon a different and very efficient multisequence Monte Carlo scheme. By construction a practical Monte Carlo MC procedure for perform- ing the maximization of P(r0 ). Thermodynamical

Irbäck, Anders

213

Monte Carlo simulations and option by Bingqian Lu  

E-print Network

Monte Carlo simulations and option pricing by Bingqian Lu Undergraduate Mathematics Department #12;Abstract Monte Carlo simulation is a legitimate and widely used technique for dealing of this technique to the stock volality and to test its accuracy by comparing the result computed by Monte Carlo

Mazzucato, Anna

214

Monte Carlo Evaluation of Resampling-Based Hypothesis Tests  

E-print Network

Monte Carlo Evaluation of Resampling-Based Hypothesis Tests Dennis D. Boos and Ji Zhang October 1998 Abstract Monte Carlo estimation of the power of tests that require resampling can be very com in correcting for bias and thus reduces computation time in Monte Carlo power studies. KEY WORDS: Bootstrap

Boos, Dennis

215

Monte-Carlo Tree Search in Crazy Stone Remi Coulom  

E-print Network

Monte-Carlo Tree Search in Crazy Stone R´emi Coulom Universit´e Charles de Gaulle, INRIA, CNRS Introduction 2 Crazy Stone's Algorithm Principles of Monte-Carlo Evaluation Tree Search Patterns 3 Playing global understanding The Monte-Carlo Approach random playouts dynamic evaluation with global

Coulom, Rémi - Groupe de Recherche sur l'Apprentissage Automatique, Université Charles de Gaulle

216

Monte Carlo Reliability Model for Microwave Monolithic Integrated Circuits  

E-print Network

Monte Carlo Reliability Model for Microwave Monolithic Integrated Circuits Aris Christou Materials of the failure rate of each component due to interaction effects of the failed components. The Monte Carlo failure rates become nonconstant. The Monte Carlo technique is an appropriate methodology used to treat

Rubloff, Gary W.

217

Use of Monte Carlo Analysis to Characterize Nitrogen Fluxes in  

E-print Network

Use of Monte Carlo Analysis to Characterize Nitrogen Fluxes in Agroecosystems S H E L I E A . M I L systems, this paper employs Monte Carlo analysis (MCA) to model major nitrogen exports during crop assessments (LCA) and environmental impact assessments. Monte Carlo simulations generate distributions

Illinois at Chicago, University of

218

Lattice kinetic Monte Carlo simulations of convective-diffusive systems  

PubMed Central

Diverse phenomena in physical, chemical, and biological systems exhibit significant stochasticity and therefore require appropriate simulations that incorporate noise explicitly into the dynamics. We present a lattice kinetic Monte Carlo approach to simulate the trajectories of tracer particles within a system in which both diffusive and convective transports are operational. While diffusive transport is readily accounted for in a kinetic Monte Carlo simulation, we demonstrate that the inclusion of bulk convection by simply biasing the rate of diffusion with the rate of convection creates unphysical, shocklike behavior in concentrated systems due to particle pile up. We report that elimination of shocklike behavior requires the proper passing of blocked convective rates along nearest-neighbor chains to the first available particle in the direction of flow. The resulting algorithm was validated for the Taylor–Aris dispersion in parallel plate flow and multidimensional flows. This is the first generally applicable lattice kinetic Monte Carlo simulation for convection-diffusion and will allow simulations of field-driven phenomena in which drift is present in addition to diffusion. PMID:19275421

Flamm, Matthew H.; Diamond, Scott L.; Sinno, Talid

2009-01-01

219

MontePython: Implementing Quantum Monte Carlo using Python  

NASA Astrophysics Data System (ADS)

We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and diffusion Monte Carlo and we describe how to implement theses methods in pure C++ and C++/Python. Furthermore we check the efficiency of the implementations in serial and parallel cases to show that the overhead using Python can be negligible. Program summaryProgram title: MontePython Catalogue identifier: ADZP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 49 519 No. of bytes in distributed program, including test data, etc.: 114 484 Distribution format: tar.gz Programming language: C++, Python Computer: PC, IBM RS6000/320, HP, ALPHA Operating system: LINUX Has the code been vectorised or parallelized?: Yes, parallelized with MPI Number of processors used: 1-96 RAM: Depends on physical system to be simulated Classification: 7.6; 16.1 Nature of problem: Investigating ab initio quantum mechanical systems, specifically Bose-Einstein condensation in dilute gases of 87Rb Solution method: Quantum Monte Carlo Running time: 225 min with 20 particles (with 4800 walkers moved in 1750 time steps) on 1 AMD Opteron TM Processor 2218 processor; Production run for, e.g., 200 particles takes around 24 hours on 32 such processors.

Nilsen, Jon Kristian

2007-11-01

220

New variational Monte Carlo method with an energy variance extrapolation for large-scale shell-model calculations  

E-print Network

We propose a new variational Monte Carlo (VMC) method with an energy variance extrapolation for large-scale shell-model calculations. This variational Monte Carlo is a stochastic optimization method with a projected correlated condensed pair state as a trial wave function, and is formulated with the M-scheme representation of projection operators, the Pfaffian and the Markov-chain Monte Carlo (MCMC). Using this method, we can stochastically calculate approximated yrast energies and electro-magnetic transition strengths. Furthermore, by combining this VMC method with energy variance extrapolation, we can estimate exact shell-model energies.

Mizusaki, Takahiro

2012-01-01

221

New variational Monte Carlo method with an energy variance extrapolation for large-scale shell-model calculations  

E-print Network

We propose a new variational Monte Carlo (VMC) method with an energy variance extrapolation for large-scale shell-model calculations. This variational Monte Carlo is a stochastic optimization method with a projected correlated condensed pair state as a trial wave function, and is formulated with the M-scheme representation of projection operators, the Pfaffian and the Markov-chain Monte Carlo (MCMC). Using this method, we can stochastically calculate approximated yrast energies and electro-magnetic transition strengths. Furthermore, by combining this VMC method with energy variance extrapolation, we can estimate exact shell-model energies.

Takahiro Mizusaki; Noritaka Shimizu

2012-01-27

222

Monte Carlo Simulation of THz Multipliers  

NASA Technical Reports Server (NTRS)

Schottky Barrier diode frequency multipliers are critical components in submillimeter and Thz space based earth observation systems. As the operating frequency of these multipliers has increased, the agreement between design predictions and experimental results has become poorer. The multiplier design is usually based on a nonlinear model using a form of harmonic balance and a model for the Schottky barrier diode. Conventional voltage dependent lumped element models do a poor job of predicting THz frequency performance. This paper will describe a large signal Monte Carlo simulation of Schottky barrier multipliers. The simulation is a time dependent particle field Monte Carlo simulation with ohmic and Schottky barrier boundary conditions included that has been combined with a fixed point solution for the nonlinear circuit interaction. The results in the paper will point out some important time constants in varactor operation and will describe the effects of current saturation and nonlinear resistances on multiplier operation.

East, J.; Blakey, P.

1997-01-01

223

Quantum Monte Carlo Calculations of Light Nuclei  

E-print Network

Variational Monte Carlo and Green's function Monte Carlo are powerful tools for calculations of properties of light nuclei using realistic two-nucleon and three-nucleon potentials. Recently the GFMC method has been extended to multiple states with the same quantum numbers. The combination of the Argonne v_18 two-nucleon and Illinois-2 three-nucleon potentials gives a good prediction of many energies of nuclei up to 12C. A number of other recent results are presented: comparison of binding energies with those obtained by the no-core shell model; the incompatibility of modern nuclear Hamiltonians with a bound tetra-neutron; difficulties in computing RMS radii of very weakly bound nuclei, such as 6He; center-of-mass effects on spectroscopic factors; and the possible use of an artificial external well in calculations of neutron-rich isotopes.

Steven C. Pieper

2004-10-27

224

Quantum Monte Carlo Calculations of Light Nuclei  

NASA Astrophysics Data System (ADS)

Variational Monte Carlo and Green's function Monte Carlo are powerful tools for cal- culations of properties of light nuclei using realistic two-nucleon (NN) and three-nucleon (NNN) potentials. Recently the GFMC method has been extended to multiple states with the same quantum numbers. The combination of the Argonne v18 two-nucleon and Illinois-2 three-nucleon potentials gives a good prediction of many energies of nuclei up to 12C. A number of other recent results are presented: comparison of binding energies with those obtained by the no-core shell model; the incompatibility of modern nuclear Hamiltonians with a bound tetra-neutron; difficulties in computing RMS radii of very weakly bound nuclei, such as 6He; center-of-mass effects on spectroscopic factors; and the possible use of an artificial external well in calculations of neutron-rich isotopes.

Pieper, Steven C.

2005-04-01

225

Quantum Monte Carlo Calculations of Light Nuclei  

E-print Network

Variational Monte Carlo and Green's function Monte Carlo are powerful tools for calculations of properties of light nuclei using realistic two-nucleon and three-nucleon potentials. Recently the GFMC method has been extended to multiple states with the same quantum numbers. The combination of the Argonne v_18 two-nucleon and Illinois-2 three-nucleon potentials gives a good prediction of many energies of nuclei up to 12C. A number of other recent results are presented: comparison of binding energies with those obtained by the no-core shell model; the incompatibility of modern nuclear Hamiltonians with a bound tetra-neutron; difficulties in computing RMS radii of very weakly bound nuclei, such as 6He; center-of-mass effects on spectroscopic factors; and the possible use of an artificial external well in calculations of neutron-rich isotopes.

Pieper, S C

2005-01-01

226

Status of Monte Carlo at Los Alamos  

SciTech Connect

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

227

Monte-Carlo Opening Books for Amazons  

NASA Astrophysics Data System (ADS)

Automatically creating opening books is a natural step towards the building of strong game-playing programs, especially when there is little available knowledge about the game. However, while recent popular Monte-Carlo Tree-Search programs showed strong results for various games, we show here that programs based on such methods cannot efficiently use opening books created using algorithms based on minimax. To overcome this issue, we propose to use an MCTS-based technique, Meta-MCTS, to create such opening books. This method, while requiring some tuning to arrive at the best opening book possible, shows promising results to create an opening book for the game of the Amazons, even if this is at the cost of removing its Monte-Carlo part.

Kloetzer, Julien

228

Evaluation Function Based Monte-Carlo LOA  

NASA Astrophysics Data System (ADS)

Recently, Monte-Carlo Tree Search (MCTS) has advanced the field of computer Go substantially. Also in the game of Lines of Action (LOA), which has been dominated so far by ??, MCTS is making an inroad. In this paper we investigate how to use a positional evaluation function in a Monte-Carlo simulation-based LOA program (MC-LOA). Four different simulation strategies are designed, called Evaluation Cut-Off, Corrective, Greedy, and Mixed. They use an evaluation function in several ways. Experimental results reveal that the Mixed strategy is the best among them. This strategy draws the moves randomly based on their transition probabilities in the first part of a simulation, but selects them based on their evaluation score in the second part of a simulation. Using this simulation strategy the MC-LOA program plays at the same level as the ?? program MIA, the best LOA-playing entity in the world.

Winands, Mark H. M.; Björnsson, Yngvi

229

New developments in PHOKHARA Monte Carlo generator  

E-print Network

The present status of the physics program, which led to the development of the Monte Carlo event generator PHOKHARA is described. The possibility of using the radiative return method in various aspects of hadronic physics, from the measurement of the hadronic cross section, to detailed investigations of the hadronic dynamics is emphasized. New results are presented showing how to measure baryon form factors using the knowledge of their spin in baryon-antibaryon production with subsequent decay.

Henryk Czyz; Agnieszka Grzelinska; Agnieszka Wapienik

2007-10-23

230

Markov Chain Monte Carlo Prof. David Page  

E-print Network

Markov Chain Monte Carlo Prof. David Page transcribed by Matthew G. Lee #12;Markov Chain � A Markov, B, and C. It is impossible to go from the state A=T, B=T, C=F to any other state #12;Notation, go from (y1',y2',...,yi-1',yi,yi+1,...,yn) to (y1',y2',...,yi- 1',yi',yi+1,...,yn) � The probability

Page Jr., C. David

231

Monte-Carlo Simulations: FLUKA vs. MCNPX  

SciTech Connect

Several experiments were performed at the Phasotron and Nuclotron accelerators in JINR Dubna in which spallation reactions and neutron transport were studied. The experimental results were checked against the predictions of the Monte-Carlo code MCNPX. The discrepancies at 1.5 GeV and 2 GeV on the 'Energy plus Transmutation' setup were observed. Therefore the experimental results were checked with another code-FLUKA.

Oden, M. [Nuclear Physics Institute of ASCR, Rez (Czech Republic); Ecole des Mines de Nantes (France); Krasa, A.; Majerle, M.; Svoboda, O.; Wagner, V. [Nuclear Physics Institute of ASCR, Rez (Czech Republic); Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University (Czech Republic)

2007-11-26

232

Monte Carlo simulation of Touschek effect  

NASA Astrophysics Data System (ADS)

We present a Monte Carlo method implementation in the code elegant for simulating Touschek scattering effects in a linac beam. The local scattering rate and the distribution of scattered electrons can be obtained from the code either for a Gaussian-distributed beam or for a general beam whose distribution function is given. In addition, scattered electrons can be tracked through the beam line and the local beam-loss rate and beam halo information recorded.

Xiao, Aimin; Borland, Michael

2010-07-01

233

Monte Carlo Simulations of Ultrathin Magnetic Dots  

E-print Network

In this work we study the thermodynamic properties of ultrathin ferromagnetic dots using Monte Carlo simulations. We investigate the vortex density as a function of the temperature and the vortex structure in monolayer dots with perpendicular anisotropy and long-range dipole interaction. The interplay between these two terms in the hamiltonian leads to an interesting behavior of the thermodynamic quantities as well as the vortex density.

M. Rapini; R. A. Dias; D. P. Landau; B. V. Costa

2006-04-10

234

A Ballistic Monte Carlo Approximation of {\\pi}  

E-print Network

We compute a Monte Carlo approximation of {\\pi} using importance sampling with shots coming out of a Mossberg 500 pump-action shotgun as the proposal distribution. An approximated value of 3.136 is obtained, corresponding to a 0.17% error on the exact value of {\\pi}. To our knowledge, this represents the first attempt at estimating {\\pi} using such method, thus opening up new perspectives towards computing mathematical constants using everyday tools.

Dumoulin, Vincent

2014-01-01

235

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

2012-03-01

236

Randomized quasi-Monte Carlo simulation of fast-ion thermalization  

NASA Astrophysics Data System (ADS)

This work investigates the applicability of the randomized quasi-Monte Carlo method for simulation of fast-ion thermalization processes in fusion plasmas, e.g. for simulation of neutral beam injection and radio frequency heating. In contrast to the standard Monte Carlo method, the quasi-Monte Carlo method uses deterministic numbers instead of pseudo-random numbers and has a statistical weak convergence close to {O}(N^{-1}) , where N is the number of markers. We have compared different quasi-Monte Carlo methods for a neutral beam injection scenario, which is solved by many realizations of the associated stochastic differential equation, discretized with the Euler-Maruyama scheme. The statistical convergence of the methods is measured for time steps up to 214.

Höök, L. J.; Johnson, T.; Hellsten, T.

2012-01-01

237

Monte Carlo dose mapping on deforming anatomy  

PubMed Central

This paper proposes a Monte Carlo-based energy and mass congruent mapping (EMCM) method to calculate the dose on deforming anatomy. Different from dose interpolation methods, EMCM separately maps each voxel’s deposited energy and mass from a source image to a reference image with a displacement vector field (DVF) generated by deformable image registration (DIR). EMCM was compared with other dose mapping methods: energy-based dose interpolation (EBDI) and trilinear dose interpolation (TDI). These methods were implemented in EGSnrc/DOSXYZnrc, validated using a numerical deformable phantom and compared for clinical CT images. On the numerical phantom with an analytically invertible deformation map, EMCM mapped the dose exactly the same as its analytic solution, while EBDI and TDI had average dose errors of 2.5% and 6.0%. For a lung patient’s IMRT treatment plan, EBDI and TDI differed from EMCM by 1.96% and 7.3% in the lung patient’s entire dose region, respectively. As a 4D Monte Carlo dose calculation technique, EMCM is accurate and its speed is comparable to 3D Monte Carlo simulation. This method may serve as a valuable tool for accurate dose accumulation as well as for 4D dosimetry QA. PMID:19741278

Zhong, Hualiang; Siebers, Jeffrey V

2010-01-01

238

Current status and new horizons in Monte Carlo simulation of X-ray CT scanners  

Microsoft Academic Search

With the advent of powerful computers and parallel processing including Grid technology, the use of Monte Carlo (MC) techniques for radiation transport simu- lation has become the most popular method for modeling radiological imaging systems and particularly X-ray com- puted tomography (CT). The stochastic nature of involved processes such as X-ray photons generation, interaction with matter and detection makes MC

Habib Zaidi; Mohammad Reza Ay

2007-01-01

239

User's guide for an optical contrast seeker Monte Carlo terminal homing simulation  

Microsoft Academic Search

This report documents the development and incorporation of a stochastic Optical Contrast Seeker Model into the existent Monte Carlo point target terminal homing 6-DOF simulation program. In addition the basic pitch and yaw seeker platform dynamics, parameter target size, seeker breaklock, seeker blind range, transport log, and helicopter induced launch transients are included. Platform imperfections such as mass unbalance and

S. L. Ohanian; A. W. Lee Jr.; C. L. Lewis

1975-01-01

240

FEM computation of groove ridge and Monte Carlo simulation in two-body abrasive wear  

Microsoft Academic Search

Abrasion is a stochastic process. It has been realized by some researchers that Monte Carlo simulation is a powerful tool to predict the wear rate of materials. The important issue for the simulation is to collect necessary basic data of worn materials, such as, ductility, plasticity, hardness, etc. The most difficult work, however, is to get parameters related to wear

Liang Fang; Qihong Cen; Kun Sun; Weimin Liu; Xiaofeng Zhang; Zhifu Huang

2005-01-01

241

Simulation of agglomeration reactors via a coupled CFD\\/direct Monte-Carlo method  

Microsoft Academic Search

The present study deals with simulation of agglomeration reactors, based on a CFD calculation method for describing the turbulent flow field, coupled with a direct Monte-Carlo method for the agglomeration process. The potentiality of stochastic methods, well suited for simulation of spherical agglomeration where complex kernels have to take into account the effects of the particles size and of the

L. Madec; L. Falk; E. Plasari

2001-01-01

242

State-of-the-art Monte Carlo 1988  

SciTech Connect

Particle transport calculations in highly dimensional and physically complex geometries, such as detector calibration, radiation shielding, space reactors, and oil-well logging, generally require Monte Carlo transport techniques. Monte Carlo particle transport can be performed on a variety of computers ranging from APOLLOs to VAXs. Some of the hardware and software developments, which now permit Monte Carlo methods to be routinely used, are reviewed in this paper. The development of inexpensive, large, fast computer memory, coupled with fast central processing units, permits Monte Carlo calculations to be performed on workstations, minicomputers, and supercomputers. The Monte Carlo renaissance is further aided by innovations in computer architecture and software development. Advances in vectorization and parallelization architecture have resulted in the development of new algorithms which have greatly reduced processing times. Finally, the renewed interest in Monte Carlo has spawned new variance reduction techniques which are being implemented in large computer codes. 45 refs.

