Monte Carlo method for random surfaces
International Nuclear Information System (INIS)
Berg, B.
1985-01-01
Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
Monte Carlo learning/biasing experiment with intelligent random numbers
International Nuclear Information System (INIS)
Booth, T.E.
1985-01-01
A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs
Study on random number generator in Monte Carlo code
International Nuclear Information System (INIS)
Oya, Kentaro; Kitada, Takanori; Tanaka, Shinichi
2011-01-01
The Monte Carlo code uses a sequence of pseudo-random numbers with a random number generator (RNG) to simulate particle histories. A pseudo-random number has its own period depending on its generation method and the period is desired to be long enough not to exceed the period during one Monte Carlo calculation to ensure the correctness especially for a standard deviation of results. The linear congruential generator (LCG) is widely used as Monte Carlo RNG and the period of LCG is not so long by considering the increasing rate of simulation histories in a Monte Carlo calculation according to the remarkable enhancement of computer performance. Recently, many kinds of RNG have been developed and some of their features are better than those of LCG. In this study, we investigate the appropriate RNG in a Monte Carlo code as an alternative to LCG especially for the case of enormous histories. It is found that xorshift has desirable features compared with LCG, and xorshift has a larger period, a comparable speed to generate random numbers, a better randomness, and good applicability to parallel calculation. (author)
Exploring pseudo- and chaotic random Monte Carlo simulations
Blais, J. A. Rod; Zhang, Zhan
2011-07-01
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.
Conditional Monte Carlo randomization tests for regression models.
Parhat, Parwen; Rosenberger, William F; Diao, Guoqing
2014-08-15
We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.
Flow in Random Microstructures: a Multilevel Monte Carlo Approach
Icardi, Matteo
2016-01-06
In this work we are interested in the fast estimation of effective parameters of random heterogeneous materials using Multilevel Monte Carlo (MLMC). MLMC is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrisation of the input randomness is not available or too expensive. We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations (PDEs) on random heterogeneous materials. We make use of the key idea of MLMC, based on different discretization levels, extending it in a more general context, making use of a hierarchy of physical resolution scales, solvers, models and other numerical/geometrical discretisation parameters. Modifications of the classical MLMC estimators are proposed to further reduce variance in cases where analytical convergence rates and asymptotic regimes are not available. Spheres, ellipsoids and general convex-shaped grains are placed randomly in the domain with different placing/packing algorithms and the effective properties of the heterogeneous medium are computed. These are, for example, effective diffusivities, conductivities, and reaction rates. The implementation of the Monte-Carlo estimators, the statistical samples and each single solver is done efficiently in parallel. The method is tested and applied for pore-scale simulations of random sphere packings.
Testing random number generators for Monte Carlo applications
International Nuclear Information System (INIS)
Sim, L.H.
1992-01-01
Central to any system for modelling radiation transport phenomena using Monte Carlo techniques is the method by which pseudo random numbers are generated. This method is commonly referred to as the Random Number Generator (RNG). It is usually a computer implemented mathematical algorithm which produces a series of numbers uniformly distributed on the interval [0,1]. If this series satisfies certain statistical tests for randomness, then for practical purposes the pseudo random numbers in the series can be considered to be random. Tests of this nature are important not only for new RNGs but also to test the implementation of known RNG algorithms in different computer environments. Six RNGs have been tested using six statistical tests and one visual test. The statistical tests are the moments, frequency (digit and number), serial, gap, and poker tests. The visual test is a simple two dimensional ordered pair display. In addition the RNGs have been tested in a specific Monte Carlo application. This type of test is often overlooked, however it is important that in addition to satisfactory performance in statistical tests, the RNG be able to perform effectively in the applications of interest. The RNGs tested here are based on a variety of algorithms, including multiplicative and linear congruential, lagged Fibonacci, and combination arithmetic and lagged Fibonacci. The effect of the Bays-Durham shuffling algorithm on the output of a known bad RNG has also been investigated. 18 refs., 11 tabs., 4 figs. of
Murthy, K. P. N.
2001-01-01
An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential b...
Random number generators tested on quantum Monte Carlo simulations.
Hongo, Kenta; Maezono, Ryo; Miura, Kenichi
2010-08-01
We have tested and compared several (pseudo) random number generators (RNGs) applied to a practical application, ground state energy calculations of molecules using variational and diffusion Monte Carlo metheds. A new multiple recursive generator with 8th-order recursion (MRG8) and the Mersenne twister generator (MT19937) are tested and compared with the RANLUX generator with five luxury levels (RANLUX-[0-4]). Both MRG8 and MT19937 are proven to give the same total energy as that evaluated with RANLUX-4 (highest luxury level) within the statistical error bars with less computational cost to generate the sequence. We also tested the notorious implementation of linear congruential generator (LCG), RANDU, for comparison. (c) 2010 Wiley Periodicals, Inc.
Generation of Random Numbers and Parallel Random Number Streams for Monte Carlo Simulations
Directory of Open Access Journals (Sweden)
L. Yu. Barash
2012-01-01
Full Text Available Modern methods and libraries for high quality pseudorandom number generation and for generation of parallel random number streams for Monte Carlo simulations are considered. The probability equidistribution property and the parameters when the property holds at dimensions up to logarithm of mesh size are considered for Multiple Recursive Generators.
Monte Carlo and Quasi-Monte Carlo Sampling
Lemieux, Christiane
2009-01-01
Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods.
Effects of changing the random number stride in Monte Carlo calculations
International Nuclear Information System (INIS)
Hendricks, J.S.
1991-01-01
This paper reports on a common practice in Monte Carlo radiation transport codes which is to start each random walk a specified number of steps up the random number sequence from the previous one. This is called the stride in the random number sequence between source particles. It is used for correlated sampling or to provide tree-structured random numbers. A new random number generator algorithm for the major Monte Carlo code MCNP has been written to allow adjustment of the random number stride. This random number generator is machine portable. The effects of varying the stride for several sample problems are examined
Monte Carlo principles and applications
Energy Technology Data Exchange (ETDEWEB)
Raeside, D E [Oklahoma Univ., Oklahoma City (USA). Health Sciences Center
1976-03-01
The principles underlying the use of Monte Carlo methods are explained, for readers who may not be familiar with the approach. The generation of random numbers is discussed, and the connection between Monte Carlo methods and random numbers is indicated. Outlines of two well established Monte Carlo sampling techniques are given, together with examples illustrating their use. The general techniques for improving the efficiency of Monte Carlo calculations are considered. The literature relevant to the applications of Monte Carlo calculations in medical physics is reviewed.
Randomized quasi-Monte Carlo simulation of fast-ion thermalization
International Nuclear Information System (INIS)
Höök, L J; Johnson, T; Hellsten, T
2012-01-01
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 2 14 . (paper)
Randomized quasi-Monte Carlo simulation of fast-ion thermalization
Höök, L. J.; Johnson, T.; Hellsten, T.
2012-01-01
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.
Non-periodic pseudo-random numbers used in Monte Carlo calculations
Barberis, Gaston E.
2007-09-01
The generation of pseudo-random numbers is one of the interesting problems in Monte Carlo simulations, mostly because the common computer generators produce periodic numbers. We used simple pseudo-random numbers generated with the simplest chaotic system, the logistic map, with excellent results. The numbers generated in this way are non-periodic, which we demonstrated for 1013 numbers, and they are obtained in a deterministic way, which allows to repeat systematically any calculation. The Monte Carlo calculations are the ideal field to apply these numbers, and we did it for simple and more elaborated cases. Chemistry and Information Technology use this kind of simulations, and the application of this numbers to quantum Monte Carlo and cryptography is immediate. I present here the techniques to calculate, analyze and use these pseudo-random numbers, show that they lack periodicity up to 1013 numbers and that they are not correlated.
Non-periodic pseudo-random numbers used in Monte Carlo calculations
International Nuclear Information System (INIS)
Barberis, Gaston E.
2007-01-01
The generation of pseudo-random numbers is one of the interesting problems in Monte Carlo simulations, mostly because the common computer generators produce periodic numbers. We used simple pseudo-random numbers generated with the simplest chaotic system, the logistic map, with excellent results. The numbers generated in this way are non-periodic, which we demonstrated for 10 13 numbers, and they are obtained in a deterministic way, which allows to repeat systematically any calculation. The Monte Carlo calculations are the ideal field to apply these numbers, and we did it for simple and more elaborated cases. Chemistry and Information Technology use this kind of simulations, and the application of this numbers to quantum Monte Carlo and cryptography is immediate. I present here the techniques to calculate, analyze and use these pseudo-random numbers, show that they lack periodicity up to 10 13 numbers and that they are not correlated
Pseudo-random number generators for Monte Carlo simulations on ATI Graphics Processing Units
Demchik, Vadim
2011-03-01
Basic uniform pseudo-random number generators are implemented on ATI Graphics Processing Units (GPU). The performance results of the realized generators (multiplicative linear congruential (GGL), XOR-shift (XOR128), RANECU, RANMAR, RANLUX and Mersenne Twister (MT19937)) on CPU and GPU are discussed. The obtained speed up factor is hundreds of times in comparison with CPU. RANLUX generator is found to be the most appropriate for using on GPU in Monte Carlo simulations. The brief review of the pseudo-random number generators used in modern software packages for Monte Carlo simulations in high-energy physics is presented.
Generation of triangulated random surfaces by the Monte Carlo method in the grand canonical ensemble
International Nuclear Information System (INIS)
Zmushko, V.V.; Migdal, A.A.
1987-01-01
A model of triangulated random surfaces which is the discrete analog of the Polyakov string is considered. An algorithm is proposed which enables one to study the model by the Monte Carlo method in the grand canonical ensemble. Preliminary results on the determination of the critical index γ are presented
Flow in Random Microstructures: a Multilevel Monte Carlo Approach
Icardi, Matteo; Tempone, Raul
2016-01-01
, where an explicit parametrisation of the input randomness is not available or too expensive. We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations (PDEs) on random heterogeneous materials. We
International Nuclear Information System (INIS)
Creutz, M.
1986-01-01
The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena
Monte Carlo Methods in Physics
International Nuclear Information System (INIS)
Santoso, B.
1997-01-01
Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained
Randomly dispersed particle fuel model in the PSG Monte Carlo neutron transport code
International Nuclear Information System (INIS)
Leppaenen, J.
2007-01-01
High-temperature gas-cooled reactor fuels are composed of thousands of microscopic fuel particles, randomly dispersed in a graphite matrix. The modelling of such geometry is complicated, especially using continuous-energy Monte Carlo codes, which are unable to apply any deterministic corrections in the calculation. This paper presents the geometry routine developed for modelling randomly dispersed particle fuels using the PSG Monte Carlo reactor physics code. The model is based on the delta-tracking method, and it takes into account the spatial self-shielding effects and the random dispersion of the fuel particles. The calculation routine is validated by comparing the results to reference MCNP4C calculations using uranium and plutonium based fuels. (authors)
Crevillén-García, D.; Power, H.
2017-08-01
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.
Crevillén-García, D; Power, H
2017-08-01
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.
Dunn, William L
2012-01-01
Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble
Directory of Open Access Journals (Sweden)
Bardenet Rémi
2013-07-01
Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.
Golden Ratio Versus Pi as Random Sequence Sources for Monte Carlo Integration
Sen, S. K.; Agarwal, Ravi P.; Shaykhian, Gholam Ali
2007-01-01
We discuss here the relative merits of these numbers as possible random sequence sources. The quality of these sequences is not judged directly based on the outcome of all known tests for the randomness of a sequence. Instead, it is determined implicitly by the accuracy of the Monte Carlo integration in a statistical sense. Since our main motive of using a random sequence is to solve real world problems, it is more desirable if we compare the quality of the sequences based on their performances for these problems in terms of quality/accuracy of the output. We also compare these sources against those generated by a popular pseudo-random generator, viz., the Matlab rand and the quasi-random generator ha/ton both in terms of error and time complexity. Our study demonstrates that consecutive blocks of digits of each of these numbers produce a good random sequence source. It is observed that randomly chosen blocks of digits do not have any remarkable advantage over consecutive blocks for the accuracy of the Monte Carlo integration. Also, it reveals that pi is a better source of a random sequence than theta when the accuracy of the integration is concerned.
Energy Technology Data Exchange (ETDEWEB)
Murata, Isao [Osaka Univ., Suita (Japan); Mori, Takamasa; Nakagawa, Masayuki; Itakura, Hirofumi
1996-03-01
The method to calculate neutronics parameters of a core composed of randomly distributed spherical fuels has been developed based on a statistical geometry model with a continuous energy Monte Carlo method. This method was implemented in a general purpose Monte Carlo code MCNP, and a new code MCNP-CFP had been developed. This paper describes the model and method how to use it and the validation results. In the Monte Carlo calculation, the location of a spherical fuel is sampled probabilistically along the particle flight path from the spatial probability distribution of spherical fuels, called nearest neighbor distribution (NND). This sampling method was validated through the following two comparisons: (1) Calculations of inventory of coated fuel particles (CFPs) in a fuel compact by both track length estimator and direct evaluation method, and (2) Criticality calculations for ordered packed geometries. This method was also confined by applying to an analysis of the critical assembly experiment at VHTRC. The method established in the present study is quite unique so as to a probabilistic model of the geometry with a great number of spherical fuels distributed randomly. Realizing the speed-up by vector or parallel computations in future, it is expected to be widely used in calculation of a nuclear reactor core, especially HTGR cores. (author).
Random number generators for large-scale parallel Monte Carlo simulations on FPGA
Lin, Y.; Wang, F.; Liu, B.
2018-05-01
Through parallelization, field programmable gate array (FPGA) can achieve unprecedented speeds in large-scale parallel Monte Carlo (LPMC) simulations. FPGA presents both new constraints and new opportunities for the implementations of random number generators (RNGs), which are key elements of any Monte Carlo (MC) simulation system. Using empirical and application based tests, this study evaluates all of the four RNGs used in previous FPGA based MC studies and newly proposed FPGA implementations for two well-known high-quality RNGs that are suitable for LPMC studies on FPGA. One of the newly proposed FPGA implementations: a parallel version of additive lagged Fibonacci generator (Parallel ALFG) is found to be the best among the evaluated RNGs in fulfilling the needs of LPMC simulations on FPGA.
Lectures on Monte Carlo methods
Madras, Neal
2001-01-01
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati
Efficient pseudo-random number generation for monte-carlo simulations using graphic processors
Mohanty, Siddhant; Mohanty, A. K.; Carminati, F.
2012-06-01
A hybrid approach based on the combination of three Tausworthe generators and one linear congruential generator for pseudo random number generation for GPU programing as suggested in NVIDIA-CUDA library has been used for MONTE-CARLO sampling. On each GPU thread, a random seed is generated on fly in a simple way using the quick and dirty algorithm where mod operation is not performed explicitly due to unsigned integer overflow. Using this hybrid generator, multivariate correlated sampling based on alias technique has been carried out using both CUDA and OpenCL languages.
Efficient pseudo-random number generation for Monte-Carlo simulations using graphic processors
International Nuclear Information System (INIS)
Mohanty, Siddhant; Mohanty, A K; Carminati, F
2012-01-01
A hybrid approach based on the combination of three Tausworthe generators and one linear congruential generator for pseudo random number generation for GPU programing as suggested in NVIDIA-CUDA library has been used for MONTE-CARLO sampling. On each GPU thread, a random seed is generated on fly in a simple way using the quick and dirty algorithm where mod operation is not performed explicitly due to unsigned integer overflow. Using this hybrid generator, multivariate correlated sampling based on alias technique has been carried out using both CUDA and OpenCL languages.
Directory of Open Access Journals (Sweden)
Qian Zhang
2014-01-01
Full Text Available The paper presents a framework for the construction of Monte Carlo finite volume element method (MCFVEM for the convection-diffusion equation with a random diffusion coefficient, which is described as a random field. We first approximate the continuous stochastic field by a finite number of random variables via the Karhunen-Loève expansion and transform the initial stochastic problem into a deterministic one with a parameter in high dimensions. Then we generate independent identically distributed approximations of the solution by sampling the coefficient of the equation and employing finite volume element variational formulation. Finally the Monte Carlo (MC method is used to compute corresponding sample averages. Statistic error is estimated analytically and experimentally. A quasi-Monte Carlo (QMC technique with Sobol sequences is also used to accelerate convergence, and experiments indicate that it can improve the efficiency of the Monte Carlo method.
Monte Carlo studies of two-dimensional random-anisotropy magnets
Denholm, D. R.; Sluckin, T. J.
1993-07-01
We have carried out a systematic set of Monte Carlo simulations of the Harris-Plischke-Zuckermann lattice model of random magnetic anisotropy on a two-dimensional square lattice, using the classical Metropolis algorithm. We have considered varying temperature T, external magnetic field H (both in the reproducible and irreproducible limits), time scale of the simulation τ in Monte Carlo steps and anisotropy ratio D/J. In the absence of randomness this model reduces to the XY model in two dimensions, which possesses the familiar Kosterlitz-Thouless low-temperature phase with algebraic but no long-range order. In the presence of random anisotropy we find evidence of a low-temperature phase with some disordered features, which might be identified with a spin-glass phase. The low-temperature Kosterlitz-Thouless phase survives at intermediate temperatures for low randomness, but is no longer present for large D/J. We have also studied the high-H approach to perfect order, for which there are theoretical predictions due to Chudnovsky.
Monte Carlo theory and practice
International Nuclear Information System (INIS)
James, F.
1987-01-01
Historically, the first large-scale calculations to make use of the Monte Carlo method were studies of neutron scattering and absorption, random processes for which it is quite natural to employ random numbers. Such calculations, a subset of Monte Carlo calculations, are known as direct simulation, since the 'hypothetical population' of the narrower definition above corresponds directly to the real population being studied. The Monte Carlo method may be applied wherever it is possible to establish equivalence between the desired result and the expected behaviour of a stochastic system. The problem to be solved may already be of a probabilistic or statistical nature, in which case its Monte Carlo formulation will usually be a straightforward simulation, or it may be of a deterministic or analytic nature, in which case an appropriate Monte Carlo formulation may require some imagination and may appear contrived or artificial. In any case, the suitability of the method chosen will depend on its mathematical properties and not on its superficial resemblance to the problem to be solved. The authors show how Monte Carlo techniques may be compared with other methods of solution of the same physical problem
Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans
International Nuclear Information System (INIS)
Stapleton, S; Zavgorodni, S; Popescu, I A; Beckham, W A
2005-01-01
The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot
Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans
Stapleton, S.; Zavgorodni, S.; Popescu, I. A.; Beckham, W. A.
2005-02-01
The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot.
International Nuclear Information System (INIS)
Cramer, S.N.
1984-01-01
The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described
Summing Feynman graphs by Monte Carlo: Planar φ3-theory and dynamically triangulated random surfaces
International Nuclear Information System (INIS)
Boulatov, D.V.
1988-01-01
New combinatorial identities are suggested relating the ratio of (n-1)th and nth orders of (planar) perturbation expansion for any quantity to some average over the ensemble of all planar graphs of the nth order. These identities are used for Monte Carlo calculation of critical exponents γ str (string susceptibility) in planar φ 3 -theory and in the dynamically triangulated random surface (DTRS) model near the convergence circle for various dimensions. In the solvable case D=1 the exact critical properties of the theory are reproduced numerically. (orig.)
Applicability of the condensed-random-walk Monte Carlo method at low energies in high-Z materials
International Nuclear Information System (INIS)
Berger, Martin J.
1998-01-01
The predictions of several Monte Carlo codes were compared with each other and with experimental results pertaining to the penetration of through gold foils of electrons incident with energies from 128 to 8 keV. The main purpose was to demonstrate that reflection and transmission coefficients, for number and energy, can be estimated reliably with a simple Monte Carlo code based on the condensed-random-walk and continuous-slowing-down approximations
International Nuclear Information System (INIS)
Chakraborty, Brahmananda
2009-01-01
Random number plays an important role in any Monte Carlo simulation. The accuracy of the results depends on the quality of the sequence of random numbers employed in the simulation. These include randomness of the random numbers, uniformity of their distribution, absence of correlation and long period. In a typical Monte Carlo simulation of particle transport in a nuclear reactor core, the history of a particle from its birth in a fission event until its death by an absorption or leakage event is tracked. The geometry of the core and the surrounding materials are exactly modeled in the simulation. To track a neutron history one needs random numbers for determining inter collision distance, nature of the collision, the direction of the scattered neutron etc. Neutrons are tracked in batches. In one batch approximately 2000-5000 neutrons are tracked. The statistical accuracy of the results of the simulation depends on the total number of particles (number of particles in one batch multiplied by the number of batches) tracked. The number of histories to be generated is usually large for a typical radiation transport problem. To track a very large number of histories one needs to generate a long sequence of independent random numbers. In other words the cycle length of the random number generator (RNG) should be more than the total number of random numbers required for simulating the given transport problem. The number of bits of the machine generally limits the cycle length. For a binary machine of p bits the maximum cycle length is 2 p . To achieve higher cycle length in the same machine one has to use either register arithmetic or bit manipulation technique
Variational Monte Carlo Technique
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 8. Variational Monte Carlo Technique: Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. General Article Volume 19 Issue 8 August 2014 pp 713-739 ...
Multi-Index Monte Carlo and stochastic collocation methods for random PDEs
Nobile, Fabio
2016-01-09
In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.
Multi-Index Monte Carlo and stochastic collocation methods for random PDEs
Nobile, Fabio; Haji Ali, Abdul Lateef; Tamellini, Lorenzo; Tempone, Raul
2016-01-01
In this talk we consider the problem of computing statistics of the solution of a partial differential equation with random data, where the random coefficient is parametrized by means of a finite or countable sequence of terms in a suitable expansion. We describe and analyze a Multi-Index Monte Carlo (MIMC) and a Multi-Index Stochastic Collocation method (MISC). the former is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using firstorder differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2). On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that in the optimal case the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally effective. We finally show the effectiveness of MIMC and MISC with some computational tests, including tests with a infinite countable number of random parameters.
Monte Carlo codes and Monte Carlo simulator program
International Nuclear Information System (INIS)
Higuchi, Kenji; Asai, Kiyoshi; Suganuma, Masayuki.
1990-03-01
Four typical Monte Carlo codes KENO-IV, MORSE, MCNP and VIM have been vectorized on VP-100 at Computing Center, JAERI. The problems in vector processing of Monte Carlo codes on vector processors have become clear through the work. As the result, it is recognized that these are difficulties to obtain good performance in vector processing of Monte Carlo codes. A Monte Carlo computing machine, which processes the Monte Carlo codes with high performances is being developed at our Computing Center since 1987. The concept of Monte Carlo computing machine and its performance have been investigated and estimated by using a software simulator. In this report the problems in vectorization of Monte Carlo codes, Monte Carlo pipelines proposed to mitigate these difficulties and the results of the performance estimation of the Monte Carlo computing machine by the simulator are described. (author)
International Nuclear Information System (INIS)
Brown, F.B.
1981-01-01
Examination of the global algorithms and local kernels of conventional general-purpose Monte Carlo codes shows that multigroup Monte Carlo methods have sufficient structure to permit efficient vectorization. A structured multigroup Monte Carlo algorithm for vector computers is developed in which many particle events are treated at once on a cell-by-cell basis. Vectorization of kernels for tracking and variance reduction is described, and a new method for discrete sampling is developed to facilitate the vectorization of collision analysis. To demonstrate the potential of the new method, a vectorized Monte Carlo code for multigroup radiation transport analysis was developed. This code incorporates many features of conventional general-purpose production codes, including general geometry, splitting and Russian roulette, survival biasing, variance estimation via batching, a number of cutoffs, and generalized tallies of collision, tracklength, and surface crossing estimators with response functions. Predictions of vectorized performance characteristics for the CYBER-205 were made using emulated coding and a dynamic model of vector instruction timing. Computation rates were examined for a variety of test problems to determine sensitivities to batch size and vector lengths. Significant speedups are predicted for even a few hundred particles per batch, and asymptotic speedups by about 40 over equivalent Amdahl 470V/8 scalar codes arepredicted for a few thousand particles per batch. The principal conclusion is that vectorization of a general-purpose multigroup Monte Carlo code is well worth the significant effort required for stylized coding and major algorithmic changes
Dynamic connectivity algorithms for Monte Carlo simulations of the random-cluster model
International Nuclear Information System (INIS)
Elçi, Eren Metin; Weigel, Martin
2014-01-01
We review Sweeny's algorithm for Monte Carlo simulations of the random cluster model. Straightforward implementations suffer from the problem of computational critical slowing down, where the computational effort per edge operation scales with a power of the system size. By using a tailored dynamic connectivity algorithm we are able to perform all operations with a poly-logarithmic computational effort. This approach is shown to be efficient in keeping online connectivity information and is of use for a number of applications also beyond cluster-update simulations, for instance in monitoring droplet shape transitions. As the handling of the relevant data structures is non-trivial, we provide a Python module with a full implementation for future reference.
Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations
Energy Technology Data Exchange (ETDEWEB)
Douglass, Michael; Bezak, Eva; Penfold, Scott [School of Chemistry and Physics, University of Adelaide, North Terrace, Adelaide 5005, South Australia (Australia) and Department of Medical Physics, Royal Adelaide Hospital, North Terrace, Adelaide 5000, South Australia (Australia)
2012-06-15
Purpose: The objective of the current work was to develop an algorithm for growing a macroscopic tumor volume from individual randomized quasi-realistic cells. The major physical and chemical components of the cell need to be modeled. It is intended to import the tumor volume into GEANT4 (and potentially other Monte Carlo packages) to simulate ionization events within the cell regions. Methods: A MATLAB Copyright-Sign code was developed to produce a tumor coordinate system consisting of individual ellipsoidal cells randomized in their spatial coordinates, sizes, and rotations. An eigenvalue method using a mathematical equation to represent individual cells was used to detect overlapping cells. GEANT4 code was then developed to import the coordinate system into GEANT4 and populate it with individual cells of varying sizes and composed of the membrane, cytoplasm, reticulum, nucleus, and nucleolus. Each region is composed of chemically realistic materials. Results: The in-house developed MATLAB Copyright-Sign code was able to grow semi-realistic cell distributions ({approx}2 Multiplication-Sign 10{sup 8} cells in 1 cm{sup 3}) in under 36 h. The cell distribution can be used in any number of Monte Carlo particle tracking toolkits including GEANT4, which has been demonstrated in this work. Conclusions: Using the cell distribution and GEANT4, the authors were able to simulate ionization events in the individual cell components resulting from 80 keV gamma radiation (the code is applicable to other particles and a wide range of energies). This virtual microdosimetry tool will allow for a more complete picture of cell damage to be developed.
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.
Elements of Monte Carlo techniques
International Nuclear Information System (INIS)
Nagarajan, P.S.
2000-01-01
The Monte Carlo method is essentially mimicking the real world physical processes at the microscopic level. With the incredible increase in computing speeds and ever decreasing computing costs, there is widespread use of the method for practical problems. The method is used in calculating algorithm-generated sequences known as pseudo random sequence (prs)., probability density function (pdf), test for randomness, extension to multidimensional integration etc
International Nuclear Information System (INIS)
Zmushko, V.V.; Migdal, A.A.
1987-01-01
A model of triangulated random surfaces which is the discrete analogue of the Polyakov string is considered in the work. An algorithm is proposed which enables one to study the model by means of the Monte Carlo method in the grand canonical ensemble. Preliminary results are presented on the evaluation of the critical index γ
International Nuclear Information System (INIS)
Rajabalinejad, M.
2010-01-01
To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.
Quasi-random Monte Carlo application in CGE systematic sensitivity analysis
Chatzivasileiadis, T.
2017-01-01
The uncertainty and robustness of Computable General Equilibrium models can be assessed by conducting a Systematic Sensitivity Analysis. Different methods have been used in the literature for SSA of CGE models such as Gaussian Quadrature and Monte Carlo methods. This paper explores the use of
International Nuclear Information System (INIS)
Dubi, A.; Gerstl, S.A.W.
1979-05-01
The contributon Monte Carlo method is based on a new recipe to calculate target responses by means of volume integral of the contributon current in a region between the source and the detector. A comprehensive description of the method, its implementation in the general-purpose MCNP code, and results of the method for realistic nonhomogeneous, energy-dependent problems are presented. 23 figures, 10 tables
International Nuclear Information System (INIS)
Wollaber, Allan Benton
2016-01-01
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating @@), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
Energy Technology Data Exchange (ETDEWEB)
Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-16
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
Energy Technology Data Exchange (ETDEWEB)
Brockway, D.; Soran, P.; Whalen, P.
1985-01-01
A Monte Carlo algorithm to efficiently calculate static alpha eigenvalues, N = ne/sup ..cap alpha..t/, for supercritical systems has been developed and tested. A direct Monte Carlo approach to calculating a static alpha is to simply follow the buildup in time of neutrons in a supercritical system and evaluate the logarithmic derivative of the neutron population with respect to time. This procedure is expensive, and the solution is very noisy and almost useless for a system near critical. The modified approach is to convert the time-dependent problem to a static ..cap alpha../sup -/eigenvalue problem and regress ..cap alpha.. on solutions of a/sup -/ k/sup -/eigenvalue problem. In practice, this procedure is much more efficient than the direct calculation, and produces much more accurate results. Because the Monte Carlo codes are intrinsically three-dimensional and use elaborate continuous-energy cross sections, this technique is now used as a standard for evaluating other calculational techniques in odd geometries or with group cross sections.
Monte Carlo simulation in nuclear medicine
International Nuclear Information System (INIS)
Morel, Ch.
2007-01-01
The Monte Carlo method allows for simulating random processes by using series of pseudo-random numbers. It became an important tool in nuclear medicine to assist in the design of new medical imaging devices, optimise their use and analyse their data. Presently, the sophistication of the simulation tools allows the introduction of Monte Carlo predictions in data correction and image reconstruction processes. The availability to simulate time dependent processes opens up new horizons for Monte Carlo simulation in nuclear medicine. In a near future, these developments will allow to tackle simultaneously imaging and dosimetry issues and soon, case system Monte Carlo simulations may become part of the nuclear medicine diagnostic process. This paper describes some Monte Carlo method basics and the sampling methods that were developed for it. It gives a referenced list of different simulation software used in nuclear medicine and enumerates some of their present and prospective applications. (author)
International Nuclear Information System (INIS)
Procassini, R J; Beck, B R
2004-01-01
It might be assumed that use of a ''high-quality'' random number generator (RNG), producing a sequence of ''pseudo random'' numbers with a ''long'' repetition period, is crucial for producing unbiased results in Monte Carlo particle transport simulations. While several theoretical and empirical tests have been devised to check the quality (randomness and period) of an RNG, for many applications it is not clear what level of RNG quality is required to produce unbiased results. This paper explores the issue of RNG quality in the context of parallel, Monte Carlo transport simulations in order to determine how ''good'' is ''good enough''. This study employs the MERCURY Monte Carlo code, which incorporates the CNPRNG library for the generation of pseudo-random numbers via linear congruential generator (LCG) algorithms. The paper outlines the usage of random numbers during parallel MERCURY simulations, and then describes the source and criticality transport simulations which comprise the empirical basis of this study. A series of calculations for each test problem in which the quality of the RNG (period of the LCG) is varied provides the empirical basis for determining the minimum repetition period which may be employed without producing a bias in the mean integrated results
Energy Technology Data Exchange (ETDEWEB)
Vrugt, Jasper A [Los Alamos National Laboratory; Hyman, James M [Los Alamos National Laboratory; Robinson, Bruce A [Los Alamos National Laboratory; Higdon, Dave [Los Alamos National Laboratory; Ter Braak, Cajo J F [NETHERLANDS; Diks, Cees G H [UNIV OF AMSTERDAM
2008-01-01
Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.