Soran, P.D.

1988-06-28

243

Status of Monte-Carlo Event Generators  

SciTech Connect

Recent progress on general-purpose Monte-Carlo event generators is reviewed with emphasis on the simulation of hard QCD processes and subsequent parton cascades. Describing full final states of high-energy particle collisions in contemporary experiments is an intricate task. Hundreds of particles are typically produced, and the reactions involve both large and small momentum transfer. The high-dimensional phase space makes an exact solution of the problem impossible. Instead, one typically resorts to regarding events as factorized into different steps, ordered descending in the mass scales or invariant momentum transfers which are involved. In this picture, a hard interaction, described through fixed-order perturbation theory, is followed by multiple Bremsstrahlung emissions off initial- and final-state and, finally, by the hadronization process, which binds QCD partons into color-neutral hadrons. Each of these steps can be treated independently, which is the basic concept inherent to general-purpose event generators. Their development is nowadays often focused on an improved description of radiative corrections to hard processes through perturbative QCD. In this context, the concept of jets is introduced, which allows to relate sprays of hadronic particles in detectors to the partons in perturbation theory. In this talk, we briefly review recent progress on perturbative QCD in event generation. The main focus lies on the general-purpose Monte-Carlo programs HERWIG, PYTHIA and SHERPA, which will be the workhorses for LHC phenomenology. A detailed description of the physics models included in these generators can be found in [8]. We also discuss matrix-element generators, which provide the parton-level input for general-purpose Monte Carlo.

Hoeche, Stefan; /SLAC

2011-08-11

244

Quantum Monte Carlo for vibrating molecules  

SciTech Connect

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

245

Kinetic Monte Carlo simulation of dislocation dynamics  

NASA Astrophysics Data System (ADS)

A kinetic Monte Carlo simulation of dislocation motion is introduced. The dislocations are assumed to be composed of pure edge and screw segments confined to a fixed lattice. The stress and temperature dependence of the dislocation velocity is studied, and finite-size effects are discussed. It is argued that surfaces and boundaries may play a significant role in the velocity of dislocations. The simulated dislocations are shown to display kinetic roughening according to the exponents predicted by the Kardar-Parisi-Zhang equation.

Lin, Karin; Chrzan, D. C.

1999-08-01

246

Spin correlations in Monte Carlo simulations.  

E-print Network

possible initial-state spin configurations contribute to the result. 4.4 tt¯ production in Hadron-Hadron Collisions Since the discovery of the top quark at the Tevatron there have been a number of studies of spin correlations in top quark pair production... Diagrams 50 D.2 Three Body Decay Feynman Diagrams 56 D.3 Four Body Decay Feynman Diagrams 62 D.4 Matrix Elements 63 1 1. Introduction In modern particle physics experiments it is important to have a Monte Carlo simula- tion which accurately predicts...

Richardson, P

247

Monte Carlo simulation for the transport beamline  

SciTech Connect

In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.

Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy)] [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy); Attili, A.; Marchetto, F.; Russo, G. [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy)] [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy); Cirrone, G. A. P.; Schillaci, F.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic)] [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic); Carpinelli, M. [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy)] [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy); Tramontana, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)] [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)

2013-07-26

248

Quantum Monte Carlo calculations for light nuclei  

SciTech Connect

Quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A {le} 8 have been made using a realistic Hamiltonian that fits NN scattering data. Results for more than two dozen different (J{sup {pi}}, T) p-shell states, not counting isobaric analogs, have been obtained. The known excitation spectra of all the nuclei are reproduced reasonably well. Density and momentum distributions and various electromagnetic moments and form factors have also been computed. These are the first microscopic calculations that directly produce nuclear shell structure from realistic NN interactions.

Wiringa, R.B. [Argonne National Lab., IL (United States). Physics Div.

1997-10-01

249

Quantum Monte Carlo calculations for light nuclei  

SciTech Connect

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

250

Quantum Monte Carlo calculations for light nuclei.  

SciTech Connect

Quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A {le} 8 are made using a realistic Hamiltonian that fits NN scattering data. Results for more than 40 different (J{pi}, T) states, plus isobaric analogs, are obtained and the known excitation spectra are reproduced reasonably well. Various density and momentum distributions and electromagnetic form factors and moments have also been computed. These are the first microscopic calculations that directly produce nuclear shell structure from realistic NN interactions.

Wiringa, R. B.

1998-10-23

251

Acceptance Rates in Multigrid Monte Carlo  

E-print Network

An approximation formula is derived for acceptance rates of nonlocal Metropolis updates in simulations of lattice field theories. The predictions of the formula agree quite well with Monte Carlo simulations of 2-dimensional Sine Gordon, XY and phi**4 models. The results are consistent with the following rule: For a critical model with a fundamental Hamiltonian H(phi) sufficiently high acceptance rates for a complete elimination of critical slowing down can only be expected if the expansion of in terms of the shift psi contains no relevant term (mass term).

M. Grabenstein; K. Pinn

1992-04-30

252

Spectral functions from Quantum Monte Carlo  

SciTech Connect

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

253

Monte Carlo Generation of Bohmian Trajectories  

E-print Network

We report on a Monte Carlo method that generates one-dimensional trajectories for Bohm's formulation of quantum mechanics that doesn't involve differentiation or integration of any equations of motion. At each time, t=n\\delta t (n=1,2,3,...), N particle positions are randomly sampled from the quantum probability density. Trajectories are built from the sorted N sampled positions at each time. These trajectories become the exact Bohm solutions in the limits N->\\infty and \\delta t -> 0. Higher dimensional problems can be solved by this method for separable wave functions. Several examples are given, including the two-slit experiment.

T. M. Coffey; R. E. Wyatt; W. C. Schieve

2008-07-01

254

Improved wave functions for quantum Monte Carlo  

E-print Network

been published or is to be published: Chapter 3: P. Seth, P. Lo´pez R?´os and R. J. Needs, “Quantum Monte Carlo study of the first-row atoms and ions”, J. Chem. Phys. 134, 084105 (2011). Chapter 4: P. Lo´pez R´?os, P. Seth, N. D. Drummond and R. J... and a pedant when it comes to indentation. I thank Neil Drummond and John Trail for helpful discussions. I am indebted to Tracey Ingham, Michael Rutter, David Taylor and Helen Verrechia for keeping TCM running smoothly. This work would not have been...

Seth, Priyanka

2013-02-05

255

Archimedes, the Free Monte Carlo simulator  

E-print Network

Archimedes is the GNU package for Monte Carlo simulations of electron transport in semiconductor devices. The first release appeared in 2004 and since then it has been improved with many new features like quantum corrections, magnetic fields, new materials, GUI, etc. This document represents the first attempt to have a complete manual. Many of the Physics models implemented are described and a detailed description is presented to make the user able to write his/her own input deck. Please, feel free to contact the author if you want to contribute to the project.

Sellier, Jean Michel D

2012-01-01

256

Biasing Monte-Carlo Simulations through RAVE Values  

Microsoft Academic Search

\\u000a The Monte-Carlo Tree Search algorithm has been successfully applied in various domains. However, its performance heavily depends\\u000a on the Monte-Carlo part. In this paper, we propose a generic way of improving the Monte-Carlo simulations by using RAVE values,\\u000a which already strongly improved the tree part of the algorithm. We prove the generality and efficiency of our approach by\\u000a showing improvements

Arpad Rimmel; Fabien Teytaud; Olivier Teytaud

2010-01-01

257

Discrete diffusion Monte Carlo for frequency-dependent radiative transfer  

SciTech Connect

Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique.

Densmore, Jeffrey D [Los Alamos National Laboratory; Kelly, Thompson G [Los Alamos National Laboratory; Urbatish, Todd J [Los Alamos National Laboratory

2010-11-17

258

MECA: a multiprocessor concept specialized to Monte Carlo  

SciTech Connect

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

259

Monte Carlo modeling of spatial coherence: free-space diffraction  

PubMed Central

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.

2008-01-01

260

Kinetic Monte Carlo with fields: diffusion in heterogeneous systems  

NASA Astrophysics Data System (ADS)

It is commonly perceived that to achieve breakthrough scientific discoveries in the 21^st century an integration of world leading experimental capabilities with theory, computational modeling and high performance computer simulations is necessary. Lying between the atomic and the macro scales, the meso scale is crucial for advancing materials research. Deterministic methods result computationally too heavy to cover length and time scales relevant for this scale. Therefore, stochastic approaches are one of the options of choice. In this talk I will describe recent progress in efficient parallelization schemes for Metropolis and kinetic Monte Carlo [1-2], and the combination of these ideas into a new hybrid Molecular Dynamics-kinetic Monte Carlo algorithm developed to study the basic mechanisms taking place in diffusion in concentrated alloys under the action of chemical and stress fields, incorporating in this way the actual driving force emerging from chemical potential gradients. Applications are shown on precipitation and segregation in nanostructured materials. Work in collaboration with E. Martinez, LANL, and with B. Sadigh, P. Erhart and A. Stukowsky, LLNL. Supported by the Center for Materials at Irradiation and Mechanical Extremes, an Energy Frontier Research Center funded by the U.S. Department of Energy (Award # 2008LANL1026) at Los Alamos National Laboratory [4pt] [1] B. Sadigh et al. to be published [2] E. Martinez et al. J. Comp. Phys. 227 (2008) 3804-3823

Alfredo Caro, Jose

2011-03-01

261

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

262

Monte Carlo modelling of a virtual wedge.  

PubMed

Compared with a set of physical photon wedges, a non physical wedge (virtual or dynamic wedge), realized by a moving collimator jaw, offers an alternative that allows creation of a wedged field with any arbitrary wedge angle instead of the traditional four physical wedges (15 degrees, 30 degrees, 45 degrees and 60 degrees). It is commonly assumed that non-physical wedges do not alter the photon spectrum compared with physical wedges that introduce beam hardening and loss of dose uniformity in the unwedged direction. In this study, we investigated the influence of a virtual wedge on the photon spectra of a 6-10 MV Siemens MD2 accelerator with the Monte Carlo code EGS4/BEAM. Good agreement was obtained between calculated and measured lateral dose profiles at the depth of maximum dose and at 10 cm depth for 20 x 20 cm2 fields for 6 and 10 MV photon beams. By comparing Monte Carlo models of a physical wedge and the virtual wedge that was studied in this work, it is confirmed that the latter has an insignificant effect on the beam quality, whereas the former can introduce significant beam hardening. PMID:10616157

Verhaegen, F; Das, I J

1999-12-01

263

THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE  

SciTech Connect

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

264

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

265

Quantum Monte Carlo calculations of neutron matter  

NASA Astrophysics Data System (ADS)

Uniform neutron matter is approximated by a cubical box containing a finite number of neutrons, with periodic boundary conditions. We report variational and Green’s function Monte Carlo calculations of the ground state of fourteen neutrons in a periodic box using the Argonne v8' two-nucleon interaction at densities up to one and half times the nuclear matter density. The effects of the finite box size are estimated using variational wave functions together with cluster expansion and chain summation techniques. They are small at subnuclear densities. We discuss the expansion of the energy of low-density neutron gas in powers of its Fermi momentum. This expansion is strongly modified by the large nn scattering length, and does not begin with the Fermi-gas kinetic energy, as assumed in both Skyrme and relativistic mean field theories. The leading term of neutron gas energy is approximately half the Fermi-gas kinetic energy. The quantum Monte Carlo results are also used to calibrate the accuracy of variational calculations employing Fermi hypernetted and single operator chain summation methods to study nucleon matter over a larger density range, with more realistic Hamiltonians including three-nucleon interactions.

Carlson, J.; Morales, J.; Pandharipande, V. R.; Ravenhall, D. G.

2003-08-01

266

Quantum Monte Carlo Calculations of Neutron Matter  

E-print Network

Uniform neutron matter is approximated by a cubic box containing a finite number of neutrons, with periodic boundary conditions. We report variational and Green's function Monte Carlo calculations of the ground state of fourteen neutrons in a periodic box using the Argonne $\\vep $ two-nucleon interaction at densities up to one and half times the nuclear matter density. The effects of the finite box size are estimated using variational wave functions together with cluster expansion and chain summation techniques. They are small at subnuclear densities. We discuss the expansion of the energy of low-density neutron gas in powers of its Fermi momentum. This expansion is strongly modified by the large nn scattering length, and does not begin with the Fermi-gas kinetic energy as assumed in both Skyrme and relativistic mean field theories. The leading term of neutron gas energy is ~ half the Fermi-gas kinetic energy. The quantum Monte Carlo results are also used to calibrate the accuracy of variational calculations employing Fermi hypernetted and single operator chain summation methods to study nucleon matter over a larger density range, with more realistic Hamiltonians including three-nucleon interactions.

J. Carlson; J. Morales Jr; V. R. Pandharipande; D. G. Ravenhall

2003-02-17

267

Monte Carlo radiative transfer in protoplanetary disks  

E-print Network

We present a new continuum 3D radiative transfer code, MCFOST, based on a Monte-Carlo method. MCFOST can be used to calculate (i) monochromatic images in scattered light and/or thermal emission, (ii) polarisation maps, (iii) interferometric visibilities, (iv) spectral energy distributions and (v) dust temperature distributions of protoplanetary disks. Several improvements to the standard Monte Carlo method are implemented in MCFOST to increase efficiency and reduce convergence time, including wavelength distribution adjustments, mean intensity calculations and an adaptive sampling of the radiation field. The reliability and efficiency of the code are tested against a previously defined benchmark, using a 2D disk configuration. No significant difference (no more than 10%, and generally much less) is found between the temperatures and SEDs calculated by MCFOST and by other codes included in the benchmark. A study of the lowest disk mass detectable by Spitzer, around young stars, is presented and the colours of ``representative'' parametric disks are compared to recent IRAC and MIPS Spitzer colours of solar-like young stars located in nearby star forming regions.

Christophe Pinte; Francois Menard; Gaspard Duchene; Pierre Bastien

2006-06-22

268

Multilevel Monte Carlo simulation of Coulomb collisions  

NASA Astrophysics Data System (ADS)

We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau-Fokker-Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ?, the computational cost of the method is O(?-2) or O(?-2(), depending on the underlying discretization, Milstein or Euler-Maruyama respectively. This is to be contrasted with a cost of O(?-3) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ?=10-5. We discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.

Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.

2014-10-01

269

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

270

Quantum Monte Carlo Calculations of Neutron Matter  

E-print Network

Uniform neutron matter is approximated by a cubic box containing a finite number of neutrons, with periodic boundary conditions. We report variational and Green's function Monte Carlo calculations of the ground state of fourteen neutrons in a periodic box using the Argonne $\\vep $ two-nucleon interaction at densities up to one and half times the nuclear matter density. The effects of the finite box size are estimated using variational wave functions together with cluster expansion and chain summation techniques. They are small at subnuclear densities. We discuss the expansion of the energy of low-density neutron gas in powers of its Fermi momentum. This expansion is strongly modified by the large nn scattering length, and does not begin with the Fermi-gas kinetic energy as assumed in both Skyrme and relativistic mean field theories. The leading term of neutron gas energy is ~ half the Fermi-gas kinetic energy. The quantum Monte Carlo results are also used to calibrate the accuracy of variational calculations ...

Carlson, J; Ravenhall, D G

2003-01-01

271

Estimating rock mass properties using Monte Carlo simulation: Ankara andesites  

NASA Astrophysics Data System (ADS)

In the paper, a previously introduced method ( Sari, 2009) is applied to the problem of estimating the rock mass properties of Ankara andesites. For this purpose, appropriate closed form (parametric) distributions are described for intact rock and discontinuity parameters of the Ankara andesites at three distinct weathering grades. Then, these distributions are included as inputs in the Rock Mass Rating ( RMR) classification system prepared in a spreadsheet model. A stochastic analysis is carried out to evaluate the influence of correlations between relevant distributions on the simulated RMR values. The model is also used in Monte Carlo simulations to estimate the possible ranges of the Hoek-Brown strength parameters of the rock under investigation. The proposed approach provides a straightforward and effective assessment of the variability of the rock mass properties. Hence, a wide array of mechanical characteristics can be adequately represented in any preliminary design consideration for a given rock mass.

Sari, Mehmet; Karpuz, Celal; Ayday, Can

2010-07-01

272

Exploring Monte Carlo Simulation Strategies for Geoscience Applications  

NASA Astrophysics Data System (ADS)

Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer generated random numbers, uniformly distributed on [0, 1], can be very different depending on the selection of pseudo-random number (PRN), quasi-random number (QRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the expected error variances are generally of different orders for the same number of random numbers. A comparative analysis of these three strategies has been carried out for geodetic and related applications in planar and spherical contexts. Based on these computational experiments, conclusions and recommendations concerning their performance and error variances are included.

Blais, J.; Grebenitcharsky, R.; Zhang, Z.

2008-12-01

273

Quantum Monte Carlo Endstation for Petascale Computing  

SciTech Connect

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

274

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

275

Ultraviolet filtering of lattice configurations and applications to Monte Carlo dynamics  

E-print Network

We present a detailed study of a filtering method based upon Dirac quasi-zero-modes 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.

Perez, Margarita Garcia; Sastre, Alfonso

2011-01-01

276

Monte Carlo study of alloy nanostructures  

NASA Astrophysics Data System (ADS)

Alloy materials with nanostructures are receiving growing interest for magnetic storage applications. Substantial experimental efforts are being devoted to synthesis of alloy nanostructures for magnetic reading-writing heads and as storage media. Further developments in this area would benefit from a detailed understanding of the thermodynamic factors underlying structural formation and transformation in relevant nanoscale geometries. This thesis is devoted to the development and application of lattice-model-based Monte Carlo simulations for investigating the phase diagrams and thermodynamic properties of alloys in two nanostructure geometries: epitaxial ultrathin films and faceted nanoparticles. Recently, ultrathin alloy films composed of size-mismatched bulk-immiscible metals, have been observed to form self-assembled lateral multilayer (SALM) structures, which provide a novel method to fabricate magnetic readers based on the giant magnetoresistance (GMR) effect. We investigate the energetic factors leading to the formation of SALM structures, focusing specifically on Fe-Ag/Mo(110) where experiments observed compositionally modulated stripe patterns with ˜ 2 nm periodicities. A lattice model framework is developed to simulate the thermodynamic stability of these films. We find that the competition between the chemical and elastic interactions leads to a minimum energy for stripes with a specific periodicity. Monte-Carlo simulations lead to predictions for the periodicity of the stripes and order-disorder transition temperatures consistent with experimental observations. Novel methods have been developed to synthesize nanoscale L10 structures with large magnetocrystalline anisotropy, but a general problem is that as-synthesized these particles form in the disordered nonmagnetic phase and an annealing step is required to induce transformation into the desired L10 structure. Since annealing can also lead to the undesirable particle coalescence, optimization of processing methods can benefit from detailed understanding of the thermodynamic and kinetic factors underlying the ordering process. We have adapted a lattice-model framework previously applied to studies of surface segregation and surface-alloying in Monte Carlo studies of nanoparticle ordering as functions of size, composition and shape. We find that both decreasing size and increasing surface segregation can reduce the ordering temperature. The connection between the results and properties is discussed, and directions for future computational research on this topic are suggested.

Yang, Bo

277

Markov Chain Monte Carlo Methods for Statistical Inference  

Microsoft Academic Search

SUMMARY These notes provide an introduction to Markov chain Monte Carlo methods and their applications to both Bayesian and frequentist statistical inference. Such methods have revolutionized what can be achieved computationally, es- pecially in the Bayesian paradigm. The account begins by discussing ordi- nary Monte Carlo methods: these have the same goals as the Markov chain versions but can only

Julian Besag

278

Self Regenerative Markov Chain Monte Carlo with Sujit K. Sahu  

E-print Network

Self Regenerative Markov Chain Monte Carlo with Adaptation Sujit K. Sahu Faculty of Mathematical{Hastings algorithm; Regeneration. 1 Introduction Markov Chain Monte Carlo (MCMC) is a key technique for calculating performed, we go on to simulate another independent candidate point from the proposal distribution

Sahu, Sujit K

279

Monte Carlo likelihood inference for missing data models  

Microsoft Academic Search

We describe a Monte Carlo method to approximate the maximum likelihood estimate (MLE), when there are missing data and the observed data likelihood is not available in closed form. This method uses simulated missing data that are independent and identically distributed and independent of the observed data. Our Monte Carlo approximation to the MLE is a consistent and asymptotically normal

Yun Ju Sung; Charles J. Geyer

2007-01-01

280

Monte-Carlo Tree Search (MCTS) for Computer Go  

E-print Network

Monte-Carlo Tree Search (MCTS) for Computer Go Bruno Bouzy bruno.bouzy@parisdescartes.fr Université game The « old » approach (*-2002) The Monte-Carlo approach (2002-2005) The MCTS approach (2006 Paris Descartes Séminaire BigMC 5 mai 2011 #12;MCTS for Computer Go 2 Outline The game of Go: a 9x9

Bouzy, Bruno

281

transient and online knowledge in Monte-Carlo exploration  

Microsoft Academic Search

We combine for Monte-Carlo exploration machine learning at four dierent time scales: - online regret, through the use of bandit algorithms and Monte-Carlo estimates; - transient learning, through the use of rapid action value estimates (RAVE) which are learnt online and used for accelerating the explo- ration and are thereafter neglected; - oine learning, by data mining of datasets of

Guillaume Chaslot; Louis Chatriot; C. Fiter; Sylvain Gelly; Jean-Baptiste Hoock; Julien Perez; Arpad Rimmel; Olivier Teytaud

282

Monte Carlo Study of Ferromagnetic Transition in Double Exchange Systems  

E-print Network

Monte Carlo Study of Ferromagnetic Transition in Double Exchange Systems Yukitoshi Motome and Nobuo to treat these fluc- tuations is the Monte Carlo (MC) method. In the MC calculations in a finite size Research), 2-1 Hirosawa, Wako, Saitama 351-0198; E-mail: motome@riken.go.jp the present DE system, since

Katsumoto, Shingo

283

VEGAS: A Monte Carlo Simulation of Intranuclear Cascades  

Microsoft Academic Search

The model dependence of the Monte Carlo simulation of intranuclear cascades generated by nucleons up to ~380 MeV incident on complex nuclei has been investigated. Differences in the details of the Monte Carlo procedure between this work and previous intranuclear-cascade calculations are discussed. The specific effects that were investigated are those attendant upon the introduction of refraction of cascade particles

K. Chen; Z. Fraenkel; G. Friedlander; J. R. Grover; J. M. Miller; Y. Shimamoto

1968-01-01

284

Quantum Monte Carlo method for attractive Coulomb potentials  

Microsoft Academic Search

Starting from an exact lower bound on the imaginary-time propagator, we\\u000apresent a Path-Integral Quantum Monte Carlo method that can handle singular\\u000aattractive potentials. We illustrate the basic ideas of this Quantum Monte\\u000aCarlo algorithm by simulating the ground state of hydrogen and helium.

J. S. Kole; H. De Raedt

2001-01-01

285

Quantum Monte Carlo method for attractive Coulomb potentials  

Microsoft Academic Search

Starting from an exact lower bound on the imaginary-time propagator, we present a path-integral quantum Monte Carlo method that can handle singular attractive potentials. We illustrate the basic ideas of this quantum Monte Carlo algorithm by simulating the ground state of hydrogen and helium.

J. S. Kole; H. de Raedt

2001-01-01

286

Auxiliary Field Quantum Monte Carlo in Continuum Systems  

Microsoft Academic Search

The auxiliary field Quantum Monte Carlo method allows Monte Carlo to be performed in any basis. This is accomplished by using the Hubbard-Stratonavich transformation to transform two body interactions into an integral over one body interactions. In practice this method has been difficult to use because while exact, it suffered from a phase problem more severe than the sign problem

Luke Shulenburger

2005-01-01

287

Quantum Monte Carlo for the Electronic Structure of Atomic Systems  

Microsoft Academic Search

In this work we tackle the problem of the electronic structure of atoms by using Quantum Monte Carlo methods. The Variational Monte Carlo method has been extensively employed with trial wave functions which include different correlation mechanisms. A reliable description of different properties such as ionization potentials and electron affinities, or excitation energies is obtained for atoms with a relatively

A. Sarsa; E. Buendía; F. J. Gálvez; P. Maldonado

2008-01-01

288

A new Monte Carlo assisted approach to detector response functions  

Microsoft Academic Search

The physical mechanisms that describe the components of NaI, Ge, and SiLi detector response have been investigated using Monte Carlo simulation. The mechanisms described focus on the shape of the Compton edge, the magnitude of the flat continuum, and the shape of the exponential tails features. These features are not accurately predicted by previous Monte Carlo simulation. Probable interaction mechanisms

Avneet Sood

2000-01-01

289

Dalton Vinicus Kozak Simulao Direta de Monte Carlo de  

E-print Network

Dalton Vinicus Kozak Simulação Direta de Monte Carlo de Escoamentos Internos e Externos de Gases;Dalton Vinicus Kozak Simulação Direta de Monte Carlo de Escoamentos Internos e Externos de Gases no Amplo no Amplo Intervalo de Rarefação com Aplicação a Problemas da Engenharia Aeroespacial" defendida por Dalton

Sharipov, Felix

290

Inverse Monte Carlo: a unified reconstruction algorithm for SPECT  

Microsoft Academic Search

Inverse Monte Carlo (IMOC) is presented as a unified reconstruction algorithm for Emission Computed Tomography (ECT) providing simultaneous compensation for scatter, attenuation, and the variation of collimator resolution with depth. The technique of inverse Monte Carlo is used to find an inverse solution to the photon transport equation (an integral equation for photon flux from a specified source) for a

Carey E. Floyd; R. E. Coleman; R. J. Jaszczak

1985-01-01

291

Bayesian Inference in Econometric Models Using Monte Carlo Integration  

Microsoft Academic Search

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

292

Monte Carlo Test Assembly for Item Pool Analysis and Extension  

ERIC Educational Resources Information Center

A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal…

Belov, Dmitry I.; Armstrong, Ronald D.

2005-01-01

293

Vectorized Monte Carlo methods for reactor lattice analysis  

NASA Technical Reports Server (NTRS)

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

Brown, F. B.

1984-01-01

294

Sampling from a polytope and hard-disk Monte Carlo  

NASA Astrophysics Data System (ADS)

The hard-disk problem, the statics and the dynamics of equal two-dimensional hard spheres in a periodic box, has had a profound influence on statistical and computational physics. Markov-chain Monte Carlo and molecular dynamics were first discussed for this model. Here we reformulate hard-disk Monte Carlo algorithms in terms of another classic problem, namely the sampling from a polytope. Local Markov-chain Monte Carlo, as proposed by Metropolis et al. in 1953, appears as a sequence of random walks in high-dimensional polytopes, while the moves of the more powerful event-chain algorithm correspond to molecular dynamics evolution. We determine the convergence properties of Monte Carlo methods in a special invariant polytope associated with hard-disk configurations, and the implications for convergence of hard-disk sampling. Finally, we discuss parallelization strategies for event-chain Monte Carlo and present results for a multicore implementation.

Kapfer, Sebastian C.; Krauth, Werner

2013-08-01

295

Monte Carlo stratified source-sampling  

SciTech Connect

In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo {open_quotes}eigenvalue of the world{close_quotes} problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. The original test-problem was treated by a special code designed specifically for that purpose. Recently ANL started work on a method for dealing with more realistic eigenvalue of the world configurations, and has been incorporating this method into VIM. The original method has been modified to take into account real-world statistical noise sources not included in the model problem. This paper constitutes a status report on work still in progress.

Blomquist, R.N.; Gelbard, E.M.

1997-09-01

296

Quantum ice: a quantum Monte Carlo study.  

PubMed

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

297

Methods for Monte Carlo simulations of biomacromolecules  

PubMed Central

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. PMID:20428473

Vitalis, Andreas; Pappu, Rohit V.

2010-01-01

298

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

299

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.

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

2013-05-01

300

Correlations in the Monte Carlo Glauber model  

NASA Astrophysics Data System (ADS)

Event-by-event fluctuations of observables are often modeled using the Monte Carlo Glauber model, in which the energy is initially deposited in sources associated with wounded nucleons. In this paper, we analyze in detail the correlations between these sources in proton-nucleus and nucleus-nucleus collisions. There are correlations arising from nucleon-nucleon correlations within each nucleus, and correlations due to the collision mechanism, which we dub twin correlations. We investigate this new phenomenon in detail. At the Brookhaven Relativistic Heavy Ion Collider and CERN Large Hadron Collider energies, correlations are found to have modest effects on size and eccentricity fluctuations, such that the Glauber model produces to a good approximation a collection of independent sources.

Blaizot, Jean-Paul; Broniowski, Wojciech; Ollitrault, Jean-Yves

2014-09-01

301

Exploring Theory Space with Monte Carlo Reweighting  

E-print Network

Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. In particular, we suggest procedures that allow more efficient collaboration between theorists and experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.

Gainer, James S; Matchev, Konstantin T; Mrenna, Stephen; Park, Myeonghun

2014-01-01

302

Exploring Theory Space with Monte Carlo Reweighting  

E-print Network

Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. In particular, we suggest procedures that allow more efficient collaboration between theorists and experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.

James S. Gainer; Joseph Lykken; Konstantin T. Matchev; Stephen Mrenna; Myeonghun Park

2014-04-28

303

Quantum Ice : a quantum Monte Carlo study  

E-print Network

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, stabilising 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.

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

2011-05-20

304

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

305

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

306

Monte Carlo applications to acoustical field solutions  

NASA Technical Reports Server (NTRS)

The Monte Carlo technique is proposed for the determination of the acoustical pressure-time history at chosen points in a partial enclosure, the central idea of this technique being the tracing of acoustical rays. A statistical model is formulated and an algorithm for pressure is developed, the conformity of which is examined by two approaches and is shown to give the known results. The concepts that are developed are applied to the determination of the transient field due to a sound source in a homogeneous medium in a rectangular enclosure with perfect reflecting walls, and the results are compared with those presented by Mintzer based on the Laplace transform approach, as well as with a normal mode solution.

Haviland, J. K.; Thanedar, B. D.

1973-01-01

307

Monte Carlo simulation of modulated phases  

SciTech Connect

This paper presents Monte Carlo simulation results for the formation of modulated phases in the framework of the two dimensional ANNNI model with a nonconserved order parameter. This work complements the earlier studies of Kaski, et al. by examining a different, wider area of parameter space and temperature. Like Kaski, et al., it is found that for certain temperatures and values of the frustration parameter, kappa, ordered domains form quickly and the correlation length grows as the square root of time. However, there exists a range of kappa for which a quench from high to low temperature results in the formation of a metastable glassy phase. In addition to the ANNNI model study, preliminary results are presented on a newly developed model which exhibits phase modulation due to the presence of elastic interactions between the different phase and with an externally applied stress. 12 refs., 12 figs.

Srolovitz, D.J.; Hassold, G.N.; Gayda, J.

1987-01-01

308

Angular biasing in implicit Monte-Carlo  

SciTech Connect

Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise.

Zimmerman, G.B.

1994-10-20

309

Monte Carlo simulations in Nuclear Medicine  

SciTech Connect

Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.

Loudos, George K. [Department of Medical Instrumentation Technology, Technological Educational Institute of Athens (Greece)

2007-11-26

310

Total Monte Carlo evaluation for dose calculations.  

PubMed

Total Monte Carlo (TMC) is a method to propagate nuclear data (ND) uncertainties in transport codes, by using a large set of ND files, which covers the ND uncertainty. The transport code is run multiple times, each time with a unique ND file, and the result is a distribution of the investigated parameter, e.g. dose, where the width of the distribution is interpreted as the uncertainty due to ND. Until recently, this was computer intensive, but with a new development, fast TMC, more applications are accessible. The aim of this work is to test the fast TMC methodology on a dosimetry application and to propagate the (56)Fe uncertainties on the predictions of the dose outside a proposed 14-MeV neutron facility. The uncertainty was found to be 4.2 %. This can be considered small; however, this cannot be generalised to all dosimetry applications and so ND uncertainties should routinely be included in most dosimetry modelling. PMID:24277871

Sjöstrand, H; Alhassan, E; Conroy, S; Duan, J; Hellesen, C; Pomp, S; Osterlund, M; Koning, A; Rochman, D

2014-10-01

311

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

312

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

313

Monte Carlo simulations in Nuclear Medicine  

NASA Astrophysics Data System (ADS)

Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.

Loudos, George K.

2007-11-01

314

A MONTE CARLO SEQUENTIAL ESTIMATION OF POINT PROCESS OPTIMUM FILTERING FOR BRAIN MACHINE INTERFACES  

E-print Network

1 A MONTE CARLO SEQUENTIAL ESTIMATION OF POINT PROCESS OPTIMUM FILTERING FOR BRAIN MACHINE Monte Carlo Sequential Estimation for Point Processes.................................................29 Simulation of Monte Carlo Sequential Estimation on Neural Spike Train Decoding............32 Interpretation

Slatton, Clint

315

Monte Carlo technique in modeling ground motion coherence in sedimentary filled valleys  

E-print Network

Monte Carlo technique in modeling ground motion coherence in sedimentary filled valleys Arrigo propagation Monte Carlo numerical simulations Site effects a b s t r a c t Using a Monte Carlo method based

Cerveny, Vlastislav

316

Crossing the mesoscale no-mans land via parallel kinetic Monte Carlo.  

SciTech Connect

The kinetic Monte Carlo method and its variants are powerful tools for modeling materials at the mesoscale, meaning at length and time scales in between the atomic and continuum. We have completed a 3 year LDRD project with the goal of developing a parallel kinetic Monte Carlo capability and applying it to materials modeling problems of interest to Sandia. In this report we give an overview of the methods and algorithms developed, and describe our new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator. We also highlight the development of several Monte Carlo models in SPPARKS for specific materials modeling applications, including grain growth, bubble formation, diffusion in nanoporous materials, defect formation in erbium hydrides, and surface growth and evolution.