International Nuclear Information System (INIS)
Meglinskii, I V
2001-01-01
The reflection spectra of a multilayer random medium - the human skin - strongly scattering and absorbing light are numerically simulated. The propagation of light in the medium and the absorption spectra are simulated by the stochastic Monte Carlo method, which combines schemes for calculations of real photon trajectories and the statistical weight method. The model takes into account the inhomogeneous spatial distribution of blood vessels, water, and melanin, the degree of blood oxygenation, and the hematocrit index. The attenuation of the incident radiation caused by reflection and refraction at Fresnel boundaries of layers inside the medium is also considered. The simulated reflection spectra are compared with the experimental reflection spectra of the human skin. It is shown that a set of parameters that was used to describe the optical properties of skin layers and their possible variations, despite being far from complete, is nevertheless sufficient for the simulation of the reflection spectra of the human skin and their quantitative analysis. (laser applications and other topics in quantum electronics)
A contribution Monte Carlo method
International Nuclear Information System (INIS)
Aboughantous, C.H.
1994-01-01
A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time
Variational Monte Carlo Technique
Indian Academy of Sciences (India)
ias
on the development of nuclear weapons in Los Alamos ..... cantly improved the paper. ... Carlo simulations of solids, Reviews of Modern Physics, Vol.73, pp.33– ... The computer algorithms are usually based on a random seed that starts the ...
Pore-scale uncertainty quantification with multilevel Monte Carlo
Icardi, Matteo; Hoel, Haakon; Long, Quan; Tempone, Raul
2014-01-01
. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost
International Nuclear Information System (INIS)
Cornejo Diaz, N.; Vergara Gil, A.; Jurado Vargas, M.
2010-01-01
The Monte Carlo method has become a valuable numerical laboratory framework in which to simulate complex physical systems. It is based on the generation of pseudo-random number sequences by numerical algorithms called random generators. In this work we assessed the suitability of different well-known random number generators for the simulation of gamma-ray spectrometry systems during efficiency calibrations. The assessment was carried out in two stages. The generators considered (Delphi's linear congruential, mersenne twister, XorShift, multiplier with carry, universal virtual array, and non-periodic logistic map based generator) were first evaluated with different statistical empirical tests, including moments, correlations, uniformity, independence of terms and the DIEHARD battery of tests. In a second step, an application-specific test was conducted by implementing the generators in our Monte Carlo program DETEFF and comparing the results obtained with them. The calculations were performed with two different CPUs, for a typical HpGe detector and a water sample in Marinelli geometry, with gamma-rays between 59 and 1800 keV. For the Non-periodic Logistic Map based generator, dependence of the most significant bits was evident. This explains the bias, in excess of 5%, of the efficiency values obtained with this generator. The results of the application-specific assessment and the statistical performance of the other algorithms studied indicate their suitability for the Monte Carlo simulation of gamma-ray spectrometry systems for efficiency calculations.
Díaz, N Cornejo; Gil, A Vergara; Vargas, M Jurado
2010-03-01
The Monte Carlo method has become a valuable numerical laboratory framework in which to simulate complex physical systems. It is based on the generation of pseudo-random number sequences by numerical algorithms called random generators. In this work we assessed the suitability of different well-known random number generators for the simulation of gamma-ray spectrometry systems during efficiency calibrations. The assessment was carried out in two stages. The generators considered (Delphi's linear congruential, mersenne twister, XorShift, multiplier with carry, universal virtual array, and non-periodic logistic map based generator) were first evaluated with different statistical empirical tests, including moments, correlations, uniformity, independence of terms and the DIEHARD battery of tests. In a second step, an application-specific test was conducted by implementing the generators in our Monte Carlo program DETEFF and comparing the results obtained with them. The calculations were performed with two different CPUs, for a typical HpGe detector and a water sample in Marinelli geometry, with gamma-rays between 59 and 1800 keV. For the Non-periodic Logistic Map based generator, dependence of the most significant bits was evident. This explains the bias, in excess of 5%, of the efficiency values obtained with this generator. The results of the application-specific assessment and the statistical performance of the other algorithms studied indicate their suitability for the Monte Carlo simulation of gamma-ray spectrometry systems for efficiency calculations. Copyright 2009 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Mercier, B.
1985-04-01
We have shown that the transport equation can be solved with particles, like the Monte-Carlo method, but without random numbers. In the Monte-Carlo method, particles are created from the source, and are followed from collision to collision until either they are absorbed or they leave the spatial domain. In our method, particles are created from the original source, with a variable weight taking into account both collision and absorption. These particles are followed until they leave the spatial domain, and we use them to determine a first collision source. Another set of particles is then created from this first collision source, and tracked to determine a second collision source, and so on. This process introduces an approximation which does not exist in the Monte-Carlo method. However, we have analyzed the effect of this approximation, and shown that it can be limited. Our method is deterministic, gives reproducible results. Furthermore, when extra accuracy is needed in some region, it is easier to get more particles to go there. It has the same kind of applications: rather problems where streaming is dominant than collision dominated problems
A Monte Carlo study of adsorption of random copolymers on random surfaces
Moghaddam, M S
2003-01-01
We study the adsorption problem of a random copolymer on a random surface in which a self-avoiding walk in three dimensions interacts with a plane defining a half-space to which the walk is confined. Each vertex of the walk is randomly labelled A with probability p sub p or B with probability 1 - p sub p , and only vertices labelled A are attracted to the surface plane. Each lattice site on the plane is also labelled either A with probability p sub s or B with probability 1 - p sub s , and only lattice sites labelled A interact with the walk. We study two variations of this model: in the first case the A-vertices of the walk interact only with the A-sites on the surface. In the second case the constraint of selective binding is removed; that is, any contact between the walk and the surface that involves an A-labelling, either from the surface or from the walk, is counted as a visit to the surface. The system is quenched in both cases, i.e. the labellings of the walk and of the surface are fixed as thermodynam...
Applications of Monte Carlo method in Medical Physics
International Nuclear Information System (INIS)
Diez Rios, A.; Labajos, M.
1989-01-01
The basic ideas of Monte Carlo techniques are presented. Random numbers and their generation by congruential methods, which underlie Monte Carlo calculations are shown. Monte Carlo techniques to solve integrals are discussed. The evaluation of a simple monodimensional integral with a known answer, by means of two different Monte Carlo approaches are discussed. The basic principles to simualate on a computer photon histories reduce variance and the current applications in Medical Physics are commented. (Author)
Ghersi, Dario; Parakh, Abhishek; Mezei, Mihaly
2017-12-05
Four pseudorandom number generators were compared with a physical, quantum-based random number generator using the NIST suite of statistical tests, which only the quantum-based random number generator could successfully pass. We then measured the effect of the five random number generators on various calculated properties in different Markov-chain Monte Carlo simulations. Two types of systems were tested: conformational sampling of a small molecule in aqueous solution and liquid methanol under constant temperature and pressure. The results show that poor quality pseudorandom number generators produce results that deviate significantly from those obtained with the quantum-based random number generator, particularly in the case of the small molecule in aqueous solution setup. In contrast, the widely used Mersenne Twister pseudorandom generator and a 64-bit Linear Congruential Generator with a scrambler produce results that are statistically indistinguishable from those obtained with the quantum-based random number generator. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
D.Ivaneyko
2005-01-01
Full Text Available We apply numerical simulations to study of the criticality of the 3D Ising model with random site quenched dilution. The emphasis is given to the issues not being discussed in detail before. In particular, we attempt a comparison of different Monte Carlo techniques, discussing regions of their applicability and advantages/disadvantages depending on the aim of a particular simulation set. Moreover, besides evaluation of the critical indices we estimate the universal ratio Γ+/Γ- for the magnetic susceptibility critical amplitudes. Our estimate Γ+/Γ- = 1.67 ± 0.15 is in a good agreement with the recent MC analysis of the random-bond Ising model giving further support that both random-site and random-bond dilutions lead to the same universality class.
Advanced Multilevel Monte Carlo Methods
Jasra, Ajay; Law, Kody; Suciu, Carina
2017-01-01
This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.
Advanced Multilevel Monte Carlo Methods
Jasra, Ajay
2017-04-24
This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.
Monte Carlo simulation for IRRMA
International Nuclear Information System (INIS)
Gardner, R.P.; Liu Lianyan
2000-01-01
Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications - IRRMA. The reasons for this include: (1) the increased cost and inadequacy of experimentation for design and interpretation purposes; (2) the availability of low cost, large memory, and fast personal computers; and (3) the general availability of general purpose Monte Carlo codes that are increasingly user-friendly, efficient, and accurate. This paper discusses the history and present status of Monte Carlo simulation for IRRMA including the general purpose (GP) and specific purpose (SP) Monte Carlo codes and future needs - primarily from the experience of the authors
Lee, Kyoung O; Holmes, Thomas W; Calderon, Adan F; Gardner, Robin P
2012-05-01
Using a Monte Carlo (MC) simulation, random walks were used for pebble tracking in a two-dimensional geometry in the presence of a biased gravity field. We investigated the effect of viscosity damping in the presence of random Gaussian fluctuations. The particle tracks were generated by Molecular Dynamics (MD) simulation for a Pebble Bed Reactor. The MD simulations were conducted in the interaction of noncohesive Hertz-Mindlin theory where the random walk MC simulation has a correlation with the MD simulation. This treatment can easily be extended to include the generation of transient gamma-ray spectra from a single pebble that contains a radioactive tracer. Then the inverse analysis thereof could be made to determine the uncertainty of the realistic measurement of transient positions of that pebble by any given radiation detection system designed for that purpose. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
Some problems on Monte Carlo method development
International Nuclear Information System (INIS)
Pei Lucheng
1992-01-01
This is a short paper on some problems of Monte Carlo method development. The content consists of deep-penetration problems, unbounded estimate problems, limitation of Mdtropolis' method, dependency problem in Metropolis' method, random error interference problems and random equations, intellectualisation and vectorization problems of general software
Monte Carlo simulation of the microcanonical ensemble
International Nuclear Information System (INIS)
Creutz, M.
1984-01-01
We consider simulating statistical systems with a random walk on a constant energy surface. This combines features of deterministic molecular dynamics techniques and conventional Monte Carlo simulations. For discrete systems the method can be programmed to run an order of magnitude faster than other approaches. It does not require high quality random numbers and may also be useful for nonequilibrium studies. 10 references
Adjoint electron Monte Carlo calculations
International Nuclear Information System (INIS)
Jordan, T.M.
1986-01-01
Adjoint Monte Carlo is the most efficient method for accurate analysis of space systems exposed to natural and artificially enhanced electron environments. Recent adjoint calculations for isotropic electron environments include: comparative data for experimental measurements on electronics boxes; benchmark problem solutions for comparing total dose prediction methodologies; preliminary assessment of sectoring methods used during space system design; and total dose predictions on an electronics package. Adjoint Monte Carlo, forward Monte Carlo, and experiment are in excellent agreement for electron sources that simulate space environments. For electron space environments, adjoint Monte Carlo is clearly superior to forward Monte Carlo, requiring one to two orders of magnitude less computer time for relatively simple geometries. The solid-angle sectoring approximations used for routine design calculations can err by more than a factor of 2 on dose in simple shield geometries. For critical space systems exposed to severe electron environments, these potential sectoring errors demand the establishment of large design margins and/or verification of shield design by adjoint Monte Carlo/experiment
Monte Carlo applications to radiation shielding problems
International Nuclear Information System (INIS)
Subbaiah, K.V.
2009-01-01
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling of physical and mathematical systems to compute their results. However, basic concepts of MC are both simple and straightforward and can be learned by using a personal computer. Uses of Monte Carlo methods require large amounts of random numbers, and it was their use that spurred the development of pseudorandom number generators, which were far quicker to use than the tables of random numbers which had been previously used for statistical sampling. In Monte Carlo simulation of radiation transport, the history (track) of a particle is viewed as a random sequence of free flights that end with an interaction event where the particle changes its direction of movement, loses energy and, occasionally, produces secondary particles. The Monte Carlo simulation of a given experimental arrangement (e.g., an electron beam, coming from an accelerator and impinging on a water phantom) consists of the numerical generation of random histories. To simulate these histories we need an interaction model, i.e., a set of differential cross sections (DCS) for the relevant interaction mechanisms. The DCSs determine the probability distribution functions (pdf) of the random variables that characterize a track; 1) free path between successive interaction events, 2) type of interaction taking place and 3) energy loss and angular deflection in a particular event (and initial state of emitted secondary particles, if any). Once these pdfs are known, random histories can be generated by using appropriate sampling methods. If the number of generated histories is large enough, quantitative information on the transport process may be obtained by simply averaging over the simulated histories. The Monte Carlo method yields the same information as the solution of the Boltzmann transport equation, with the same interaction model, but is easier to implement. In particular, the simulation of radiation
Reflections on early Monte Carlo calculations
International Nuclear Information System (INIS)
Spanier, J.
1992-01-01
Monte Carlo methods for solving various particle transport problems developed in parallel with the evolution of increasingly sophisticated computer programs implementing diffusion theory and low-order moments calculations. In these early years, Monte Carlo calculations and high-order approximations to the transport equation were seen as too expensive to use routinely for nuclear design but served as invaluable aids and supplements to design with less expensive tools. The earliest Monte Carlo programs were quite literal; i.e., neutron and other particle random walk histories were simulated by sampling from the probability laws inherent in the physical system without distoration. Use of such analogue sampling schemes resulted in a good deal of time being spent in examining the possibility of lowering the statistical uncertainties in the sample estimates by replacing simple, and intuitively obvious, random variables by those with identical means but lower variances
Monte Carlo simulation of Markov unreliability models
International Nuclear Information System (INIS)
Lewis, E.E.; Boehm, F.
1984-01-01
A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-01-01
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros
2016-08-29
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
Strategije drevesnega preiskovanja Monte Carlo
VODOPIVEC, TOM
2018-01-01
Po preboju pri igri go so metode drevesnega preiskovanja Monte Carlo (ang. Monte Carlo tree search – MCTS) sprožile bliskovit napredek agentov za igranje iger: raziskovalna skupnost je od takrat razvila veliko variant in izboljšav algoritma MCTS ter s tem zagotovila napredek umetne inteligence ne samo pri igrah, ampak tudi v številnih drugih domenah. Čeprav metode MCTS združujejo splošnost naključnega vzorčenja z natančnostjo drevesnega preiskovanja, imajo lahko v praksi težave s počasno konv...
Current and future applications of Monte Carlo
International Nuclear Information System (INIS)
Zaidi, H.
2003-01-01
Full text: The use of radionuclides in medicine has a long history and encompasses a large area of applications including diagnosis and radiation treatment of cancer patients using either external or radionuclide radiotherapy. The 'Monte Carlo method'describes a very broad area of science, in which many processes, physical systems, and phenomena are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is as similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions (pdfs). As the number of individual events (called 'histories') is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. The use of the Monte Carlo method to simulate radiation transport has become the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides as well as the assessment of image quality and quantitative accuracy of radionuclide imaging. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the nuclear medicine community at large. Many of these questions will be answered when Monte Carlo techniques are implemented and used for more routine calculations and for in-depth investigations. In this paper, the conceptual role of the Monte Carlo method is briefly introduced and followed by a survey of its different applications in diagnostic and therapeutic
Is Monte Carlo embarrassingly parallel?
Energy Technology Data Exchange (ETDEWEB)
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
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)
Is Monte Carlo embarrassingly parallel?
International Nuclear Information System (INIS)
Hoogenboom, J. E.
2012-01-01
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)
Exact Monte Carlo for molecules
International Nuclear Information System (INIS)
Lester, W.A. Jr.; Reynolds, P.J.
1985-03-01
A brief summary of the fixed-node quantum Monte Carlo method is presented. Results obtained for binding energies, the classical barrier height for H + H 2 , and the singlet-triplet splitting in methylene are presented and discussed. 17 refs
Monte Carlo - Advances and Challenges
International Nuclear Information System (INIS)
Brown, Forrest B.; Mosteller, Russell D.; Martin, William R.
2008-01-01
Abstract only, full text follows: With ever-faster computers and mature Monte Carlo production codes, there has been tremendous growth in the application of Monte Carlo methods to the analysis of reactor physics and reactor systems. In the past, Monte Carlo methods were used primarily for calculating k eff of a critical system. More recently, Monte Carlo methods have been increasingly used for determining reactor power distributions and many design parameters, such as β eff , l eff , τ, reactivity coefficients, Doppler defect, dominance ratio, etc. These advanced applications of Monte Carlo methods are now becoming common, not just feasible, but bring new challenges to both developers and users: Convergence of 3D power distributions must be assured; confidence interval bias must be eliminated; iterated fission probabilities are required, rather than single-generation probabilities; temperature effects including Doppler and feedback must be represented; isotopic depletion and fission product buildup must be modeled. This workshop focuses on recent advances in Monte Carlo methods and their application to reactor physics problems, and on the resulting challenges faced by code developers and users. The workshop is partly tutorial, partly a review of the current state-of-the-art, and partly a discussion of future work that is needed. It should benefit both novice and expert Monte Carlo developers and users. In each of the topic areas, we provide an overview of needs, perspective on past and current methods, a review of recent work, and discussion of further research and capabilities that are required. Electronic copies of all workshop presentations and material will be available. The workshop is structured as 2 morning and 2 afternoon segments: - Criticality Calculations I - convergence diagnostics, acceleration methods, confidence intervals, and the iterated fission probability, - Criticality Calculations II - reactor kinetics parameters, dominance ratio, temperature
Monte Carlo techniques for analyzing deep-penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1986-01-01
Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications
(U) Introduction to Monte Carlo Methods
Energy Technology Data Exchange (ETDEWEB)
Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-20
Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.
Crop canopy BRDF simulation and analysis using Monte Carlo method
Huang, J.; Wu, B.; Tian, Y.; Zeng, Y.
2006-01-01
This author designs the random process between photons and crop canopy. A Monte Carlo model has been developed to simulate the Bi-directional Reflectance Distribution Function (BRDF) of crop canopy. Comparing Monte Carlo model to MCRM model, this paper analyzes the variations of different LAD and
Biases in Monte Carlo eigenvalue calculations
Energy Technology Data Exchange (ETDEWEB)
Gelbard, E.M.
1992-12-01
The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ``fixed-source`` case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (``replicated``) over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.
Biases in Monte Carlo eigenvalue calculations
Energy Technology Data Exchange (ETDEWEB)
Gelbard, E.M.
1992-01-01
The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.
Biases in Monte Carlo eigenvalue calculations
International Nuclear Information System (INIS)
Gelbard, E.M.
1992-01-01
The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ''fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (''replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here
Isotopic depletion with Monte Carlo
International Nuclear Information System (INIS)
Martin, W.R.; Rathkopf, J.A.
1996-06-01
This work considers a method to deplete isotopes during a time- dependent Monte Carlo simulation of an evolving system. The method is based on explicitly combining a conventional estimator for the scalar flux with the analytical solutions to the isotopic depletion equations. There are no auxiliary calculations; the method is an integral part of the Monte Carlo calculation. The method eliminates negative densities and reduces the variance in the estimates for the isotope densities, compared to existing methods. Moreover, existing methods are shown to be special cases of the general method described in this work, as they can be derived by combining a high variance estimator for the scalar flux with a low-order approximation to the analytical solution to the depletion equation
Zimmerman, George B.
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
International Nuclear Information System (INIS)
Zimmerman, G.B.
1997-01-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics
International Nuclear Information System (INIS)
Zimmerman, George B.
1997-01-01
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.; Dean, D.J.; Langanke, K.
1997-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) 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, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.
1996-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs
Parallel Monte Carlo reactor neutronics
International Nuclear Information System (INIS)
Blomquist, R.N.; Brown, F.B.
1994-01-01
The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved
Adaptive Multilevel Monte Carlo Simulation
Hoel, H
2011-08-23
This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).
Geometrical splitting in Monte Carlo
International Nuclear Information System (INIS)
Dubi, A.; Elperin, T.; Dudziak, D.J.
1982-01-01
A statistical model is presented by which a direct statistical approach yielded an analytic expression for the second moment, the variance ratio, and the benefit function in a model of an n surface-splitting Monte Carlo game. In addition to the insight into the dependence of the second moment on the splitting parameters the main importance of the expressions developed lies in their potential to become a basis for in-code optimization of splitting through a general algorithm. Refs
Extending canonical Monte Carlo methods
International Nuclear Information System (INIS)
Velazquez, L; Curilef, S
2010-01-01
In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C α with α≈0.2 for the particular case of the 2D ten-state Potts model
International Nuclear Information System (INIS)
Kennedy, D.C. II.
1987-01-01
This is an update on the progress of the BREMMUS Monte Carlo simulator, particularly in its current incarnation, BREM5. The present report is intended only as a follow-up to the Mark II/Granlibakken proceedings, and those proceedings should be consulted for a complete description of the capabilities and goals of the BREMMUS program. The new BREM5 program improves on the previous version of BREMMUS, BREM2, in a number of important ways. In BREM2, the internal loop (oblique) corrections were not treated in consistent fashion, a deficiency that led to renormalization scheme-dependence; i.e., physical results, such as cross sections, were dependent on the method used to eliminate infinities from the theory. Of course, this problem cannot be tolerated in a Monte Carlo designed for experimental use. BREM5 incorporates a new way of treating the oblique corrections, as explained in the Granlibakken proceedings, that guarantees renormalization scheme-independence and dramatically simplifies the organization and calculation of radiative corrections. This technique is to be presented in full detail in a forthcoming paper. BREM5 is, at this point, the only Monte Carlo to contain the entire set of one-loop corrections to electroweak four-fermion processes and renormalization scheme-independence. 3 figures
Statistical implications in Monte Carlo depletions - 051
International Nuclear Information System (INIS)
Zhiwen, Xu; Rhodes, J.; Smith, K.
2010-01-01
As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)
Monte Carlo simulation of experiments
International Nuclear Information System (INIS)
Opat, G.I.
1977-07-01
An outline of the technique of computer simulation of particle physics experiments by the Monte Carlo method is presented. Useful special purpose subprograms are listed and described. At each stage the discussion is made concrete by direct reference to the programs SIMUL8 and its variant MONTE-PION, written to assist in the analysis of the radiative decay experiments μ + → e + ν sub(e) antiνγ and π + → e + ν sub(e)γ, respectively. These experiments were based on the use of two large sodium iodide crystals, TINA and MINA, as e and γ detectors. Instructions for the use of SIMUL8 and MONTE-PION are given. (author)
Introduction to the Monte Carlo methods
International Nuclear Information System (INIS)
Uzhinskij, V.V.
1993-01-01
Codes illustrating the use of Monte Carlo methods in high energy physics such as the inverse transformation method, the ejection method, the particle propagation through the nucleus, the particle interaction with the nucleus, etc. are presented. A set of useful algorithms of random number generators is given (the binomial distribution, the Poisson distribution, β-distribution, γ-distribution and normal distribution). 5 figs., 1 tab
Energy Technology Data Exchange (ETDEWEB)
Lee, Jae Yong; Kim, Song Hyun; Shin, Chang Ho; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of)
2014-05-15
In this study, as a preliminary study to develop an implicit method having high accuracy, the distribution characteristics of spherical particles were evaluated by using explicit modeling techniques in various volume packing fractions. This study was performed to evaluate implicitly simulated distribution of randomly packed spheres in a medium. At first, an explicit modeling method to simulate random packed spheres in a hexahedron medium was proposed. The distributed characteristics of l{sub p} and r{sub p}, which are used in the particle position sampling, was estimated. It is analyzed that the use of the direct exponential distribution, which is generally used in the implicit modeling, can cause the distribution bias of the spheres. It is expected that the findings in this study can be utilized for improving the accuracy in using the implicit method. Spherical particles, which are randomly distributed in medium, are utilized for the radiation shields, fusion reactor blanket, fuels of VHTR reactors. Due to the difficulty on the simulation of the stochastic distribution, Monte Carlo (MC) method has been mainly considered as the tool for the analysis of the particle transport. For the MC modeling of the spherical particles, three methods are known; repeated structure, explicit modeling, and implicit modeling. Implicit method (called as the track length sampling method) is a modeling method that is the sampling based modeling technique of each spherical geometry (or track length of the sphere) during the MC simulation. Implicit modeling method has advantages in high computational efficiency and user convenience. However, it is noted that the implicit method has lower modeling accuracy in various finite mediums.
Liu, Baoshun; Li, Ziqiang; Zhao, Xiujian
2015-02-21
In this research, Monte-Carlo Continuity Random Walking (MC-RW) model was used to study the relation between electron transport and photocatalysis of nano-crystalline (nc) clusters. The effects of defect energy disorder, spatial disorder of material structure, electron density, and interfacial transfer/recombination on the electron transport and the photocatalysis were studied. Photocatalytic activity is defined as 1/τ from a statistical viewpoint with τ being the electron average lifetime. Based on the MC-RW simulation, a clear physical and chemical "picture" was given for the photocatalytic kinetic analysis of nc-clusters. It is shown that the increase of defect energy disorder and material spatial structural disorder, such as the decrease of defect trap number, the increase of crystallinity, the increase of particle size, and the increase of inter-particle connection, can enhance photocatalytic activity through increasing electron transport ability. The increase of electron density increases the electron Fermi level, which decreases the activation energy for electron de-trapping from traps to extending states, and correspondingly increases electron transport ability and photocatalytic activity. Reducing recombination of electrons and holes can increase electron transport through the increase of electron density and then increases the photocatalytic activity. In addition to the electron transport, the increase of probability for electrons to undergo photocatalysis can increase photocatalytic activity through the increase of the electron interfacial transfer speed.
International Nuclear Information System (INIS)
Xiong, Chuan; Shi, Jiancheng
2014-01-01
To date, the light scattering models of snow consider very little about the real snow microstructures. The ideal spherical or other single shaped particle assumptions in previous snow light scattering models can cause error in light scattering modeling of snow and further cause errors in remote sensing inversion algorithms. This paper tries to build up a snow polarized reflectance model based on bicontinuous medium, with which the real snow microstructure is considered. The accurate specific surface area of bicontinuous medium can be analytically derived. The polarized Monte Carlo ray tracing technique is applied to the computer generated bicontinuous medium. With proper algorithms, the snow surface albedo, bidirectional reflectance distribution function (BRDF) and polarized BRDF can be simulated. The validation of model predicted spectral albedo and bidirectional reflectance factor (BRF) using experiment data shows good results. The relationship between snow surface albedo and snow specific surface area (SSA) were predicted, and this relationship can be used for future improvement of snow specific surface area (SSA) inversion algorithms. The model predicted polarized reflectance is validated and proved accurate, which can be further applied in polarized remote sensing. -- Highlights: • Bicontinuous random medium were used for real snow microstructure modeling. • Photon tracing technique with polarization status tracking ability was applied. • SSA–albedo relationship of snow is close to that of sphere based medium. • Validation of albedo and BRDF showed good results. • Validation of polarized reflectance showed good agreement with experiment data
Random number generators in support of Monte Carlo problems in physics
International Nuclear Information System (INIS)
Dyadkin, I.G.
1993-01-01
The ability to support a modern users' expectations of random number generators to solve problems in physics is analyzed. The capabilities of the newest concepts and the old pseudo-random algorithms are compared. The author is in favor of multiplicative generators. Due to the 64-bit arithmetic of a modern PC, multiplicative generators have a sufficient number of periods (up to 2 62 ) and are quicker to generate and to govern independent sequences for parallel processing. In addition they are able to replicate sub-sequences (without storing their seeds) for each standard trial in any code and to simulate spatial and planar directions and EXP(-x) distributions often needed as ''bricks'' for simulating events in physics. Hundreds of multipliers for multiplicative generators have been tabulated and tested, and the required speeds have been obtained. (author)
Multilevel Monte Carlo Approaches for Numerical Homogenization
Efendiev, Yalchin R.
2015-10-01
In this article, we study the application of multilevel Monte Carlo (MLMC) approaches to numerical random homogenization. Our objective is to compute the expectation of some functionals of the homogenized coefficients, or of the homogenized solutions. This is accomplished within MLMC by considering different sizes of representative volumes (RVEs). Many inexpensive computations with the smallest RVE size are combined with fewer expensive computations performed on larger RVEs. Likewise, when it comes to homogenized solutions, different levels of coarse-grid meshes are used to solve the homogenized equation. We show that, by carefully selecting the number of realizations at each level, we can achieve a speed-up in the computations in comparison to a standard Monte Carlo method. Numerical results are presented for both one-dimensional and two-dimensional test-cases that illustrate the efficiency of the approach.
Monte Carlo Particle Lists: MCPL
DEFF Research Database (Denmark)
Kittelmann, Thomas; Klinkby, Esben Bryndt; Bergbäck Knudsen, Erik
2017-01-01
A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular...... simulation packages. Program summary: Program Title: MCPL. Program Files doi: http://dx.doi.org/10.17632/cby92vsv5g.1 Licensing provisions: CC0 for core MCPL, see LICENSE file for details. Programming language: C and C++ External routines/libraries: Geant4, MCNP, McStas, McXtrace Nature of problem: Saving...
Statistics of Monte Carlo methods used in radiation transport calculation
International Nuclear Information System (INIS)
Datta, D.
2009-01-01
Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport
Sampling from a polytope and hard-disk Monte Carlo
International Nuclear Information System (INIS)
Kapfer, Sebastian C; Krauth, Werner
2013-01-01
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
Monte Carlo techniques in radiation therapy
Verhaegen, Frank
2013-01-01
Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...
Mean field simulation for Monte Carlo integration
Del Moral, Pierre
2013-01-01
In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko
Monte Carlo surface flux tallies
International Nuclear Information System (INIS)
Favorite, Jeffrey A.
2010-01-01
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.
Monte Carlo simulations of neutron scattering instruments
International Nuclear Information System (INIS)
Aestrand, Per-Olof; Copenhagen Univ.; Lefmann, K.; Nielsen, K.
2001-01-01
A Monte Carlo simulation is an important computational tool used in many areas of science and engineering. The use of Monte Carlo techniques for simulating neutron scattering instruments is discussed. The basic ideas, techniques and approximations are presented. Since the construction of a neutron scattering instrument is very expensive, Monte Carlo software used for design of instruments have to be validated and tested extensively. The McStas software was designed with these aspects in mind and some of the basic principles of the McStas software will be discussed. Finally, some future prospects are discussed for using Monte Carlo simulations in optimizing neutron scattering experiments. (R.P.)
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Liang, Faming
2009-01-01
The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration
Quantum Monte Carlo for vibrating molecules
International Nuclear Information System (INIS)
Brown, W.R.; Lawrence Berkeley National Lab., CA
1996-08-01
Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H 2 O and C 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 2 O and C 3 . In order to construct accurate trial wavefunctions for C 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 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 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
International Nuclear Information System (INIS)
Ohta, Shigemi
1996-01-01
The Self-Test Monte Carlo (STMC) method resolves the main problems in using algebraic pseudo-random numbers for Monte Carlo (MC) calculations: that they can interfere with MC algorithms and lead to erroneous results, and that such an error often cannot be detected without known exact solution. STMC is based on good randomness of about 10 10 bits available from physical noise or transcendental numbers like π = 3.14---. Various bit modifiers are available to get more bits for applications that demands more than 10 10 random bits such as lattice quantum chromodynamics (QCD). These modifiers are designed so that a) each of them gives a bit sequence comparable in randomness as the original if used separately from each other, and b) their mutual interference when used jointly in a single MC calculation is adjustable. Intermediate data of the MC calculation itself are used to quantitatively test and adjust the mutual interference of the modifiers in respect of the MC algorithm. STMC is free of systematic error and gives reliable statistical error. Also it can be easily implemented on vector and parallel supercomputers. (author)
Cooper, M A
2000-01-01
We present various approximations for the angular distribution of particles emerging from an optically thick, purely isotropically scattering region into a vacuum. Our motivation is to use such a distribution for the Fleck-Canfield random walk method [1] for implicit Monte Carlo (IMC) [2] radiation transport problems. We demonstrate that the cosine distribution recommended in the original random walk paper [1] is a poor approximation to the angular distribution predicted by transport theory. Then we examine other approximations that more closely match the transport angular distribution.
International Nuclear Information System (INIS)
Moore, J.G.
1974-01-01
The Monte Carlo code MONK is a general program written to provide a high degree of flexibility to the user. MONK is distinguished by its detailed representation of nuclear data in point form i.e., the cross-section is tabulated at specific energies instead of the more usual group representation. The nuclear data are unadjusted in the point form but recently the code has been modified to accept adjusted group data as used in fast and thermal reactor applications. The various geometrical handling capabilities and importance sampling techniques are described. In addition to the nuclear data aspects, the following features are also described; geometrical handling routines, tracking cycles, neutron source and output facilities. 12 references. (U.S.)
Monte Carlo lattice program KIM
International Nuclear Information System (INIS)
Cupini, E.; De Matteis, A.; Simonini, R.
1980-01-01
The Monte Carlo program KIM solves the steady-state linear neutron transport equation for a fixed-source problem or, by successive fixed-source runs, for the eigenvalue problem, in a two-dimensional thermal reactor lattice. Fluxes and reaction rates are the main quantities computed by the program, from which power distribution and few-group averaged cross sections are derived. The simulation ranges from 10 MeV to zero and includes anisotropic and inelastic scattering in the fast energy region, the epithermal Doppler broadening of the resonances of some nuclides, and the thermalization phenomenon by taking into account the thermal velocity distribution of some molecules. Besides the well known combinatorial geometry, the program allows complex configurations to be represented by a discrete set of points, an approach greatly improving calculation speed
Advanced Computational Methods for Monte Carlo Calculations
Energy Technology Data Exchange (ETDEWEB)
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-12
This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.
Nested Sampling with Constrained Hamiltonian Monte Carlo
Betancourt, M. J.
2010-01-01
Nested sampling is a powerful approach to Bayesian inference ultimately limited by the computationally demanding task of sampling from a heavily constrained probability distribution. An effective algorithm in its own right, Hamiltonian Monte Carlo is readily adapted to efficiently sample from any smooth, constrained distribution. Utilizing this constrained Hamiltonian Monte Carlo, I introduce a general implementation of the nested sampling algorithm.
Monte Carlo study of the multiquark systems
International Nuclear Information System (INIS)
Kerbikov, B.O.; Polikarpov, M.I.; Zamolodchikov, A.B.
1986-01-01
Random walks have been used to calculate the energies of the ground states in systems of N=3, 6, 9, 12 quarks. Multiquark states with N>3 are unstable with respect to the spontaneous dissociation into color singlet hadrons. The modified Green's function Monte Carlo algorithm which proved to be more simple and much accurate than the conventional few body methods have been employed. In contrast to other techniques, the same equations are used for any number of particles, while the computer time increases only linearly V, S the number of particles
Diffusion quantum Monte Carlo for molecules
International Nuclear Information System (INIS)
Lester, W.A. Jr.
1986-07-01
A quantum mechanical Monte Carlo method has been used for the treatment of molecular problems. The imaginary-time Schroedinger equation written with a shift in zero energy [E/sub T/ - V(R)] can be interpreted as a generalized diffusion equation with a position-dependent rate or branching term. Since diffusion is the continuum limit of a random walk, one may simulate the Schroedinger equation with a function psi (note, not psi 2 ) as a density of ''walks.'' The walks undergo an exponential birth and death as given by the rate term. 16 refs., 2 tabs
Monte Carlo Treatment Planning for Advanced Radiotherapy
DEFF Research Database (Denmark)
Cronholm, Rickard
This Ph.d. project describes the development of a workflow for Monte Carlo Treatment Planning for clinical radiotherapy plans. The workflow may be utilized to perform an independent dose verification of treatment plans. Modern radiotherapy treatment delivery is often conducted by dynamically...... modulating the intensity of the field during the irradiation. The workflow described has the potential to fully model the dynamic delivery, including gantry rotation during irradiation, of modern radiotherapy. Three corner stones of Monte Carlo Treatment Planning are identified: Building, commissioning...... and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...
The MC21 Monte Carlo Transport Code
International Nuclear Information System (INIS)
Sutton TM; Donovan TJ; Trumbull TH; Dobreff PS; Caro E; Griesheimer DP; Tyburski LJ; Carpenter DC; Joo H
2007-01-01
MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities
Monte Carlo method for solving a parabolic problem
Directory of Open Access Journals (Sweden)
Tian Yi
2016-01-01
Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2016-01-06
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef; Nobile, Fabio; Tempone, Raul
2016-01-01
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef; Nobile, Fabio; Tempone, Raul
2015-01-01
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2015-01-07
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.
DEFF Research Database (Denmark)
Cherchi, Elisabetta; Guevara, Cristian Angelo
2012-01-01
of parameters increases is usually known as the “curse of dimensionality” in the simulation methods. We investigate this problem in the case of the random coefficients Logit model. We compare the traditional Maximum Simulated Likelihood (MSL) method with two alternative estimation methods: the Expectation......–Maximization (EM) and the Laplace Approximation (HH) methods that do not require simulation. We use Monte Carlo experimentation to investigate systematically the performance of the methods under different circumstances, including different numbers of variables, sample sizes and structures of the variance...
International Nuclear Information System (INIS)
Mazzone, A.M.
1987-01-01
In order to study channeling effects and implants of heavy ions with energy of few MeV in silicon, ion distributions are calculated with a Monte Carlo method for axial [(001) axis], planar, and nominally random directions for As + and P + ions implanted into silicon with energies in the range 100 keV to 2 MeV. The calculation indicates an appreciable channeling at the higher energy only for the (001) axis and the (110) planes. For heavy ions with energy in the MeV range the subsidence of channeling into major channels and the disappearance of minor channels are shown
Monte Carlo techniques for analyzing deep penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1985-01-01
A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications
Monte Carlo techniques for analyzing deep penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.; Gonnord, J.; Hendricks, J.S.
1985-01-01
A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications. 29 refs
Importance iteration in MORSE Monte Carlo calculations
International Nuclear Information System (INIS)
Kloosterman, J.L.; Hoogenboom, J.E.
1994-01-01
An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example that shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation
Monte Carlo approaches to light nuclei
International Nuclear Information System (INIS)
Carlson, J.
1990-01-01
Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of 16 O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs
Monte Carlo approaches to light nuclei
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.
Importance iteration in MORSE Monte Carlo calculations
International Nuclear Information System (INIS)
Kloosterman, J.L.; Hoogenboom, J.E.
1994-02-01
An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example, which shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation. (orig.)
Monte carlo simulation for soot dynamics
Zhou, Kun
2012-01-01
A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.
Monte Carlo Codes Invited Session
International Nuclear Information System (INIS)
Trama, J.C.; Malvagi, F.; Brown, F.
2013-01-01
This document lists 22 Monte Carlo codes used in radiation transport applications throughout the world. For each code the names of the organization and country and/or place are given. We have the following computer codes. 1) ARCHER, USA, RPI; 2) COG11, USA, LLNL; 3) DIANE, France, CEA/DAM Bruyeres; 4) FLUKA, Italy and CERN, INFN and CERN; 5) GEANT4, International GEANT4 collaboration; 6) KENO and MONACO (SCALE), USA, ORNL; 7) MC21, USA, KAPL and Bettis; 8) MCATK, USA, LANL; 9) MCCARD, South Korea, Seoul National University; 10) MCNP6, USA, LANL; 11) MCU, Russia, Kurchatov Institute; 12) MONK and MCBEND, United Kingdom, AMEC; 13) MORET5, France, IRSN Fontenay-aux-Roses; 14) MVP2, Japan, JAEA; 15) OPENMC, USA, MIT; 16) PENELOPE, Spain, Barcelona University; 17) PHITS, Japan, JAEA; 18) PRIZMA, Russia, VNIITF; 19) RMC, China, Tsinghua University; 20) SERPENT, Finland, VTT; 21) SUPERMONTECARLO, China, CAS INEST FDS Team Hefei; and 22) TRIPOLI-4, France, CEA Saclay
Advanced computers and Monte Carlo
International Nuclear Information System (INIS)
Jordan, T.L.
1979-01-01
High-performance parallelism that is currently available is synchronous in nature. It is manifested in such architectures as Burroughs ILLIAC-IV, CDC STAR-100, TI ASC, CRI CRAY-1, ICL DAP, and many special-purpose array processors designed for signal processing. This form of parallelism has apparently not been of significant value to many important Monte Carlo calculations. Nevertheless, there is much asynchronous parallelism in many of these calculations. A model of a production code that requires up to 20 hours per problem on a CDC 7600 is studied for suitability on some asynchronous architectures that are on the drawing board. The code is described and some of its properties and resource requirements ae identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resources of some asynchronous multiprocessor architectures. Arguments are made for programer aids and special syntax to identify and support important asynchronous parallelism. 2 figures, 5 tables
Adaptive Markov Chain Monte Carlo
Jadoon, Khan
2016-08-08
A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In the MCMC simulations, posterior distribution was computed using Bayes rule. The electromagnetic forward model based on the full solution of Maxwell\\'s equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD mini-Explorer. The model parameters and uncertainty for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness are not well estimated as compared to layers electrical conductivity because layer thicknesses in the model exhibits a low sensitivity to the EMI measurements, and is hence difficult to resolve. Application of the proposed MCMC based inversion to the field measurements in a drip irrigation system demonstrate that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provide useful insight about parameter uncertainty for the assessment of the model outputs.
Monte Carlo Techniques for Nuclear Systems - Theory Lectures
International Nuclear Information System (INIS)
Brown, Forrest B.; Univ. of New Mexico, Albuquerque, NM
2016-01-01
These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations
Monte Carlo Techniques for Nuclear Systems - Theory Lectures
Energy Technology Data Exchange (ETDEWEB)
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.
2016-11-29
These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Monte Carlo simulation of grain growth
Directory of Open Access Journals (Sweden)
Paulo Blikstein
1999-07-01
Full Text Available Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical behavior of the atoms is properly reproduced; microstructural evolution depends only on the real topology of the grains and not on any kind of geometric simplification. Computer simulation has the advantage of allowing the user to visualize graphically the procedures, even dynamically and in three dimensions. Single-phase alloy grain growth simulation was carried out by calculating the free energy of each atom in the lattice (with its present crystallographic orientation and comparing this value to another one calculated with a different random orientation. When the resulting free energy is lower or equal to the initial value, the new orientation replaces the former. The measure of time is the Monte Carlo Step (MCS, which involves a series of trials throughout the lattice. A very close relationship between experimental and theoretical values for the grain growth exponent (n was observed.
Quantum Monte Carlo approaches for correlated systems
Becca, Federico
2017-01-01
Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...
Monte Carlo simulations for plasma physics
International Nuclear Information System (INIS)
Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X.
2000-07-01
Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)
Frontiers of quantum Monte Carlo workshop: preface
International Nuclear Information System (INIS)
Gubernatis, J.E.
1985-01-01
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
Monte Carlo code development in Los Alamos
International Nuclear Information System (INIS)
Carter, L.L.; Cashwell, E.D.; Everett, C.J.; Forest, C.A.; Schrandt, R.G.; Taylor, W.M.; Thompson, W.L.; Turner, G.D.
1974-01-01
The present status of Monte Carlo code development at Los Alamos Scientific Laboratory is discussed. A brief summary is given of several of the most important neutron, photon, and electron transport codes. 17 references. (U.S.)
Experience with the Monte Carlo Method
Energy Technology Data Exchange (ETDEWEB)
Hussein, E M.A. [Department of Mechanical Engineering University of New Brunswick, Fredericton, N.B., (Canada)
2007-06-15
Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed.
Experience with the Monte Carlo Method
International Nuclear Information System (INIS)
Hussein, E.M.A.
2007-01-01
Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed
Monte Carlo Transport for Electron Thermal Transport
Chenhall, Jeffrey; Cao, Duc; Moses, Gregory
2015-11-01
The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.
A continuation multilevel Monte Carlo algorithm
Collier, Nathan; Haji Ali, Abdul Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul
2014-01-01
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error
Simulation and the Monte Carlo method
Rubinstein, Reuven Y
2016-01-01
Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...
Hybrid Monte Carlo methods in computational finance
Leitao Rodriguez, A.
2017-01-01
Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the
Bartalini, P.; Kryukov, A.; Selyuzhenkov, Ilya V.; Sherstnev, A.; Vologdin, A.
2004-01-01
We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB and discuss future plans to develop this Data Base further within the CERN LCG framework.
Multilevel Monte Carlo in Approximate Bayesian Computation
Jasra, Ajay
2017-02-13
In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.
Monte Carlo method applied to medical physics
International Nuclear Information System (INIS)
Oliveira, C.; Goncalves, I.F.; Chaves, A.; Lopes, M.C.; Teixeira, N.; Matos, B.; Goncalves, I.C.; Ramalho, A.; Salgado, J.
2000-01-01
The main application of the Monte Carlo method to medical physics is dose calculation. This paper shows some results of two dose calculation studies and two other different applications: optimisation of neutron field for Boron Neutron Capture Therapy and optimization of a filter for a beam tube for several purposes. The time necessary for Monte Carlo calculations - the highest boundary for its intensive utilisation - is being over-passed with faster and cheaper computers. (author)
International Nuclear Information System (INIS)
Wilson, Brandon M; Smith, Barton L
2013-01-01
Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)
Monte Carlo Simulations of Phosphate Polyhedron Connectivity in Glasses
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ALAM,TODD M.
1999-12-21
Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.
Markov Chain Monte Carlo from Lagrangian Dynamics.
Lan, Shiwei; Stathopoulos, Vasileios; Shahbaba, Babak; Girolami, Mark
2015-04-01
Hamiltonian Monte Carlo (HMC) improves the computational e ciency of the Metropolis-Hastings algorithm by reducing its random walk behavior. Riemannian HMC (RHMC) further improves the performance of HMC by exploiting the geometric properties of the parameter space. However, the geometric integrator used for RHMC involves implicit equations that require fixed-point iterations. In some cases, the computational overhead for solving implicit equations undermines RHMC's benefits. In an attempt to circumvent this problem, we propose an explicit integrator that replaces the momentum variable in RHMC by velocity. We show that the resulting transformation is equivalent to transforming Riemannian Hamiltonian dynamics to Lagrangian dynamics. Experimental results suggests that our method improves RHMC's overall computational e ciency in the cases considered. All computer programs and data sets are available online (http://www.ics.uci.edu/~babaks/Site/Codes.html) in order to allow replication of the results reported in this paper.
Monte Carlo simulation in statistical physics an introduction
Binder, Kurt
1992-01-01
The Monte Carlo method is a computer simulation method which uses random numbers to simulate statistical fluctuations The method is used to model complex systems with many degrees of freedom Probability distributions for these systems are generated numerically and the method then yields numerically exact information on the models Such simulations may be used tosee how well a model system approximates a real one or to see how valid the assumptions are in an analyical theory A short and systematic theoretical introduction to the method forms the first part of this book The second part is a practical guide with plenty of examples and exercises for the student Problems treated by simple sampling (random and self-avoiding walks, percolation clusters, etc) are included, along with such topics as finite-size effects and guidelines for the analysis of Monte Carlo simulations The two parts together provide an excellent introduction to the theory and practice of Monte Carlo simulations
Successful vectorization - reactor physics Monte Carlo code
International Nuclear Information System (INIS)
Martin, W.R.
1989-01-01
Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)
Yang, Jing; Youssef, Mostafa; Yildiz, Bilge
2018-01-01
In this work, we quantify oxygen self-diffusion in monoclinic-phase zirconium oxide as a function of temperature and oxygen partial pressure. A migration barrier of each type of oxygen defect was obtained by first-principles calculations. Random walk theory was used to quantify the diffusivities of oxygen interstitials by using the calculated migration barriers. Kinetic Monte Carlo simulations were used to calculate diffusivities of oxygen vacancies by distinguishing the threefold- and fourfold-coordinated lattice oxygen. By combining the equilibrium defect concentrations obtained in our previous work together with the herein calculated diffusivity of each defect species, we present the resulting oxygen self-diffusion coefficients and the corresponding atomistically resolved transport mechanisms. The predicted effective migration barriers and diffusion prefactors are in reasonable agreement with the experimentally reported values. This work provides insights into oxygen diffusion engineering in Zr O2 -related devices and parametrization for continuum transport modeling.
A multi-microcomputer system for Monte Carlo calculations
International Nuclear Information System (INIS)
Hertzberger, L.O.; Berg, B.; Krasemann, H.
1981-01-01
We propose a microcomputer system which allows parallel processing for Monte Carlo calculations in lattice gauge theories, simulations of high energy physics experiments and presumably many other fields of current interest. The master-n-slave multiprocessor system is based on the Motorola MC 68000 microprocessor. One attraction if this processor is that it allows up to 16 M Byte random access memory. (orig.)
Flexible polymers in a nematic medium : a Monte Carlo simulation
Vliet, J.H. van; Luyten, M.C.; Brinke, G. ten
Monte Carlo simulations of self-avoiding random walks surrounded by aligned rods on a square lattice and a simple cubic lattice were performed to address the topological constraints involved for dilute solutions of flexible polymers in a highly oriented nematic solvent. The nematic constraint
Monte Carlo strategies in scientific computing
Liu, Jun S
2008-01-01
This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...
Off-diagonal expansion quantum Monte Carlo.
Albash, Tameem; Wagenbreth, Gene; Hen, Itay
2017-12-01
We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.
Shell model the Monte Carlo way
International Nuclear Information System (INIS)
Ormand, W.E.
1995-01-01
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
Shell model the Monte Carlo way
Energy Technology Data Exchange (ETDEWEB)
Ormand, W.E.
1995-03-01
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.
SPQR: a Monte Carlo reactor kinetics code
International Nuclear Information System (INIS)
Cramer, S.N.; Dodds, H.L.
1980-02-01
The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations
Monte Carlo method for array criticality calculations
International Nuclear Information System (INIS)
Dickinson, D.; Whitesides, G.E.
1976-01-01
The Monte Carlo method for solving neutron transport problems consists of mathematically tracing paths of individual neutrons collision by collision until they are lost by absorption or leakage. The fate of the neutron after each collision is determined by the probability distribution functions that are formed from the neutron cross-section data. These distributions are sampled statistically to establish the successive steps in the neutron's path. The resulting data, accumulated from following a large number of batches, are analyzed to give estimates of k/sub eff/ and other collision-related quantities. The use of electronic computers to produce the simulated neutron histories, initiated at Los Alamos Scientific Laboratory, made the use of the Monte Carlo method practical for many applications. In analog Monte Carlo simulation, the calculation follows the physical events of neutron scattering, absorption, and leakage. To increase calculational efficiency, modifications such as the use of statistical weights are introduced. The Monte Carlo method permits the use of a three-dimensional geometry description and a detailed cross-section representation. Some of the problems in using the method are the selection of the spatial distribution for the initial batch, the preparation of the geometry description for complex units, and the calculation of error estimates for region-dependent quantities such as fluxes. The Monte Carlo method is especially appropriate for criticality safety calculations since it permits an accurate representation of interacting units of fissile material. Dissimilar units, units of complex shape, moderators between units, and reflected arrays may be calculated. Monte Carlo results must be correlated with relevant experimental data, and caution must be used to ensure that a representative set of neutron histories is produced
Improved Monte Carlo Method for PSA Uncertainty Analysis
International Nuclear Information System (INIS)
Choi, Jongsoo
2016-01-01
The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard
Applicability of quasi-Monte Carlo for lattice systems
International Nuclear Information System (INIS)
Ammon, Andreas; Deutsches Elektronen-Synchrotron; Hartung, Tobias; Jansen, Karl; Leovey, Hernan; Griewank, Andreas; Mueller-Preussker, Michael
2013-11-01
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.
Vectorizing and macrotasking Monte Carlo neutral particle algorithms
International Nuclear Information System (INIS)
Heifetz, D.B.
1987-04-01
Monte Carlo algorithms for computing neutral particle transport in plasmas have been vectorized and macrotasked. The techniques used are directly applicable to Monte Carlo calculations of neutron and photon transport, and Monte Carlo integration schemes in general. A highly vectorized code was achieved by calculating test flight trajectories in loops over arrays of flight data, isolating the conditional branches to as few a number of loops as possible. A number of solutions are discussed to the problem of gaps appearing in the arrays due to completed flights, which impede vectorization. A simple and effective implementation of macrotasking is achieved by dividing the calculation of the test flight profile among several processors. A tree of random numbers is used to ensure reproducible results. The additional memory required for each task may preclude using a larger number of tasks. In future machines, the limit of macrotasking may be possible, with each test flight, and split test flight, being a separate task
Applicability of quasi-Monte Carlo for lattice systems
Energy Technology Data Exchange (ETDEWEB)
Ammon, Andreas [Berlin Humboldt-Univ. (Germany). Dept. of Physics; Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Hartung, Tobias [King' s College London (United Kingdom). Dept. of Mathematics; Jansen, Karl [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leovey, Hernan; Griewank, Andreas [Berlin Humboldt-Univ. (Germany). Dept. of Mathematics; Mueller-Preussker, Michael [Berlin Humboldt-Univ. (Germany). Dept. of Physics
2013-11-15
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{sup -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{sup -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.
Monte Carlo Simulation in Statistical Physics An Introduction
Binder, Kurt
2010-01-01
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...
Improved Monte Carlo Method for PSA Uncertainty Analysis
Energy Technology Data Exchange (ETDEWEB)
Choi, Jongsoo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2016-10-15
The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard.
Two proposed convergence criteria for Monte Carlo solutions
International Nuclear Information System (INIS)
Forster, R.A.; Pederson, S.P.; Booth, T.E.
1992-01-01
The central limit theorem (CLT) can be applied to a Monte Carlo solution if two requirements are satisfied: (1) The random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these two conditions are satisfied, a confidence interval (CI) based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the Monte Carlo tally being used. The Monte Carlo practitioner has a limited number of marginal methods to assess the fulfillment of the second requirement, such as statistical error reduction proportional to 1/√N with error magnitude guidelines. Two proposed methods are discussed in this paper to assist in deciding if N is large enough: estimating the relative variance of the variance (VOV) and examining the empirical history score probability density function (pdf)
Profit Forecast Model Using Monte Carlo Simulation in Excel
Directory of Open Access Journals (Sweden)
Petru BALOGH
2014-01-01
Full Text Available Profit forecast is very important for any company. The purpose of this study is to provide a method to estimate the profit and the probability of obtaining the expected profit. Monte Carlo methods are stochastic techniques–meaning they are based on the use of random numbers and probability statistics to investigate problems. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities they will occur for any choice of action. Our example of Monte Carlo simulation in Excel will be a simplified profit forecast model. Each step of the analysis will be described in detail. The input data for the case presented: the number of leads per month, the percentage of leads that result in sales, , the cost of a single lead, the profit per sale and fixed cost, allow obtaining profit and associated probabilities of achieving.
Monte Carlo simulation applied to alpha spectrometry
International Nuclear Information System (INIS)
Baccouche, S.; Gharbi, F.; Trabelsi, A.
2007-01-01
Alpha particle spectrometry is a widely-used analytical method, in particular when we deal with pure alpha emitting radionuclides. Monte Carlo simulation is an adequate tool to investigate the influence of various phenomena on this analytical method. We performed an investigation of those phenomena using the simulation code GEANT of CERN. The results concerning the geometrical detection efficiency in different measurement geometries agree with analytical calculations. This work confirms that Monte Carlo simulation of solid angle of detection is a very useful tool to determine with very good accuracy the detection efficiency.
Simplified monte carlo simulation for Beijing spectrometer
International Nuclear Information System (INIS)
Wang Taijie; Wang Shuqin; Yan Wuguang; Huang Yinzhi; Huang Deqiang; Lang Pengfei
1986-01-01
The Monte Carlo method based on the functionization of the performance of detectors and the transformation of values of kinematical variables into ''measured'' ones by means of smearing has been used to program the Monte Carlo simulation of the performance of the Beijing Spectrometer (BES) in FORTRAN language named BESMC. It can be used to investigate the multiplicity, the particle type, and the distribution of four-momentum of the final states of electron-positron collision, and also the response of the BES to these final states. Thus, it provides a measure to examine whether the overall design of the BES is reasonable and to decide the physical topics of the BES
Self-learning Monte Carlo (dynamical biasing)
International Nuclear Information System (INIS)
Matthes, W.
1981-01-01
In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)
Burnup calculations using Monte Carlo method
International Nuclear Information System (INIS)
Ghosh, Biplab; Degweker, S.B.
2009-01-01
In the recent years, interest in burnup calculations using Monte Carlo methods has gained momentum. Previous burn up codes have used multigroup transport theory based calculations followed by diffusion theory based core calculations for the neutronic portion of codes. The transport theory methods invariably make approximations with regard to treatment of the energy and angle variables involved in scattering, besides approximations related to geometry simplification. Cell homogenisation to produce diffusion, theory parameters adds to these approximations. Moreover, while diffusion theory works for most reactors, it does not produce accurate results in systems that have strong gradients, strong absorbers or large voids. Also, diffusion theory codes are geometry limited (rectangular, hexagonal, cylindrical, and spherical coordinates). Monte Carlo methods are ideal to solve very heterogeneous reactors and/or lattices/assemblies in which considerable burnable poisons are used. The key feature of this approach is that Monte Carlo methods permit essentially 'exact' modeling of all geometrical detail, without resort to ene and spatial homogenization of neutron cross sections. Monte Carlo method would also be better for in Accelerator Driven Systems (ADS) which could have strong gradients due to the external source and a sub-critical assembly. To meet the demand for an accurate burnup code, we have developed a Monte Carlo burnup calculation code system in which Monte Carlo neutron transport code is coupled with a versatile code (McBurn) for calculating the buildup and decay of nuclides in nuclear materials. McBurn is developed from scratch by the authors. In this article we will discuss our effort in developing the continuous energy Monte Carlo burn-up code, McBurn. McBurn is intended for entire reactor core as well as for unit cells and assemblies. Generally, McBurn can do burnup of any geometrical system which can be handled by the underlying Monte Carlo transport code
Improvements for Monte Carlo burnup calculation
Energy Technology Data Exchange (ETDEWEB)
Shenglong, Q.; Dong, Y.; Danrong, S.; Wei, L., E-mail: qiangshenglong@tsinghua.org.cn, E-mail: d.yao@npic.ac.cn, E-mail: songdr@npic.ac.cn, E-mail: luwei@npic.ac.cn [Nuclear Power Inst. of China, Cheng Du, Si Chuan (China)
2015-07-01
Monte Carlo burnup calculation is development trend of reactor physics, there would be a lot of work to be done for engineering applications. Based on Monte Carlo burnup code MOI, non-fuel burnup calculation methods and critical search suggestions will be mentioned in this paper. For non-fuel burnup, mixed burnup mode will improve the accuracy of burnup calculation and efficiency. For critical search of control rod position, a new method called ABN based on ABA which used by MC21 will be proposed for the first time in this paper. (author)
A keff calculation method by Monte Carlo
International Nuclear Information System (INIS)
Shen, H; Wang, K.
2008-01-01
The effective multiplication factor (k eff ) is defined as the ratio between the number of neutrons in successive generations, which definition is adopted by most Monte Carlo codes (e.g. MCNP). Also, it can be thought of as the ratio of the generation rate of neutrons by the sum of the leakage rate and the absorption rate, which should exclude the effect of the neutron reaction such as (n, 2n) and (n, 3n). This article discusses the Monte Carlo method for k eff calculation based on the second definition. A new code has been developed and the results are presented. (author)
Monte Carlo electron/photon transport
International Nuclear Information System (INIS)
Mack, J.M.; Morel, J.E.; Hughes, H.G.
1985-01-01
A review of nonplasma coupled electron/photon transport using Monte Carlo method is presented. Remarks are mainly restricted to linerarized formalisms at electron energies from 1 keV to 1000 MeV. Applications involving pulse-height estimation, transport in external magnetic fields, and optical Cerenkov production are discussed to underscore the importance of this branch of computational physics. Advances in electron multigroup cross-section generation is reported, and its impact on future code development assessed. Progress toward the transformation of MCNP into a generalized neutral/charged-particle Monte Carlo code is described. 48 refs
Monte Carlo simulation of neutron scattering instruments
International Nuclear Information System (INIS)
Seeger, P.A.
1995-01-01
A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width
Simulation of transport equations with Monte Carlo
International Nuclear Information System (INIS)
Matthes, W.