Garcia Cardona, Cristina (San Diego State University); Webb, Edmund Blackburn, III; Wagner, Gregory John; Tikare, Veena; Holm, Elizabeth Ann; Plimpton, Steven James; Thompson, Aidan Patrick; Slepoy, Alexander (U. S. Department of Energy, NNSA); Zhou, Xiao Wang; Battaile, Corbett Chandler; Chandross, Michael Evan

2009-10-01

317

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

318

Stochastic Approximation in Monte Carlo Computation  

E-print Network

the spectral density for a physical system. A remarkable feature of the WL algorithm is that it is not trapped led to many successful applications of the algorithm in statistical physics and biophysics; however the energy landscape of the distribution is rugged. [In terms of physics, -log{p0(x)} is called the energy

Liang, Faming

319

Recent advances and future prospects for Monte Carlo  

SciTech Connect

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

320

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

321

Quantum Monte Carlo with non-local chiral interactions  

NASA Astrophysics Data System (ADS)

Quantum Monte Carlo methods have been used very successfully to calculate the ground state properties of a variety of nuclear and other strongly interacting many body systems. An exciting recent development in low energy nuclear physics is the formulation of nuclear Hamiltonians based on the symmetries of quantum chromodynamics via chiral effective field theory. However, the usual coordinate space based quantum Monte Carlo implementation is unsuitable for these Hamiltonians due to the presence of non-localites. Here we report on our recent work in developing a new quantum Monte Carlo algorithm suitable for these non-local Hamiltonians, and present some results for pure neutron matter.

Roggero, A.; Mukherjee, A.; Pederiva, F.

2014-07-01

322

Variance reduction in Monte Carlo analysis of rarefied gas diffusion.  

NASA Technical Reports Server (NTRS)

The problem of rarefied diffusion between parallel walls is solved using the Monte Carlo method. The diffusing molecules are evaporated or emitted from one of the two parallel walls and diffuse through another molecular species. The Monte Carlo analysis treats the diffusing molecule as undergoing a Markov random walk, and the local macroscopic properties are found as the expected value of the random variable, the random walk payoff. By biasing the transition probabilities and changing the collision payoffs, the expected Markov walk payoff is retained but its variance is reduced so that the Monte Carlo result has a much smaller error.

Perlmutter, M.

1972-01-01

323

Symmetry constraints and variational principles in diffusion quantum Monte Carlo calculations of excited-state energies  

Microsoft Academic Search

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding\\u000athe lowest energy many-fermion wave function with the same nodal surface as a\\u000achosen trial function. It has proved itself among the most accurate methods\\u000aavailable for calculating many-electron ground states, and is one of the few\\u000aapproaches that can be applied to systems large enough to act as

W. M. C. Foulkes; Randolph Q. Hoodand; R. J. Needs

1999-01-01

324

Symmetry constraints and variational principles in diffusion quantum Monte Carlo calculations of excited-state energies  

Microsoft Academic Search

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding the lowest energy many-fermion wave function with the same nodal surface as a chosen trial function. It has proved itself among the most accurate methods available for calculating many-electron ground states, and is one of the few approaches that can be applied to systems large enough to act as

W. M. C. Foulkes; Randolph Q. Hood; R. J. Needs

1999-01-01

325

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

326

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

327

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; Haren, Raymond; Clark, Frank O.

2006-05-01

328

Monte Carlo simulation of stoquastic Hamiltonians  

E-print Network

Stoquastic Hamiltonians are characterized by the property that their off-diagonal matrix elements in the standard product basis are real and non-positive. Many interesting quantum models fall into this class including the Transverse field Ising Model (TIM), the Heisenberg model on bipartite graphs, and the bosonic Hubbard model. Here we consider the problem of estimating the ground state energy of a local stoquastic Hamiltonian $H$ with a promise that the ground state of $H$ has a non-negligible correlation with some `guiding' state that admits a concise classical description. A formalized version of this problem called Guided Stoquastic Hamiltonian is shown to be complete for the complexity class MA (a probabilistic analogue of NP). To prove this result we employ the Projection Monte Carlo algorithm with a variable number of walkers. Secondly, we show that the ground state and thermal equilibrium properties of the ferromagnetic TIM can be simulated in polynomial time on a classical probabilistic computer. This result is based on the approximation algorithm for the classical ferromagnetic Ising model due to Jerrrum and Sinclair (1993).

Sergey Bravyi

2014-02-10

329

Moderato: A Monte-Carlo radiographic simulation  

NASA Astrophysics Data System (ADS)

To ensure security on nuclear power plants, Electricité de France uses radiographic inspection for systemmatic pipe control. The extreme temperature and pressure conditions to which pipes are submitted may generate structural defects that must be detected and characterized. In order to provide valuable evidence on inspection capability, EDF is involved in the evaluation of a radiographic data simulation software (MODERATO). According to EDF's requirements the whole radiographic process is modeled according to its physical behavior and incorporates new optimization adaptive techniques to decrease execution time so that computation time remains acceptable. According to EDF's needs sources are Iridium and Cobalt ones. Objects and flaws of any size or shape, described by their CAD descriptions, can be simulated. It is suitable for simulating complex objects like casted elbows or welding. The detector consists in films and lead screens that can be combined. The model is completely microscopic and is based on Monte-Carlo simulation, so that each photon and electron behavior is computed one after the other. During evaluation, the blur resulting from scattering of photons in the absorbing material has been observed and measured on test radiographs; the detector response has also been studied. Resulting images are correct and are suitable for further applications like image processing or 3D reconstruction.

Bonin, A.; Lavayssière, B.; Chalmond, B.

2000-05-01

330

Measuring Berry curvature with quantum Monte Carlo  

NASA Astrophysics Data System (ADS)

The Berry curvature and its descendant, the Berry phase, play an important role in quantum mechanics. They can be used to understand the Aharonov-Bohm effect, define topological Chern numbers, and generally to investigate the geometric properties of a quantum ground state manifold. While Berry curvature has been well studied in the regimes of few-body physics and noninteracting particles, its use in the regime of strong interactions is hindered by the lack of numerical methods to solve for it. In this paper I fill this gap by implementing a quantum Monte Carlo method to solve for the Berry curvature, based on interpreting Berry curvature as a leading correction to imaginary time ramps. I demonstrate my algorithm using the transverse-field Ising model in one and two dimensions, the latter of which is nonintegrable. Despite the fact that the Berry curvature gives information about the phase of the wave function, I show that the algorithm has no sign or phase problem for standard sign-problem-free Hamiltonians. My algorithm scales similarly to conventional methods as a function of system size and energy gap, and therefore should prove a valuable tool in investigating the quantum geometry of many-body systems.

Kolodrubetz, Michael

2014-01-01

331

Atomistic Monte Carlo Simulation of Lipid Membranes  

PubMed Central

Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol. PMID:24469314

Wustner, Daniel; Sklenar, Heinz

2014-01-01

332

Low variance methods for Monte Carlo simulation of phonon transport  

E-print Network

Computational studies in kinetic transport are of great use in micro and nanotechnologies. In this work, we focus on Monte Carlo methods for phonon transport, intended for studies in microscale heat transfer. After reviewing ...

Péraud, Jean-Philippe M. (Jean-Philippe Michel)

2011-01-01

333

Monte Carlo computations of the hadronic mass spectrum  

SciTech Connect

This paper summarizes two talks presented at the Orbis Scientiae Meeting, 1982. Monte Carlo results on the mass gap (or glueball mass) and on the masses of the lightest quark-model hadrons are illustrated.

Rebbi, C.

1982-01-01

334

MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD  

EPA Science Inventory

A predictive screening model was developed for fate and transport of viruses in the unsaturated zone. A database of input parameters allowed Monte Carlo analysis with the model. The resulting kernel densities of predicted attenuation during percolation indicated very ...

335

Metodi di Monte Carlo applicati a sistemi di comunicazione digitali.  

E-print Network

??L’interpretazione dei fenomeni aleatori con metodi statistici conobbe una rinascita a partire dal 1945-1946 con l’avvento del campionamento statistico, ribattezzato Metodo di Monte Carlo; quest’ultimo… (more)

Agostini, Giulia

2012-01-01

336

DETERMINING UNCERTAINTY IN PHYSICAL PARAMETER MEASUREMENTS BY MONTE CARLO SIMULATION  

EPA Science Inventory

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...

337

Enhancements in Continuous-Energy Monte Carlo Capabilities in SCALE  

SciTech Connect

Monte Carlo tools in SCALE are commonly used in criticality safety calculations as well as sensitivity and uncertainty analysis, depletion, and criticality alarm system analyses. Recent improvements in the continuous-energy data generated by the AMPX code system and significant advancements in the continuous-energy treatment in the KENO Monte Carlo eigenvalue codes facilitate the use of SCALE Monte Carlo codes to model geometrically complex systems with enhanced solution fidelity. The addition of continuous-energy treatment to the SCALE Monaco code, which can be used with automatic variance reduction in the hybrid MAVRIC sequence, provides significant enhancements, especially for criticality alarm system modeling. This paper describes some of the advancements in continuous-energy Monte Carlo codes within the SCALE code system.

Bekar, Kursat B [ORNL] [ORNL; Celik, Cihangir [ORNL] [ORNL; Wiarda, Dorothea [ORNL] [ORNL; Peplow, Douglas E. [ORNL] [ORNL; Rearden, Bradley T [ORNL] [ORNL; Dunn, Michael E [ORNL] [ORNL

2013-01-01

338

Monte Carlo methods for parallel processing of diffusion equations  

E-print Network

A Monte Carlo algorithm for solving simple linear systems using a random walk is demonstrated and analyzed. The described algorithm solves for each element in the solution vector independently. Furthermore, it is demonstrated ...

Vafadari, Cyrus

2013-01-01

339

Validation of Phonon Physics in the CDMS Detector Monte Carlo  

E-print Network

The SuperCDMS collaboration is a dark matter search effort aimed at detecting the scattering of WIMP dark matter from nuclei in cryogenic germanium targets. The CDMS Detector Monte Carlo (CDMS-DMC) is a simulation tool ...

McCarthy, K. A.

340

Monte Carlo variance reduction approaches for non-Boltzmann tallies  

SciTech Connect

Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed.

Booth, T.E.

1992-12-01

341

Markovian Monte Carlo solutions of the NLO QCD evolution equations  

E-print Network

We present precision Monte Carlo calculations solving the QCD evolution equations up to the next-to-leading-order (NLO) level. They employ forward Markovian Monte Carlo (FMC) algorithms, which provide the rigorous solutions of the QCD evolution equations. Appropriate Monte Carlo algorithms are described in detail. They are implemented in the form of the Monte Carlo program EvolFMC, which features the NLO kernels for the QCD evolution. The presented numerical results agree with those from independent, non-MC, programs (QCDNum16, APCheb33) at the level of 0.1%. In this way we have demonstrated the feasibility of the precision MC calculations for the QCD evolution and provided very useful numerical tests (benchmarks) for other, non-Markovian, MC algorithms developed recently.

K. Golec-Biernat; S. Jadach; W. Placzek; M. Skrzypek

2006-03-03

342

Trabecular bone dosimetry using a Monte Carlo code  

E-print Network

TRABECULAR BONE DOSIMETRY USING A MONTE CARLO CODE by ANNE ZUZARTE DE MENDONCA Submitted to the Office of Graduate Studies of Texas Ad'tM University in partial fulfillement of the requirements for the degree of MASTER OF SCIENCE August 1993... Major Subject: Nuclear Engineering TRABECULAR BONE DOSIMETRY USING A MONTE CARLO CODE A thesis by ANNE ZUZARTE DE ~NCA Submitted to Texas AdtM University in partial fulfillement of the requirements for the degree of MASTER OF SCIENCE Approved...

Zuzarte de Mendonca, Anne

2012-06-07

343

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

344

Monte Carlo methods and applications in nuclear physics  

SciTech Connect

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

345

Combining Old-Fashioned Computer Go with Monte Carlo Go  

Microsoft Academic Search

In this paper we discuss the idea of combining old-fashioned computer Go with Monte Carlo Go. We introduce an analyze-after approach to random simulations. We also briefly present the other features of our present Monte Carlo implementation with upper confidence trees. We then explain our approach to adding this implementation as a module in the GNU Go 3.6 engine, and

Florin Chelaru; Liviu Ciortuz

2008-01-01

346

PROGRESSIVE STRATEGIES FOR MONTE-CARLO TREE SEARCH  

Microsoft Academic Search

Monte-Carlo Tree Search (MCTS) is a new best-first search guided by the results of Monte-Carlo simulations. In this article, we introduce two progressive strategies for MCTS, called progressive bias and progressive unpruning. They enable the use of relatively time-expensive heuristic knowledge without speed reduction. Progressive bias directs the search according to heuristic knowledge. Progressive unpruning first reduces the branching factor,

GUILLAUME M. J-B. CHASLOT; H. JAAP VAN DEN HERIK; JOS W. H. M. UITERWIJK; BRUNO BOUZY

2008-01-01

347

Progressive Strategies for Monte-Carlo Tree Search  

Microsoft Academic Search

Monte-Carlo Tree Search (MCTS) is a new best-flrst search guided by the results of Monte-Carlo simulations. In this article we introduce two progressive strategies for MCTS, called progressive bias and progressive unpruning. They enable the use of rel- atively time-expensive heuristic knowledge without speed reduction. Progressive bias directs the search according to heuristic knowledge. Progressive unpruning flrst reduces the branching

G. M. J. B. Chaslot; M. H. M. Winands; B. Bouzy; JOS W. H. M. UITERWIJK

2007-01-01

348

MOS2: an efficient MOnte Carlo Simulator for MOS devices  

Microsoft Academic Search

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 Riccò; Franco Venturi

1988-01-01

349

Public Infrastructure for Monte Carlo Simulation : publicMCatBATAN  

NASA Astrophysics Data System (ADS)

The first cluster-based public computing for Monte Carlo simulation in Indonesia is introduced. The system has been developed to enable public to perform Monte Carlo simulation on a parallel computer through an integrated and user friendly dynamic web interface. The beta version, so called publicMC@BATAN, has been released and implemented for internal users at the National Nuclear Energy Agency (BATAN). In this paper the concept and architecture of publicMC@BATAN are presented.

Waskita, A. A.; Prasetyo, N. A.; Akbar, Z.; Handoko, L. T.

2010-06-01

350

Monte Carlo simulation and measurement of nanoscale n-MOSFETs  

Microsoft Academic Search

The output characteristics of state-of-the-art n-MOSFETs with effective channel lengths of 40 and 60 nm have been measured and compared with full-band Monte Carlo simulations. The device structures are obtained by process simulation based on comprehensive secondary ion mass spectroscopy and capacitance-voltage measurements. Good agreement between the measured output characteristics and the full-band Monte Carlo simulations is found without any

F. M. Bufler; Yoshinori Asahi; Hisao Yoshimura; Christoph Zechner; A. Schenk; Wolfgang Fichtner

2003-01-01

351

Efficient Block Sampling Strategies for Sequential Monte Carlo Methods  

Microsoft Academic Search

Sequential Monte Carlo (SMC) methods are a powerful set of simulation-based techniques for sampling sequentially from a sequence of complex probability distribu- tions. These methods rely on a combination of importance sampling and resampling techniques. In a Markov chain Monte Carlo (MCMC) framework, block sampling strate- gies often perform much better than algorithms based on one-at-a-time sampling strate- gies if

Arnaud Doucet; Mark Briers; Stéphane Sénécal

2006-01-01

352

Quantum Monte Carlo Methods for Strongly Correlated Electron Systems  

Microsoft Academic Search

We review some of the recent development in quantum Monte Carlo (QMC) methods for models of strongly correlated electron systems.\\u000a QMC is a promising general theoretical tool to study many-body systems, and has been widely applied in areas spanning condensed-matter,\\u000a high-energy, and nuclear physics. Recent progress has included two new methods, the ground-state and finite-temperature constrained\\u000a path Monte Carlo methods.

Shiwei Zhang

353

Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms  

Microsoft Academic Search

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

354

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

355

Monte Carlo for top background at the Tevatron  

E-print Network

We review the use of Monte Carlo simulation to model backgrounds to top signal at the Tevatron experiments, CDF and D0, as well as the relevant measurements done by the experiments. We'll concentrate on the modeling of W and Z boson production in association with jets, in particular heavy flavor jets, and also comment on the Tevatron experience using matched Monte Carlo.

Amnon Harel

2008-07-25

356

Predicting three-body abrasive wear using Monte Carlo methods  

Microsoft Academic Search

Predicting wear of materials under three-body abrasion is a challenging project, since three-body abrasion is more complicated than two-body abrasion. In this paper, a Monte Carlo model for simulating plastic deformation wear rate, i.e. low-cycle fatigue wear rate, is proposed. The Manson–Coffin formula and the Palmgrom–Miner linear accumulated-damage principle were used in the model as well as the Monte Carlo

Liang Fang; Weimin Liu; Daoshan Du; Xiaofeng Zhang; Qunji Xue

2004-01-01

357

Constant pressure hybrid Molecular Dynamics-Monte Carlo simulations  

Microsoft Academic Search

New hybrid Molecular Dynamics-Monte Carlo methods are proposed to increase the efficiency of constant-pressure simulations. Two variations of the isobaric Molecular Dynamics component of the algorithms are considered. In the first, we use the extended-ensemble method of Andersen [H. C. Andersen, J. Chem. Phys. 72, 2384 (1980)]. In the second, we arrive at a new constant-pressure Monte Carlo technique based

Roland Faller; Juan J. de Pablo

2002-01-01

358

Exponent Monte Carlo for Quick Statistical Circuit Simulation  

Microsoft Academic Search

\\u000a The main goals of this article are to report an implementation and a quantitative study of Exponent Monte Carlo, an enhanced\\u000a version of Monte Carlo for verifying high circuit yield in the presence of random process variations. Results on industry-grade\\u000a standard cell netlists and compact models in 45nm show that EMC predicts reasonable results at least 1,000 times faster than

Paul Zuber; Vladimir Matvejev; Philippe Roussel; Petr Dobrovolný; Miguel Miranda

2009-01-01

359

Instantons and Monte Carlo Methods in Quantum Mechanics  

E-print Network

In these lectures we describe the use of Monte Carlo simulations in understanding the role of tunneling events, instantons, in a quantum mechanical toy model. We study, in particular, a variety of methods that have been used in the QCD context, such as Monte Carlo simulations of the partition function, cooling and heating, the random and interacting instanton liquid model, and numerical simulations of non-Gaussian corrections to the semi-classical approximation.

Thomas Schaefer

2004-11-08

360

Quantum Monte Carlo study of small hydrocarbon atomization energies  

Microsoft Academic Search

A benchmark study of atomization energies is reported for 22 hydrocarbons using single determinant trial functions in the diffusion Monte Carlo (DMC) variant of the quantum Monte Carlo (QMC) method. The DMC atomization energies are compared to experiment, a complete basis set approach (CBS-Q), density functional theory with the B3LYP functional, and coupled-cluster singles, doubles and perturbative triples, CCSD(T), methods.

A. C. Kollias; D. Domin; G. Hill; M. Frenklach; W. A. Lester Jr.

2006-01-01

361

Monte-Carlo Exploration for Deterministic Planning Hootan Nakhost and Martin Muller  

E-print Network

-playing domains such as Go and General Game Playing. Monte-Carlo Random Walk (MRW) planning applies Monte- CarloMonte-Carlo Exploration for Deterministic Planning Hootan Nakhost and Martin M¨uller Department on Monte-Carlo simulation have recently led to breakthrough performance im- provements in difficult game

Müller, Martin

362

History and Territory Heuristics for Monte Carlo go Bruno Bouzy1  

E-print Network

History and Territory Heuristics for Monte Carlo go Bruno Bouzy1 1 Université Paris 5, UFR de.math-info.univ-paris5.fr/~bouzy/ Abstract This paper assesses two heuristics within the 19x19 Monte Carlo go framework]. Keywords: Computer Go, Monte Carlo, Territory, History Heuristic. 1. Introduction Monte Carlo (MC

Bouzy, Bruno

363

Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search  

E-print Network

nature of Go po- sitions is Monte-Carlo evaluation. Monte-Carlo evaluation consists in averaging #12;2 REfficient Selectivity and Backup Operators in Monte-Carlo Tree Search Rémi Coulom LIFL, SequeL, INRIA Futurs, Université Charles de Gaulle, Lille, France Abstract. Monte-Carlo evaluation consists

Paris-Sud XI, Université de

364

Quantum Monte Carlo calculations of the one-body density matrix and excitation energies of silicon  

E-print Network

for realistic systems are the variational quantum Monte Carlo1,2 VMC and diffusion quantum Monte Carlo2,3 DMCQuantum Monte Carlo calculations of the one-body density matrix and excitation energies of silicon, Madingley Road, Cambridge CB3 0HE, United Kingdom Received 8 October 1997 Quantum Monte Carlo QMC techniques

Kent, Paul

365

Monte Carlo study of the Baxter-Wu model Nir Schreiber and Dr. Joan Adler  

E-print Network

Monte Carlo study of the Baxter-Wu model Nir Schreiber and Dr. Joan Adler Monte Carlo study of the Baxter-Wu model ­ p.1/40 #12;Outline Theory of phase transitions, Monte Carlo simulations and finite size scaling Landau-Wang algorithm Results Summary Monte Carlo study of the Baxter-Wu model ­ p.2/40 #12;Phase

Adler, Joan

366

Monte Carlo EM for Generalized Linear Mixed Models using Randomized Spherical Radial  

E-print Network

Monte Carlo EM for Generalized Linear Mixed Models using Randomized Spherical Radial Integration by Monte Carlo methods. However, in practice, the Monte Carlo sample sizes required for convergence for such methods. One solution is to use Monte Carlo approximation, as proposed by Wei and Tanner (1990

Booth, James

367

A Monte Carlo method to compute the exchange coefficient in the double porosity model  

E-print Network

A Monte Carlo method to compute the exchange coefficient in the double porosity model Fabien: Monte Carlo methods, double porosity model, ran- dom walk on squares, fissured media AMS Classification: 76S05 (65C05 76M35) Published in Monte Carlo Methods Appl.. Proc. of Monte Carlo and probabilistic

Paris-Sud XI, Université de

368

Monte Carlo Simulation of Electrodeposition of Copper: A Multistep Free Energy Calculation  

E-print Network

Monte Carlo Simulation of Electrodeposition of Copper: A Multistep Free Energy Calculation S such as continuum Monte Carlo, kinetic Monte Carlo (KMC), and molecular dynamics have been used for simulating is very time-consuming. Thus a less time-consuming and novel multistep continuum Monte Carlo simulation

Subramanian, Venkat

369

Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments  

SciTech Connect

Most criticality safety calculations are performed using Monte Carlo techniques because of Monte Carlo's ability to handle complex three-dimensional geometries. For Monte Carlo calculations, the more histories sampled, the lower the standard deviation of the resulting estimates. The common intuition is, therefore, that the more histories, the better; as a result, analysts tend to run Monte Carlo analyses as long as possible (or at least to a minimum acceptable uncertainty). For Monte Carlo criticality safety analyses, however, the optimization situation is complicated by the fact that procedures usually require that an extra margin of safety be added because of the statistical uncertainty of the Monte Carlo calculations. This additional safety margin affects the impact of the choice of the calculational standard deviation, both on production and on safety. This paper shows that, under the assumptions of normally distributed benchmarking calculational errors and exact compliance with the upper subcritical limit (USL), the standard deviation that optimizes production is zero, but there is a non-zero value of the calculational standard deviation that minimizes the risk of inadvertently labeling a supercritical configuration as subcritical. Furthermore, this value is shown to be a simple function of the typical benchmarking step outcomes--the bias, the standard deviation of the bias, the upper subcritical limit, and the number of standard deviations added to calculated k-effectives before comparison to the USL.

Pevey, Ronald E.

2005-09-15

370

Monte Carlo simulation of large electron fields  

PubMed Central

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 6 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 buildup 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

2010-01-01

371

Markov Chain Monte Carlo Methods in Biostatistics Andrew Gelman  

E-print Network

Markov Chain Monte Carlo Methods in Biostatistics Andrew Gelman Department of Statistics Columbia May 21, 1996 1 Introduction Appropriate models in biostatistics are often quite complicated, re ecting in biostatistics. These readers can use this article as an introduction to the ways in which Markov chain Monte

Gelman, Andrew

372

Photon beam description in PEREGRINE for Monte Carlo dose calculations  

Microsoft Academic Search

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

Cox

1997-01-01

373

4 Monte Carlo Methods in Classical Statistical Physics  

E-print Network

4 Monte Carlo Methods in Classical Statistical Physics Wolfhard Janke Institut f¨ur Theoretische update algorithms (Metropolis, heat-bath, Glauber). Then methods for the statistical analysis of the thus Carlo Methods in Classical Statistical Physics, Lect. Notes Phys. 739, 79­140 (2008) DOI 10

Janke, Wolfhard

374

Remedy for the fermion sign problem in the diffusion Monte Carlo method for few fermions with antisymmetric diffusion process  

Microsoft Academic Search

We suggest an exact approach to help remedy the fermion sign problem in diffusion quantum Monte Carlo simulations. The approach is based on an explicit suppression of symmetric modes in the Schrödinger equation by means of a modified stochastic diffusion process (antisymmetric diffusion process). We introduce this algorithm and illustrate it on potential models in one dimension (1D) and show

Yuriy Mishchenko

2006-01-01

375

Effective Bayesian inference by data-driven Markov chain Monte Carlo for object recognition and image segmentation  

Microsoft Academic Search

This article presents a mathematical paradigm called Data Driven Markov Chain Monte Carlo (DDMCMC) for effective stochastic inference in the Bayesian framework. We apply the DDMCMC paradigm to two typical problems in image analysis: object recognition and image segmentation. In both problems, the solution spaces are not only high dimensional but heterogeneously-structured in the sense that they are composed of

Song-Chun Zhu; Zhuowen Tu; Rong Zhang

2000-01-01

376

Monte Carlo Simulation of the Law of the Maximum of a Levy Process Monte Carlo Simulation of the Law of the Maximum of a  

E-print Network

1/ 17 Monte Carlo Simulation of the Law of the Maximum of a L´evy Process Monte Carlo Simulation of Mathematical Sciences, University of Bath #12;2/ 17 Monte Carlo Simulation of the Law of the Maximum of a L´evy Process Motivation #12;2/ 17 Monte Carlo Simulation of the Law of the Maximum of a L´evy Process

377

Coupling Deterministic and Monte Carlo Transport Methods for the Simulation of Gamma-Ray Spectroscopy Scenarios  

SciTech Connect

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

378

Monte Carlo Methods and Appl., Vol. 11, No. 1, pp. 39 55 (2005) Grid-based Quasi-Monte Carlo Applications  

E-print Network

Monte Carlo Methods and Appl., Vol. 11, No. 1, pp. 39 ­ 55 (2005) c VSP 2005 Grid-based Quasi-Monte -- In this paper, we extend the techniques used in Grid-based Monte Carlo appli- cations to Grid-based quasi-Monte in quasirandom sequences prevents us from applying many of our Grid-based Monte Carlo techniques to Grid- based

Li, Yaohang

379

A novel Kinetic Monte Carlo algorithm for Non-Equilibrium Simulations  

NASA Astrophysics Data System (ADS)

We have developed an off-lattice kinetic Monte Carlo simulation scheme for reaction-diffusion problems in soft matter systems. The definition of transition probabilities in the Monte Carlo scheme are taken identical to the transition rates in a renormalized master equation of the diffusion process and match that of the Glauber dynamics of Ising model. Our scheme provides several advantages over the Brownian dynamics technique for non-equilibrium simulations. Since particle displacements are accepted/rejected in a Monte Carlo fashion as opposed to moving particles following a stochastic equation of motion, nonphysical movements (e.g., violation of a hard core assumption) are not possible (these moves have zero acceptance). Further, the absence of a stochastic ``noise'' term resolves the computational difficulties associated with generating statistically independent trajectories with definitive mean properties. Finally, since the timestep is independent of the magnitude of the interaction forces, much longer time-steps can be employed than Brownian dynamics. We discuss the applications of this scheme for dynamic self-assembly of photo-switchable nanoparticles and dynamical problems in polymeric systems.

Jha, Prateek; Kuzovkov, Vladimir; Grzybowski, Bartosz; Olvera de La Cruz, Monica

2012-02-01

380

Quantum Monte-Carlo method applied to Non-Markovian barrier transmission  

E-print Network

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be important. In this work, a new approach based on quantum Monte-Carlo addressing this problem is presented. The exact dynamics of a system coupled to an environment is replaced by a set of stochastic evolutions of the system density. The quantum Monte-Carlo method is applied to systems with quadratic potentials. In all range of temperature and coupling, the stochastic method matches the exact evolution showing that non-Markovian effects can be simulated accurately. A comparison with other theories like Nakajima-Zwanzig or Time-ConvolutionLess ones shows that only the latter can be competitive if the expansion in terms of coupling constant is made at least to fourth order. A systematic study of the inverted parabola case is made at different temperatures and coupling constants. The asymptotic passing probability is estimated in different approaches including the Markovian limit. Large differences with the exact result are seen in the latter case or when only second order in the coupling strength is considered as it is generally assumed in nuclear transport models. On opposite, if fourth order in the coupling or quantum Monte-Carlo method is used, a perfect agreement is obtained.

G. Hupin; D. Lacroix

2010-01-05

381

Characteristics of electron movement in variational Monte Carlo simulations  

SciTech Connect

Improving the efficiency of quantum Monte Carlo (QMC) to make possible the study of large molecules poses a great challenge. Evaluating the efficiency of Monte Carlo sampling, however, is at a rudimentary level and in need of new algorithms. Instead of the autocorrelation time as an efficiency measure for Monte Carlo simulations, we propose a direct method to characterize the movement of electrons in atoms or molecules during variational Monte Carlo computations. Further, the approach makes possible an efficient diagnostic tool to understand objectively many interesting issues in QMC. The usefulness of the method is demonstrated by comparisons among improved Metropolis algorithms and the original Metropolis algorithm. We also present an optimization method for choosing step sizes for Monte Carlo walkers. These step sizes are governed by the acceptance ratio of the electrons closest to the heaviest nucleus. Step sizes obtained for Ne and Ar are consistent with those obtained by the autocorrelation approach. Our study shows no evidence to support distinctions of core and valence electrons during simulations, and confirms that, in most cases, moving electrons individually is more efficient than moving all the electrons at once. We find that trapped'' or stale'' configurations are due to a large quantum force, and a solution to this problem is suggested.

Sun, Z.; Soto, M.M.; Lester, W.A. Jr. (Chemical Sciences Division Lawrence Berkeley Laboratory (United States) Department of Chemistry University of California, Berkeley, Berkeley, California 94720 (United States))

1994-01-15

382

A new method to assess Monte Carlo convergence  

SciTech Connect

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

383

Monte Carlo treatment planning for photon and electron beams  

NASA Astrophysics Data System (ADS)

During the last few decades, accuracy in photon and electron radiotherapy has increased substantially. This is partly due to enhanced linear accelerator technology, providing more flexibility in field definition (e.g. the usage of computer-controlled dynamic multileaf collimators), which led to intensity modulated radiotherapy (IMRT). Important improvements have also been made in the treatment planning process, more specifically in the dose calculations. Originally, dose calculations relied heavily on analytic, semi-analytic and empirical algorithms. The more accurate convolution/superposition codes use pre-calculated Monte Carlo dose "kernels" partly accounting for tissue density heterogeneities. It is generally recognized that the Monte Carlo method is able to increase accuracy even further. Since the second half of the 1990s, several Monte Carlo dose engines for radiotherapy treatment planning have been introduced. To enable the use of a Monte Carlo treatment planning (MCTP) dose engine in clinical circumstances, approximations have been introduced to limit the calculation time. In this paper, the literature on MCTP is reviewed, focussing on patient modeling, approximations in linear accelerator modeling and variance reduction techniques. An overview of published comparisons between MC dose engines and conventional dose calculations is provided for phantom studies and clinical examples, evaluating the added value of MCTP in the clinic. An overview of existing Monte Carlo dose engines and commercial MCTP systems is presented and some specific issues concerning the commissioning of a MCTP system are discussed.

Reynaert, N.; van der Marck, S. C.; Schaart, D. R.; Van der Zee, W.; Van Vliet-Vroegindeweij, C.; Tomsej, M.; Jansen, J.; Heijmen, B.; Coghe, M.; De Wagter, C.

2007-04-01

384

MOVE ORDERING VS HEAVY PLAYOUTS: WHERE SHOULD HEURISTICS BE APPLIED IN MONTE CARLO GO?  

E-print Network

MOVE ORDERING VS HEAVY PLAYOUTS: WHERE SHOULD HEURISTICS BE APPLIED IN MONTE CARLO GO? Peter Drake effective place to apply heuristics. KEYWORDS artificial intelligence, Go game, Monte Carlo, UCT, heuristics Carlo Go (Brügmann 1993, Coulom 2006, Gelly et al. 2006, Drake and Uurtamo 2007). Monte Carlo Go

Drake, Peter

385

Move Pruning Techniques for Monte-Carlo Go Bruno Bouzy1  

E-print Network

Move Pruning Techniques for Monte-Carlo Go Bruno Bouzy1 Universit´e Ren´e Descartes, Paris, bouzy in the Monte-Carlo go play- ing program Indigo. For each candidate move, PP launches random games starting Carlo approach was started on experiments [5] reproducing the original approach of Monte Carlo go [8

Bouzy, Bruno

386

Quantum Monte Carlo Simulations of Solid 4 P.A. Whitlock1  

E-print Network

Quantum Monte Carlo Simulations of Solid 4 He P.A. Whitlock1 and S.A. Vitiello2 1 Computer Carlo calculations at zero temperature; diffusion Monte Carlo, and finally, the finite temperature path integral Monte Carlo method. A brief introduction to the technique will be given followed by a discussion

Whitlock, Paula

387

Residual Monte Carlo high-order solver for Moment-Based Accelerated Thermal Radiative Transfer equations  

NASA Astrophysics Data System (ADS)

In this article we explore the possibility of replacing Standard Monte Carlo (SMC) transport sweeps within a Moment-Based Accelerated Thermal Radiative Transfer (TRT) algorithm with a Residual Monte Carlo (RMC) formulation. Previous Moment-Based Accelerated TRT implementations have encountered trouble when stochastic noise from SMC transport sweeps accumulates over several iterations and pollutes the low-order system. With RMC we hope to significantly lower the build-up of statistical error at a much lower cost. First, we display encouraging results for a zero-dimensional test problem. Then, we demonstrate that we can achieve a lower degree of error in two one-dimensional test problems by employing an RMC transport sweep with multiple orders of magnitude fewer particles per sweep. We find that by reformulating the high-order problem, we can compute more accurate solutions at a fraction of the cost.

Willert, Jeffrey; Park, H.

2014-11-01

388

Rao-Blackwellised Interacting Markov Chain Monte Carlo for Electromagnetic Scattering Inversion  

E-print Network

The following electromagnetism (EM) inverse problem is addressed. It consists in estimating local radioelectric properties of materials recovering an object from the global EM scattering measurement, at various incidences and wave frequencies. This large scale ill-posed inverse problem is explored by an intensive exploitation of an efficient 2D Maxwell solver, distributed on High Performance Computing (HPC) machines. Applied to a large training data set, a statistical analysis reduces the problem to a simpler probabilistic metamodel, on which Bayesian inference can be performed. Considering the radioelectric properties as a dynamic stochastic process, evolving in function of the frequency, it is shown how advanced Markov Chain Monte Carlo methods, called Sequential Monte Carlo (SMC) or interacting particles, can provide estimations of the EM properties of each material, and their associated uncertainties.