1975-09-01
The main purpose of the report is to explain the relation between the transport equation and the Monte Carlo game used for its solution. The introduction of artificial particles carrying a weight provides one with high flexibility in constructing many different games for the solution of the same equation. This flexibility opens a way to construct a Monte Carlo game for the solution of the adjoint transport equation. Emphasis is laid mostly on giving a clear understanding of what to do and not on the details of how to do a specific game
Monte Carlo dose distributions for radiosurgery
International Nuclear Information System (INIS)
Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E.
2001-01-01
The precision of Radiosurgery Treatment planning systems is limited by the approximations of their algorithms and by their dosimetrical input data. This fact is especially important in small fields. However, the Monte Carlo methods is an accurate alternative as it considers every aspect of particle transport. In this work an acoustic neurinoma is studied by comparing the dose distribution of both a planning system and Monte Carlo. Relative shifts have been measured and furthermore, Dose-Volume Histograms have been calculated for target and adjacent organs at risk. (orig.)
Exploring Various Monte Carlo Simulations for Geoscience Applications
Blais, R.
2010-12-01
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.
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
Monte Carlo simulation with the Gate software using grid computing
International Nuclear Information System (INIS)
Reuillon, R.; Hill, D.R.C.; Gouinaud, C.; El Bitar, Z.; Breton, V.; Buvat, I.
2009-03-01
Monte Carlo simulations are widely used in emission tomography, for protocol optimization, design of processing or data analysis methods, tomographic reconstruction, or tomograph design optimization. Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the 'Multiple Replications In Parallel' approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-science), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses. (authors)
Specialized Monte Carlo codes versus general-purpose Monte Carlo codes
International Nuclear Information System (INIS)
Moskvin, Vadim; DesRosiers, Colleen; Papiez, Lech; Lu, Xiaoyi
2002-01-01
The possibilities of Monte Carlo modeling for dose calculations and optimization treatment are quite limited in radiation oncology applications. The main reason is that the Monte Carlo technique for dose calculations is time consuming while treatment planning may require hundreds of possible cases of dose simulations to be evaluated for dose optimization. The second reason is that general-purpose codes widely used in practice, require an experienced user to customize them for calculations. This paper discusses the concept of Monte Carlo code design that can avoid the main problems that are preventing wide spread use of this simulation technique in medical physics. (authors)
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Liang, Faming
2009-03-01
The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.
A continuation multilevel Monte Carlo algorithm
Collier, Nathan
2014-09-05
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. © 2014, Springer Science+Business Media Dordrecht.
Parallel processing Monte Carlo radiation transport codes
International Nuclear Information System (INIS)
McKinney, G.W.
1994-01-01
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
Monte Carlo determination of heteroepitaxial misfit structures
DEFF Research Database (Denmark)
Baker, J.; Lindgård, Per-Anker
1996-01-01
We use Monte Carlo simulations to determine the structure of KBr overlayers on a NaCl(001) substrate, a system with large (17%) heteroepitaxial misfit. The equilibrium relaxation structure is determined for films of 2-6 ML, for which extensive helium-atom scattering data exist for comparison...
The Monte Carlo applied for calculation dose
International Nuclear Information System (INIS)
Peixoto, J.E.
1988-01-01
The Monte Carlo method is showed for the calculation of absorbed dose. The trajectory of the photon is traced simulating sucessive interaction between the photon and the substance that consist the human body simulator. The energy deposition in each interaction of the simulator organ or tissue per photon is also calculated. (C.G.C.) [pt
Monte Carlo code for neutron radiography
International Nuclear Information System (INIS)
Milczarek, Jacek J.; Trzcinski, Andrzej; El-Ghany El Abd, Abd; Czachor, Andrzej
2005-01-01
The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms
Monte Carlo code for neutron radiography
Energy Technology Data Exchange (ETDEWEB)
Milczarek, Jacek J. [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)]. E-mail: jjmilcz@cyf.gov.pl; Trzcinski, Andrzej [Institute for Nuclear Studies, Swierk, 05-400 Otwock (Poland); El-Ghany El Abd, Abd [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland); Nuclear Research Center, PC 13759, Cairo (Egypt); Czachor, Andrzej [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)
2005-04-21
The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms.
Monte Carlo method in neutron activation analysis
International Nuclear Information System (INIS)
Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.
2009-01-01
Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA
Atomistic Monte Carlo simulation of lipid membranes
DEFF Research Database (Denmark)
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol....
Computer system for Monte Carlo experimentation
International Nuclear Information System (INIS)
Grier, D.A.
1986-01-01
A new computer system for Monte Carlo Experimentation is presented. The new system speeds and simplifies the process of coding and preparing a Monte Carlo Experiment; it also encourages the proper design of Monte Carlo Experiments, and the careful analysis of the experimental results. A new functional language is the core of this system. Monte Carlo Experiments, and their experimental designs, are programmed in this new language; those programs are compiled into Fortran output. The Fortran output is then compiled and executed. The experimental results are analyzed with a standard statistics package such as Si, Isp, or Minitab or with a user-supplied program. Both the experimental results and the experimental design may be directly loaded into the workspace of those packages. The new functional language frees programmers from many of the details of programming an experiment. Experimental designs such as factorial, fractional factorial, or latin square are easily described by the control structures and expressions of the language. Specific mathematical modes are generated by the routines of the language
Scalable Domain Decomposed Monte Carlo Particle Transport
Energy Technology Data Exchange (ETDEWEB)
O' Brien, Matthew Joseph [Univ. of California, Davis, CA (United States)
2013-12-05
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.|info:eu-repo/dai/nl/101275080
2015-01-01
Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying
Monte Carlo studies of ZEPLIN III
Dawson, J; Davidge, D C R; Gillespie, J R; Howard, A S; Jones, W G; Joshi, M; Lebedenko, V N; Sumner, T J; Quenby, J J
2002-01-01
A Monte Carlo simulation of a two-phase xenon dark matter detector, ZEPLIN III, has been achieved. Results from the analysis of a simulated data set are presented, showing primary and secondary signal distributions from low energy gamma ray events.
Dynamic bounds coupled with Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Rajabalinejad, M., E-mail: M.Rajabalinejad@tudelft.n [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands); Meester, L.E. [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Gelder, P.H.A.J.M. van; Vrijling, J.K. [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands)
2011-02-15
For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.
Dynamic bounds coupled with Monte Carlo simulations
Rajabali Nejad, Mohammadreza; Meester, L.E.; van Gelder, P.H.A.J.M.; Vrijling, J.K.
2011-01-01
For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper
Design and analysis of Monte Carlo experiments
Kleijnen, Jack P.C.; Gentle, J.E.; Haerdle, W.; Mori, Y.
2012-01-01
By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (such as differential calculus), but are used for numerical experimentation. The goal of these experiments is to answer questions about the real world; i.e., the experimenters may use their models to
Monte Carlo simulations in theoretical physic
International Nuclear Information System (INIS)
Billoire, A.
1991-01-01
After a presentation of the MONTE CARLO method principle, the method is applied, first to the critical exponents calculations in the three dimensions ISING model, and secondly to the discrete quantum chromodynamic with calculation times in function of computer power. 28 refs., 4 tabs
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the
Coded aperture optimization using Monte Carlo simulations
International Nuclear Information System (INIS)
Martineau, A.; Rocchisani, J.M.; Moretti, J.L.
2010-01-01
Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.
Monte Carlo studies of uranium calorimetry
International Nuclear Information System (INIS)
Brau, J.; Hargis, H.J.; Gabriel, T.A.; Bishop, B.L.
1985-01-01
Detailed Monte Carlo calculations of uranium calorimetry are presented which reveal a significant difference in the responses of liquid argon and plastic scintillator in uranium calorimeters. Due to saturation effects, neutrons from the uranium are found to contribute only weakly to the liquid argon signal. Electromagnetic sampling inefficiencies are significant and contribute substantially to compensation in both systems. 17 references
Uncertainty analysis in Monte Carlo criticality computations
International Nuclear Information System (INIS)
Qi Ao
2011-01-01
Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.
Prospect on general software of Monte Carlo method
International Nuclear Information System (INIS)
Pei Lucheng
1992-01-01
This is a short paper on the prospect of Monte Carlo general software. The content consists of cluster sampling method, zero variance technique, self-improved method, and vectorized Monte Carlo method
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung; Liang, Faming
2009-01-01
in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method
Effect of error propagation of nuclide number densities on Monte Carlo burn-up calculations
International Nuclear Information System (INIS)
Tohjoh, Masayuki; Endo, Tomohiro; Watanabe, Masato; Yamamoto, Akio
2006-01-01
As a result of improvements in computer technology, the continuous energy Monte Carlo burn-up calculation has received attention as a good candidate for an assembly calculation method. However, the results of Monte Carlo calculations contain the statistical errors. The results of Monte Carlo burn-up calculations, in particular, include propagated statistical errors through the variance of the nuclide number densities. Therefore, if statistical error alone is evaluated, the errors in Monte Carlo burn-up calculations may be underestimated. To make clear this effect of error propagation on Monte Carlo burn-up calculations, we here proposed an equation that can predict the variance of nuclide number densities after burn-up calculations, and we verified this equation using enormous numbers of the Monte Carlo burn-up calculations by changing only the initial random numbers. We also verified the effect of the number of burn-up calculation points on Monte Carlo burn-up calculations. From these verifications, we estimated the errors in Monte Carlo burn-up calculations including both statistical and propagated errors. Finally, we made clear the effects of error propagation on Monte Carlo burn-up calculations by comparing statistical errors alone versus both statistical and propagated errors. The results revealed that the effects of error propagation on the Monte Carlo burn-up calculations of 8 x 8 BWR fuel assembly are low up to 60 GWd/t
Monte Carlo techniques in diagnostic and therapeutic nuclear medicine
International Nuclear Information System (INIS)
Zaidi, H.
2002-01-01
Monte Carlo techniques have become one of the most popular tools in different areas of medical radiation physics following the development and subsequent implementation of powerful computing systems for clinical use. In particular, they have been extensively applied to simulate processes involving random behaviour and to quantify physical parameters that are difficult or even impossible to calculate analytically or to determine by experimental measurements. The use of the Monte Carlo method to simulate radiation transport turned out to be the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides. There is broad consensus in accepting that the earliest Monte Carlo calculations in medical radiation physics were made in the area of nuclear medicine, where the technique was used for dosimetry modelling and computations. Formalism and data based on Monte Carlo calculations, developed by the Medical Internal Radiation Dose (MIRD) committee of the Society of Nuclear Medicine, were published in a series of supplements to the Journal of Nuclear Medicine, the first one being released in 1968. Some of these pamphlets made extensive use of Monte Carlo calculations to derive specific absorbed fractions for electron and photon sources uniformly distributed in organs of mathematical phantoms. Interest in Monte Carlo-based dose calculations with β-emitters has been revived with the application of radiolabelled monoclonal antibodies to radioimmunotherapy. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the medical physics
Monte Carlo Volcano Seismic Moment Tensors
Waite, G. P.; Brill, K. A.; Lanza, F.
2015-12-01
Inverse modeling of volcano seismic sources can provide insight into the geometry and dynamics of volcanic conduits. But given the logistical challenges of working on an active volcano, seismic networks are typically deficient in spatial and temporal coverage; this potentially leads to large errors in source models. In addition, uncertainties in the centroid location and moment-tensor components, including volumetric components, are difficult to constrain from the linear inversion results, which leads to a poor understanding of the model space. In this study, we employ a nonlinear inversion using a Monte Carlo scheme with the objective of defining robustly resolved elements of model space. The model space is randomized by centroid location and moment tensor eigenvectors. Point sources densely sample the summit area and moment tensors are constrained to a randomly chosen geometry within the inversion; Green's functions for the random moment tensors are all calculated from modeled single forces, making the nonlinear inversion computationally reasonable. We apply this method to very-long-period (VLP) seismic events that accompany minor eruptions at Fuego volcano, Guatemala. The library of single force Green's functions is computed with a 3D finite-difference modeling algorithm through a homogeneous velocity-density model that includes topography, for a 3D grid of nodes, spaced 40 m apart, within the summit region. The homogenous velocity and density model is justified by long wavelength of VLP data. The nonlinear inversion reveals well resolved model features and informs the interpretation through a better understanding of the possible models. This approach can also be used to evaluate possible station geometries in order to optimize networks prior to deployment.
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J.E. [Delft University of Technology, Interfaculty Reactor Institute, Delft (Netherlands)
2000-07-01
The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)
International Nuclear Information System (INIS)
Hoogenboom, J.E.
2000-01-01
The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)
Monte Carlo computation in the applied research of nuclear technology
International Nuclear Information System (INIS)
Xu Shuyan; Liu Baojie; Li Qin
2007-01-01
This article briefly introduces Monte Carlo Methods and their properties. It narrates the Monte Carlo methods with emphasis in their applications to several domains of nuclear technology. Monte Carlo simulation methods and several commonly used computer software to implement them are also introduced. The proposed methods are demonstrated by a real example. (authors)
Monte Carlo-based tail exponent estimator
Barunik, Jozef; Vacha, Lukas
2010-11-01
In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.
No-compromise reptation quantum Monte Carlo
International Nuclear Information System (INIS)
Yuen, W K; Farrar, Thomas J; Rothstein, Stuart M
2007-01-01
Since its publication, the reptation quantum Monte Carlo algorithm of Baroni and Moroni (1999 Phys. Rev. Lett. 82 4745) has been applied to several important problems in physics, but its mathematical foundations are not well understood. We show that their algorithm is not of typical Metropolis-Hastings type, and we specify conditions required for the generated Markov chain to be stationary and to converge to the intended distribution. The time-step bias may add up, and in many applications it is only the middle of a reptile that is the most important. Therefore, we propose an alternative, 'no-compromise reptation quantum Monte Carlo' to stabilize the middle of the reptile. (fast track communication)
Status of Monte Carlo at Los Alamos
International Nuclear Information System (INIS)
Thompson, W.L.; Cashwell, E.D.
1980-01-01
At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time
Monte Carlo simulations in skin radiotherapy
International Nuclear Information System (INIS)
Sarvari, A.; Jeraj, R.; Kron, T.
2000-01-01
The primary goal of this work was to develop a procedure for calculation the appropriate filter shape for a brachytherapy applicator used for skin radiotherapy. In the applicator a radioactive source is positioned close to the skin. Without a filter, the resultant dose distribution would be highly nonuniform.High uniformity is usually required however. This can be achieved using an appropriately shaped filter, which flattens the dose profile. Because of the complexity of the transport and geometry, Monte Carlo simulations had to be used. An 192 Ir high dose rate photon source was used. All necessary transport parameters were simulated with the MCNP4B Monte Carlo code. A highly efficient iterative procedure was developed, which enabled calculation of the optimal filter shape in only few iterations. The initially non-uniform dose distributions became uniform within a percent when applying the filter calculated by this procedure. (author)
Coevolution Based Adaptive Monte Carlo Localization (CEAMCL
Directory of Open Access Journals (Sweden)
Luo Ronghua
2008-11-01
Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.
Multilevel sequential Monte-Carlo samplers
Jasra, Ajay
2016-01-01
Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.
Monte Carlo simulation of gas Cerenkov detectors
International Nuclear Information System (INIS)
Mack, J.M.; Jain, M.; Jordan, T.M.
1984-01-01
Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier
Hypothesis testing of scientific Monte Carlo calculations
Wallerberger, Markus; Gull, Emanuel
2017-11-01
The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.
Multilevel sequential Monte-Carlo samplers
Jasra, Ajay
2016-01-05
Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.
Monte Carlo Simulation for Particle Detectors
Pia, Maria Grazia
2012-01-01
Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...
Status of Monte Carlo at Los Alamos
International Nuclear Information System (INIS)
Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.
1980-05-01
Four papers were presented by Group X-6 on April 22, 1980, at the Oak Ridge Radiation Shielding Information Center (RSIC) Seminar-Workshop on Theory and Applications of Monte Carlo Methods. These papers are combined into one report for convenience and because they are related to each other. The first paper (by Thompson and Cashwell) is a general survey about X-6 and MCNP and is an introduction to the other three papers. It can also serve as a resume of X-6. The second paper (by Godfrey) explains some of the details of geometry specification in MCNP. The third paper (by Cashwell and Schrandt) illustrates calculating flux at a point with MCNP; in particular, the once-more-collided flux estimator is demonstrated. Finally, the fourth paper (by Thompson, Deutsch, and Booth) is a tutorial on some variance-reduction techniques. It should be required for a fledging Monte Carlo practitioner
Topological zero modes in Monte Carlo simulations
International Nuclear Information System (INIS)
Dilger, H.
1994-08-01
We present an improvement of global Metropolis updating steps, the instanton hits, used in a hybrid Monte Carlo simulation of the two-flavor Schwinger model with staggered fermions. These hits are designed to change the topological sector of the gauge field. In order to match these hits to an unquenched simulation with pseudofermions, the approximate zero mode structure of the lattice Dirac operator has to be considered explicitly. (orig.)
Handbook of Markov chain Monte Carlo
Brooks, Steve
2011-01-01
""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.
The lund Monte Carlo for jet fragmentation
International Nuclear Information System (INIS)
Sjoestrand, T.
1982-03-01
We present a Monte Carlo program based on the Lund model for jet fragmentation. Quark, gluon, diquark and hadron jets are considered. Special emphasis is put on the fragmentation of colour singlet jet systems, for which energy, momentum and flavour are conserved explicitly. The model for decays of unstable particles, in particular the weak decay of heavy hadrons, is described. The central part of the paper is a detailed description on how to use the FORTRAN 77 program. (Author)
Monte Carlo methods for preference learning
DEFF Research Database (Denmark)
Viappiani, P.
2012-01-01
Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....
Monte Carlo methods for shield design calculations
International Nuclear Information System (INIS)
Grimstone, M.J.
1974-01-01
A suite of Monte Carlo codes is being developed for use on a routine basis in commercial reactor shield design. The methods adopted for this purpose include the modular construction of codes, simplified geometries, automatic variance reduction techniques, continuous energy treatment of cross section data, and albedo methods for streaming. Descriptions are given of the implementation of these methods and of their use in practical calculations. 26 references. (U.S.)
General purpose code for Monte Carlo simulations
International Nuclear Information System (INIS)
Wilcke, W.W.
1983-01-01
A general-purpose computer called MONTHY has been written to perform Monte Carlo simulations of physical systems. To achieve a high degree of flexibility the code is organized like a general purpose computer, operating on a vector describing the time dependent state of the system under simulation. The instruction set of the computer is defined by the user and is therefore adaptable to the particular problem studied. The organization of MONTHY allows iterative and conditional execution of operations
Autocorrelations in hybrid Monte Carlo simulations
International Nuclear Information System (INIS)
Schaefer, Stefan; Virotta, Francesco
2010-11-01
Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)
Sequential Monte Carlo with Highly Informative Observations
Del Moral, Pierre; Murray, Lawrence M.
2014-01-01
We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is simulating bridges between given initial and final values. The basic idea is to introduce a schedule of intermediate weighting and resampling times between observation times, which guide particles towards the final state. This can always be done for continuous-...
Monte Carlo codes use in neutron therapy
International Nuclear Information System (INIS)
Paquis, P.; Mokhtari, F.; Karamanoukian, D.; Pignol, J.P.; Cuendet, P.; Iborra, N.
1998-01-01
Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)
Quantum Monte Carlo calculations of light nuclei
International Nuclear Information System (INIS)
Pandharipande, V. R.
1999-01-01
Quantum Monte Carlo methods provide an essentially exact way to calculate various properties of nuclear bound, and low energy continuum states, from realistic models of nuclear interactions and currents. After a brief description of the methods and modern models of nuclear forces, we review the results obtained for all the bound, and some continuum states of up to eight nucleons. Various other applications of the methods are reviewed along with future prospects
Monte-Carlo simulation of electromagnetic showers
International Nuclear Information System (INIS)
Amatuni, Ts.A.
1984-01-01
The universal ELSS-1 program for Monte Carlo simulation of high energy electromagnetic showers in homogeneous absorbers of arbitrary geometry is written. The major processes and effects of electron and photon interaction with matter, particularly the Landau-Pomeranchuk-Migdal effect, are taken into account in the simulation procedures. The simulation results are compared with experimental data. Some characteristics of shower detectors and electromagnetic showers for energies up 1 TeV are calculated
Cost of splitting in Monte Carlo transport
International Nuclear Information System (INIS)
Everett, C.J.; Cashwell, E.D.
1978-03-01
In a simple transport problem designed to estimate transmission through a plane slab of x free paths by Monte Carlo methods, it is shown that m-splitting (m > or = 2) does not pay unless exp(x) > m(m + 3)/(m - 1). In such a case, the minimum total cost in terms of machine time is obtained as a function of m, and the optimal value of m is determined
Monte Carlo simulation of Touschek effect
Directory of Open Access Journals (Sweden)
Aimin Xiao
2010-07-01
Full Text Available 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.
Monte Carlo method for neutron transport problems
International Nuclear Information System (INIS)
Asaoka, Takumi
1977-01-01
Some methods for decreasing variances in Monte Carlo neutron transport calculations are presented together with the results of sample calculations. A general purpose neutron transport Monte Carlo code ''MORSE'' was used for the purpose. The first method discussed in this report is the method of statistical estimation. As an example of this method, the application of the coarse-mesh rebalance acceleration method to the criticality calculation of a cylindrical fast reactor is presented. Effective multiplication factor and its standard deviation are presented as a function of the number of histories and comparisons are made between the coarse-mesh rebalance method and the standard method. Five-group neutron fluxes at core center are also compared with the result of S4 calculation. The second method is the method of correlated sampling. This method was applied to the perturbation calculation of control rod worths in a fast critical assembly (FCA-V-3) Two methods of sampling (similar flight paths and identical flight paths) are tested and compared with experimental results. For every cases the experimental value lies within the standard deviation of the Monte Carlo calculations. The third method is the importance sampling. In this report a biased selection of particle flight directions discussed. This method was applied to the flux calculation in a spherical fast neutron system surrounded by a 10.16 cm iron reflector. Result-direction biasing, path-length stretching, and no biasing are compared with S8 calculation. (Aoki, K.)
Biased Monte Carlo optimization: the basic approach
International Nuclear Information System (INIS)
Campioni, Luca; Scardovelli, Ruben; Vestrucci, Paolo
2005-01-01
It is well-known that the Monte Carlo method is very successful in tackling several kinds of system simulations. It often happens that one has to deal with rare events, and the use of a variance reduction technique is almost mandatory, in order to have Monte Carlo efficient applications. The main issue associated with variance reduction techniques is related to the choice of the value of the biasing parameter. Actually, this task is typically left to the experience of the Monte Carlo user, who has to make many attempts before achieving an advantageous biasing. A valuable result is provided: a methodology and a practical rule addressed to establish an a priori guidance for the choice of the optimal value of the biasing parameter. This result, which has been obtained for a single component system, has the notable property of being valid for any multicomponent system. In particular, in this paper, the exponential and the uniform biases of exponentially distributed phenomena are investigated thoroughly
Lattice gauge theories and Monte Carlo simulations
International Nuclear Information System (INIS)
Rebbi, C.
1981-11-01
After some preliminary considerations, the discussion of quantum gauge theories on a Euclidean lattice takes up the definition of Euclidean quantum theory and treatment of the continuum limit; analogy is made with statistical mechanics. Perturbative methods can produce useful results for strong or weak coupling. In the attempts to investigate the properties of the systems for intermediate coupling, numerical methods known as Monte Carlo simulations have proved valuable. The bulk of this paper illustrates the basic ideas underlying the Monte Carlo numerical techniques and the major results achieved with them according to the following program: Monte Carlo simulations (general theory, practical considerations), phase structure of Abelian and non-Abelian models, the observables (coefficient of the linear term in the potential between two static sources at large separation, mass of the lowest excited state with the quantum numbers of the vacuum (the so-called glueball), the potential between two static sources at very small distance, the critical temperature at which sources become deconfined), gauge fields coupled to basonic matter (Higgs) fields, and systems with fermions
Generalized hybrid Monte Carlo - CMFD methods for fission source convergence
International Nuclear Information System (INIS)
Wolters, Emily R.; Larsen, Edward W.; Martin, William R.
2011-01-01
In this paper, we generalize the recently published 'CMFD-Accelerated Monte Carlo' method and present two new methods that reduce the statistical error in CMFD-Accelerated Monte Carlo. The CMFD-Accelerated Monte Carlo method uses Monte Carlo to estimate nonlinear functionals used in low-order CMFD equations for the eigenfunction and eigenvalue. The Monte Carlo fission source is then modified to match the resulting CMFD fission source in a 'feedback' procedure. The two proposed methods differ from CMFD-Accelerated Monte Carlo in the definition of the required nonlinear functionals, but they have identical CMFD equations. The proposed methods are compared with CMFD-Accelerated Monte Carlo on a high dominance ratio test problem. All hybrid methods converge the Monte Carlo fission source almost immediately, leading to a large reduction in the number of inactive cycles required. The proposed methods stabilize the fission source more efficiently than CMFD-Accelerated Monte Carlo, leading to a reduction in the number of active cycles required. Finally, as in CMFD-Accelerated Monte Carlo, the apparent variance of the eigenfunction is approximately equal to the real variance, so the real error is well-estimated from a single calculation. This is an advantage over standard Monte Carlo, in which the real error can be underestimated due to inter-cycle correlation. (author)
Monte Carlo methods and models in finance and insurance
Korn, Ralf; Kroisandt, Gerald
2010-01-01
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...
Calculations of pair production by Monte Carlo methods
International Nuclear Information System (INIS)
Bottcher, C.; Strayer, M.R.
1991-01-01
We describe some of the technical design issues associated with the production of particle-antiparticle pairs in very large accelerators. To answer these questions requires extensive calculation of Feynman diagrams, in effect multi-dimensional integrals, which we evaluate by Monte Carlo methods on a variety of supercomputers. We present some portable algorithms for generating random numbers on vector and parallel architecture machines. 12 refs., 14 figs
Global Monte Carlo Simulation with High Order Polynomial Expansions
International Nuclear Information System (INIS)
William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin
2007-01-01
The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as 'local' piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi's method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source convergence
Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method
2002-01-01
This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.
Monte Carlo simulation of the three-state vector Potts model on a three-dimensional random lattice
International Nuclear Information System (INIS)
Jianbo Zhang; Heping Ying
1991-09-01
We have performed a numerical simulation of the three-state vector Potts model on a three-dimensional random lattice. The averages of energy density, magnetization, specific heat and susceptibility of the system in the N 3 (N=8,10,12) lattices were calculated. The results show that a first order nature of the Z(3) symmetry breaking transition appears, as characterized by a thermal hysterisis in the energy density as well as an abrupt drop of magnetization being sharper and discontinuous with increasing of volume in the cross-over region. The results obtained on the random lattice were consistent with those obtained on the three-dimensional cubic lattice. (author). 12 refs, 4 figs
International Nuclear Information System (INIS)
Kamaeva, O.B.; Polevoj, V.B.
1983-01-01
Realization of BESM-6 computer of a technique is described for calculating a wide class of reactivity disturbances by plotting trajectories in undisturbed and disturbed systems using one sequence of random numbers. The technique was realized on the base of earlier created programs of calculation of widespreed (PERL) and local (LAVR) reactivity disturbances. The efficiency of the technique and programs is demonstrated by calculation of change of effective neutron-multiplication factor when absorber is substituted for fuel element in a BFS-40 critical assembly and by calculation of control drum characteristics
Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system
International Nuclear Information System (INIS)
Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo
2000-01-01
Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency
The MCLIB library: Monte Carlo simulation of neutron scattering instruments
Energy Technology Data Exchange (ETDEWEB)
Seeger, P.A.
1995-09-01
Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC{_}RUN) which use the library are shown as an example.
Experiences with the parallelisation of Monte Carlo problems
International Nuclear Information System (INIS)
Schmidt, F.; Dax, W.; Luger, M.
1990-01-01
Monte Carlo problems can be parallelized in a natural way. Therefore parallelisation of production codes can be performed quite easily provided the codes are written in FORTRAN and can be transferred to the parallel machine and this machine has a pseudo random number generator available. The MORSE code is a code which can be transferred. We have done this to the CRAY-2 and the 32 processor version of the TX2 which is a binary tree structured parallel machine based on INTEL 80286 processors. We are able to reach efficiencies up to 95% for realistic problems. Thus the same throughput as on one processor on the CRAY-2 could be reached. First experiments on the INTEL i860 based TX3 indicate an additional gain of a factor 100. This will permit the reconsideration of the Monte Carlo method in both nuclear engineering and as a general numerical tool. (author)
Mesh-based weight window approach for Monte Carlo simulation
International Nuclear Information System (INIS)
Liu, L.; Gardner, R.P.
1997-01-01
The Monte Carlo method has been increasingly used to solve particle transport problems. Statistical fluctuation from random sampling is the major limiting factor of its application. To obtain the desired precision, variance reduction techniques are indispensable for most practical problems. Among various variance reduction techniques, the weight window method proves to be one of the most general, powerful, and robust. The method is implemented in the current MCNP code. An importance map is estimated during a regular Monte Carlo run, and then the map is used in the subsequent run for splitting and Russian roulette games. The major drawback of this weight window method is lack of user-friendliness. It normally requires that users divide the large geometric cells into smaller ones by introducing additional surfaces to ensure an acceptable spatial resolution of the importance map. In this paper, we present a new weight window approach to overcome this drawback
Molecular physics and chemistry applications of quantum Monte Carlo
International Nuclear Information System (INIS)
Reynolds, P.J.; Barnett, R.N.; Hammond, B.L.; Lester, W.A. Jr.
1985-09-01
We discuss recent work with the diffusion quantum Monte Carlo (QMC) method in its application to molecular systems. The formal correspondence of the imaginary time Schroedinger equation to a diffusion equation allows one to calculate quantum mechanical expectation values as Monte Carlo averages over an ensemble of random walks. We report work on atomic and molecular total energies, as well as properties including electron affinities, binding energies, reaction barriers, and moments of the electronic charge distribution. A brief discussion is given on how standard QMC must be modified for calculating properties. Calculated energies and properties are presented for a number of molecular systems, including He, F, F - , H 2 , N, and N 2 . Recent progress in extending the basic QMC approach to the calculation of ''analytic'' (as opposed to finite-difference) derivatives of the energy is presented, together with an H 2 potential-energy curve obtained using analytic derivatives. 39 refs., 1 fig., 2 tabs
The MCLIB library: Monte Carlo simulation of neutron scattering instruments
International Nuclear Information System (INIS)
Seeger, P.A.
1995-01-01
Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC RUN) which use the library are shown as an example
Investigating the impossible: Monte Carlo simulations
International Nuclear Information System (INIS)
Kramer, Gary H.; Crowley, Paul; Burns, Linda C.