Giraud, François

2012-01-01

389

Rao-Blackwellised Interacting Markov Chain Monte Carlo for Electromagnetic Scattering Inversion  

NASA Astrophysics Data System (ADS)

The following electromagnetism (EM) inverse problem is addressed. It consists in estimating local radioelectric properties of materials recovering an object from the global EM scattering measurement, at various incidences and wave frequencies. This large scale ill-posed inverse problem is explored by an intensive exploitation of an efficient 2D Maxwell solver, distributed on High Performance Computing (HPC) machines. Applied to a large training data set, a statistical analysis reduces the problem to a simpler probabilistic metamodel, on which Bayesian inference can be performed. Considering the radioelectric properties as a dynamic stochastic process, evolving in function of the frequency, it is shown how advanced Markov Chain Monte Carlo methods, called Sequential Monte Carlo (SMC) or interacting particles, can provide estimations of the EM properties of each material, and their associated uncertainties.

Giraud, F.; Minvielle, P.; Sancandi, M.; Del Moral, P.

2012-09-01

390

Efficient Monte Carlo for High Excursions of Gaussian Random Fields  

E-print Network

Our focus is on the design and analysis of efficient Monte Carlo methods for computing tail probabilities for the suprema of Gaussian random fields, along with conditional expectations of functionals of the fields given the existence of excursions above high levels, $b$. Naive Monte Carlo takes an exponential, in $b$, computational cost to estimate these probabilities and conditional expectations for a prescribed relative accuracy. In contrast, our Monte Carlo procedures achieve, at worst, polynomial complexity in $b$, assuming only that the mean and covariance functions are Holder continuous. We also explain how to fine tune the construction of our procedures in the presence of additional regularity, such as homogeneity and smoothness, in order to further improve the efficiency.

Adler, Robert J; Liu, Jingchen

2010-01-01

391

Magnitude of bias in Monte Carlo eigenvalue calculations  

SciTech Connect

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

392

Quantum monte carlo calculations of light nuclei using chiral potentials.  

PubMed

We present the first Green's function Monte Carlo calculations of light nuclei with nuclear interactions derived from chiral effective field theory up to next-to-next-to-leading order. Up to this order, the interactions can be constructed in a local form and are therefore amenable to quantum Monte Carlo calculations. We demonstrate a systematic improvement with each order for the binding energies of A=3 and A=4 systems. We also carry out the first few-body tests to study perturbative expansions of chiral potentials at different orders, finding that higher-order corrections are more perturbative for softer interactions. Our results confirm the necessity of a three-body force for correct reproduction of experimental binding energies and radii, and pave the way for studying few- and many-nucleon systems using quantum Monte Carlo methods with chiral interactions. PMID:25415900

Lynn, J E; Carlson, J; Epelbaum, E; Gandolfi, S; Gezerlis, A; Schwenk, A

2014-11-01

393

A Multivariate Time Series Method for Monte Carlo Reactor Analysis  

SciTech Connect

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

394

Efficiency of Monte Carlo Sampling in Chaotic Systems  

E-print Network

In this paper we investigate how the complexity of chaotic phase spaces affect the efficiency of importance sampling Monte Carlo simulations. We focus on a flat-histogram simulation of the distribution of finite-time Lyapunov exponent in a simple chaotic system and obtain analytically that the computational effort of the simulation: (i) scales polynomially with the finite-time, a tremendous improvement over the exponential scaling obtained in usual uniform sampling simulations; and (ii) the polynomial scaling is sub-optimal, a phenomenon known as critical slowing down. We show that critical slowing down appears because of the limited possibilities to issue a local proposal on the Monte Carlo procedure in chaotic systems. These results remain valid in other methods and show how generic properties of chaotic systems limit the efficiency of Monte Carlo simulations.

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

2014-07-20

395

Quantum Monte Carlo Calculations of Light Nuclei Using Chiral Potentials  

NASA Astrophysics Data System (ADS)

We present the first Green's function Monte Carlo calculations of light nuclei with nuclear interactions derived from chiral effective field theory up to next-to-next-to-leading order. Up to this order, the interactions can be constructed in a local form and are therefore amenable to quantum Monte Carlo calculations. We demonstrate a systematic improvement with each order for the binding energies of A =3 and A =4 systems. We also carry out the first few-body tests to study perturbative expansions of chiral potentials at different orders, finding that higher-order corrections are more perturbative for softer interactions. Our results confirm the necessity of a three-body force for correct reproduction of experimental binding energies and radii, and pave the way for studying few- and many-nucleon systems using quantum Monte Carlo methods with chiral interactions.

Lynn, J. E.; Carlson, J.; Epelbaum, E.; Gandolfi, S.; Gezerlis, A.; Schwenk, A.

2014-11-01

396

Efficient Monte Carlo characterization of quantum operations for qudits  

NASA Astrophysics Data System (ADS)

For qubits, Monte Carlo estimation of the average fidelity of Clifford unitaries is efficient: it requires a number of experiments that is independent of the number n of qubits and classical computational resources that scale only polynomially in n. Here, we identify the requirements for efficient Monte Carlo estimation and the corresponding properties of the measurement operator basis when replacing two-level qubits by p-level qudits. Our analysis illuminates the intimate connection between mutually unbiased measurements and the existence of unitaries that can be characterized efficiently. It allows us to propose a "hierarchy" of generalizations of the standard Pauli basis from qubits to qudits according to the associated scaling of resources required in Monte Carlo estimation of the average fidelity.

Gualdi, Giulia; Licht, David; Reich, Daniel M.; Koch, Christiane P.

2014-09-01

397

Properties of Reactive Oxygen Species by Quantum Monte Carlo  

E-print Network

The electronic properties of the oxygen molecule, in its singlet and triplet states, and of many small oxygen-containing radicals and anions have important roles in different fields of Chemistry, Biology and Atmospheric Science. Nevertheless, the electronic structure of such species is a challenge for ab-initio computational approaches because of the difficulties to correctly describe the statical and dynamical correlation effects in presence of one or more unpaired electrons. Only the highest-level quantum chemical approaches can yield reliable characterizations of their molecular properties, such as binding energies, equilibrium structures, molecular vibrations, charge distribution and polarizabilities. In this work we use the variational Monte Carlo (VMC) and the lattice regularized Monte Carlo (LRDMC) methods to investigate the equilibrium geometries and molecular properties of oxygen and oxygen reactive species. Quantum Monte Carlo methods are used in combination with the Jastrow Antisymmetrized Geminal ...

Zen, Andrea; Guidoni, Leonardo

2014-01-01

398

A Monte Carlo burnup code linking MCNP and REBUS.  

SciTech Connect

The REBUS-3 burnup code, used in the ANL RERTR Program, is a very general code that uses diffusion theory (DIF3D) to obtain the fluxes required for reactor burnup analyses. Diffusion theory works well for most reactors. However, to include the effects of exact geometry and strong absorbers that are difficult to model using diffusion theory, a Monte Carlo method is required. MCNP, a general-purpose, generalized-geometry, time-dependent, Monte Carlo transport code, is the most widely used Monte Carlo code. This paper presents a linking of the MCNP code and the REBUS burnup code to perform these difficult burnup analyses. The linked code will permit the use of the full capabilities of REBUS which include non-equilibrium and equilibrium burnup analyses. Results of burnup analyses using this new linked code are also presented.

Hanan, N. A.

1998-10-19

399

Quantum Monte Carlo calculations of light nuclei using chiral potentials  

E-print Network

We present the first Green's function Monte Carlo calculations of light nuclei with nuclear interactions derived from chiral effective field theory up to next-to-next-to-leading order. Up to this order, the interactions can be constructed in local form and are therefore amenable to quantum Monte Carlo calculations. We demonstrate a systematic improvement with each order for the binding energies of $A=3$ and $A=4$ systems. We also carry out the first few-body tests to study perturbative expansions of chiral potentials at different orders, finding that higher-order corrections are more perturbative for softer interactions. Our results confirm the necessity of a three-body force for correct reproduction of experimental binding energies and radii, and pave the way for studying few- and many-nucleon systems using quantum Monte Carlo methods with chiral interactions.

J. E. Lynn; J. Carlson; E. Epelbaum; S. Gandolfi; A. Gezerlis; A. Schwenk

2014-06-11

400

Quantum Monte Carlo calculations of light nuclei using chiral potentials  

E-print Network

We present the first Green's function Monte Carlo calculations of light nuclei with nuclear interactions derived from chiral effective field theory up to next-to-next-to-leading order. Up to this order, the interactions can be constructed in local form and are therefore amenable to quantum Monte Carlo calculations. We demonstrate a systematic improvement with each order for the binding energies of $A=3$ and $A=4$ systems. We also carry out the first few-body tests to study perturbative expansions of chiral potentials at different orders, finding that higher-order corrections are more perturbative for softer interactions. Our results confirm the necessity of a three-body force for correct reproduction of experimental binding energies and radii, and pave the way for studying few- and many-nucleon systems using quantum Monte Carlo methods with chiral interactions.

Lynn, J E; Epelbaum, E; Gandolfi, S; Gezerlis, A; Schwenk, A

2014-01-01

401

Efficient Monte Carlo characterization of quantum operations for qudits  

E-print Network

For qubits, Monte Carlo estimation of the average fidelity of Clifford unitaries is efficient -- it requires a number of experiments that is independent of the number $n$ of qubits and classical computational resources that scale only polynomially in $n$. Here, we identify the requirements for efficient Monte Carlo estimation and the corresponding properties of the measurement operator basis when replacing two-level qubits by $p$-level qudits. Our analysis illuminates the intimate connection between mutually unbiased measurements and the existence of unitaries that can be characterized efficiently. It allows us to propose a 'hierarchy' of generalizations of the standard Pauli basis from qubits to qudits according to the associated scaling of resources required in Monte Carlo estimation of the average fidelity.

Giulia Gualdi; David Licht; Daniel M. Reich; Christiane P. Koch

2014-04-06

402

Tool for Rapid Analysis of Monte Carlo Simulations  

NASA Technical Reports Server (NTRS)

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very di cult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The Tool for Rapid Analysis of Monte Carlo simulations (TRAM) has been used in recent design and analysis work for the Orion vehicle, greatly decreasing the time it takes to evaluate performance requirements. A previous version of this tool was developed to automatically identify driving design variables in Monte Carlo data sets. This paper describes a new, parallel version, of TRAM implemented on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.

2011-01-01

403

The Monte Carlo method in quantum field theory  

E-print Network

This series of six lectures is an introduction to using the Monte Carlo method to carry out nonperturbative studies in quantum field theories. Path integrals in quantum field theory are reviewed, and their evaluation by the Monte Carlo method with Markov-chain based importance sampling is presented. Properties of Markov chains are discussed in detail and several proofs are presented, culminating in the fundamental limit theorem for irreducible Markov chains. The example of a real scalar field theory is used to illustrate the Metropolis-Hastings method and to demonstrate the effectiveness of an action-preserving (microcanonical) local updating algorithm in reducing autocorrelations. The goal of these lectures is to provide the beginner with the basic skills needed to start carrying out Monte Carlo studies in quantum field theories, as well as to present the underlying theoretical foundations of the method.

Colin Morningstar

2007-02-20

404

Applicability of Quasi-Monte Carlo for lattice systems  

E-print Network

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over random observations generated from ordinary Monte Carlo simulations scales like $N^{-1/2}$, where $N$ is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this scaling for certain problems to $N^{-1}$, or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling of all investigated observables in both cases.

Andreas Ammon; Tobias Hartung; Karl Jansen; Hernan Leovey; Andreas Griewank; Micheal Müller-Preussker

2013-11-19

405

Application of biasing techniques to the contributon Monte Carlo method  

SciTech Connect

Recently, a new Monte Carlo Method called the Contribution Monte Carlo Method was developed. The method is based on the theory of contributions, and uses a new receipe for estimating target responses by a volume integral over the contribution current. The analog features of the new method were discussed in previous publications. The application of some biasing methods to the new contribution scheme is examined here. A theoretical model is developed that enables an analytic prediction of the benefit to be expected when these biasing schemes are applied to both the contribution method and regular Monte Carlo. This model is verified by a variety of numerical experiments and is shown to yield satisfying results, especially for deep-penetration problems. Other considerations regarding the efficient use of the new method are also discussed, and remarks are made as to the application of other biasing methods. 14 figures, 1 tables.

Dubi, A.; Gerstl, S.A.W.

1980-01-01

406

Optimum and efficient sampling for variational quantum Monte Carlo  

E-print Network

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial wavefunctions, that is to Variational quantum Monte Carlo. Almost all previous implementations employ samples distributed as the physical probability density of the trial wavefunction, and assume the Central Limit Theorem to be valid. In this paper we provide an analysis of random error in estimation and optimisation that leads naturally to new sampling strategies with improved computational and statistical properties. A rigorous lower limit to the random error is derived, and an efficient sampling strategy presented that significantly increases computational efficiency. In addition the infinite variance heavy tailed random errors of optimum parameters in conventional methods are replaced with a Normal random error, strengthening the theoretical basis of optimisation. The method is ...

Trail, John Robert; 10.1063/1.3488651

2010-01-01

407

A Supersymmetric Approach to Excited States via Quantum Monte Carlo  

E-print Network

We present here a supersymmetric (SUSY) approach for determining excitation energies within the context of a quantum Monte Carlo scheme. By using the fact that SUSY quantum mechanics gives rises to a series of isospectral Hamiltonians, we show that Monte Carlo ground-state calculations in the SUSY partners can be used to reconstruct accurately both the spectrum and states of an arbitrary Schr\\"odinger equation. Since the ground-state of each partner potential is node-less, we avoid any ``node''-problem typically associated with the Monte Carlo technique. While we provide an example of using this approach to determine the tunneling states in a double-well potential, the method is applicable to any 1D potential problem. We conclude by discussing the extension to higher dimensions.

Eric R. Bittner; Jeremy B. Maddox; Donald J. Kouri

2009-03-27

408

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 ± 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

409

Monte Carlo calculation of monitor unit for electron arc therapy  

SciTech Connect

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

410

Exact Monte Carlo Method for Continuum Fermion Systems  

SciTech Connect

We offer a new proposal for the Monte Carlo treatment of many-fermion systems in continuous space. It is based upon diffusion Monte Carlo with significant modifications: correlated pairs of random walkers that carry opposite signs, different functions ''guide'' walkers of different signs, the Gaussians used for members of a pair are correlated, and walkers can cancel so as to conserve their expected future contributions. We report results for free-fermion systems and a fermion fluid with 14 {sup 3}He atoms, where it proves stable and correct. Its computational complexity grows with particle number, but slowly enough to make interesting physics within the reach of contemporary computers.

Kalos, M. H.; Pederiva, Francesco

2000-10-23

411

Monte Carlo Simulations of Phosphate Polyhedron Connectivity in Glasses  

SciTech Connect

Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

ALAM,TODD M.

1999-12-21

412

Monte Carlo simulations of phosphate polyhedron connectivity in glasses  

SciTech Connect

Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

ALAM,TODD M.

2000-01-01

413

Lattice-gas Monte Carlo study of adsorption in pores  

NASA Astrophysics Data System (ADS)

A lattice-gas model of adsorption inside cylindrical pores is evaluated with Monte Carlo simulations. The model incorporates two kinds of sites: (a line of) “axial” sites and surrounding “cylindrical shell” sites, in the ratio 1:7. The adsorption isotherms are calculated in either the grand canonical or canonical ensembles. At low temperature, there occur quasitransitions that would be genuine thermodynamic transitions in mean-field theory. Comparisons between the Monte Carlo and mean-field theory results for the heat capacity and adsorption isotherms are provided.

Trasca, Raluca A.; Calbi, M. Mercedes; Cole, Milton W.; Riccardo, Jose L.

2004-01-01

414

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

415

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

416

Precise Monte Carlo Simulation of Single-Photon Detectors  

E-print Network

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.

Mario Stip?evi?; Daniel J. Gauthier

2014-11-13

417

Energies of the first row atoms from quantum Monte Carlo  

E-print Network

All-electron variational and diffusion quantum Monte Carlo calculations of the ground state energies of the first row atoms (Li to Ne) are reported. We use trial wavefunctions of four types: single determinant Slater-Jastrow wavefunctions; multi-determinant Slater-Jastrow wavefunctions; single determinant Slater-Jastrow wavefunctions with backflow transformations; multi-determinant Slater-Jastrow wavefunctions with backflow transformations. At the diffusion quantum Monte Carlo level and using our best trial wavefunctions we recover 99% or more of the correlation energy for Li, Be, B, C, N, and Ne, 97% for O, and 98% for F.

Brown, Matthew; Rios, Pablo Lopez; Needs, Richard; 10.1063/1.2743972

2010-01-01

418

General Construction of Irreversible Kernel in Markov Chain Monte Carlo  

E-print Network

The Markov chain Monte Carlo update method to construct an irreversible kernel has been reviewed and extended to general state spaces. The several convergence conditions of the Markov chain were discussed. The alternative methods to the Gibbs sampler and the Metropolis-Hastings algorithm were proposed and assessed in some models. The distribution convergence and the sampling efficiency are significantly improved in the Potts model, the bivariate Gaussian model, and so on. This approach using the irreversible kernel can be applied to any Markov chain Monte Carlo sampling and it is expected to improve the efficiency in general.

Hidemaro Suwa; Synge Todo

2012-07-02

419

Accurate energy differences with Quantum Monte Carlo  

Microsoft Academic Search

Computation of accurate energy differences is of primary importance in the study of transformations as those occurring in solid to solid phase transitions or chemical reactions. In stochastic quantum simulations this can be done efficiently, employing correlated sampling techniques whereby fluctuations cancel with each other leading to results with a much smaller statistical error. Although correlated sampling is very effective

Simone Chiesa; David Ceperley; Jeongnim Kim; Richard Martin

2006-01-01

420

Monte Carlo Method for a Quantum Measurement Process by a Single-Electron Transistor  

E-print Network

We derive the quantum trajectory or stochastic (conditional) master equation for a single superconducting Cooper-pair box (SCB) charge qubit measured by a single-electron transistor (SET) detector. This stochastic master equation describes the random evolution of the measured SCB qubit density matrix which both conditions and is conditioned on a particular realization of the measured electron tunneling events through the SET junctions. Hence it can be regarded as a Monte Carlo method that allows us to simulate the continuous quantum measurement process. We show that the master equation for the "partially" reduced density matrix [Y. Makhlin et.al., Phys. Rev. Lett. 85, 4578 (2000)] can be obtained when a "partial" average is taken on the stochastic master equation over the fine grained measurement records of the tunneling events in the SET. Finally, we present some Monte Carlo simulation results for the SCB/SET measurement process. We also analyze the probability distribution P(m,t) of finding m electrons that have tunneled into the drain of the SET in time t to demonstrate the connection between the quantum trajectory approach and the "partially" reduced density matrix approach.