2000-01-01
Designing and testing new equipment can be an expensive and time consuming process or the desired performance characteristics may preclude its construction due to technological shortcomings. Cost may also prevent equipment being purchased for other scenarios to be tested. An alternative is to use Monte Carlo simulations to make the investigations. This presentation exemplifies how Monte Carlo code calculations can be used to fill the gap. An example is given for the investigation of two sizes of germanium detector (70 mm and 80 mm diameter) at four different crystal thicknesses (15, 20, 25, and 30 mm) and makes predictions on how the size affects the counting efficiency and the Minimum Detectable Activity (MDA). The Monte Carlo simulations have shown that detector efficiencies can be adequately modelled using photon transport if the data is used to investigate trends. The investigation of the effect of detector thickness on the counting efficiency has shown that thickness for a fixed diameter detector of either 70 mm or 80 mm is unimportant up to 60 keV. At higher photon energies, the counting efficiency begins to decrease as the thickness decreases as expected. The simulations predict that the MDA of either the 70 mm or 80 mm diameter detectors does not differ by more than a factor of 1.15 at 17 keV or 1.2 at 60 keV when comparing detectors of equivalent thicknesses. The MDA is slightly increased at 17 keV, and rises by about 52% at 660 keV, when the thickness is decreased from 30 mm to 15 mm. One could conclude from this information that the extra cost associated with the larger area Ge detectors may not be justified for the slight improvement predicted in the MDA. (author)
A review of Monte Carlo techniques used in various fields of radiation protection
International Nuclear Information System (INIS)
Koblinger, L.
1987-06-01
Monte Carlo methods and their utilization in radiation protection are overviewed. Basic principles and the most frequently used sampling methods are described. Examples range from the simulation of the random walk of photons and neutrons to neutron spectrum unfolding. (author)
Monte Carlo simulations on SIMD computer architectures
International Nuclear Information System (INIS)
Burmester, C.P.; Gronsky, R.; Wille, L.T.
1992-01-01
In this paper algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SIMD) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carl updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures
Monte Carlo Simulation of an American Option
Directory of Open Access Journals (Sweden)
Gikiri Thuo
2007-04-01
Full Text Available We implement gradient estimation techniques for sensitivity analysis of option pricing which can be efficiently employed in Monte Carlo simulation. Using these techniques we can simultaneously obtain an estimate of the option value together with the estimates of sensitivities of the option value to various parameters of the model. After deriving the gradient estimates we incorporate them in an iterative stochastic approximation algorithm for pricing an option with early exercise features. We illustrate the procedure using an example of an American call option with a single dividend that is analytically tractable. In particular we incorporate estimates for the gradient with respect to the early exercise threshold level.
Monte Carlo eigenfunction strategies and uncertainties
International Nuclear Information System (INIS)
Gast, R.C.; Candelore, N.R.
1974-01-01
Comparisons of convergence rates for several possible eigenfunction source strategies led to the selection of the ''straight'' analog of the analytic power method as the source strategy for Monte Carlo eigenfunction calculations. To insure a fair game strategy, the number of histories per iteration increases with increasing iteration number. The estimate of eigenfunction uncertainty is obtained from a modification of a proposal by D. B. MacMillan and involves only estimates of the usual purely statistical component of uncertainty and a serial correlation coefficient of lag one. 14 references. (U.S.)
ATLAS Monte Carlo tunes for MC09
The ATLAS collaboration
2010-01-01
This note describes the ATLAS tunes of underlying event and minimum bias description for the main Monte Carlo generators used in the MC09 production. For the main shower generators, pythia and herwig (with jimmy), the MRST LO* parton distribution functions (PDFs) were used for the first time in ATLAS. Special studies on the performance of these, conceptually new, PDFs for high pt physics processes at LHC energies are presented. In addition, a tune of jimmy for CTEQ6.6 is presented, for use with MC@NLO.
Markov chains analytic and Monte Carlo computations
Graham, Carl
2014-01-01
Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies.A detailed and rigorous presentation of Markov chains with discrete time and state space.An appendix presenting probabilistic notions that are nec
Atomistic Monte Carlo simulation of lipid membranes
DEFF Research Database (Denmark)
Wüstner, Daniel; Sklenar, Heinz
2014-01-01
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches...
Monte Carlo method in radiation transport problems
International Nuclear Information System (INIS)
Dejonghe, G.; Nimal, J.C.; Vergnaud, T.
1986-11-01
In neutral radiation transport problems (neutrons, photons), two values are important: the flux in the phase space and the density of particles. To solve the problem with Monte Carlo method leads to, among other things, build a statistical process (called the play) and to provide a numerical value to a variable x (this attribution is called score). Sampling techniques are presented. Play biasing necessity is proved. A biased simulation is made. At last, the current developments (rewriting of programs for instance) are presented due to several reasons: two of them are the vectorial calculation apparition and the photon and neutron transport in vacancy media [fr
Mosaic crystal algorithm for Monte Carlo simulations
Seeger, P A
2002-01-01
An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)
A note on simultaneous Monte Carlo tests
DEFF Research Database (Denmark)
Hahn, Ute
In this short note, Monte Carlo tests of goodness of fit for data of the form X(t), t ∈ I are considered, that reject the null hypothesis if X(t) leaves an acceptance region bounded by an upper and lower curve for some t in I. A construction of the acceptance region is proposed that complies to a...... to a given target level of rejection, and yields exact p-values. The construction is based on pointwise quantiles, estimated from simulated realizations of X(t) under the null hypothesis....
Monte Carlo methods to calculate impact probabilities
Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.
2014-09-01
Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward
MBR Monte Carlo Simulation in PYTHIA8
Ciesielski, R.
We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.
Spectral functions from Quantum Monte Carlo
International Nuclear Information System (INIS)
Silver, R.N.
1989-01-01
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 T c 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
An analysis of Monte Carlo tree search
CSIR Research Space (South Africa)
James, S
2017-02-01
Full Text Available Tree Search Steven James∗, George Konidaris† & Benjamin Rosman∗‡ ∗University of the Witwatersrand, Johannesburg, South Africa †Brown University, Providence RI 02912, USA ‡Council for Scientific and Industrial Research, Pretoria, South Africa steven....james@students.wits.ac.za, gdk@cs.brown.edu, brosman@csir.co.za Abstract Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in re- cent years. Despite the vast amount of research into MCTS, the effect of modifications...
Monte Carlo simulation for the transport beamline
Energy Technology Data Exchange (ETDEWEB)
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [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); 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); Carpinelli, M. [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)
2013-07-26
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.
Monte Carlo simulation for the transport beamline
International Nuclear Information System (INIS)
Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.; Tramontana, A.
2013-01-01
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
Monte Carlo modelling for neutron guide losses
International Nuclear Information System (INIS)
Cser, L.; Rosta, L.; Toeroek, Gy.
1989-09-01
In modern research reactors, neutron guides are commonly used for beam conducting. The neutron guide is a well polished or equivalently smooth glass tube covered inside by sputtered or evaporated film of natural Ni or 58 Ni isotope where the neutrons are totally reflected. A Monte Carlo calculation was carried out to establish the real efficiency and the spectral as well as spatial distribution of the neutron beam at the end of a glass mirror guide. The losses caused by mechanical inaccuracy and mirror quality were considered and the effects due to the geometrical arrangement were analyzed. (author) 2 refs.; 2 figs
Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians
Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan
2018-02-01
Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.
Phase transition in nonuniform Josephson arrays: Monte Carlo simulations
Lozovik, Yu. E.; Pomirchy, L. M.
1994-01-01
Disordered 2D system with Josephson interactions is considered. Disordered XY-model describes the granular films, Josephson arrays etc. Two types of disorder are analyzed: (1) randomly diluted system: Josephson coupling constants J ij are equal to J with probability p or zero (bond percolation problem); (2) coupling constants J ij are positive and distributed randomly and uniformly in some interval either including the vicinity of zero or apart from it. These systems are simulated by Monte Carlo method. Behaviour of potential energy, specific heat, phase correlation function and helicity modulus are analyzed. The phase diagram of the diluted system in T c-p plane is obtained.
Exploring Monte Carlo Simulation Strategies for Geoscience Applications
Blais, J.; Grebenitcharsky, R.; Zhang, Z.
2008-12-01
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.
Discrete diffusion Monte Carlo for frequency-dependent radiative transfer
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Thompson, Kelly G.; Urbatsch, Todd J.
2011-01-01
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. (author)
Monte Carlo criticality analysis for dissolvers with neutron poison
International Nuclear Information System (INIS)
Yu, Deshun; Dong, Xiufang; Pu, Fuxiang.
1987-01-01
Criticality analysis for dissolvers with neutron poison is given on the basis of Monte Carlo method. In Monte Carlo calculations of thermal neutron group parameters for fuel pieces, neutron transport length is determined in terms of maximum cross section approach. A set of related effective multiplication factors (K eff ) are calculated by Monte Carlo method for the three cases. Related numerical results are quite useful for the design and operation of this kind of dissolver in the criticality safety analysis. (author)
Temperature variance study in Monte-Carlo photon transport theory
International Nuclear Information System (INIS)
Giorla, J.
1985-10-01
We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr
Algorithms for Monte Carlo calculations with fermions
International Nuclear Information System (INIS)
Weingarten, D.
1985-01-01
We describe a fermion Monte Carlo algorithm due to Petcher and the present author and another due to Fucito, Marinari, Parisi and Rebbi. For the first algorithm we estimate the number of arithmetic operations required to evaluate a vacuum expectation value grows as N 11 /msub(q) on an N 4 lattice with fixed periodicity in physical units and renormalized quark mass msub(q). For the second algorithm the rate of growth is estimated to be N 8 /msub(q) 2 . Numerical experiments are presented comparing the two algorithms on a lattice of size 2 4 . With a hopping constant K of 0.15 and β of 4.0 we find the number of operations for the second algorithm is about 2.7 times larger than for the first and about 13 000 times larger than for corresponding Monte Carlo calculations with a pure gauge theory. An estimate is given for the number of operations required for more realistic calculations by each algorithm on a larger lattice. (orig.)
Quantum Monte Carlo for atoms and molecules
International Nuclear Information System (INIS)
Barnett, R.N.
1989-11-01
The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H 2 , LiH, Li 2 , and H 2 O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li 2 , and H 2 O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations, the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions
Parallel Monte Carlo Search for Hough Transform
Lopes, Raul H. C.; Franqueira, Virginia N. L.; Reid, Ivan D.; Hobson, Peter R.
2017-10-01
We investigate the problem of line detection in digital image processing and in special how state of the art algorithms behave in the presence of noise and whether CPU efficiency can be improved by the combination of a Monte Carlo Tree Search, hierarchical space decomposition, and parallel computing. The starting point of the investigation is the method introduced in 1962 by Paul Hough for detecting lines in binary images. Extended in the 1970s to the detection of space forms, what came to be known as Hough Transform (HT) has been proposed, for example, in the context of track fitting in the LHC ATLAS and CMS projects. The Hough Transform transfers the problem of line detection, for example, into one of optimization of the peak in a vote counting process for cells which contain the possible points of candidate lines. The detection algorithm can be computationally expensive both in the demands made upon the processor and on memory. Additionally, it can have a reduced effectiveness in detection in the presence of noise. Our first contribution consists in an evaluation of the use of a variation of the Radon Transform as a form of improving theeffectiveness of line detection in the presence of noise. Then, parallel algorithms for variations of the Hough Transform and the Radon Transform for line detection are introduced. An algorithm for Parallel Monte Carlo Search applied to line detection is also introduced. Their algorithmic complexities are discussed. Finally, implementations on multi-GPU and multicore architectures are discussed.
Monte Carlo simulation for radiographic applications
International Nuclear Information System (INIS)
Tillack, G.R.; Bellon, C.
2003-01-01
Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of Monte Carlo models is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). It opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper discusses the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. (orig.) [de
Reactor perturbation calculations by Monte Carlo methods
International Nuclear Information System (INIS)
Gubbins, M.E.
1965-09-01
Whilst Monte Carlo methods are useful for reactor calculations involving complicated geometry, it is difficult to apply them to the calculation of perturbation worths because of the large amount of computing time needed to obtain good accuracy. Various ways of overcoming these difficulties are investigated in this report, with the problem of estimating absorbing control rod worths particularly in mind. As a basis for discussion a method of carrying out multigroup reactor calculations by Monte Carlo methods is described. Two methods of estimating a perturbation worth directly, without differencing two quantities of like magnitude, are examined closely but are passed over in favour of a third method based on a correlation technique. This correlation method is described, and demonstrated by a limited range of calculations for absorbing control rods in a fast reactor. In these calculations control rod worths of between 1% and 7% in reactivity are estimated to an accuracy better than 10% (3 standard errors) in about one hour's computing time on the English Electric KDF.9 digital computer. (author)
Nonlinear Spatial Inversion Without Monte Carlo Sampling
Curtis, A.; Nawaz, A.
2017-12-01
High-dimensional, nonlinear inverse or inference problems usually have non-unique solutions. The distribution of solutions are described by probability distributions, and these are usually found using Monte Carlo (MC) sampling methods. These take pseudo-random samples of models in parameter space, calculate the probability of each sample given available data and other information, and thus map out high or low probability values of model parameters. However, such methods would converge to the solution only as the number of samples tends to infinity; in practice, MC is found to be slow to converge, convergence is not guaranteed to be achieved in finite time, and detection of convergence requires the use of subjective criteria. We propose a method for Bayesian inversion of categorical variables such as geological facies or rock types in spatial problems, which requires no sampling at all. The method uses a 2-D Hidden Markov Model over a grid of cells, where observations represent localized data constraining the model in each cell. The data in our example application are seismic properties such as P- and S-wave impedances or rock density; our model parameters are the hidden states and represent the geological rock types in each cell. The observations at each location are assumed to depend on the facies at that location only - an assumption referred to as `localized likelihoods'. However, the facies at a location cannot be determined solely by the observation at that location as it also depends on prior information concerning its correlation with the spatial distribution of facies elsewhere. Such prior information is included in the inversion in the form of a training image which represents a conceptual depiction of the distribution of local geologies that might be expected, but other forms of prior information can be used in the method as desired. The method provides direct (pseudo-analytic) estimates of posterior marginal probability distributions over each variable
Odd-flavor Simulations by the Hybrid Monte Carlo
Takaishi, Tetsuya; Takaishi, Tetsuya; De Forcrand, Philippe
2001-01-01
The standard hybrid Monte Carlo algorithm is known to simulate even flavors QCD only. Simulations of odd flavors QCD, however, can be also performed in the framework of the hybrid Monte Carlo algorithm where the inverse of the fermion matrix is approximated by a polynomial. In this exploratory study we perform three flavors QCD simulations. We make a comparison of the hybrid Monte Carlo algorithm and the R-algorithm which also simulates odd flavors systems but has step-size errors. We find that results from our hybrid Monte Carlo algorithm are in agreement with those from the R-algorithm obtained at very small step-size.
Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations
International Nuclear Information System (INIS)
Brown, F.
2007-01-01
Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue (k eff ) and eigenfunction (fission source distribution) of the fundamental mode. A recently proposed method for accelerating convergence of the Monte Carlo power iteration using Wielandt's method has been implemented in a test version of MCNP5. The method is shown to provide dramatic improvements in convergence rates and to greatly reduce the possibility of false convergence assessment. The method is effective and efficient, improving the Monte Carlo figure-of-merit for many problems. In addition, the method should eliminate most of the underprediction bias in confidence intervals for Monte Carlo criticality calculations. (authors)
Monte Carlo shielding analyses using an automated biasing procedure
International Nuclear Information System (INIS)
Tang, J.S.; Hoffman, T.J.
1988-01-01
A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost
Igo - A Monte Carlo Code For Radiotherapy Planning
International Nuclear Information System (INIS)
Goldstein, M.; Regev, D.
1999-01-01
The goal of radiation therapy is to deliver a lethal dose to the tumor, while minimizing the dose to normal tissues and vital organs. To carry out this task, it is critical to calculate correctly the 3-D dose delivered. Monte Carlo transport methods (especially the Adjoint Monte Carlo have the potential to provide more accurate predictions of the 3-D dose the currently used methods. IG0 is a Monte Carlo code derived from the general Monte Carlo Program - MCNP, tailored specifically for calculating the effects of radiation therapy. This paper describes the IG0 transport code, the PIG0 interface and some preliminary results
Quantum statistical Monte Carlo methods and applications to spin systems
International Nuclear Information System (INIS)
Suzuki, M.
1986-01-01
A short review is given concerning the quantum statistical Monte Carlo method based on the equivalence theorem that d-dimensional quantum systems are mapped onto (d+1)-dimensional classical systems. The convergence property of this approximate tansformation is discussed in detail. Some applications of this general appoach to quantum spin systems are reviewed. A new Monte Carlo method, ''thermo field Monte Carlo method,'' is presented, which is an extension of the projection Monte Carlo method at zero temperature to that at finite temperatures
Variational Variance Reduction for Monte Carlo Criticality Calculations
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Larsen, Edward W.
2001-01-01
A new variational variance reduction (VVR) method for Monte Carlo criticality calculations was developed. This method employs (a) a variational functional that is more accurate than the standard direct functional, (b) a representation of the deterministically obtained adjoint flux that is especially accurate for optically thick problems with high scattering ratios, and (c) estimates of the forward flux obtained by Monte Carlo. The VVR method requires no nonanalog Monte Carlo biasing, but it may be used in conjunction with Monte Carlo biasing schemes. Some results are presented from a class of criticality calculations involving alternating arrays of fuel and moderator regions
Applications of the Monte Carlo method in radiation protection
International Nuclear Information System (INIS)
Kulkarni, R.N.; Prasad, M.A.
1999-01-01
This paper gives a brief introduction to the application of the Monte Carlo method in radiation protection. It may be noted that an exhaustive review has not been attempted. The special advantage of the Monte Carlo method has been first brought out. The fundamentals of the Monte Carlo method have next been explained in brief, with special reference to two applications in radiation protection. Some sample current applications have been reported in the end in brief as examples. They are, medical radiation physics, microdosimetry, calculations of thermoluminescence intensity and probabilistic safety analysis. The limitations of the Monte Carlo method have also been mentioned in passing. (author)
A New Approach to Monte Carlo Simulations in Statistical Physics
Landau, David P.
2002-08-01
Monte Carlo simulations [1] have become a powerful tool for the study of diverse problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, most often in the canonical ensemble, and over the past several decades enormous improvements have been made in performance. Nonetheless, difficulties arise near phase transitions-due to critical slowing down near 2nd order transitions and to metastability near 1st order transitions, and these complications limit the applicability of the method. We shall describe a new Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is known, all thermodynamic properties can be calculated. This approach can be extended to multi-dimensional parameter spaces and should be effective for systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc. Generalizations should produce a broadly applicable optimization tool. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).
EGS4, Electron Photon Shower Simulation by Monte-Carlo
International Nuclear Information System (INIS)
1998-01-01
1 - Description of program or function: The EGS code system is one of a chain of three codes designed to solve the electromagnetic shower problem by Monte Carlo simulation. This chain makes possible simulation of almost any electron-photon transport problem conceivable. The structure of the system, with its global features, modular form, and structured programming, is readily adaptable to virtually any interfacing scheme that is desired on the part of the user. EGS4 is a package of subroutines plus block data with a flexible user interface. This allows for greater flexibility without requiring the user to be overly familiar with the internal details of the code. Combining this with the macro facility capabilities of the Mortran3 language, this reduces the likelihood that user edits will introduce bugs into the code. EGS4 uses material cross section and branching ratio data created and fit by the companion code, PEGS4. EGS4 allows for the implementation of importance sampling and other variance reduction techniques such as leading particle biasing, splitting, path length biasing, Russian roulette, etc. 2 - Method of solution: EGS employs the Monte Carlo method of solution. It allows all of the fundamental processes to be included and arbitrary geometries can be treated, also. Other minor processes, such as photoneutron production, can be added as a further generalization. Since showers develop randomly according to the quantum laws of probability, each shower is different. We again are led to the Monte Carlo method. 3 - Restrictions on the complexity of the problem: None noted
Quantum Monte Carlo studies in Hamiltonian lattice gauge theory
International Nuclear Information System (INIS)
Hamer, C.J.; Samaras, M.; Bursill, R.J.
2000-01-01
Full text: The application of Monte Carlo methods to the 'Hamiltonian' formulation of lattice gauge theory has been somewhat neglected, and lags at least ten years behind the classical Monte Carlo simulations of Euclidean lattice gauge theory. We have applied a Green's Function Monte Carlo algorithm to lattice Yang-Mills theories in the Hamiltonian formulation, combined with a 'forward-walking' technique to estimate expectation values and correlation functions. In this approach, one represents the wave function in configuration space by a discrete ensemble of random walkers, and application of the time development operator is simulated by a diffusion and branching process. The approach has been used to estimate the ground-state energy and Wilson loop values in the U(1) theory in (2+1)D, and the SU(3) Yang-Mills theory in (3+1)D. The finite-size scaling behaviour has been explored, and agrees with the predictions of effective Lagrangian theory, and weak-coupling expansions. Crude estimates of the string tension are derived, which agree with previous results at intermediate couplings; but more accurate results for larger loops will be required to establish scaling behaviour at weak couplings. A drawback to this method is that it is necessary to introduce a 'trial' or 'guiding wave function' to guide the walkers towards the most probable regions of configuration space, in order to achieve convergence and accuracy. The 'forward-walking' estimates should be independent of this guidance, but in fact for the SU(3) case they turn out to be sensitive to the choice of trial wave function. It would be preferable to use some sort of Metropolis algorithm instead to produce a correct distribution of walkers: this may point in the direction of a Path Integral Monte Carlo approach
Neutron monitor generated data distributions in quantum variational Monte Carlo
Kussainov, A. S.; Pya, N.
2016-08-01
We have assessed the potential applications of the neutron monitor hardware as random number generator for normal and uniform distributions. The data tables from the acquisition channels with no extreme changes in the signal level were chosen as the retrospective model. The stochastic component was extracted by fitting the raw data with splines and then subtracting the fit. Scaling the extracted data to zero mean and variance of one is sufficient to obtain a stable standard normal random variate. Distributions under consideration pass all available normality tests. Inverse transform sampling is suggested to use as a source of the uniform random numbers. Variational Monte Carlo method for quantum harmonic oscillator was used to test the quality of our random numbers. If the data delivery rate is of importance and the conventional one minute resolution neutron count is insufficient, we could always settle for an efficient seed generator to feed into the faster algorithmic random number generator or create a buffer.
From Monte Carlo to Quantum Computation
Heinrich, Stefan
2001-01-01
Quantum computing was so far mainly concerned with discrete problems. Recently, E. Novak and the author studied quantum algorithms for high dimensional integration and dealt with the question, which advantages quantum computing can bring over classical deterministic or randomized methods for this type of problem. In this paper we give a short introduction to the basic ideas of quantum computing and survey recent results on high dimensional integration. We discuss connections to the Monte Carl...
Selection of important Monte Carlo histories
International Nuclear Information System (INIS)
Egbert, Stephen D.
1987-01-01
The 1986 Dosimetry System (DS86) for Japanese A-bomb survivors uses information describing the behavior of individual radiation particles, simulated by Monte Carlo methods, to calculate the transmission of radiation into structures and, thence, into humans. However, there are practical constraints on the number of such particle 'histories' that may be used. First, the number must be sufficiently high to provide adequate statistical precision fir any calculated quantity of interest. For integral quantities, such as dose or kerma, statistical precision of approximately 5% (standard deviation) is required to ensure that statistical uncertainties are not a major contributor to the overall uncertainty of the transmitted value. For differential quantities, such as scalar fluence spectra, 10 to 15% standard deviation on individual energy groups is adequate. Second, the number of histories cannot be so large as to require an unacceptably large amount of computer time to process the entire survivor data base. Given that there are approx. 30,000 survivors, each having 13 or 14 organs of interest, the number of histories per organ must be constrained to less than several ten's of thousands at the very most. Selection and use of the most important Monte Carlo leakage histories from among all those calculated allows the creation of an efficient house and organ radiation transmission system for use at RERF. While attempts have been made during the adjoint Monte Carlo calculation to bias the histories toward an efficient dose estimate, this effort has been far from satisfactory. Many of the adjoint histories on a typical leakage tape are either starting in an energy group in which there is very little kerma or dose or leaking into an energy group with very little free-field couple with. By knowing the typical free-field fluence and the fluence-to-dose factors with which the leaking histories will be used, one can select histories rom a leakage tape that will contribute to dose
Pore-scale uncertainty quantification with multilevel Monte Carlo
Icardi, Matteo
2014-01-06
Computational fluid dynamics (CFD) simulations of pore-scale transport processes in porous media have recently gained large popularity. However the geometrical details of the pore structures can be known only in a very low number of samples and the detailed flow computations can be carried out only on a limited number of cases. The explicit introduction of randomness in the geometry and in other setup parameters can be crucial for the optimization of pore-scale investigations for random homogenization. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost of estimating quantities of interest within a prescribed accuracy constraint. Random samples of pore geometries with a hierarchy of geometrical complexities and grid refinements, are synthetically generated and used to propagate the uncertainties in the flow simulations and compute statistics of macro-scale effective parameters.
A first look at Quasi-Monte Carlo for lattice field theory problems
International Nuclear Information System (INIS)
Jansen, K.; Leovey, H.; Griewank, A.; Nube, A.; Humboldt-Universitaet, Berlin; Mueller-Preussker, M.
2012-11-01
In this project we initiate an investigation of the applicability of Quasi-Monte Carlo methods to lattice field theories in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Monte Carlo simulation behaves like N -1/2 , where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems to up to N -1 . We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
Quasi-Monte Carlo methods for lattice systems. A first look
International Nuclear Information System (INIS)
Jansen, K.; Cyprus Univ., Nicosia; Leovey, H.; Griewank, A.; Nube, A.; Humboldt-Universitaet, Berlin; Mueller-Preussker, M.
2013-02-01
We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N -1/2 , where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems up to N -1 . We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
A contribution to the Monte Carlo method in the reactor theory
International Nuclear Information System (INIS)
Lieberoth, J.
1976-01-01
The report gives a contribution to the further development of the Monte-Carlo Method to solve the neutron transport problem. The necessary fundamentals, mainly of statistical nature, are collected and partly derived, such as the statistical weight, the use of random numbers or the Monte-Carlo integration method. Special emphasis is put on the so-called team-method, which will help to reduce the statistical error of Monte-Carlo estimates, and on the path-method, which can be used to calculate the neutron fluxes in pre-defined local points
Response decomposition with Monte Carlo correlated coupling
International Nuclear Information System (INIS)
Ueki, T.; Hoogenboom, J.E.; Kloosterman, J.L.
2001-01-01
Particle histories that contribute to a detector response are categorized according to whether they are fully confined inside a source-detector enclosure or cross and recross the same enclosure. The contribution from the confined histories is expressed using a forward problem with the external boundary condition on the source-detector enclosure. The contribution from the crossing and recrossing histories is expressed as the surface integral at the same enclosure of the product of the directional cosine and the fluxes in the foregoing forward problem and the adjoint problem for the whole spatial domain. The former contribution can be calculated by a standard forward Monte Carlo. The latter contribution can be calculated by correlated coupling of forward and adjoint histories independently of the former contribution. We briefly describe the computational method and discuss its application to perturbation analysis for localized material changes. (orig.)
Response decomposition with Monte Carlo correlated coupling
Energy Technology Data Exchange (ETDEWEB)
Ueki, T.; Hoogenboom, J.E.; Kloosterman, J.L. [Delft Univ. of Technology (Netherlands). Interfaculty Reactor Inst.
2001-07-01
Particle histories that contribute to a detector response are categorized according to whether they are fully confined inside a source-detector enclosure or cross and recross the same enclosure. The contribution from the confined histories is expressed using a forward problem with the external boundary condition on the source-detector enclosure. The contribution from the crossing and recrossing histories is expressed as the surface integral at the same enclosure of the product of the directional cosine and the fluxes in the foregoing forward problem and the adjoint problem for the whole spatial domain. The former contribution can be calculated by a standard forward Monte Carlo. The latter contribution can be calculated by correlated coupling of forward and adjoint histories independently of the former contribution. We briefly describe the computational method and discuss its application to perturbation analysis for localized material changes. (orig.)
Monte Carlo simulations of low background detectors
International Nuclear Information System (INIS)
Miley, H.S.; Brodzinski, R.L.; Hensley, W.K.; Reeves, J.H.
1995-01-01
An implementation of the Electron Gamma Shower 4 code (EGS4) has been developed to allow convenient simulation of typical gamma ray measurement systems. Coincidence gamma rays, beta spectra, and angular correlations have been added to adequately simulate a complete nuclear decay and provide corrections to experimentally determined detector efficiencies. This code has been used to strip certain low-background spectra for the purpose of extremely low-level assay. Monte Carlo calculations of this sort can be extremely successful since low background detectors are usually free of significant contributions from poorly localized radiation sources, such as cosmic muons, secondary cosmic neutrons, and radioactive construction or shielding materials. Previously, validation of this code has been obtained from a series of comparisons between measurements and blind calculations. An example of the application of this code to an exceedingly low background spectrum stripping will be presented. (author) 5 refs.; 3 figs.; 1 tab
Homogenized group cross sections by Monte Carlo
International Nuclear Information System (INIS)
Van Der Marck, S. C.; Kuijper, J. C.; Oppe, J.
2006-01-01
Homogenized group cross sections play a large role in making reactor calculations efficient. Because of this significance, many codes exist that can calculate these cross sections based on certain assumptions. However, the application to the High Flux Reactor (HFR) in Petten, the Netherlands, the limitations of such codes imply that the core calculations would become less accurate when using homogenized group cross sections (HGCS). Therefore we developed a method to calculate HGCS based on a Monte Carlo program, for which we chose MCNP. The implementation involves an addition to MCNP, and a set of small executables to perform suitable averaging after the MCNP run(s) have completed. Here we briefly describe the details of the method, and we report on two tests we performed to show the accuracy of the method and its implementation. By now, this method is routinely used in preparation of the cycle to cycle core calculations for HFR. (authors)
Nuclear reactions in Monte Carlo codes
Ferrari, Alfredo
2002-01-01
The physics foundations of hadronic interactions as implemented in most Monte Carlo codes are presented together with a few practical examples. The description of the relevant physics is presented schematically split into the major steps in order to stress the different approaches required for the full understanding of nuclear reactions at intermediate and high energies. Due to the complexity of the problem, only a few semi-qualitative arguments are developed in this paper. The description will be necessarily schematic and somewhat incomplete, but hopefully it will be useful for a first introduction into this topic. Examples are shown mostly for the high energy regime, where all mechanisms mentioned in the paper are at work and to which perhaps most of the readers are less accustomed. Examples for lower energies can be found in the references. (43 refs) .
Angular biasing in implicit Monte-Carlo
International Nuclear Information System (INIS)
Zimmerman, G.B.
1994-01-01
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
An accurate nonlinear Monte Carlo collision operator
International Nuclear Information System (INIS)
Wang, W.X.; Okamoto, M.; Nakajima, N.; Murakami, S.
1995-03-01
A three dimensional nonlinear Monte Carlo collision model is developed based on Coulomb binary collisions with the emphasis both on the accuracy and implementation efficiency. The operator of simple form fulfills particle number, momentum and energy conservation laws, and is equivalent to exact Fokker-Planck operator by correctly reproducing the friction coefficient and diffusion tensor, in addition, can effectively assure small-angle collisions with a binary scattering angle distributed in a limited range near zero. Two highly vectorizable algorithms are designed for its fast implementation. Various test simulations regarding relaxation processes, electrical conductivity, etc. are carried out in velocity space. The test results, which is in good agreement with theory, and timing results on vector computers show that it is practically applicable. The operator may be used for accurately simulating collisional transport problems in magnetized and unmagnetized plasmas. (author)
Computation cluster for Monte Carlo calculations
International Nuclear Information System (INIS)
Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S.
2010-01-01
Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)
Monte Carlo stratified source-sampling
International Nuclear Information System (INIS)
Blomquist, R.N.; Gelbard, E.M.
1997-01-01
In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo open-quotes eigenvalue of the worldclose 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
Monte Carlo simulation of a CZT detector
International Nuclear Information System (INIS)
Chun, Sung Dae; Park, Se Hwan; Ha, Jang Ho; Kim, Han Soo; Cho, Yoon Ho; Kang, Sang Mook; Kim, Yong Kyun; Hong, Duk Geun
2008-01-01
CZT detector is one of the most promising radiation detectors for hard X-ray and γ-ray measurement. The energy spectrum of CZT detector has to be simulated to optimize the detector design. A CZT detector was fabricated with dimensions of 5x5x2 mm 3 . A Peltier cooler with a size of 40x40 mm 2 was installed below the fabricated CZT detector to reduce the operation temperature of the detector. Energy spectra of were measured with 59.5 keV γ-ray from 241 Am. A Monte Carlo code was developed to simulate the CZT energy spectrum, which was measured with a planar-type CZT detector, and the result was compared with the measured one. The simulation was extended to the CZT detector with strip electrodes. (author)
Vectorization of Monte Carlo particle transport
International Nuclear Information System (INIS)
Burns, P.J.; Christon, M.; Schweitzer, R.; Lubeck, O.M.; Wasserman, H.J.; Simmons, M.L.; Pryor, D.V.
1989-01-01
This paper reports that fully vectorized versions of the Los Alamos National Laboratory benchmark code Gamteb, a Monte Carlo photon transport algorithm, were developed for the Cyber 205/ETA-10 and Cray X-MP/Y-MP architectures. Single-processor performance measurements of the vector and scalar implementations were modeled in a modified Amdahl's Law that accounts for additional data motion in the vector code. The performance and implementation strategy of the vector codes are related to architectural features of each machine. Speedups between fifteen and eighteen for Cyber 205/ETA-10 architectures, and about nine for CRAY X-MP/Y-MP architectures are observed. The best single processor execution time for the problem was 0.33 seconds on the ETA-10G, and 0.42 seconds on the CRAY Y-MP
Computation cluster for Monte Carlo calculations
Energy Technology Data Exchange (ETDEWEB)
Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S. [Dep. Of Nuclear Physics and Technology, Faculty of Electrical Engineering and Information, Technology, Slovak Technical University, Ilkovicova 3, 81219 Bratislava (Slovakia)
2010-07-01
Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)
Monte Carlo calculations of channeling radiation
International Nuclear Information System (INIS)
Bloom, S.D.; Berman, B.L.; Hamilton, D.C.; Alguard, M.J.; Barrett, J.H.; Datz, S.; Pantell, R.H.; Swent, R.H.
1981-01-01
Results of classical Monte Carlo calculations are presented for the radiation produced by ultra-relativistic positrons incident in a direction parallel to the (110) plane of Si in the energy range 30 to 100 MeV. The results all show the characteristic CR(channeling radiation) peak in the energy range 20 keV to 100 keV. Plots of the centroid energies, widths, and total yields of the CR peaks as a function of energy show the power law dependences of γ 1 5 , γ 1 7 , and γ 2 5 respectively. Except for the centroid energies and power-law dependence is only approximate. Agreement with experimental data is good for the centroid energies and only rough for the widths. Adequate experimental data for verifying the yield dependence on γ does not yet exist
Monte Carlo simulation of neutron scattering instruments
International Nuclear Information System (INIS)
Seeger, P.A.; Daemen, L.L.; Hjelm, R.P. Jr.
1998-01-01
A code package consisting of the Monte Carlo Library MCLIB, the executing code MC RUN, the web application MC Web, and various ancillary codes is proposed as an open standard for simulation of neutron scattering instruments. The architecture of the package includes structures to define surfaces, regions, and optical elements contained in regions. A particle is defined by its vector position and velocity, its time of flight, its mass and charge, and a polarization vector. The MC RUN code handles neutron transport and bookkeeping, while the action on the neutron within any region is computed using algorithms that may be deterministic, probabilistic, or a combination. Complete versatility is possible because the existing library may be supplemented by any procedures a user is able to code. Some examples are shown
Monte Carlo simulation of the ARGO
International Nuclear Information System (INIS)
Depaola, G.O.
1997-01-01
We use GEANT Monte Carlo code to design an outline of the geometry and simulate the performance of the Argentine gamma-ray observer (ARGO), a telescope based on silicon strip detector technlogy. The γ-ray direction is determined by geometrical means and the angular resolution is calculated for small variations of the basic design. The results show that the angular resolutions vary from a few degrees at low energies (∝50 MeV) to 0.2 , approximately, at high energies (>500 MeV). We also made simulations using as incoming γ-ray the energy spectrum of PKS0208-512 and PKS0528+134 quasars. Moreover, a method based on multiple scattering theory is also used to determine the incoming energy. We show that this method is applicable to energy spectrum. (orig.)
Variational Monte Carlo study of pentaquark states
Energy Technology Data Exchange (ETDEWEB)
Mark W. Paris
2005-07-01
Accurate numerical solution of the five-body Schrodinger equation is effected via variational Monte Carlo. The spectrum is assumed to exhibit a narrow resonance with strangeness S=+1. A fully antisymmetrized and pair-correlated five-quark wave function is obtained for the assumed non-relativistic Hamiltonian which has spin, isospin, and color dependent pair interactions and many-body confining terms which are fixed by the non-exotic spectra. Gauge field dynamics are modeled via flux tube exchange factors. The energy determined for the ground states with J=1/2 and negative (positive) parity is 2.22 GeV (2.50 GeV). A lower energy negative parity state is consistent with recent lattice results. The short-range structure of the state is analyzed via its diquark content.
Geometric Monte Carlo and black Janus geometries
Energy Technology Data Exchange (ETDEWEB)
Bak, Dongsu, E-mail: dsbak@uos.ac.kr [Physics Department, University of Seoul, Seoul 02504 (Korea, Republic of); B.W. Lee Center for Fields, Gravity & Strings, Institute for Basic Sciences, Daejeon 34047 (Korea, Republic of); Kim, Chanju, E-mail: cjkim@ewha.ac.kr [Department of Physics, Ewha Womans University, Seoul 03760 (Korea, Republic of); Kim, Kyung Kiu, E-mail: kimkyungkiu@gmail.com [Department of Physics, Sejong University, Seoul 05006 (Korea, Republic of); Department of Physics, College of Science, Yonsei University, Seoul 03722 (Korea, Republic of); Min, Hyunsoo, E-mail: hsmin@uos.ac.kr [Physics Department, University of Seoul, Seoul 02504 (Korea, Republic of); Song, Jeong-Pil, E-mail: jeong_pil_song@brown.edu [Department of Chemistry, Brown University, Providence, RI 02912 (United States)
2017-04-10
We describe an application of the Monte Carlo method to the Janus deformation of the black brane background. We present numerical results for three and five dimensional black Janus geometries with planar and spherical interfaces. In particular, we argue that the 5D geometry with a spherical interface has an application in understanding the finite temperature bag-like QCD model via the AdS/CFT correspondence. The accuracy and convergence of the algorithm are evaluated with respect to the grid spacing. The systematic errors of the method are determined using an exact solution of 3D black Janus. This numerical approach for solving linear problems is unaffected initial guess of a trial solution and can handle an arbitrary geometry under various boundary conditions in the presence of source fields.
Radiation Modeling with Direct Simulation Monte Carlo
Carlson, Ann B.; Hassan, H. A.
1991-01-01
Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.
Monte Carlo work at Argonne National Laboratory
International Nuclear Information System (INIS)
Gelbard, E.M.; Prael, R.E.
1974-01-01
A simple model of the Monte Carlo process is described and a (nonlinear) recursion relation between fission sources in successive generations is developed. From the linearized form of these recursion relations, it is possible to derive expressions for the mean square coefficients of error modes in the iterates and for correlation coefficients between fluctuations in successive generations. First-order nonlinear terms in the recursion relation are analyzed. From these nonlinear terms an expression for the bias in the eigenvalue estimator is derived, and prescriptions for measuring the bias are formulated. Plans for the development of the VIM code are reviewed, and the proposed treatment of small sample perturbations in VIM is described. 6 references. (U.S.)
Methods for Monte Carlo simulations of biomacromolecules.
Vitalis, Andreas; Pappu, Rohit V
2009-01-01
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.
Monte Carlo modelling of TRIGA research reactor
El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.
2010-10-01
The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.
PEPSI: a Monte Carlo generator for polarized leptoproduction
International Nuclear Information System (INIS)
Mankiewicz, L.
1992-01-01
We describe PEPSI (Polarized Electron Proton Scattering Interactions) a Monte Carlo program for the polarized deep inelastic leptoproduction mediated by electromagnetic interaction. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering and requires the standard polarization-independent JETSET routines to perform fragmentation into final hadrons. (orig.)
Closed-shell variational quantum Monte Carlo simulation for the ...
African Journals Online (AJOL)
Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... Nigeria Journal of Pure and Applied Physics ... The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock (RHF) scheme.
Efficiency and accuracy of Monte Carlo (importance) sampling
Waarts, P.H.
2003-01-01
Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed
Exponential convergence on a continuous Monte Carlo transport problem
International Nuclear Information System (INIS)
Booth, T.E.
1997-01-01
For more than a decade, it has been known that exponential convergence on discrete transport problems was possible using adaptive Monte Carlo techniques. An adaptive Monte Carlo method that empirically produces exponential convergence on a simple continuous transport problem is described
Multiple histogram method and static Monte Carlo sampling
Inda, M.A.; Frenkel, D.
2004-01-01
We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From
A Monte Carlo approach to combating delayed completion of ...
African Journals Online (AJOL)
The objective of this paper is to unveil the relevance of Monte Carlo critical path analysis in resolving problem of delays in scheduled completion of development projects. Commencing with deterministic network scheduling, Monte Carlo critical path analysis was advanced by assigning probability distributions to task times.
New Approaches and Applications for Monte Carlo Perturbation Theory
Energy Technology Data Exchange (ETDEWEB)
Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan; Leppänen, Jaakko; Palmiotti, Giuseppe; Salvatores, Massimo; Sen, Sonat; Shwageraus, Eugene; Fratoni, Massimiliano
2017-02-01
This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.
A Monte Carlo algorithm for the Vavilov distribution
International Nuclear Information System (INIS)
Yi, Chul-Young; Han, Hyon-Soo
1999-01-01
Using the convolution property of the inverse Laplace transform, an improved Monte Carlo algorithm for the Vavilov energy-loss straggling distribution of the charged particle is developed, which is relatively simple and gives enough accuracy to be used for most Monte Carlo applications
Neutron point-flux calculation by Monte Carlo
International Nuclear Information System (INIS)
Eichhorn, M.
1986-04-01
A survey of the usual methods for estimating flux at a point is given. The associated variance-reducing techniques in direct Monte Carlo games are explained. The multigroup Monte Carlo codes MC for critical systems and PUNKT for point source-point detector-systems are represented, and problems in applying the codes to practical tasks are discussed. (author)
Multiple Monte Carlo Testing with Applications in Spatial Point Processes
DEFF Research Database (Denmark)
Mrkvička, Tomáš; Myllymäki, Mari; Hahn, Ute
with a function as the test statistic, 3) several Monte Carlo tests with functions as test statistics. The rank test has correct (global) type I error in each case and it is accompanied with a p-value and with a graphical interpretation which shows which subtest or which distances of the used test function......(s) lead to the rejection at the prescribed significance level of the test. Examples of null hypothesis from point process and random set statistics are used to demonstrate the strength of the rank envelope test. The examples include goodness-of-fit test with several test functions, goodness-of-fit test...
A Monte Carlo study of radiation trapping effects
International Nuclear Information System (INIS)
Wang, J.B.; Williams, J.F.; Carter, C.J.
1997-01-01
A Monte Carlo simulation of radiative transfer in an atomic beam is carried out to investigate the effects of radiation trapping on electron-atom collision experiments. The collisionally excited atom is represented by a simple electric dipole, for which the emission intensity distribution is well known. The spatial distribution, frequency and free path of this and the sequential dipoles were determined by a computer random generator according to the probabilities given by quantum theory. By altering the atomic number density at the target site, the pressure dependence of the observed atomic lifetime, the angular intensity distribution and polarisation of the radiation field is studied. 7 refs., 5 figs
Monte Carlo codes use in neutron therapy; Application de codes Monte Carlo en neutrontherapie
Energy Technology Data Exchange (ETDEWEB)
Paquis, P.; Mokhtari, F.; Karamanoukian, D. [Hopital Pasteur, 06 - Nice (France); Pignol, J.P. [Hopital du Hasenrain, 68 - Mulhouse (France); Cuendet, P. [CEA Centre d' Etudes de Saclay, 91 - Gif-sur-Yvette (France). Direction des Reacteurs Nucleaires; Fares, G.; Hachem, A. [Faculte des Sciences, 06 - Nice (France); Iborra, N. [Centre Antoine-Lacassagne, 06 - Nice (France)
1998-04-01
Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)
Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro
2001-01-01
This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.
Research on perturbation based Monte Carlo reactor criticality search
International Nuclear Information System (INIS)
Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang
2013-01-01
Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)
Reconstruction of Monte Carlo replicas from Hessian parton distributions
Energy Technology Data Exchange (ETDEWEB)
Hou, Tie-Jiun [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Gao, Jun [INPAC, Shanghai Key Laboratory for Particle Physics and Cosmology,Department of Physics and Astronomy, Shanghai Jiao-Tong University, Shanghai 200240 (China); High Energy Physics Division, Argonne National Laboratory,Argonne, Illinois, 60439 (United States); Huston, Joey [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Schmidt, Carl; Stump, Daniel [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Wang, Bo-Ting; Xie, Ke Ping [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Dulat, Sayipjamal [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); School of Physics Science and Technology, Xinjiang University,Urumqi, Xinjiang 830046 (China); Center for Theoretical Physics, Xinjiang University,Urumqi, Xinjiang 830046 (China); Pumplin, Jon; Yuan, C.P. [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States)
2017-03-20
We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.
Monte Carlo Solutions for Blind Phase Noise Estimation
Directory of Open Access Journals (Sweden)
Çırpan Hakan
2009-01-01
Full Text Available This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN channels. The main contributions of the paper are (i the development of a Monte Carlo framework for phase noise estimation, with special attention to sequential importance sampling and Rao-Blackwellization, (ii the interpretation of existing Monte Carlo solutions within this generic framework, and (iii the derivation of a novel phase noise estimator. Contrary to the ad hoc phase noise estimators that have been proposed in the past, the estimators considered in this paper are derived from solid probabilistic and performance-determining arguments. Computer simulations demonstrate that, on one hand, the Monte Carlo phase noise estimators outperform the existing estimators and, on the other hand, our newly proposed solution exhibits a lower complexity than the existing Monte Carlo solutions.
Linear filtering applied to Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Morrison, G.W.; Pike, D.H.; Petrie, L.M.
1975-01-01
A significant improvement in the acceleration of the convergence of the eigenvalue computed by Monte Carlo techniques has been developed by applying linear filtering theory to Monte Carlo calculations for multiplying systems. A Kalman filter was applied to a KENO Monte Carlo calculation of an experimental critical system consisting of eight interacting units of fissile material. A comparison of the filter estimate and the Monte Carlo realization was made. The Kalman filter converged in five iterations to 0.9977. After 95 iterations, the average k-eff from the Monte Carlo calculation was 0.9981. This demonstrates that the Kalman filter has the potential of reducing the calculational effort of multiplying systems. Other examples and results are discussed
Problems in radiation shielding calculations with Monte Carlo methods
International Nuclear Information System (INIS)
Ueki, Kohtaro
1985-01-01
The Monte Carlo method is a very useful tool for solving a large class of radiation transport problem. In contrast with deterministic method, geometric complexity is a much less significant problem for Monte Carlo calculations. However, the accuracy of Monte Carlo calculations is of course, limited by statistical error of the quantities to be estimated. In this report, we point out some typical problems to solve a large shielding system including radiation streaming. The Monte Carlo coupling technique was developed to settle such a shielding problem accurately. However, the variance of the Monte Carlo results using the coupling technique of which detectors were located outside the radiation streaming, was still not enough. So as to bring on more accurate results for the detectors located outside the streaming and also for a multi-legged-duct streaming problem, a practicable way of ''Prism Scattering technique'' is proposed in the study. (author)
Cluster monte carlo method for nuclear criticality safety calculation
International Nuclear Information System (INIS)
Pei Lucheng
1984-01-01
One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further
Hybrid SN/Monte Carlo research and results
International Nuclear Information System (INIS)
Baker, R.S.
1993-01-01
The neutral particle transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S N ) and stochastic (Monte Carlo) methods are applied. The Monte Carlo and S N regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid Monte Carlo/S N method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor S N is well suited for by themselves. The hybrid method has been successfully applied to realistic shielding problems. The vectorized Monte Carlo algorithm in the hybrid method has been ported to the massively parallel architecture of the Connection Machine. Comparisons of performance on a vector machine (Cray Y-MP) and the Connection Machine (CM-2) show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when realistic problems requiring variance reduction are considered. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
International Nuclear Information System (INIS)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Monte Carlo based diffusion coefficients for LMFBR analysis
International Nuclear Information System (INIS)
Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira
2010-01-01
A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)
Present status and future prospects of neutronics Monte Carlo
International Nuclear Information System (INIS)
Gelbard, E.M.
1990-01-01
It is fair to say that the Monte Carlo method, over the last decade, has grown steadily more important as a neutronics computational tool. Apparently this has happened for assorted reasons. Thus, for example, as the power of computers has increased, the cost of the method has dropped, steadily becoming less and less of an obstacle to its use. In addition, more and more sophisticated input processors have now made it feasible to model extremely complicated systems routinely with really remarkable fidelity. Finally, as we demand greater and greater precision in reactor calculations, Monte Carlo is often found to be the only method accurate enough for use in benchmarking. Cross section uncertainties are now almost the only inherent limitations in our Monte Carlo capabilities. For this reason Monte Carlo has come to occupy a special position, interposed between experiment and other computational techniques. More and more often deterministic methods are tested by comparison with Monte Carlo, and cross sections are tested by comparing Monte Carlo with experiment. In this way one can distinguish very clearly between errors due to flaws in our numerical methods, and those due to deficiencies in cross section files. The special role of Monte Carlo as a benchmarking tool, often the only available benchmarking tool, makes it crucially important that this method should be polished to perfection. Problems relating to Eigenvalue calculations, variance reduction and the use of advanced computers are reviewed in this paper. (author)
Application of Monte Carlo method to solving boundary value problem of differential equations
International Nuclear Information System (INIS)
Zuo Yinghong; Wang Jianguo
2012-01-01
This paper introduces the foundation of the Monte Carlo method and the way how to generate the random numbers. Based on the basic thought of the Monte Carlo method and finite differential method, the stochastic model for solving the boundary value problem of differential equations is built. To investigate the application of the Monte Carlo method to solving the boundary value problem of differential equations, the model is used to solve Laplace's equations with the first boundary condition and the unsteady heat transfer equation with initial values and boundary conditions. The results show that the boundary value problem of differential equations can be effectively solved with the Monte Carlo method, and the differential equations with initial condition can also be calculated by using a stochastic probability model which is based on the time-domain finite differential equations. Both the simulation results and theoretical analyses show that the errors of numerical results are lowered as the number of simulation particles is increased. (authors)
Comparison of Monte Carlo method and deterministic method for neutron transport calculation
International Nuclear Information System (INIS)
Mori, Takamasa; Nakagawa, Masayuki
1987-01-01
The report outlines major features of the Monte Carlo method by citing various applications of the method and techniques used for Monte Carlo codes. Major areas of its application include analysis of measurements on fast critical assemblies, nuclear fusion reactor neutronics analysis, criticality safety analysis, evaluation by VIM code, and calculation for shielding. Major techniques used for Monte Carlo codes include the random walk method, geometric expression method (combinatorial geometry, 1, 2, 4-th degree surface and lattice geometry), nuclear data expression, evaluation method (track length, collision, analog (absorption), surface crossing, point), and dispersion reduction (Russian roulette, splitting, exponential transform, importance sampling, corrected sampling). Major features of the Monte Carlo method are as follows: 1) neutron source distribution and systems of complex geometry can be simulated accurately, 2) physical quantities such as neutron flux in a place, on a surface or at a point can be evaluated, and 3) calculation requires less time. (Nogami, K.)
Pushing the limits of Monte Carlo simulations for the three-dimensional Ising model
Ferrenberg, Alan M.; Xu, Jiahao; Landau, David P.
2018-04-01
While the three-dimensional Ising model has defied analytic solution, various numerical methods like Monte Carlo, Monte Carlo renormalization group, and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff cluster flipping algorithm with both 32-bit and 53-bit random number generators and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising Model, with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, e.g., logarithmic derivatives of magnetization and derivatives of magnetization cumulants, we have obtained the critical inverse temperature Kc=0.221 654 626 (5 ) and the critical exponent of the correlation length ν =0.629 912 (86 ) with precision that exceeds all previous Monte Carlo estimates.
A radiating shock evaluated using Implicit Monte Carlo Diffusion
International Nuclear Information System (INIS)
Cleveland, M.; Gentile, N.
2013-01-01
Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)
Recommender engine for continuous-time quantum Monte Carlo methods
Huang, Li; Yang, Yi-feng; Wang, Lei
2017-03-01
Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.
Discrete Diffusion Monte Carlo for Electron Thermal Transport
Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory
2014-10-01
The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio
Neutron flux calculation by means of Monte Carlo methods
International Nuclear Information System (INIS)
Barz, H.U.; Eichhorn, M.
1988-01-01
In this report a survey of modern neutron flux calculation procedures by means of Monte Carlo methods is given. Due to the progress in the development of variance reduction techniques and the improvements of computational techniques this method is of increasing importance. The basic ideas in application of Monte Carlo methods are briefly outlined. In more detail various possibilities of non-analog games and estimation procedures are presented, problems in the field of optimizing the variance reduction techniques are discussed. In the last part some important international Monte Carlo codes and own codes of the authors are listed and special applications are described. (author)
Uncertainty Propagation in Monte Carlo Depletion Analysis
International Nuclear Information System (INIS)
Shim, Hyung Jin; Kim, Yeong-il; Park, Ho Jin; Joo, Han Gyu; Kim, Chang Hyo
2008-01-01
A new formulation aimed at quantifying uncertainties of Monte Carlo (MC) tallies such as k eff and the microscopic reaction rates of nuclides and nuclide number densities in MC depletion analysis and examining their propagation behaviour as a function of depletion time step (DTS) is presented. It is shown that the variance of a given MC tally used as a measure of its uncertainty in this formulation arises from four sources; the statistical uncertainty of the MC tally, uncertainties of microscopic cross sections and nuclide number densities, and the cross correlations between them and the contribution of the latter three sources can be determined by computing the correlation coefficients between the uncertain variables. It is also shown that the variance of any given nuclide number density at the end of each DTS stems from uncertainties of the nuclide number densities (NND) and microscopic reaction rates (MRR) of nuclides at the beginning of each DTS and they are determined by computing correlation coefficients between these two uncertain variables. To test the viability of the formulation, we conducted MC depletion analysis for two sample depletion problems involving a simplified 7x7 fuel assembly (FA) and a 17x17 PWR FA, determined number densities of uranium and plutonium isotopes and their variances as well as k ∞ and its variance as a function of DTS, and demonstrated the applicability of the new formulation for uncertainty propagation analysis that need be followed in MC depletion computations. (authors)
Pseudopotentials for quantum-Monte-Carlo-calculations
International Nuclear Information System (INIS)
Burkatzki, Mark Thomas
2008-01-01
The author presents scalar-relativistic energy-consistent Hartree-Fock pseudopotentials for the main-group and 3d-transition-metal elements. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculations. The author demonstrates their transferability through extensive benchmark calculations of atomic excitation spectra as well as molecular properties. In particular, the author computes the vibrational frequencies and binding energies of 26 first- and second-row diatomic molecules using post Hartree-Fock methods, finding excellent agreement with the corresponding all-electron values. The author shows that the presented pseudopotentials give superior accuracy than other existing pseudopotentials constructed specifically for QMC. The localization error and the efficiency in QMC are discussed. The author also presents QMC calculations for selected atomic and diatomic 3d-transitionmetal systems. Finally, valence basis sets of different sizes (VnZ with n=D,T,Q,5 for 1st and 2nd row; with n=D,T for 3rd to 5th row; with n=D,T,Q for the 3d transition metals) optimized for the pseudopotentials are presented. (orig.)
Parallel Monte Carlo simulation of aerosol dynamics
Zhou, K.
2014-01-01
A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.
SERPENT Monte Carlo reactor physics code
International Nuclear Information System (INIS)
Leppaenen, J.
2010-01-01
SERPENT is a three-dimensional continuous-energy Monte Carlo reactor physics burnup calculation code, developed at VTT Technical Research Centre of Finland since 2004. The code is specialized in lattice physics applications, but the universe-based geometry description allows transport simulation to be carried out in complicated three-dimensional geometries as well. The suggested applications of SERPENT include generation of homogenized multi-group constants for deterministic reactor simulator calculations, fuel cycle studies involving detailed assembly-level burnup calculations, validation of deterministic lattice transport codes, research reactor applications, educational purposes and demonstration of reactor physics phenomena. The Serpent code has been publicly distributed by the OECD/NEA Data Bank since May 2009 and RSICC in the U. S. since March 2010. The code is being used in some 35 organizations in 20 countries around the world. This paper presents an overview of the methods and capabilities of the Serpent code, with examples in the modelling of WWER-440 reactor physics. (Author)
Radon counting statistics - a Monte Carlo investigation
International Nuclear Information System (INIS)
Scott, A.G.
1996-01-01
Radioactive decay is a Poisson process, and so the Coefficient of Variation (COV) of open-quotes nclose quotes counts of a single nuclide is usually estimated as 1/√n. This is only true if the count duration is much shorter than the half-life of the nuclide. At longer count durations, the COV is smaller than the Poisson estimate. Most radon measurement methods count the alpha decays of 222 Rn, plus the progeny 218 Po and 214 Po, and estimate the 222 Rn activity from the sum of the counts. At long count durations, the chain decay of these nuclides means that every 222 Rn decay must be followed by two other alpha decays. The total number of decays is open-quotes 3Nclose quotes, where N is the number of radon decays, and the true COV of the radon concentration estimate is 1/√(N), √3 larger than the Poisson total count estimate of 1/√3N. Most count periods are comparable to the half lives of the progeny, so the relationship between COV and count time is complex. A Monte-Carlo estimate of the ratio of true COV to Poisson estimate was carried out for a range of count periods from 1 min to 16 h and three common radon measurement methods: liquid scintillation, scintillation cell, and electrostatic precipitation of progeny. The Poisson approximation underestimates COV by less than 20% for count durations of less than 60 min
Monte Carlo simulations for heavy ion dosimetry
Energy Technology Data Exchange (ETDEWEB)
Geithner, O.
2006-07-26
Water-to-air stopping power ratio (s{sub w,air}) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s{sub w,air}, the influence of fragments and I-values on s{sub w,air} for carbon ion beams was investigated. The value of s{sub w,air} deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)
The Monte Carlo calculation of gamma family
International Nuclear Information System (INIS)
Shibata, Makio
1980-01-01
The method of the Monte Carlo calculation for gamma family was investigated. The effects of the variation of values or terms of parameters on observed quantities were studied. The terms taken for the standard calculation are the scaling law for the model, simple proton spectrum for primary cosmic ray, a constant cross section of interaction, zero probability of neutral pion production, and the bending of the curve of primary energy spectrum. This is called S model. Calculations were made by changing one of above mentioned parameters. The chamber size, the mixing of gamma and hadrons, and the family size were fitted to the practical ECC data. When the model was changed from the scaling law to the CKP model, the energy spectrum of the family was able to be expressed by the CKP model better than the scaling law. The scaling law was better in the symmetry around the family center. It was denied that primary cosmic ray mostly consists of heavy particles. The increase of the interaction cross section was necessary in view of the frequency of the families. (Kato, T.)
Monte Carlo Production Management at CMS
Boudoul, G.; Pol, A; Srimanobhas, P; Vlimant, J R; Franzoni, Giovanni
2015-01-01
The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events.During the runI of LHC (2010-2012), CMS has produced over 12 Billion simulated events,organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up).In order toaggregate the information needed for the configuration and prioritization of the events production,assure the book-keeping and of all the processing requests placed by the physics analysis groups,and to interface with the CMS production infrastructure,the web-based service Monte Carlo Management (McM) has been developed and put in production in 2012.McM is based on recent server infrastructure technology (CherryPy + java) and relies on a CouchDB database back-end.This contribution will coverthe one and half year of operational experience managing samples of simulated events for CMS,the evolution of its functionalitiesand the extension of its capabi...
Atomistic Monte Carlo Simulation of Lipid Membranes
Directory of Open Access Journals (Sweden)
Daniel Wüstner
2014-01-01
Full Text Available 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.
Monte Carlo benchmarking: Validation and progress
International Nuclear Information System (INIS)
Sala, P.
2010-01-01
Document available in abstract form only. Full text of publication follows: Calculational tools for radiation shielding at accelerators are faced with new challenges from the present and next generations of particle accelerators. All the details of particle production and transport play a role when dealing with huge power facilities, therapeutic ion beams, radioactive beams and so on. Besides the traditional calculations required for shielding, activation predictions have become an increasingly critical component. Comparison and benchmarking with experimental data is obviously mandatory in order to build up confidence in the computing tools, and to assess their reliability and limitations. Thin target particle production data are often the best tools for understanding the predictive power of individual interaction models and improving their performances. Complex benchmarks (e.g. thick target data, deep penetration, etc.) are invaluable in assessing the overall performances of calculational tools when all ingredients are put at work together. A review of the validation procedures of Monte Carlo tools will be presented with practical and real life examples. The interconnections among benchmarks, model development and impact on shielding calculations will be highlighted. (authors)
Rare event simulation using Monte Carlo methods
Rubino, Gerardo
2009-01-01
In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...