Hsi-Sheng Goan

2004-06-15

421

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

SciTech Connect

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

422

On the Gap-Tooth direct simulation Monte Carlo method  

E-print Network

This thesis develops and evaluates Gap-tooth DSMC (GT-DSMC), a direct Monte Carlo simulation procedure for dilute gases combined with the Gap-tooth method of Gear, Li, and Kevrekidis. The latter was proposed as a means of ...

Armour, Jessica D

2012-01-01

423

Diffusion Monte Carlo studies of isotope-substituted water trimers  

NASA Astrophysics Data System (ADS)

We report the ground-state properties of several partially deuterated water trimers calculated with the rigid-body diffusion Monte Carlo method. Rotational constants are compared with recent experiments and good agreement is found. Tunneling splittings for the hydrogen flip in (HDO) 3 are predicted. New results are predicted for the experimentally unexamined mixed trimers.

Sorenson, Jon M.; Gregory, Jonathon K.; Clary, David C.

1996-12-01

424

Monte Carlo event generators for hadron-hadron collisions  

SciTech Connect

A brief review of Monte Carlo event generators for simulating hadron-hadron collisions is presented. Particular emphasis is placed on comparisons of the approaches used to describe physics elements and identifying their relative merits and weaknesses. This review summarizes a more detailed report.

Knowles, I.G. [Argonne National Lab., IL (United States). High Energy Physics Div.; Protopopescu, S.D. [Brookhaven National Lab., Upton, NY (United States)

1993-06-01

425

Radiative Return at NLO: the PHOKHARA Monte Carlo generator  

E-print Network

Electron--positron annihilation into hadrons plus an energetic photon from initial state radiation allows the hadronic cross-section to be measured over a wide range of energies at high luminosity meson factories. A Monte Carlo generator called PHOKHARA has been constructed, which simulates this process at the next-to-leading order accuracy.

German Rodrigo; Henryk Czyz; Johann H. Kuhn

2002-05-10

426

Exact retrospective Monte Carlo computation of arithmetic average Asian options  

Microsoft Academic Search

Taking advantage of the recent litterature on exact simulation algorithms (Beskos, Papaspiliopoulos and Roberts) and unbiased estimation of the expectation of certain fonctional integrals (Wagner, Beskos et al. and Fearnhead et al.), we apply an exact simulation based technique for pricing continuous arithmetic average Asian options in the Black and Scholes framework. Unlike existing Monte Carlo methods, we are no

Benjamin Jourdain; Mohamed Sbai

2007-01-01

427

Monte-Carlo Tree Search in Production Management Problems  

Microsoft Academic Search

Classical search algorithms rely on the existence of a suffic iently powerful evalua- tion function for non-terminal states. In many task domains, the development of such an evaluation function requires substantial effort and domain knowledge, or is not even possible. As an alternative in recent years, Monte-Carlo evaluation has been succesfully applied in such task domains. In this paper, we

Guillaume Chaslot; Steven de Jong; Jahn-Takeshi Saito; Jos Uiterwijk

428

Pointwise and functional approximations in Monte Carlo maximum likelihood estimation  

Microsoft Academic Search

We consider the use of Monte Carlo methods to obtain maximum likelihood estimates for random effects models and distinguish between the pointwise and functional approaches. We explore the relationship between the two approaches and compare them with the EM algorithm. The functional approach is more ambitious but the approximation is local in nature which we demonstrate graphically using two simple

Anthony Y. C. Kuk; Yuk W. Cheng

1999-01-01

429

Monte Carlo Tree Search Techniques in the Game of Kriegspiel  

Microsoft Academic Search

Monte Carlo tree search has brought significant improvements to the level of computer players in games such as Go, but so far it has not been used very extensively in games of strongly imperfect in- formation with a dynamic board and an emphasis on risk management and decision making under un- certainty. In this paper we explore its application to

Paolo Ciancarini; Gian Piero Favini

2009-01-01

430

Improved geometry representations for Monte Carlo radiation transport.  

SciTech Connect

ITS (Integrated Tiger Series) permits a state-of-the-art Monte Carlo solution of linear time-integrated coupled electron/photon radiation transport problems with or without the presence of macroscopic electric and magnetic fields of arbitrary spatial dependence. ITS allows designers to predict product performance in radiation environments.

Martin, Matthew Ryan (Cornell University)

2004-08-01

431

Pluto: A Monte Carlo Simulation Tool for Hadronic Physics  

E-print Network

Pluto is a Monte-Carlo event generator designed for hadronic interactions from Pion production threshold to intermediate energies of a few GeV per nucleon, as well as for studies of heavy ion reactions. This report gives an overview of the design of the package, the included models and the user interface.

I. Froehlich; L. Cazon Boado; T. Galatyuk; V. Hejny; R. Holzmann; M. Kagarlis; W. Kuehn; J. G. Messchendorp; V. Metag; M. -A. Pleier; W. Przygoda; B. Ramstein; J. Ritman; P. Salabura; J. Stroth; M. Sudol

2007-08-17

432

On Monte Carlo methods for estimating ratios of normalizing constants  

Microsoft Academic Search

Recently, estimating ratios of normalizing constants has played an important role in Bayesian computations. Applications of estimating ratios of normalizing constants arise in many aspects of Bayesian statistical inference. In this article, we present an overview and discuss the current Monte Carlo methods for estimating ratios of normalizing constants. Then we propose a new ratio importance sampling method and establish

Ming-Hui Chen; Qi-Man Shao

1997-01-01

433

Monte Carlo sampling from the quantum state space. II  

E-print Network

High-quality random samples of quantum states are needed for a variety of tasks in quantum information and quantum computation. Searching the high-dimensional quantum state space for a global maximum of an objective function with many local maxima or evaluating an integral over a region in the quantum state space are but two exemplary applications of many. These tasks can only be performed reliably and efficiently with Monte Carlo methods, which involve good samplings of the parameter space in accordance with the relevant target distribution. We show how the Markov-chain Monte Carlo method known as Hamiltonian Monte Carlo, or Hybrid Monte Carlo, can be adapted to this context. It is applicable when an efficient parameterization of the state space is available. The resulting random walk is entirely inside the physical parameter space, and the Hamiltonian dynamics enable us to take big steps, thereby avoiding strong correlations between successive sample points while enjoying a high acceptance rate. We use examples of single and double qubit measurements for illustration.

Yi-Lin Seah; Jiangwei Shang; Hui Khoon Ng; David John Nott; Berthold-Georg Englert

2014-07-29

434

Monte Carlo algorithms for Hardy-Weinberg Proportions  

E-print Network

Monte Carlo algorithms for Hardy-Weinberg Proportions #3; By MARK HUBER Department of Mathematics The Hardy-Weinberg law is of basic importance in studying biological systems, and it is important to be able to determine if a population is in Hardy-Weinberg equilibrium. For #12;nite populations, this means testing

West, Mike

435

Monte Carlo Algorithms for Hardy-Weinberg Proportions  

E-print Network

Monte Carlo Algorithms for Hardy-Weinberg Proportions Mark Huber,1 Yuguo Chen,2 Ian Dinwoodie,2 Department of Mathematics, Duke University, Durham, NC 27708-0320, USA April 25, 2005 Summary The Hardy-Weinberg its importance, many tests have been devised to determine if a finite population follows Hardy-Weinberg

West, Mike

436

Nodal Pulay terms for accurate diffusion quantum Monte Carlo forces  

Microsoft Academic Search

Exact expressions are derived for forces within the mixed and pure fixed-node diffusion quantum Monte Carlo (DMC) methods. These expressions include the ``nodal terms'' which arise from the discontinuity in the gradient of the DMC wave function at the nodal surface. We devise a practical scheme for estimating the nodal terms, and demonstrate that their inclusion leads to very accurate

A. Badinski; P. D. Haynes; R. J. Needs

2008-01-01

437

Quantum Monte Carlo studies of quantum dots in magnetic fields  

Microsoft Academic Search

We have studied the ground and excited states of confined two-dimensional (2D) electrons in various magnetic field strengths by the variational and diffusion Monte Carlo methods. These 2D quantum dots are of great theoretical interest, because it is possible to go from a weakly to a strongly correlated system by tuning the relative strength of the external potential to the

Wolfgang Geist; Lang Zeng; Mei-Yin Chou; Cyrus Umrigar; Francesco Pederiva

2003-01-01

438

Quantum Monte Carlo study of quantum dots in magnetic fields  

Microsoft Academic Search

We have studied the ground state energies and quantum numbers of confined two-dimensional (2D) electrons in weak and intermediate magnetic field strengths using quantum Monte Carlo methods. These 2D quantum dots are of theoretical interest, because it is possible to go from a weakly to a strongly correlated system by tuning the relative strength of the external potential to the

Wolfgang Geist; Lang Zeng; Mei-Yin Chou

2004-01-01

439

Dynamic correlations with time-dependent quantum Monte Carlo  

Microsoft Academic Search

In this paper, we solve quantum many-body problem by propagating ensembles of trajectories and guiding waves in physical space. We introduce the “effective potential” correction within the recently proposed time-dependent quantum Monte Carlo methodology to incorporate the nonlocal quantum correlation effects between the electrons. The associated correlation length is calculated by adaptive kernel density estimation over the walker distribution. The

Ivan P. Christov

2008-01-01

440

Sampling the exact electron distribution by diffusion quantum Monte Carlo  

Microsoft Academic Search

By the accummulation of branching factors in diffusion quantum Monte Carlo (DQMC) and their use as statistical weights, instead of the standard deletion and replication of configurations, we can estimate the averages of (nondifferential) operators taken over the exact electron distribution. This requires only a trivial modification of existing DQMC codes. We illustrate our algorithm by computing ground-state properties for

Allan L. L. East; Stuart M. Rothstein; Jan Vrbika

1988-01-01

441

Dynamic correlations with time-dependent quantum Monte Carlo  

Microsoft Academic Search

In this paper, we solve quantum many-body problem by propagating ensembles of trajectories and guiding waves in physical space. We introduce the ``effective potential'' correction within the recently proposed time-dependent quantum Monte Carlo methodology to incorporate the nonlocal quantum correlation effects between the electrons. The associated correlation length is calculated by adaptive kernel density estimation over the walker distribution. The

Ivan P. Christov; Ivan P

2008-01-01

442

Disordered quantum dots: A diffusion quantum Monte Carlo study  

Microsoft Academic Search

We report diffusion quantum Monte Carlo (DQMC) calculations of disordered quantum dots in the presence of an external magnetic field. The addition spectra, spin configuration, Hund's rule, and many-body densities are investigated up to 13 electrons. The data from DQMC is in excellent agreement with exact diagonalization for disorder-free quantum dots, and in marked difference with those obtained from unrestricted

A. D. Güçlü; Jian-Sheng Wang; Hong Guo

2003-01-01

443

Time step bias improvement in diffusion Monte Carlo simulations  

Microsoft Academic Search

A Makri-Miller approximation to the exact propagator and the improved split-operator propagator proposed by Drozdov are implemented within the diffusion Monte Carlo method for the simulation of boson systems, and confronted with the Trotter formula and with the importance sampling technique. As a preliminary approach, we compute analytically the time step bias of the mean energy for the different propagators

Massimo Mella; Gabriele Morosi; Dario Bressanini

2000-01-01

444

Searching for Convergence in Phylogenetic Markov Chain Monte Carlo  

Microsoft Academic Search

Markov chain Monte Carlo (MCMC) is a methodology that is gaining widespread use in the phylogenetics community and is central to phylogenetic software packages such as MrBayes. An important issue for users of MCMC methods is how to select appropriate values for adjustable parameters such as the length of the Markov chain or chains, the sampling density, the proposal mechanism,

ROBERT G. BEIKO; JONATHAN M. KEITH; TIMOTHY J. HARLOW; Mark Ragan

2006-01-01

445

A new method to assess Monte Carlo convergence  

SciTech Connect

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

446

Multicanonical multigrid Monte Carlo method and effective autocorellation time  

E-print Network

We report tests of the recently proposed multicanonical multigrid Monte Carlo method for the two-dimensional $\\Phi^4$ field theory. Defining an effective autocorrelation time we obtain real time improvement factors of about one order of magnitude compared with standard multicanonical simulations.

W. Janke; T. Sauer

1993-12-09

447

Monte Carlo Vadose Zone Model for Soil Remedial Criteria  

Microsoft Academic Search

Many vadose zone models are available for environmental remediation, but few offer the procedures for verifying model predictions with field data and for dealing with uncertainties associated with model input parameters. This article presents a modified model combining a one-dimensional vadose-zone transport model and a simple groundwater mixing model with a function of Monte Carlo simulation (MCS). The modified model

Yue Rong; Rueen Fang Wang

2000-01-01

448

Atic Backscatter Study Using Monte Carlo Methods in Fluka & Root  

Microsoft Academic Search

A Monte Carlo analysis, based upon FLUKA, of neutron backscatter albedoes is presented using the ATIC balloon experiment as a study case. Preparation of the FLUKA input geometry has been accomplished by means of a new semi-automatic procedure for converting GEANT3 simulations. Resultant particle fluences (neutrons, photons, and charged particles) produced by incident Carbon nuclei striking ATIC with energies up

T. Wilson; L. Pinsky; A. Empl; K. Lee; V. Andersen; J. Isbert; J. Wefel; F. Carminati; A. Fasso; A. Ferrari; P. Sala; E. Futo; J. Ranft

2002-01-01

449

Implementation of Monte Carlo Simulations for the Gamma Knife System  

Microsoft Academic Search

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

450

Monte Carlo Simulation for Gamma Knife Radiosurgery using the Grid  

Microsoft Academic Search

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

451

Monte Carlo simulation to study the kinetics of CO methanation  

NASA Astrophysics Data System (ADS)

A Monte Carlo model, based on the methanation of carbon monoxide and hydrogen on a catalytic surface represented by a square lattice, is presented. It is found that the accumulation of adsorbed species on the surface can bring about the 'poisoning' phenomenon seen in catalysts, and that surface diffusion and suitable gas composition can eliminate the phenomenon.

Guo, Ziang Yun; Zhong, Bing; Peng, Shao Yi

1995-02-01

452

Forced Couette flow simulations using direct simulation Monte Carlo method  

Microsoft Academic Search

Three-dimensional unsteady flows between two infinite walls are simulated by using the direct simulation Monte Carlo (DSMC) method. An artificial forcing that mimics the centrifugal force in the Taylor problem has been applied to the flow. The sampled behaviors of the resulting flow, including the long time average and the disturbance components, are studied. The computations have been preformed using

William W. Liou; Yichuan Fang

2004-01-01

453

Russian roulette efficiency in Monte Carlo resonant absorption calculations  

Microsoft Academic Search

The resonant absorption calculation in media containing heavy resonant nuclei is one of the most difficult problems treated in reactor physics. Deterministic techniques need many approximations to solve this kind of problem. On the other hand, the Monte Carlo method is a reliable mathematical tool for evaluating the neutron resonance escape probability. But it suffers from large statistical deviations of

J Ghassoun; A Jehouani

2000-01-01

454

The Use of Monte Carlo Techniques to Teach Probability.  

ERIC Educational Resources Information Center

Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…

Newell, G. J.; MacFarlane, J. D.

1985-01-01

455

An Analysis Tool for Flight Dynamics Monte Carlo Simulations  

E-print Network

of Individual Variables : : : : : : : : : 80 XI Aerodynamic Flutter Variables for the Analysis of Failure Regions : : 83 XII Aerodynamic Flutter Ranking of Variable Combinations : : : : : : : 85 XIII Ascent Abort Individual Variables... : : : : : : : : : : : : : : : : : : : 95 XIV Ascent Abort Monte Carlo Results : : : : : : : : : : : : : : : : : : : 99 xi LIST OF FIGURES FIGURE Page 1 Spacecraft Design and Analysis Cycle : : : : : : : : : : : : : : : : : 2 2 Analysis Tool for Flight Dynamics Simulations...

Restrepo, Carolina 1982-

2011-05-20

456

Monte Carlo Studies of Sampling Strategies for Estimating Tributary Loads  

Microsoft Academic Search

Monte Carlo techniques were used to evaluate the accuracy and precision of tributary load estimates, as these are affected by sampling frequency and pattern, calculation method, watershed size, and parameter behavior during storm runoff events. Simulated years consisting of 1460 observations were chosen at random with replacement from data sets of more than 4000 samples. Patterned subsampling of these simulated

R. Peter Richards; Jim Holloway

1987-01-01

457

Monte Carlo Optimization for Conflict Resolution in Air Traffic Control  

E-print Network

Monte Carlo Optimization for Conflict Resolution in Air Traffic Control A. Lecchini , W. Glover assurance, is one of the main tasks of Air Traffic Control. Conflict resolution refers to the process used by air traffic controllers to prevent loss of separation. Conflict resolution involves issuing

Cambridge, University of

458

Monte Carlo simulations on a Rubik's cube model  

Microsoft Academic Search

We perform Monte Carlo simulations on a Rubik's cube model. In particular we derive thermodynamic and kinetic information of the Rubik cube with assigned energy functions. Through simulation studies one can gain information on its energy landscape. The similarity between the current model and several well-known protein-folding simulation models will be discussed.