The GENIE neutrino Monte Carlo generator
International Nuclear Information System (INIS)
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.
2010-01-01
GENIE 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.
Efficient sampling algorithms for Monte Carlo based treatment planning
International Nuclear Information System (INIS)
DeMarco, J.J.; Solberg, T.D.; Chetty, I.; Smathers, J.B.
1998-01-01
Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed
The statistical error of Green's function Monte Carlo
International Nuclear Information System (INIS)
Ceperley, D.M.
1986-01-01
The statistical error in the ground state energy as calculated by Green's Function Monte Carlo (GFMC) is analyzed and a simple approximate formula is derived which relates the error to the number of steps of the random walk, the variational energy of the trial function, and the time step of the random walk. Using this formula it is argued that as the thermodynamic limit is approached with N identical molecules, the computer time needed to reach a given error per molecule increases as N/sup n/ where 0.5 < b < 1.5 and as the nuclear charge Z of a system is increased the computer time necessary to reach a given error grows as Z/sup 5.5/. Thus GFMC simulations will be most useful for calculating the properties of low Z elements. The implications for choosing the optimal trial function from a series of trial functions is also discussed
Vector Monte Carlo simulations on atmospheric scattering of polarization qubits.
Li, Ming; Lu, Pengfei; Yu, Zhongyuan; Yan, Lei; Chen, Zhihui; Yang, Chuanghua; Luo, Xiao
2013-03-01
In this paper, a vector Monte Carlo (MC) method is proposed to study the influence of atmospheric scattering on polarization qubits for satellite-based quantum communication. The vector MC method utilizes a transmittance method to solve the photon free path for an inhomogeneous atmosphere and random number sampling to determine whether the type of scattering is aerosol scattering or molecule scattering. Simulations are performed for downlink and uplink. The degrees and the rotations of polarization are qualitatively and quantitatively obtained, which agree well with the measured results in the previous experiments. The results show that polarization qubits are well preserved in the downlink and uplink, while the number of received single photons is less than half of the total transmitted single photons for both links. Moreover, our vector MC method can be applied for the scattering of polarized light in other inhomogeneous random media.
Planning Tunnel Construction Using Markov Chain Monte Carlo (MCMC
Directory of Open Access Journals (Sweden)
Juan P. Vargas
2015-01-01
Full Text Available Tunnels, drifts, drives, and other types of underground excavation are very common in mining as well as in the construction of roads, railways, dams, and other civil engineering projects. Planning is essential to the success of tunnel excavation, and construction time is one of the most important factors to be taken into account. This paper proposes a simulation algorithm based on a stochastic numerical method, the Markov chain Monte Carlo method, that can provide the best estimate of the opening excavation times for the classic method of drilling and blasting. Taking account of technical considerations that affect the tunnel excavation cycle, the simulation is developed through a computational algorithm. Using the Markov chain Monte Carlo method, the unit operations involved in the underground excavation cycle are identified and assigned probability distributions that, with random number input, make it possible to simulate the total excavation time. The results obtained with this method are compared with a real case of tunneling excavation. By incorporating variability in the planning, it is possible to determine with greater certainty the ranges over which the execution times of the unit operations fluctuate. In addition, the financial risks associated with planning errors can be reduced and the exploitation of resources maximized.
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.
2010-01-01
model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order
Time step length versus efficiency of Monte Carlo burnup calculations
International Nuclear Information System (INIS)
Dufek, Jan; Valtavirta, Ville
2014-01-01
Highlights: • Time step length largely affects efficiency of MC burnup calculations. • Efficiency of MC burnup calculations improves with decreasing time step length. • Results were obtained from SIE-based Monte Carlo burnup calculations. - Abstract: We demonstrate that efficiency of Monte Carlo burnup calculations can be largely affected by the selected time step length. This study employs the stochastic implicit Euler based coupling scheme for Monte Carlo burnup calculations that performs a number of inner iteration steps within each time step. In a series of calculations, we vary the time step length and the number of inner iteration steps; the results suggest that Monte Carlo burnup calculations get more efficient as the time step length is reduced. More time steps must be simulated as they get shorter; however, this is more than compensated by the decrease in computing cost per time step needed for achieving a certain accuracy
GE781: a Monte Carlo package for fixed target experiments
Davidenko, G.; Funk, M. A.; Kim, V.; Kuropatkin, N.; Kurshetsov, V.; Molchanov, V.; Rud, S.; Stutte, L.; Verebryusov, V.; Zukanovich Funchal, R.
The Monte Carlo package for the fixed target experiment B781 at Fermilab, a third generation charmed baryon experiment, is described. This package is based on GEANT 3.21, ADAMO database and DAFT input/output routines.
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung
2009-11-01
Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.
Optix: A Monte Carlo scintillation light transport code
Energy Technology Data Exchange (ETDEWEB)
Safari, M.J., E-mail: mjsafari@aut.ac.ir [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Afarideh, H. [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Ghal-Eh, N. [School of Physics, Damghan University, PO Box 36716-41167, Damghan (Iran, Islamic Republic of); Davani, F. Abbasi [Nuclear Engineering Department, Shahid Beheshti University, PO Box 1983963113, Tehran (Iran, Islamic Republic of)
2014-02-11
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. -- Highlights: • Monte Carlo simulation of scintillation light transport in 3D geometry. • Evaluation of angular distribution of detected photons. • Benchmark studies to check the accuracy of Monte Carlo simulations.
Dosimetric measurements and Monte Carlo simulation for achieving ...
Indian Academy of Sciences (India)
Research Articles Volume 74 Issue 3 March 2010 pp 457-468 ... Food irradiation; electron accelerator; Monte Carlo; dose uniformity. ... for radiation processing of food and medical products is being commissioned at our centre in Indore, India.
Usefulness of the Monte Carlo method in reliability calculations
International Nuclear Information System (INIS)
Lanore, J.M.; Kalli, H.
1977-01-01
Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels
Suppression of the initial transient in Monte Carlo criticality simulations
International Nuclear Information System (INIS)
Richet, Y.
2006-12-01
Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)
Monte Carlo calculations of electron diffusion in materials
International Nuclear Information System (INIS)
Schroeder, U.G.
1976-01-01
By means of simulated experiments, various transport problems for 10 Mev electrons are investigated. For this purpose, a special Monte-Carlo programme is developed, and with this programme calculations are made for several material arrangements. (orig./LN) [de
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)
2013-07-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
International Nuclear Information System (INIS)
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.
2013-01-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
Calculation of toroidal fusion reactor blankets by Monte Carlo
International Nuclear Information System (INIS)
Macdonald, J.L.; Cashwell, E.D.; Everett, C.J.
1977-01-01
A brief description of the calculational method is given. The code calculates energy deposition in toroidal geometry, but is a continuous energy Monte Carlo code, treating the reaction cross sections as well as the angular scattering distributions in great detail
The Monte Carlo simulation of the Ladon photon beam facility
International Nuclear Information System (INIS)
Strangio, C.
1976-01-01
The backward compton scattering of laser light against high energy electrons has been simulated with a Monte Carlo method. The main features of the produced photon beam are reported as well as a careful description of the numerical calculation
Monte Carlo variance reduction approaches for non-Boltzmann tallies
International Nuclear Information System (INIS)
Booth, T.E.
1992-12-01
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed
Combinatorial nuclear level density by a Monte Carlo method
International Nuclear Information System (INIS)
Cerf, N.
1994-01-01
We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki
2015-01-01
informative data about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method
Studies of Monte Carlo Modelling of Jets at ATLAS
Kar, Deepak; The ATLAS collaboration
2017-01-01
The predictions of different Monte Carlo generators for QCD jet production, both in multijets and for jets produced in association with other objects, are presented. Recent improvements in showering Monte Carlos provide new tools for assessing systematic uncertainties associated with these jets. Studies of the dependence of physical observables on the choice of shower tune parameters and new prescriptions for assessing systematic uncertainties associated with the choice of shower model and tune are presented.
Herwig: The Evolution of a Monte Carlo Simulation
CERN. Geneva
2015-01-01
Monte Carlo event generation has seen significant developments in the last 10 years starting with preparation for the LHC and then during the first LHC run. I will discuss the basic ideas behind Monte Carlo event generators and then go on to discuss these developments, focussing on the developments in Herwig(++) event generator. I will conclude by presenting the current status of event generation together with some results of the forthcoming new version of Herwig, Herwig 7.
Clinical considerations of Monte Carlo for electron radiotherapy treatment planning
International Nuclear Information System (INIS)
Faddegon, Bruce; Balogh, Judith; Mackenzie, Robert; Scora, Daryl
1998-01-01
Technical requirements for Monte Carlo based electron radiotherapy treatment planning are outlined. The targeted overall accuracy for estimate of the delivered dose is the least restrictive of 5% in dose, 5 mm in isodose position. A system based on EGS4 and capable of achieving this accuracy is described. Experience gained in system design and commissioning is summarized. The key obstacle to widespread clinical use of Monte Carlo is lack of clinically acceptable measurement based methodology for accurate commissioning
NUEN-618 Class Project: Actually Implicit Monte Carlo
Energy Technology Data Exchange (ETDEWEB)
Vega, R. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brunner, T. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-12-14
This research describes a new method for the solution of the thermal radiative transfer (TRT) equations that is implicit in time which will be called Actually Implicit Monte Carlo (AIMC). This section aims to introduce the TRT equations, as well as the current workhorse method which is known as Implicit Monte Carlo (IMC). As the name of the method proposed here indicates, IMC is a misnomer in that it is only semi-implicit, which will be shown in this section as well.
Monte Carlo methods and applications in nuclear physics
International Nuclear Information System (INIS)
Carlson, J.
1990-01-01
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
Monte Carlo methods and applications in nuclear physics
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
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.
Study of the Transition Flow Regime using Monte Carlo Methods
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
Modern analysis of ion channeling data by Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Nowicki, Lech [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland)]. E-mail: lech.nowicki@fuw.edu.pl; Turos, Andrzej [Institute of Electronic Materials Technology, Wolczynska 133, 01-919 Warsaw (Poland); Ratajczak, Renata [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Stonert, Anna [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Garrido, Frederico [Centre de Spectrometrie Nucleaire et Spectrometrie de Masse, CNRS-IN2P3-Universite Paris-Sud, 91405 Orsay (France)
2005-10-15
Basic scheme of ion channeling spectra Monte Carlo simulation is reformulated in terms of statistical sampling. The McChasy simulation code is described and two examples of the code applications are presented. These are: calculation of projectile flux in uranium dioxide crystal and defect analysis for ion implanted InGaAsP/InP superlattice. Virtues and pitfalls of defect analysis using Monte Carlo simulations are discussed.
Monte Carlos of the new generation: status and progress
International Nuclear Information System (INIS)
Frixione, Stefano
2005-01-01
Standard parton shower monte carlos are designed to give reliable descriptions of low-pT physics. In the very high-energy regime of modern colliders, this is may lead to largely incorrect predictions of the basic reaction processes. This motivated the recent theoretical efforts aimed at improving monte carlos through the inclusion of matrix elements computed beyond the leading order in QCD. I briefly review the progress made, and discuss bottom production at the Tevatron
Monte carlo sampling of fission multiplicity.
Energy Technology Data Exchange (ETDEWEB)
Hendricks, J. S. (John S.)
2004-01-01
Two new methods have been developed for fission multiplicity modeling in Monte Carlo calculations. The traditional method of sampling neutron multiplicity from fission is to sample the number of neutrons above or below the average. For example, if there are 2.7 neutrons per fission, three would be chosen 70% of the time and two would be chosen 30% of the time. For many applications, particularly {sup 3}He coincidence counting, a better estimate of the true number of neutrons per fission is required. Generally, this number is estimated by sampling a Gaussian distribution about the average. However, because the tail of the Gaussian distribution is negative and negative neutrons cannot be produced, a slight positive bias can be found in the average value. For criticality calculations, the result of rejecting the negative neutrons is an increase in k{sub eff} of 0.1% in some cases. For spontaneous fission, where the average number of neutrons emitted from fission is low, the error also can be unacceptably large. If the Gaussian width approaches the average number of fissions, 10% too many fission neutrons are produced by not treating the negative Gaussian tail adequately. The first method to treat the Gaussian tail is to determine a correction offset, which then is subtracted from all sampled values of the number of neutrons produced. This offset depends on the average value for any given fission at any energy and must be computed efficiently at each fission from the non-integrable error function. The second method is to determine a corrected zero point so that all neutrons sampled between zero and the corrected zero point are killed to compensate for the negative Gaussian tail bias. Again, the zero point must be computed efficiently at each fission. Both methods give excellent results with a negligible computing time penalty. It is now possible to include the full effects of fission multiplicity without the negative Gaussian tail bias.
Dosimetry applications in GATE Monte Carlo toolkit.
Papadimitroulas, Panagiotis
2017-09-01
Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Monte Carlo and analytic simulations in nanoparticle-enhanced radiation therapy
Directory of Open Access Journals (Sweden)
Paro AD
2016-09-01
Full Text Available Autumn D Paro,1 Mainul Hossain,2 Thomas J Webster,1,3,4 Ming Su1,4 1Department of Chemical Engineering, Northeastern University, Boston, MA, USA; 2NanoScience Technology Center and School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida, USA; 3Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, Saudi Arabia; 4Wenzhou Institute of Biomaterials and Engineering, Chinese Academy of Science, Wenzhou Medical University, Zhejiang, People’s Republic of China Abstract: Analytical and Monte Carlo simulations have been used to predict dose enhancement factors in nanoparticle-enhanced X-ray radiation therapy. Both simulations predict an increase in dose enhancement in the presence of nanoparticles, but the two methods predict different levels of enhancement over the studied energy, nanoparticle materials, and concentration regime for several reasons. The Monte Carlo simulation calculates energy deposited by electrons and photons, while the analytical one only calculates energy deposited by source photons and photoelectrons; the Monte Carlo simulation accounts for electron–hole recombination, while the analytical one does not; and the Monte Carlo simulation randomly samples photon or electron path and accounts for particle interactions, while the analytical simulation assumes a linear trajectory. This study demonstrates that the Monte Carlo simulation will be a better choice to evaluate dose enhancement with nanoparticles in radiation therapy. Keywords: nanoparticle, dose enhancement, Monte Carlo simulation, analytical simulation, radiation therapy, tumor cell, X-ray
pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis
White, J.; Brakefield, L. K.
2015-12-01
The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.
Directory of Open Access Journals (Sweden)
José Luiz Ferreira Martins
2011-09-01
. From these data was taken at random samples with, respectively, 10, 15 and 20 elements and were performed simulations by Monte Carlo method. Comparing the results of the sample with 160 elements and the data generated by simulation is observed that good results can be obtained by using Monte Carlo method in estimating productivity of industrial welding. On the other hand in Brazilian construction industry the value of productivity average is normally used as a productivity indicator and is based on historical data from other projects collected and measured only after project completion, which is a limitation. This article presents a tool for evaluation of the implementation in real time, enabling adjustments in estimates and monitoring productivity during the project. Similarly, in biddings, budgets and schedule estimations, the use of this tool could enable the adoption of other estimative different from of the average productivity, which is commonly used and as an alternative are suggested three criteria: optimistic, average and pessimistic productivity.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki; Long, Quan; Scavino, Marco; Tempone, Raul
2015-01-01
Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki
2015-01-07
Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments
International Nuclear Information System (INIS)
Pevey, Ronald E.
2005-01-01
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
Alternative implementations of the Monte Carlo power method
International Nuclear Information System (INIS)
Blomquist, R.N.; Gelbard, E.M.
2002-01-01
We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency
Present status of transport code development based on Monte Carlo method
International Nuclear Information System (INIS)
Nakagawa, Masayuki
1985-01-01
The present status of development in Monte Carlo code is briefly reviewed. The main items are the followings; Application fields, Methods used in Monte Carlo code (geometry spectification, nuclear data, estimator and variance reduction technique) and unfinished works, Typical Monte Carlo codes and Merits of continuous energy Monte Carlo code. (author)
Monte Carlo systems used for treatment planning and dose verification
Energy Technology Data Exchange (ETDEWEB)
Brualla, Lorenzo [Universitaetsklinikum Essen, NCTeam, Strahlenklinik, Essen (Germany); Rodriguez, Miguel [Centro Medico Paitilla, Balboa (Panama); Lallena, Antonio M. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain)
2017-04-15
General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations. (orig.) [German] Seit mehreren Jahrzehnten werden allgemein anwendbare Monte-Carlo-Codes zur Simulation des Strahlungstransports benutzt, um die Verteilung der absorbierten Dosis in der perkutanen Strahlentherapie mit Photonen und Elektronen zu evaluieren. Die damit erzielten Ergebnisse sind meist akkurater als solche, die mit nichtstochastischen Methoden herkoemmlicher Bestrahlungsplanungssysteme erzielt werden koennen. Wegen des damit verbundenen Arbeitsaufwands und der langen Dauer der Berechnungen wurden Monte-Carlo-Simulationen von Dosisverteilungen in der konventionellen Strahlentherapie in der Vergangenheit im Wesentlichen in der Forschung eingesetzt. Im Bemuehen, Monte-Carlo
Monte Carlo simulation of AB-copolymers with saturating bonds
Chertovich, A V; Khokhlov, A R; Bohr, J
2003-01-01
Structural transitions in a single AB-copolymer chain where saturating bonds can be formed between A-and B-units are studied by means of Monte Carlo computer simulations using the bond fluctuation model. Three transitions are found, coil-globule, coil-hairpin and globule-hairpin, depending on the nature of a particular AB-sequence: statistical random sequence, diblock sequence and 'random-complementary' sequence (one-half of such an AB-sequence is random with Bernoulli statistics while the other half is complementary to the first one). The properties of random-complementary sequences are closer to those of diblock sequences than to the properties of random sequences. The model (although quite rough) is expected to represent some basic features of real RNA molecules, i.e. the formation of secondary structure of RNA due to hydrogen bonding of corresponding bases and stacking interactions of the base pairs in helixes. We introduce the notation of RNA-like copolymers and discuss in what sense the sequences studie...
Exact Monte Carlo for few-fermion systems
International Nuclear Information System (INIS)
Kalos, M.H.
1991-01-01
The author reconsiders the fundamental difficulties of fermion Monte Carlo as applied to few-body systems. He concludes that necessary ingredients of successful algorithms include the following: there must be equal populations of random walkers that carry positive and negative weights. The positions of positive walkers should be selected from a distribution that uses Green's functions to couple all walkers. The positions of negative walkers should be generated from those of positive walkers by means of odd permutations. The correct importance functions that take into account the global interactions of the populations are different for positive and negative walkers. Use of such important functions breaks the symmetry that otherwise would exist between configurations (of the entire population) and configurations derived by interchanging positive and negative walkers. Based upon these observations, he has constructed a stable and accurate algorithm that solves a fully-polarized, three-dimensional three-body model problem
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
Directory of Open Access Journals (Sweden)
Roberto S. Flowers-Cano
2018-02-01
Full Text Available Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP, bias-corrected bootstrap (BC, accelerated bias-corrected bootstrap (BCA and a modified version of the standard bootstrap (MSB. Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.
Convergence testing for MCNP5 Monte Carlo eigenvalue calculations
International Nuclear Information System (INIS)
Brown, F.; Nease, B.; Cheatham, J.
2007-01-01
Determining convergence of Monte Carlo criticality problems is complicated by the statistical noise inherent in the random, walks of the neutrons in each generation. The latest version of MCNP5 incorporates an important new tool for assessing convergence: the Shannon entropy of the fission source distribution, H src . Shannon entropy is a well-known concept from information theory and provides a single number for each iteration to help characterize convergence trends for the fission source distribution. MCNP5 computes H src for each iteration, and these values may be plotted to examine convergence trends. Convergence testing should include both k eff and H src , since the fission distribution will converge more slowly than k eff , especially when the dominance ratio is close to 1.0. (authors)
Treatment planning in radiosurgery: parallel Monte Carlo simulation software
Energy Technology Data Exchange (ETDEWEB)
Scielzo, G [Galliera Hospitals, Genova (Italy). Dept. of Hospital Physics; Grillo Ruggieri, F [Galliera Hospitals, Genova (Italy) Dept. for Radiation Therapy; Modesti, M; Felici, R [Electronic Data System, Rome (Italy); Surridge, M [University of South Hampton (United Kingdom). Parallel Apllication Centre
1995-12-01
The main objective of this research was to evaluate the possibility of direct Monte Carlo simulation for accurate dosimetry with short computation time. We made us of: graphics workstation, linear accelerator, water, PMMA and anthropomorphic phantoms, for validation purposes; ionometric, film and thermo-luminescent techniques, for dosimetry; treatment planning system for comparison. Benchmarking results suggest that short computing times can be obtained with use of the parallel version of EGS4 that was developed. Parallelism was obtained assigning simulation incident photons to separate processors, and the development of a parallel random number generator was necessary. Validation consisted in: phantom irradiation, comparison of predicted and measured values good agreement in PDD and dose profiles. Experiments on anthropomorphic phantoms (with inhomogeneities) were carried out, and these values are being compared with results obtained with the conventional treatment planning system.
Markov Chain Monte Carlo Bayesian Learning for Neural Networks
Goodrich, Michael S.
2011-01-01
Conventional training methods for neural networks involve starting al a random location in the solution space of the network weights, navigating an error hyper surface to reach a minimum, and sometime stochastic based techniques (e.g., genetic algorithms) to avoid entrapment in a local minimum. It is further typically necessary to preprocess the data (e.g., normalization) to keep the training algorithm on course. Conversely, Bayesian based learning is an epistemological approach concerned with formally updating the plausibility of competing candidate hypotheses thereby obtaining a posterior distribution for the network weights conditioned on the available data and a prior distribution. In this paper, we developed a powerful methodology for estimating the full residual uncertainty in network weights and therefore network predictions by using a modified Jeffery's prior combined with a Metropolis Markov Chain Monte Carlo method.
Monte Carlo applications at Hanford Engineering Development Laboratory
International Nuclear Information System (INIS)
Carter, L.L.; Morford, R.J.; Wilcox, A.D.
1980-03-01
Twenty applications of neutron and photon transport with Monte Carlo have been described to give an overview of the current effort at HEDL. A satisfaction factor was defined which quantitatively assigns an overall return for each calculation relative to the investment in machine time and expenditure of manpower. Low satisfaction factors are frequently encountered in the calculations. Usually this is due to limitations in execution rates of present day computers, but sometimes a low satisfaction factor is due to computer code limitations, calendar time constraints, or inadequacy of the nuclear data base. Present day computer codes have taken some of the burden off of the user. Nevertheless, it is highly desirable for the engineer using the computer code to have an understanding of particle transport including some intuition for the problems being solved, to understand the construction of sources for the random walk, to understand the interpretation of tallies made by the code, and to have a basic understanding of elementary biasing techniques
Spatial distribution sampling and Monte Carlo simulation of radioactive isotopes
Krainer, Alexander Michael
2015-01-01
This work focuses on the implementation of a program for random sampling of uniformly spatially distributed isotopes for Monte Carlo particle simulations and in specific FLUKA. With FLUKA it is possible to calculate the radio nuclide production in high energy fields. The decay of these nuclide, and therefore the resulting radiation field, however can only be simulated in the same geometry. This works gives the tool to simulate the decay of the produced nuclide in other geometries. With that the radiation field from an irradiated object can be simulated in arbitrary environments. The sampling of isotope mixtures was tested by simulating a 50/50 mixture of $Cs^{137}$ and $Co^{60}$. These isotopes are both well known and provide therefore a first reliable benchmark in that respect. The sampling of uniformly distributed coordinates was tested using the histogram test for various spatial distributions. The advantages and disadvantages of the program compared to standard methods are demonstrated in the real life ca...
Monte Carlo sampling strategies for lattice gauge calculations
International Nuclear Information System (INIS)
Guralnik, G.; Zemach, C.; Warnock, T.
1985-01-01
We have sought to optimize the elements of the Monte Carlo processes for thermalizing and decorrelating sequences of lattice gauge configurations and for this purpose, to develop computational and theoretical diagnostics to compare alternative techniques. These have been applied to speed up generations of random matrices, compare heat bath and Metropolis stepping methods, and to study autocorrelations of sequences in terms of the classical moment problem. The efficient use of statistically correlated lattice data is an optimization problem depending on the relation between computer times to generate lattice sequences of sufficiently small correlation and times to analyze them. We can solve this problem with the aid of a representation of auto-correlation data for various step lags as moments of positive definite distributions, using methods known for the moment problem to put bounds on statistical variances, in place of estimating the variances by too-lengthy computer runs
A residual Monte Carlo method for discrete thermal radiative diffusion
International Nuclear Information System (INIS)
Evans, T.M.; Urbatsch, T.J.; Lichtenstein, H.; Morel, J.E.
2003-01-01
Residual Monte Carlo methods reduce statistical error at a rate of exp(-bN), where b is a positive constant and N is the number of particle histories. Contrast this convergence rate with 1/√N, which is the rate of statistical error reduction for conventional Monte Carlo methods. Thus, residual Monte Carlo methods hold great promise for increased efficiency relative to conventional Monte Carlo methods. Previous research has shown that the application of residual Monte Carlo methods to the solution of continuum equations, such as the radiation transport equation, is problematic for all but the simplest of cases. However, the residual method readily applies to discrete systems as long as those systems are monotone, i.e., they produce positive solutions given positive sources. We develop a residual Monte Carlo method for solving a discrete 1D non-linear thermal radiative equilibrium diffusion equation, and we compare its performance with that of the discrete conventional Monte Carlo method upon which it is based. We find that the residual method provides efficiency gains of many orders of magnitude. Part of the residual gain is due to the fact that we begin each timestep with an initial guess equal to the solution from the previous timestep. Moreover, fully consistent non-linear solutions can be obtained in a reasonable amount of time because of the effective lack of statistical noise. We conclude that the residual approach has great potential and that further research into such methods should be pursued for more general discrete and continuum systems
Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement
Directory of Open Access Journals (Sweden)
Joko Siswantoro
2014-01-01
Full Text Available Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement.
Siswantoro, Joko; Prabuwono, Anton Satria; Abdullah, Azizi; Idrus, Bahari
2014-01-01
Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
Monte Carlo studies of high-transverse-energy hadronic interactions
International Nuclear Information System (INIS)
Corcoran, M.D.
1985-01-01
A four-jet Monte Carlo calculation has been used to simulate hadron-hadron interactions which deposit high transverse energy into a large-solid-angle calorimeter and limited solid-angle regions of the calorimeter. The calculation uses first-order QCD cross sections to generate two scattered jets and also produces beam and target jets. Field-Feynman fragmentation has been used in the hadronization. The sensitivity of the results to a few features of the Monte Carlo program has been studied. The results are found to be very sensitive to the method used to ensure overall energy conservation after the fragmentation of the four jets is complete. Results are also sensitive to the minimum momentum transfer in the QCD subprocesses and to the distribution of p/sub T/ to the jet axis and the multiplicities in the fragmentation. With reasonable choices of these features of the Monte Carlo program, good agreement with data at Fermilab/CERN SPS energies is obtained, comparable to the agreement achieved with more sophisticated parton-shower models. With other choices, however, the calculation gives qualitatively different results which are in strong disagreement with the data. These results have important implications for extracting physics conclusions from Monte Carlo calculations. It is not possible to test the validity of a particular model or distinguish between different models unless the Monte Carlo results are unambiguous and different models exhibit clearly different behavior
Parallel MCNP Monte Carlo transport calculations with MPI
International Nuclear Information System (INIS)
Wagner, J.C.; Haghighat, A.
1996-01-01
The steady increase in computational performance has made Monte Carlo calculations for large/complex systems possible. However, in order to make these calculations practical, order of magnitude increases in performance are necessary. The Monte Carlo method is inherently parallel (particles are simulated independently) and thus has the potential for near-linear speedup with respect to the number of processors. Further, the ever-increasing accessibility of parallel computers, such as workstation clusters, facilitates the practical use of parallel Monte Carlo. Recognizing the nature of the Monte Carlo method and the trends in available computing, the code developers at Los Alamos National Laboratory implemented the message-passing general-purpose Monte Carlo radiation transport code MCNP (version 4A). The PVM package was chosen by the MCNP code developers because it supports a variety of communication networks, several UNIX platforms, and heterogeneous computer systems. This PVM version of MCNP has been shown to produce speedups that approach the number of processors and thus, is a very useful tool for transport analysis. Due to software incompatibilities on the local IBM SP2, PVM has not been available, and thus it is not possible to take advantage of this useful tool. Hence, it became necessary to implement an alternative message-passing library package into MCNP. Because the message-passing interface (MPI) is supported on the local system, takes advantage of the high-speed communication switches in the SP2, and is considered to be the emerging standard, it was selected
Monte Carlo methods for the reliability analysis of Markov systems
International Nuclear Information System (INIS)
Buslik, A.J.
1985-01-01
This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator
A general transform for variance reduction in Monte Carlo simulations
International Nuclear Information System (INIS)
Becker, T.L.; Larsen, E.W.
2011-01-01
This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)
Acceleration of monte Carlo solution by conjugate gradient method
International Nuclear Information System (INIS)
Toshihisa, Yamamoto
2005-01-01
The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)
Study of Gamma spectra by Monte Carlo simulation
International Nuclear Information System (INIS)
Cantaragiu, A.; Gheorghies, A.; Borcia, C.
2008-01-01
The purpose of this paper is obtaining gamma ray spectra by means of a scintillation detector applying the Monte Carlo statistic simulation method using the EGS4 program. The Monte Carlo algorithm implies that the physical system is described by the probability density function which allows generating random figures and the result is taken as an average of numbers which were observed. The EGS4 program allows the simulation of the following physical processes: the photo-electrical effect, the Compton effect, the electron positron pairs generation and the Rayleigh diffusion. The gamma rays recorded by the detector are converted into electrical pulses and the gamma ray spectra are acquired and processed by means of the Nomad Plus portable spectrometer connected to a computer. As a gamma ray sources 137Cs and 60Co are used whose spectra drawn and used for study the interaction of the gamma radiations with the scintillation detector. The parameters which varied during the acquisition of the gamma ray spectra are the distance between source and detector and the measuring time. Due to the statistical processes in the detector, the peak looks like a Gauss distribution. The identification of the gamma quantum energy value is achieved by the experimental spectra peaks, thus gathering information about the position of the peak, the width and the area of the peak respectively. By means of the EGS4 program a simulation is run using these parameters and an 'ideal' spectrum is obtained, a spectrum which is not influenced by the statistical processes which take place inside the detector. Then, the convolution of the spectra is achieved by means of a normalised Gauss function. There is a close match between the experimental results and those simulated in the EGS4 program because the interactions which occurred during the simulation have a statistical behaviour close to the real one. (authors)
Applications guide to the MORSE Monte Carlo code
International Nuclear Information System (INIS)
Cramer, S.N.
1985-08-01
A practical guide for the implementation of the MORESE-CG Monte Carlo radiation transport computer code system is presented. The various versions of the MORSE code are compared and contrasted, and the many references dealing explicitly with the MORSE-CG code are reviewed. The treatment of angular scattering is discussed, and procedures for obtaining increased differentiality of results in terms of reaction types and nuclides from a multigroup Monte Carlo code are explained in terms of cross-section and geometry data manipulation. Examples of standard cross-section data input and output are shown. Many other features of the code system are also reviewed, including (1) the concept of primary and secondary particles, (2) fission neutron generation, (3) albedo data capability, (4) DOMINO coupling, (5) history file use for post-processing of results, (6) adjoint mode operation, (7) variance reduction, and (8) input/output. In addition, examples of the combinatorial geometry are given, and the new array of arrays geometry feature (MARS) and its three-dimensional plotting code (JUNEBUG) are presented. Realistic examples of user routines for source, estimation, path-length stretching, and cross-section data manipulation are given. A deatiled explanation of the coupling between the random walk and estimation procedure is given in terms of both code parameters and physical analogies. The operation of the code in the adjoint mode is covered extensively. The basic concepts of adjoint theory and dimensionality are discussed and examples of adjoint source and estimator user routines are given for all common situations. Adjoint source normalization is explained, a few sample problems are given, and the concept of obtaining forward differential results from adjoint calculations is covered. Finally, the documentation of the standard MORSE-CG sample problem package is reviewed and on-going and future work is discussed
International Nuclear Information System (INIS)
Kling, A.; Barao, F.J.C.; Nakagawa, M.; Tavora, L.
2001-01-01
The following topics were dealt with: Electron and photon interactions and transport mechanisms, random number generation, applications in medical physisc, microdosimetry, track structure, radiobiological modeling, Monte Carlo method in radiotherapy, dosimetry, and medical accelerator simulation, neutron transport, high-energy hadron transport. (HSI)
Thomas B. Lynch; Jeffrey H. Gove
2014-01-01
The typical "double counting" application of the mirage method of boundary correction cannot be applied to sampling systems such as critical height sampling (CHS) that are based on a Monte Carlo sample of a tree (or debris) attribute because the critical height (or other random attribute) sampled from a mirage point is generally not equal to the critical...
New family of probability distributions with applications to Monte Carlo studies
International Nuclear Information System (INIS)
Johnson, M.E.; Tietjen, G.L.; Beckman, R.J.
1980-01-01
A new probability distribution is presented that offers considerable potential for providing stochastic inputs to Monte Carlo simulation studies. The distribution includes the exponential power family as a special case. An efficient computational strategy is proposed for random variate generation. An example for testing the hypothesis of unit variance illustrates the advantages of the proposed distribution
Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations
Hoogenboom, J. Eduard; Dufek, Jan
2014-06-01
This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.
Monte Carlo simulation of neutron counters for safeguards applications
International Nuclear Information System (INIS)
Looman, Marc; Peerani, Paolo; Tagziria, Hamid
2009-01-01
MCNP-PTA is a new Monte Carlo code for the simulation of neutron counters for nuclear safeguards applications developed at the Joint Research Centre (JRC) in Ispra (Italy). After some preliminary considerations outlining the general aspects involved in the computational modelling of neutron counters, this paper describes the specific details and approximations which make up the basis of the model implemented in the code. One of the major improvements allowed by the use of Monte Carlo simulation is a considerable reduction in both the experimental work and in the reference materials required for the calibration of the instruments. This new approach to the calibration of counters using Monte Carlo simulation techniques is also discussed.
LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events
Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V
2008-01-01
In this paper we report on LCG Monte Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC collaborations by experts. In many cases, the modern Monte Carlo simulation of physical processes requires expert knowledge in Monte Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project.
Monte Carlo simulated dynamical magnetization of single-chain magnets
Energy Technology Data Exchange (ETDEWEB)
Li, Jun; Liu, Bang-Gui, E-mail: bgliu@iphy.ac.cn
2015-03-15
Here, a dynamical Monte-Carlo (DMC) method is used to study temperature-dependent dynamical magnetization of famous Mn{sub 2}Ni system as typical example of single-chain magnets with strong magnetic anisotropy. Simulated magnetization curves are in good agreement with experimental results under typical temperatures and sweeping rates, and simulated coercive fields as functions of temperature are also consistent with experimental curves. Further analysis indicates that the magnetization reversal is determined by both thermal-activated effects and quantum spin tunnelings. These can help explore basic properties and applications of such important magnetic systems. - Highlights: • Monte Carlo simulated magnetization curves are in good agreement with experimental results. • Simulated coercive fields as functions of temperature are consistent with experimental results. • The magnetization reversal is understood in terms of the Monte Carlo simulations.
BACKWARD AND FORWARD MONTE CARLO METHOD IN POLARIZED RADIATIVE TRANSFER
Energy Technology Data Exchange (ETDEWEB)
Yong, Huang; Guo-Dong, Shi; Ke-Yong, Zhu, E-mail: huangy_zl@263.net [School of Aeronautical Science and Engineering, Beihang University, Beijing 100191 (China)
2016-03-20
In general, the Stocks vector cannot be calculated in reverse in the vector radiative transfer. This paper presents a novel backward and forward Monte Carlo simulation strategy to study the vector radiative transfer in the participated medium. A backward Monte Carlo process is used to calculate the ray trajectory and the endpoint of the ray. The Stocks vector is carried out by a forward Monte Carlo process. A one-dimensional graded index semi-transparent medium was presented as the physical model and the thermal emission consideration of polarization was studied in the medium. The solution process to non-scattering, isotropic scattering, and the anisotropic scattering medium, respectively, is discussed. The influence of the optical thickness and albedo on the Stocks vector are studied. The results show that the U, V-components of the apparent Stocks vector are very small, but the Q-component of the apparent Stocks vector is relatively larger, which cannot be ignored.
Minimum variance Monte Carlo importance sampling with parametric dependence
International Nuclear Information System (INIS)
Ragheb, M.M.H.; Halton, J.; Maynard, C.W.
1981-01-01
An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de
MORET: Version 4.B. A multigroup Monte Carlo criticality code
International Nuclear Information System (INIS)
Jacquet, Olivier; Miss, Joachim; Courtois, Gerard
2003-01-01
MORET 4 is a three dimensional multigroup Monte Carlo code which calculates the effective multiplication factor (keff) of any configurations more or less complex as well as reaction rates in the different volumes of the geometry and the leakage out of the system. MORET 4 is the Monte Carlo code of the APOLLO2-MORET 4 standard route of CRISTAL, the French criticality package. It is the most commonly used Monte Carlo code for French criticality calculations. During the last four years, the MORET 4 team has developed or improved the following major points: modernization of the geometry, implementation of perturbation algorithms, source distribution convergence, statistical detection of stationarity, unbiased variance estimation and creation of pre-processing and post-processing tools. The purpose of this paper is not only to present the new features of MORET but also to detail clearly the physical models and the mathematical methods used in the code. (author)
Monte Carlo tests of the ELIPGRID-PC algorithm
International Nuclear Information System (INIS)
Davidson, J.R.
1995-04-01
The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM reg-sign PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within ±0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangular sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error
Rapid Monte Carlo Simulation of Gravitational Wave Galaxies
Breivik, Katelyn; Larson, Shane L.
2015-01-01
With the detection of gravitational waves on the horizon, astrophysical catalogs produced by gravitational wave observatories can be used to characterize the populations of sources and validate different galactic population models. Efforts to simulate gravitational wave catalogs and source populations generally focus on population synthesis models that require extensive time and computational power to produce a single simulated galaxy. Monte Carlo simulations of gravitational wave source populations can also be used to generate observation catalogs from the gravitational wave source population. Monte Carlo simulations have the advantes of flexibility and speed, enabling rapid galactic realizations as a function of galactic binary parameters with less time and compuational resources required. We present a Monte Carlo method for rapid galactic simulations of gravitational wave binary populations.
Stabilization effect of fission source in coupled Monte Carlo simulations
Energy Technology Data Exchange (ETDEWEB)
Olsen, Borge; Dufek, Jan [Div. of Nuclear Reactor Technology, KTH Royal Institute of Technology, AlbaNova University Center, Stockholm (Sweden)
2017-08-15
A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.
Exploring cluster Monte Carlo updates with Boltzmann machines
Wang, Lei
2017-11-01
Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.
Exploring cluster Monte Carlo updates with Boltzmann machines.
Wang, Lei
2017-11-01
Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.
Analysis of error in Monte Carlo transport calculations
International Nuclear Information System (INIS)
Booth, T.E.
1979-01-01
The Monte Carlo method for neutron transport calculations suffers, in part, because of the inherent statistical errors associated with the method. Without an estimate of these errors in advance of the calculation, it is difficult to decide what estimator and biasing scheme to use. Recently, integral equations have been derived that, when solved, predicted errors in Monte Carlo calculations in nonmultiplying media. The present work allows error prediction in nonanalog Monte Carlo calculations of multiplying systems, even when supercritical. Nonanalog techniques such as biased kernels, particle splitting, and Russian Roulette are incorporated. Equations derived here allow prediction of how much a specific variance reduction technique reduces the number of histories required, to be weighed against the change in time required for calculation of each history. 1 figure, 1 table
A Monte Carlo burnup code linking MCNP and REBUS
International Nuclear Information System (INIS)
Hanan, N.A.; Olson, A.P.; Pond, R.B.; Matos, J.E.
1998-01-01
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 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. (author)
A Multivariate Time Series Method for Monte Carlo Reactor Analysis
International Nuclear Information System (INIS)
Taro Ueki
2008-01-01
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
A Monte Carlo burnup code linking MCNP and REBUS
International Nuclear Information System (INIS)
Hanan, N. A.
1998-01-01
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
Calibration and Monte Carlo modelling of neutron long counters
Tagziria, H
2000-01-01
The Monte Carlo technique has become a very powerful tool in radiation transport as full advantage is taken of enhanced cross-section data, more powerful computers and statistical techniques, together with better characterisation of neutron and photon source spectra. At the National Physical Laboratory, calculations using the Monte Carlo radiation transport code MCNP-4B have been combined with accurate measurements to characterise two long counters routinely used to standardise monoenergetic neutron fields. New and more accurate response function curves have been produced for both long counters. A novel approach using Monte Carlo methods has been developed, validated and used to model the response function of the counters and determine more accurately their effective centres, which have always been difficult to establish experimentally. Calculations and measurements agree well, especially for the De Pangher long counter for which details of the design and constructional material are well known. The sensitivit...
Geometry and Dynamics for Markov Chain Monte Carlo
Barp, Alessandro; Briol, François-Xavier; Kennedy, Anthony D.; Girolami, Mark
2018-03-01
Markov Chain Monte Carlo methods have revolutionised mathematical computation and enabled statistical inference within many previously intractable models. In this context, Hamiltonian dynamics have been proposed as an efficient way of building chains which can explore probability densities efficiently. The method emerges from physics and geometry and these links have been extensively studied by a series of authors through the last thirty years. However, there is currently a gap between the intuitions and knowledge of users of the methodology and our deep understanding of these theoretical foundations. The aim of this review is to provide a comprehensive introduction to the geometric tools used in Hamiltonian Monte Carlo at a level accessible to statisticians, machine learners and other users of the methodology with only a basic understanding of Monte Carlo methods. This will be complemented with some discussion of the most recent advances in the field which we believe will become increasingly relevant to applied scientists.
Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Naess, Arvid
2012-01-01
This paper discusses the estimation of the failure probability of wind turbines required by codes of practice for designing them. The Standard Monte Carlo (SMC) simulations may be used for this reason conceptually as an alternative to the popular Peaks-Over-Threshold (POT) method. However......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy...... is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated...
Monte Carlo simulation of continuous-space crystal growth
International Nuclear Information System (INIS)
Dodson, B.W.; Taylor, P.A.
1986-01-01
We describe a method, based on Monte Carlo techniques, of simulating the atomic growth of crystals without the discrete lattice space assumed by conventional Monte Carlo growth simulations. Since no lattice space is assumed, problems involving epitaxial growth, heteroepitaxy, phonon-driven mechanisms, surface reconstruction, and many other phenomena incompatible with the lattice-space approximation can be studied. Also, use of the Monte Carlo method circumvents to some extent the extreme limitations on simulated timescale inherent in crystal-growth techniques which might be proposed using molecular dynamics. The implementation of the new method is illustrated by studying the growth of strained-layer superlattice (SLS) interfaces in two-dimensional Lennard-Jones atomic systems. Despite the extreme simplicity of such systems, the qualitative features of SLS growth seen here are similar to those observed experimentally in real semiconductor systems
Adaptive anisotropic diffusion filtering of Monte Carlo dose distributions
International Nuclear Information System (INIS)
Miao Binhe; Jeraj, Robert; Bao Shanglian; Mackie, Thomas R
2003-01-01
The Monte Carlo method is the most accurate method for radiotherapy dose calculations, if used correctly. However, any Monte Carlo dose calculation is burdened with statistical noise. In this paper, denoising of Monte Carlo dose distributions with a three-dimensional adaptive anisotropic diffusion method was investigated. The standard anisotropic diffusion method was extended by changing the filtering parameters adaptively according to the local statistical noise. Smoothing of dose distributions with different noise levels in an inhomogeneous phantom, a conventional and an IMRT treatment case is shown. The resultant dose distributions were analysed using several evaluating criteria. It is shown that the adaptive anisotropic diffusion method can reduce statistical noise significantly (two to five times, corresponding to the reduction of simulation time by a factor of up to 20), while preserving important gradients of the dose distribution well. The choice of free parameters of the method was found to be fairly robust
Benchmarking time-dependent neutron problems with Monte Carlo codes
International Nuclear Information System (INIS)
Couet, B.; Loomis, W.A.
1990-01-01
Many nuclear logging tools measure the time dependence of a neutron flux in a geological formation to infer important properties of the formation. The complex geometry of the tool and the borehole within the formation does not permit an exact deterministic modelling of the neutron flux behaviour. While this exact simulation is possible with Monte Carlo methods the computation time does not facilitate quick turnaround of results useful for design and diagnostic purposes. Nonetheless a simple model based on the diffusion-decay equation for the flux of neutrons of a single energy group can be useful in this situation. A combination approach where a Monte Carlo calculation benchmarks a deterministic model in terms of the diffusion constants of the neutrons propagating in the media and their flux depletion rates thus offers the possibility of quick calculation with assurance as to accuracy. We exemplify this approach with the Monte Carlo benchmarking of a logging tool problem, showing standoff and bedding response. (author)
Parallelization of a Monte Carlo particle transport simulation code
Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.
2010-05-01
We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.
Parallel Monte Carlo simulations on an ARC-enabled computing grid
International Nuclear Information System (INIS)
Nilsen, Jon K; Samset, Bjørn H
2011-01-01
Grid computing opens new possibilities for running heavy Monte Carlo simulations of physical systems in parallel. The presentation gives an overview of GaMPI, a system for running an MPI-based random walker simulation on grid resources. Integrating the ARC middleware and the new storage system Chelonia with the Ganga grid job submission and control system, we show that MPI jobs can be run on a world-wide computing grid with good performance and promising scaling properties. Results for relatively communication-heavy Monte Carlo simulations run on multiple heterogeneous, ARC-enabled computing clusters in several countries are presented.
Parameter uncertainty and model predictions: a review of Monte Carlo results
International Nuclear Information System (INIS)
Gardner, R.H.; O'Neill, R.V.
1979-01-01
Studies of parameter variability by Monte Carlo analysis are reviewed using repeated simulations of the model with randomly selected parameter values. At the beginning of each simulation, parameter values are chosen from specific frequency distributions. This process is continued for a number of iterations sufficient to converge on an estimate of the frequency distribution of the output variables. The purpose was to explore the general properties of error propagaton in models. Testing the implicit assumptions of analytical methods and pointing out counter-intuitive results produced by the Monte Carlo approach are additional points covered
An improved wavelength selection scheme for Monte Carlo solvers applied to hypersonic plasmas
International Nuclear Information System (INIS)
Feldick, Andrew; Modest, Michael F.
2011-01-01
A new databasing scheme is developed for Monte Carlo Ray Tracing methods applied to hypersonic planetary entry. In this scheme, the complex relationships for the emission wavelength selection of atomic and molecular species in nonequilibrium flows are simplified by developing random number relationships for individual transitions, as opposed to using relationships for the spectral emission coefficient of a given species. These new techniques speed up wavelength selection by about 2 orders of magnitude, and offer flexibility for use in weighted or part-spectrum Monte Carlo solvers.
Directory of Open Access Journals (Sweden)
Hammou Amine Bouziane
2013-03-01
Full Text Available We study the thermodynamic and structural properties of a flexible homopolymer chain using both multi canonical Monte Carlo method and Wang-Landau method. In this work, we focus on the coil-globule transition. Starting from a completely random chain, we have obtained a globule for different sizes of the chain. The implementation of these advanced Monte Carlo methods allowed us to obtain a flat histogram in energy space and calculate various thermodynamic quantities such as the density of states, the free energy and the specific heat. Structural quantities such as the radius of gyration where also calculated.
RNA folding kinetics using Monte Carlo and Gillespie algorithms.
Clote, Peter; Bayegan, Amir H
2018-04-01
RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .
Monte Carlo burnup codes acceleration using the correlated sampling method
International Nuclear Information System (INIS)
Dieudonne, C.
2013-01-01
For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this document we present an original methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time we develop a theoretical model to study the features of the correlated sampling method to understand its effects on depletion calculations. In a third time the implementation of this method in the TRIPOLI-4 code will be discussed, as well as the precise calculation scheme used to bring important speed-up of the depletion calculation. We will begin to validate and optimize the perturbed depletion scheme with the calculation of a REP-like fuel cell depletion. Then this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes. (author) [fr
Modelling of electron contamination in clinical photon beams for Monte Carlo dose calculation
International Nuclear Information System (INIS)
Yang, J; Li, J S; Qin, L; Xiong, W; Ma, C-M
2004-01-01
The purpose of this work is to model electron contamination in clinical photon beams and to commission the source model using measured data for Monte Carlo treatment planning. In this work, a planar source is used to represent the contaminant electrons at a plane above the upper jaws. The source size depends on the dimensions of the field size at the isocentre. The energy spectra of the contaminant electrons are predetermined using Monte Carlo simulations for photon beams from different clinical accelerators. A 'random creep' method is employed to derive the weight of the electron contamination source by matching Monte Carlo calculated monoenergetic photon and electron percent depth-dose (PDD) curves with measured PDD curves. We have integrated this electron contamination source into a previously developed multiple source model and validated the model for photon beams from Siemens PRIMUS accelerators. The EGS4 based Monte Carlo user code BEAM and MCSIM were used for linac head simulation and dose calculation. The Monte Carlo calculated dose distributions were compared with measured data. Our results showed good agreement (less than 2% or 2 mm) for 6, 10 and 18 MV photon beams
Response matrix Monte Carlo based on a general geometry local calculation for electron transport
International Nuclear Information System (INIS)
Ballinger, C.T.; Rathkopf, J.A.; Martin, W.R.
1991-01-01
A Response Matrix Monte Carlo (RMMC) method has been developed for solving electron transport problems. This method was born of the need to have a reliable, computationally efficient transport method for low energy electrons (below a few hundred keV) in all materials. Today, condensed history methods are used which reduce the computation time by modeling the combined effect of many collisions but fail at low energy because of the assumptions required to characterize the electron scattering. Analog Monte Carlo simulations are prohibitively expensive since electrons undergo coulombic scattering with little state change after a collision. The RMMC method attempts to combine the accuracy of an analog Monte Carlo simulation with the speed of the condensed history methods. Like condensed history, the RMMC method uses probability distributions functions (PDFs) to describe the energy and direction of the electron after several collisions. However, unlike the condensed history method the PDFs are based on an analog Monte Carlo simulation over a small region. Condensed history theories require assumptions about the electron scattering to derive the PDFs for direction and energy. Thus the RMMC method samples from PDFs which more accurately represent the electron random walk. Results show good agreement between the RMMC method and analog Monte Carlo. 13 refs., 8 figs
Optimization of the Monte Carlo code for modeling of photon migration in tissue.
Zołek, Norbert S; Liebert, Adam; Maniewski, Roman
2006-10-01
The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.
Quasi-Monte Carlo methods: applications to modeling of light transport in tissue
Schafer, Steven A.
1996-05-01
Monte Carlo modeling of light propagation can accurately predict the distribution of light in scattering materials. A drawback of Monte Carlo methods is that they converge inversely with the square root of the number of iterations. Theoretical considerations suggest that convergence which scales inversely with the first power of the number of iterations is possible. We have previously shown that one can obtain at least a portion of that improvement by using van der Corput sequences in place of a conventional pseudo-random number generator. Here, we present our further analysis, and show that quasi-Monte Carlo methods do have limited applicability to light scattering problems. We also discuss potential improvements which may increase the applicability.
A first look at quasi-Monte Carlo for lattice field theory problems
International Nuclear Information System (INIS)
Jansen, K; Nube, A; Leovey, H; Griewank, A; Mueller-Preussker, M
2013-01-01
In this project we initiate an investigation of the applicability of Quasi-Monte Carlo methods to lattice field theories in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Monte Carlo simulation behaves like N −1/2 , where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems to up to N −1 . We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling
Quasi-Monte Carlo methods for lattice systems. A first look
Energy Technology Data Exchange (ETDEWEB)
Jansen, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Cyprus Univ., Nicosia (Cyprus). Dept. of Physics; Leovey, H.; Griewank, A. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Mathematik; Nube, A. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik; Mueller-Preussker, M. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik
2013-02-15
We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N{sup -1/2}, where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems up to N{sup -1}. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
A first look at Quasi-Monte Carlo for lattice field theory problems
Energy Technology Data Exchange (ETDEWEB)
Jansen, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leovey, H.; Griewank, A. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Mathematik; Nube, A. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik; Mueller-Preussker, M. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik
2012-11-15
In this project we initiate an investigation of the applicability of Quasi-Monte Carlo methods to lattice field theories in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Monte Carlo simulation behaves like N{sup -1/2}, where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems to up to N{sup -1}. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
MCNP-REN a Monte Carlo tool for neutron detector design
Abhold, M E
2002-01-01
The development of neutron detectors makes extensive use of the predictions of detector response through the use of Monte Carlo techniques in conjunction with the point reactor model. Unfortunately, the point reactor model fails to accurately predict detector response in common applications. For this reason, the general Monte Carlo code developed at Los Alamos National Laboratory, Monte Carlo N-Particle (MCNP), was modified to simulate the pulse streams that would be generated by a neutron detector and normally analyzed by a shift register. This modified code, MCNP-Random Exponentially Distributed Neutron Source (MCNP-REN), along with the Time Analysis Program, predicts neutron detector response without using the point reactor model, making it unnecessary for the user to decide whether or not the assumptions of the point model are met for their application. MCNP-REN is capable of simulating standard neutron coincidence counting as well as neutron multiplicity counting. Measurements of mixed oxide fresh fuel w...
Monte Carlo calculation of Dancoff factors in irregular geometries
International Nuclear Information System (INIS)
Feher, S.; Hoogenboom, J.E.; Leege, P.F.A. de; Valko, J.
1994-01-01
A Monte Carlo program is described that calculates Dancoff factors in arbitrary arrangements of cylindrical or spherical fuel elements. The fuel elements can have different diameters and material compositions, and they are allowed to be black or partially transparent. Calculations of the Dancoff factor is based on its collision probability definition. The Monte Carlo approach is recommended because it is equally applicable in simple and in complicated geometries. It is shown that some of the commonly used algorithms are inaccurate even in infinite regular lattices. An example of application includes the Canada deuterium uranium (CANDU) 37-pin fuel bundle, which requires different Dancoff factors for the symmetrically different fuel pin positions
Scouting the feasibility of Monte Carlo reactor dynamics simulations
International Nuclear Information System (INIS)
Legrady, David; Hoogenboom, J. Eduard
2008-01-01
In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)
Scouting the feasibility of Monte Carlo reactor dynamics simulations
Energy Technology Data Exchange (ETDEWEB)
Legrady, David [Forschungszentrum Dresden-Rossendorf, Dresden (Germany); Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)
2008-07-01
In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)
Monte Carlo studies of domain growth in two dimensions
International Nuclear Information System (INIS)
Yaldram, K.; Ahsan Khan, M.
1983-07-01
Monte Carlo simulations have been carried out to study the effect of temperature on the kinetics of domain growth. The concept of ''spatial entropy'' is introduced. It is shown that ''spatial entropy'' of the domain can be used to give a measure of the roughening of the domain. Most of the roughening is achieved during the initial time (t< or approx. 10 Monte Carlo cycles), the rate of roughening being greater for higher temperatures. For later times the roughening of the domain for different temperatures proceeds at essentially the same rate. (author)
Grain-boundary melting: A Monte Carlo study
DEFF Research Database (Denmark)
Besold, Gerhard; Mouritsen, Ole G.
1994-01-01
Grain-boundary melting in a lattice-gas model of a bicrystal is studied by Monte Carlo simulation using the grand canonical ensemble. Well below the bulk melting temperature T(m), a disordered liquidlike layer gradually emerges at the grain boundary. Complete interfacial wetting can be observed...... when the temperature approaches T(m) from below. Monte Carlo data over an extended temperature range indicate a logarithmic divergence w(T) approximately - ln(T(m)-T) of the width of the disordered layer w, in agreement with mean-field theory....
Control Variates for Monte Carlo Valuation of American Options
DEFF Research Database (Denmark)
Rasmussen, Nicki S.
2005-01-01
This paper considers two applications of control variates to the Monte Carlo valuation of American options. The main contribution of the paper lies in the particular choice of a control variate for American or Bermudan options. It is shown that for any martingale process used as a control variate...... technique is used for improving the least-squares Monte Carlo (LSM) approach for determining exercise strategies. The suggestions made allow for more efficient estimation of the continuation value, used in determining the strategy. An additional suggestion is made in order to improve the stability...
MONK - a general purpose Monte Carlo neutronics program
International Nuclear Information System (INIS)
Sherriffs, V.S.W.
1978-01-01
MONK is a Monte Carlo neutronics code written principally for criticality calculations relevant to the transport, storage, and processing of fissile material. The code exploits the ability of the Monte Carlo method to represent complex shapes with very great accuracy. The nuclear data used is derived from the UK Nuclear Data File processed to the required format by a subsidiary program POND. A general description is given of the MONK code together with the subsidiary program SCAN which produces diagrams of the system specified. Details of the data input required by MONK and SCAN are also given. (author)
Proceedings of the conference on frontiers of Quantum Monte Carlo
International Nuclear Information System (INIS)
Gubernatis, J.E.
1986-01-01
This journal of conference proceedings includes papers on topics such as: computers and science; Quantum Monte Carlo; condensed matter physics (with papers including the statistical error of Green's Function Monte Carlo, a study of Trotter-like approximations, simulations of the Hubbard model, and stochastic simulation of fermions); chemistry (including papers on quantum simulations of aqueous systems, fourier path integral methods, and a study of electron solvation in polar solvents using path integral calculations); atomic molecular and nuclear physics; high-energy physics, and advanced computer designs
Results of the Monte Carlo 'simple case' benchmark exercise
International Nuclear Information System (INIS)
2003-11-01
A new 'simple case' benchmark intercomparison exercise was launched, intended to study the importance of the fundamental nuclear data constants, physics treatments and geometry model approximations, employed by Monte Carlo codes in common use. The exercise was also directed at determining the level of agreement which can be expected between measured and calculated quantities, using current state or the art modelling codes and techniques. To this end, measurements and Monte Carlo calculations of the total (or gross) neutron count rates have been performed using a simple moderated 3 He cylindrical proportional counter array or 'slab monitor' counting geometry, deciding to select a very simple geometry for this exercise
Proton therapy analysis using the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Noshad, Houshyar [Center for Theoretical Physics and Mathematics, AEOI, P.O. Box 14155-1339, Tehran (Iran, Islamic Republic of)]. E-mail: hnoshad@aeoi.org.ir; Givechi, Nasim [Islamic Azad University, Science and Research Branch, Tehran (Iran, Islamic Republic of)
2005-10-01
The range and straggling data obtained from the transport of ions in matter (TRIM) computer program were used to determine the trajectories of monoenergetic 60 MeV protons in muscle tissue by using the Monte Carlo technique. The appropriate profile for the shape of a proton pencil beam in proton therapy as well as the dose deposited in the tissue were computed. The good agreements between our results as compared with the corresponding experimental values are presented here to show the reliability of our Monte Carlo method.
PEPSI — a Monte Carlo generator for polarized leptoproduction
Mankiewicz, L.; Schäfer, A.; Veltri, M.
1992-09-01
We describe PEPSI (Polarized Electron Proton Scattering Interactions), a Monte Carlo program for polarized deep inelastic leptoproduction mediated by electromagnetic interaction, and explain how to use it. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering. The hard virtual gamma-parton scattering is generated according to the polarization-dependent QCD cross-section of the first order in α S. PEPSI requires the standard polarization-independent JETSET routines to simulate the fragmentation into final hadrons.
PEPSI - a Monte Carlo generator for polarized leptoproduction
International Nuclear Information System (INIS)
Mankiewicz, L.
1992-01-01
We describe PEPSI (Polarized Electron Proton Scattering Interactions) a Monte Carlo program for polarized deep inelastic leptoproduction mediated by electromagnetic interaction, and explain how to use it. The code is a modification of the Lepto 4.3 Lund Monte Carlo for unpolarized scattering. The hard virtual gamma-parton scattering is generated according to the polarization-dependent QCD cross-section of the first order in α S . PEPSI requires the standard polarization-independent JETSET routines to simulate the fragmentation into final hadrons. (orig.)
Monte Carlo simulation of a gas-sampled hadron calorimeter
Energy Technology Data Exchange (ETDEWEB)
Chang, C Y; Kunori, S; Rapp, P; Talaga, R; Steinberg, P; Tylka, A J; Wang, Z M
1988-02-15
A prototype of the OPAL barrel hadron calorimeter, which is a gas-sampled calorimeter using plastic streamer tubes, was exposed to pions at energies between 1 and 7 GeV. The response of the detector was simulated using the CERN GEANT3 Monte Carlo program. By using the observed high energy muon signals to deduce details of the streamer formation, the Monte Carlo program was able to reproduce the observed calorimeter response. The behavior of the hadron calorimeter when placed behind a lead glass electromagnetic calorimeter was also investigated.