Chi-Lun Lee

2007-01-01

459

Monte Carlo simulations on a Rubik's cube model  

NASA Astrophysics Data System (ADS)

We perform Monte Carlo simulations on a Rubik's cube model. In particular we derive thermodynamic and kinetic information of the Rubik cube with assigned energy functions. Through simulation studies one can gain information on its energy landscape. The similarity between the current model and several well-known protein-folding simulation models will be discussed.

Lee, Chi-Lun

2007-03-01

460

Bayesian methods, maximum entropy, and quantum Monte Carlo  

SciTech Connect

We heuristically discuss the application of the method of maximum entropy to the extraction of dynamical information from imaginary-time, quantum Monte Carlo data. The discussion emphasizes the utility of a Bayesian approach to statistical inference and the importance of statistically well-characterized data. 14 refs.

Gubernatis, J.E.; Silver, R.N. (Los Alamos National Lab., NM (United States)); Jarrell, M. (Cincinnati Univ., OH (United States))

1991-01-01

461

Path Integral Monte-Carlo Calculations for Relativistic Oscillator  

E-print Network

The problem of Relativistic Oscillator has been studied in the framework of Path Integral Monte-Carlo(PIMC) approach. Ultra-relativistic and non-relativistic limits have been discussed. We show that PIMC method can be effectively used for investigation of relativistic systems.

Alexandr Ivanov; Oleg Pavlovsky

2014-11-11

462

Exploring Mass Perception with Markov Chain Monte Carlo  

ERIC Educational Resources Information Center

Several previous studies have examined the ability to judge the relative mass of objects in idealized collisions. With a newly developed technique of psychological Markov chain Monte Carlo sampling (A. N. Sanborn & T. L. Griffiths, 2008), this work explores participants; perceptions of different collision mass ratios. The results reveal…

Cohen, Andrew L.; Ross, Michael G.

2009-01-01

463

Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review  

Microsoft Academic Search

A critical issue for users of Markov chain Monte Carlo (MCMC) methods in applications is how to determine when it is safe to stop sampling and use the samples to estimate characteristics of the distribution of interest. Research into methods of computing theoretical convergence bounds holds promise for the future but to date has yielded relatively little of practical use

Mary Kathryn Cowles; Bradley P. Carlin

1996-01-01

464

Image Segmentation by Data-Driven Markov Chain Monte Carlo  

Microsoft Academic Search

Abstract: This paper presents a computational paradigm called Data-Driven Markov Chain MonteCarlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The papercontributes to image segmentation in four aspects. Firstly, it designs ecient andwell balanced Markov Chain dynamics to explore the complex solution space, and thusachieves a nearly global optimal solution independent of initial segmentations. Secondly, itpresents a mathematical principle

Zhuowen Tu; Song-Chun Zhu

2002-01-01

465

Monte Carlo Radiation Analysis of a Spacecraft Radioisotope Power System  

NASA Technical Reports Server (NTRS)

A Monte Carlo statistical computer analysis was used to create neutron and photon radiation predictions for the General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS RTG). The GPHS RTG is being used on several NASA planetary missions. Analytical results were validated using measured health physics data.

Wallace, M.

1994-01-01

466

Monte Carlo Modeling of Io's [OI] Aurora in Eclipse  

NASA Astrophysics Data System (ADS)

A 3D direct Monte Carlo simulation is used to simulate Io's atmospheric interaction (upon entering eclipse) with electrons from the plasma torus. It is found that the flux tube depletion across Io controls the latitude of the bright wake feature.

Moore, C. H.; Goldstein, D. B.; Varghese, P. L.; Trafton, L. M.; Stapelfeldt, K.

2006-03-01

467

APS undulator and wiggler sources: Monte-Carlo simulation  

SciTech Connect

Standard insertion devices will be provided to each sector by the Advanced Photon Source. It is important to define the radiation characteristics of these general purpose devices. In this document,results of Monte-Carlo simulation are presented. These results, based on the SHADOW program, include the APS Undulator A (UA), Wiggler A (WA), and Wiggler B (WB).

Xu, S.L.; Lai, B.; Viccaro, P.J.

1992-02-01

468

NOTE: Monte Carlo study of TLD measurements in air cavities  

NASA Astrophysics Data System (ADS)

Thermoluminescent dosimeters (TLDs) are used for verification of the delivered dose during IMRT treatment of head and neck carcinomas. The TLDs are put into a plastic tube, which is placed in the nasal cavities through the treated volume. In this study, the dose distribution to a phantom having a cylindrical air cavity containing a tube was calculated by Monte Carlo methods and the results were compared with data from a treatment planning system (TPS) to evaluate the accuracy of the TLD measurements. The phantom was defined in the DOSXYZnrc Monte Carlo code and calculations were performed with 6 MV fields, with the TLD tube placed at different positions within the cylindrical air cavity. A similar phantom was defined in the pencil beam based TPS. Differences between the Monte Carlo and the TPS calculations of the absorbed dose to the TLD tube were found to be small for an open symmetrical field. For a half-beam field through the air cavity, there was a larger discrepancy. Furthermore, dose profiles through the cylindrical air cavity show, as expected, that the treatment planning system overestimates the absorbed dose in the air cavity. This study shows that when using an open symmetrical field, Monte Carlo calculations of absorbed doses to a TLD tube in a cylindrical air cavity give results comparable to a pencil beam based treatment planning system.

Haraldsson, Pia; Knöös, Tommy; Nyström, Håkan; Engström, Per

2003-09-01

469

Assessing protein loop flexibility by hierarchical Monte Carlo sampling  

E-print Network

Assessing protein loop flexibility by hierarchical Monte Carlo sampling Jerome Nilmeier ,1 Lan Hua, University of New Mexico, Albuquerque, New Mexico 87131 March 8, 2011 Abstract Loop flexibility is often to the flexible loop in triosephosphate isomerase that caps the active site, and demonstrate that the resulting

Coutsias, Evangelos

470

BROWNIAN PROCESSES FOR MONTE CARLO INTEGRATION ON COMPACT LIE GROUPS  

E-print Network

BROWNIAN PROCESSES FOR MONTE CARLO INTEGRATION ON COMPACT LIE GROUPS S. SAID, The University for the evaluation of integrals of smooth functions defined on compact Lie groups. The approach is based on the ergodic property of Brownian processes in compact Lie groups. The paper provides an elementary proof

Manton, Jonathan

471

Using Supervised Learning to Improve Monte Carlo Integral Estimation  

E-print Network

(importance sampling, quasi-Monte Carlo, etc.) without adding bias. An extensive set of experiments the fuel-burn metrics of future commercial aircraft and sonic boom loudness measures, and the efficiency, computational cost, significant increases in accuracy are gained. Nomenclature b = bias of M Dx = set of samples

Alonso, Juan J.

472

Improved analysis of bias in Monte Carlo criticality safety  

Microsoft Academic Search

Criticality safety, the prevention of nuclear chain reactions, depends on Monte Carlo computer codes for most commercial applications. One major shortcoming of these codes is the limited accuracy of the atomic and nuclear data files they depend on. In order to apply a code and its data files to a given criticality safety problem, the code must first be benchmarked

Thomas C. Haley

2000-01-01

473

Advanced Interacting Sequential Monte Carlo Sampling for Inverse Scattering  

E-print Network

techniques have been developed in the domain of agricultural and food materials, radar absorbers [4], etc Sequential Monte Carlo (SMC) or interacting particles ­ can take benefit of the structure and provide local, tomography, ionospheric sounding or SAR (Synthetic Aperture Radar). In electromagnetism (EM), the direct

Del Moral , Pierre

474

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

475

Exchange Monte Carlo Method and Application to Spin Glass Simulations  

Microsoft Academic Search

We propose an efficient Monte Carlo algorithm for simulating a ``hardly-relaxing'' system, in which many replicas with different temperatures are simultaneouslysimulated and a virtual process exchanging configurations of thesereplicas is introduced. This exchange process is expected to let the system at low temperatures escape from a local minimum. By using this algorithm the three-dimensional ±J Ising spin glass model is

Koji Hukushima; Koji Nemoto

1996-01-01

476

Parallel Monte Carlo Ion Recombination Simulation in Orca  

E-print Network

Parallel Monte Carlo Ion Recombination Simulation in Orca Frank J. Seinstra Department of Mathematics and Computer Science Vrije Universiteit Amsterdam, The Netherlands August 1996 Abstract: Orca in most languages for dis­ tributed programming is based on message passing. In Orca, however, a shared

Seinstra, Frank J.

477

The Number of Iterations in Monte Carlo Studies of Robustness.  

ERIC Educational Resources Information Center

A recent survey of simulation studies concluded that an overwhelming majority of papers do not report a rationale for the number of iterations carried out in Monte Carlo robustness (MCR) experiments. The survey suggested that researchers might benefit from adopting a hypothesis testing strategy in the planning and reporting of simulation studies.…

Robey, Randall R.; Barcikowski, Robert S.

478

MONTE CARLO METHODS IN FUZZY NON-LINEAR REGRESSION  

Microsoft Academic Search

We apply our new fuzzy Monte Carlo method to certain fuzzy non-linear regression problems to estimate the best solution. The best solution is a vector of triangular fuzzy numbers, for the fuzzy coefficients in the model, which minimizes an error measure. We use a quasi-random number generator to produce random sequences of these fuzzy vectors which uniformly fill the search

AREEG ABDALLA; JAMES BUCKLEY

2008-01-01

479

Detailed Heat Generation Simulations via the Monte Carlo Method  

E-print Network

details of Joule heating in bulk silicon with Monte Carlo simulations including acoustic and optical and particularly relevant to the heating and reliability of nanoscale and thin-film transistors. Joule heating, as in most semiconductors, high-field Joule heating is typically dominated by optical phonon emission

Dutton, Robert W.

480

On modelling continuous agglomerative crystal precipitation via Monte Carlo simulation  

Microsoft Academic Search

A model of agglomerative crystal precipitation based on the Monte Carlo simulation technique is investigated. The processes of nucleation, crystal growth and aggregation are first simulated to obtain the particle size distribution (PSD) for continuous mixed-suspension, mixed-product-removal (MSMPR) aggregative precipitation. An extension is then made to account for particle disruption by considering two alternative particle size reduction mechanisms — one

G. O Falope; A. G Jones; R Zauner

2001-01-01

481

Multiple Tree for Partially Observable Monte-Carlo Tree Search  

E-print Network

We propose an algorithm for computing approximate Nash equilibria of partially observable games using Monte-Carlo tree search based on recent bandit methods. We obtain experimental results for the game of phantom tic-tac-toe, showing that strong strategies can be efficiently computed by our algorithm.

Auger, David

2011-01-01

482

ENVIRONMENTAL MODELING: 1 APPLICATIONS: MONTE CARLO SENSITIVITY SIMULATIONS  

E-print Network

in the attempts to determine the levels of concentrations and depositions of the harmful air pollutants on very SIMULATIONS TO THE PROBLEM OF AIR POLLUTION TRANSPORT 3 1.1 The Danish Eulerian Model #12;Chapter 1 APPLICATIONS: MONTE CARLO SENSITIVITY SIMULATIONS TO THE PROBLEM OF AIR POLLUTION

Dimov, Ivan

483

Impact of random numbers on parallel Monte Carlo application  

SciTech Connect

A number of graduate students are involved at various level of research in this project. We investigate the basic issues in materials using Monte Carlo simulations with specific interest in heterogeneous materials. Attempts have been made to seek collaborations with the DOE laboratories. Specific details are given.

Pandey, Ras B.

2002-10-22

484

Realistic Monte Carlo simulation of Ga67 SPECT imaging  

Microsoft Academic Search

Describes a comprehensive Monte Carlo program tailored for efficient simulation of realistic Ga-67 SPECT imaging through the entire range of photon emission energies. The authors' approach incorporates several new features developed by them and by others. It is now being used to optimize and evaluate the performance of various methods of compensating for photon scatter, attenuation, and nonstationary distance- and

Stephen C. Moore; G. El Fakhri

2001-01-01

485

Dipolar Gay-Berne Liquid Crystals:. a Monte Carlo Study  

NASA Astrophysics Data System (ADS)

The phase diagrams of several dipolar Gay-Berne systems are generated using Monte Carlo simulations. Particular emphasis is placed upon the location, order and nature of the liquid crystalline phases observed at high fluid densities. The accuracy of the reaction field method is re-affirmed.

Houssa, Mohammed; Rull, Luis F.; McGrother, Simon C.

486

Markov Chain Monte Carlo with Linchpin Variables Felipe Acosta  

E-print Network

Markov Chain Monte Carlo with Linchpin Variables Felipe Acosta School of Statistics University@cmc.edu Galin L. Jones School of Statistics University of Minnesota galin@umn.edu March 13, 2014 Abstract Many-Hastings step is being performed. We use this to construct uniformly ergodic linchpin variable samplers for two

Jones, Galin

487

Efficient Cosmological Parameter Estimation with Hamiltonian Monte Carlo  

E-print Network

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 and boosts up the efficiency by at least a factor of D in a D-dimensional parameter space. Therefor 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.

Amir Hajian

2006-08-30

488

Quantum Monte Carlo calculations of symmetric nuclear matter  

E-print Network

We present an accurate numerical study of the equation of state of nuclear matter based on realistic nucleon--nucleon interactions by means of Auxiliary Field Diffusion Monte Carlo (AFDMC) calculations. The AFDMC method samples the spin and isospin degrees of freedom allowing for quantum simulations of large nucleonic systems and can provide quantitative understanding of problems in nuclear structure and astrophysics.

Stefano Gandolfi; Francesco Pederiva; Stefano Fantoni; Kevin E. Schmidt

2006-07-12

489

Feature Correspondence: A Markov Chain Monte Carlo Approach  

E-print Network

large impact in many areas of societal importance, such as architecture, entertainment, space a Bayesian perspective it is also sound. Unfortunately, no closed-form solution exists for calculating, a popular Markov chain Monte Carlo MCMC method, to samplefromthe posterior. In particular, we propose two di

Thrun, Sebastian

490

Feature Correspondence: A Markov Chain Monte Carlo Approach  

E-print Network

large impact in many areas of societal importance, such as architecture, entertainment, space a Bayesian perspective it is also sound. Unfortunately, no closed­form solution exists for calculating, a popular Markov chain Monte Carlo (MCMC) method, to sample from the posterior. In particular, we propose

Thrun, Sebastian

491

Discussion to "Sequential Monte Carlo for Bayesian Computation" YANAN FAN (UNIVERSITY OF NEW SOUTH WALES, AUSTRALIA)  

E-print Network

Discussion to "Sequential Monte Carlo for Bayesian Computation" YANAN FAN (UNIVERSITY OF NEW SOUTH, S. A., Fan, Y. & Tanaka, M. M. (2006). Sequential Monte Carlo without likelihoods. University of New

Fan, Yanan

492

APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)  

EPA Science Inventory

Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

493

Parallel algorithms for Monte Carlo particle transport simulation on exascale computing architectures  

E-print Network

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there ...

Romano, Paul K. (Paul Kollath)

2013-01-01

494

Monte Carlo f calculation of the neoclassical ion current in a rotating island  

E-print Network

Monte Carlo f calculation of the neoclassical ion current in a rotating island A. Bergmann, E. Poli is considered. We use a guiding centre f code augmented by a Monte Carlo model of pitch angle collisions

495

Combining final score with winning percentage by sigmoid function in Monte-Carlo simulations  

Microsoft Academic Search

Monte-Carlo method recently has produced good results in Go. Monte-Carlo Go uses a move which has the highest mean value of either winning percentage or final score. In a past research, winning percentage is superior to final score in Monte-Carlo Go. We investigated them in BlokusDuo, which is a relatively new game, and showed that Monte-Carlo using final score is

K. Shibahara; Y. Kotani

2008-01-01

496

When Are Quasi-Monte Carlo Algorithms Efficient for High Dimensional Integrals?  

Microsoft Academic Search

Recently, quasi-Monte Carlo algorithms have been successfully used for multivariate integration of high dimensiond, and were significantly more efficient than Monte Carlo algorithms. The existing theory of the worst case error bounds of quasi-Monte Carlo algorithms does not explain this phenomenon. This paper presents a partial answer to why quasi-Monte Carlo algorithms can work well for arbitrarily larged. It is

Ian H. Sloan; Henryk Wozniakowski

1998-01-01

497

Direct aperture optimization for IMRT using Monte Carlo generated beamlets  

SciTech Connect

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

498

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

499

Direct aperture optimization for IMRT using Monte Carlo generated beamlets.  

PubMed

This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods. PMID:17089832

Bergman, Alanah M; Bush, Karl; Milette, Marie-Pierre; Popescu, I Antoniu; Otto, Karl; Duzenli, Cheryl

2006-10-01

500

Fast Monte Carlo for radiation therapy: the PEREGRINE Project  

SciTech Connect

The purpose of the PEREGRINE program is to bring high-speed, high- accuracy, high-resolution Monte Carlo dose calculations to the desktop in the radiation therapy clinic. PEREGRINE is a three- dimensional Monte Carlo dose calculation system designed specifically for radiation therapy planning. It provides dose distributions from external beams of photons, electrons, neutrons, and protons as well as from brachytherapy sources. Each external radiation source particle passes through collimator jaws and beam modifiers such as blocks, compensators, and wedges that are used to customize the treatment to maximize the dose to the tumor. Absorbed dose is tallied in the patient or phantom as Monte Carlo simulation particles are followed through a Cartesian transport mesh that has been manually specified or determined from a CT scan of the patient. This paper describes PEREGRINE capabilities, results of benchmark comparisons, calculation times and performance, and the significance of Monte Carlo calculations for photon teletherapy. PEREGRINE results show excellent agreement with a comprehensive set of measurements for a wide variety of clinical photon beam geometries, on both homogeneous and heterogeneous test samples or phantoms. PEREGRINE is capable of calculating >350 million histories per hour for a standard clinical treatment plan. This results in a dose distribution with voxel