#### Sample records for monte carlo importance

1. Efficiency and accuracy of Monte Carlo (importance) sampling

NARCIS (Netherlands)

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

2. Monte Carlo methods

OpenAIRE

Bardenet, R.

2012-01-01

ISBN:978-2-7598-1032-1; International audience; 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 theoretic...

3. Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

KAUST Repository

Cheon, Sooyoung

2013-02-16

Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

4. Extended Ensemble Monte Carlo

OpenAIRE

Iba, Yukito

2000-01-01

Extended Ensemble Monte Carlo''is a generic term that indicates a set of algorithms which are now popular in a variety of fields in physics and statistical information processing. Exchange Monte Carlo (Metropolis-Coupled Chain, Parallel Tempering), Simulated Tempering (Expanded Ensemble Monte Carlo), and Multicanonical Monte Carlo (Adaptive Umbrella Sampling) are typical members of this family. Here we give a cross-disciplinary survey of these algorithms with special emphasis on the great f...

5. Monte Carlo fundamentals

Energy Technology Data Exchange (ETDEWEB)

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

1996-02-01

This report is composed of the lecture notes from the first half of a 32-hour graduate-level course on Monte Carlo methods offered at KAPL. These notes, prepared by two of the principle developers of KAPLs RACER Monte Carlo code, cover the fundamental theory, concepts, and practices for Monte Carlo analysis. In particular, a thorough grounding in the basic fundamentals of Monte Carlo methods is presented, including random number generation, random sampling, the Monte Carlo approach to solving transport problems, computational geometry, collision physics, tallies, and eigenvalue calculations. Furthermore, modern computational algorithms for vector and parallel approaches to Monte Carlo calculations are covered in detail, including fundamental parallel and vector concepts, the event-based algorithm, master/slave schemes, parallel scaling laws, and portability issues.

6. Automatic variance reduction for Monte Carlo simulations via the local importance function transform

Energy Technology Data Exchange (ETDEWEB)

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of real particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a black box. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.

7. Automatic variance reduction for Monte Carlo simulations via the local importance function transform

Energy Technology Data Exchange (ETDEWEB)

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of real particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a black box. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.

8. Exploring Monte Carlo methods

CERN Document Server

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

9. Automated importance generation and biasing techniques for Monte Carlo shielding techniques by the TRIPOLI-3 code

Energy Technology Data Exchange (ETDEWEB)

Both, J.P.; Nimal, J.C.; Vergnaud, T. (CEA Centre d' Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette (France). Service d' Etudes des Reacteurs et de Mathematiques Appliquees)

1990-01-01

We discuss an automated biasing procedure for generating the parameters necessary to achieve efficient Monte Carlo biasing shielding calculations. The biasing techniques considered here are exponential transform and collision biasing deriving from the concept of the biased game based on the importance function. We use a simple model of the importance function with exponential attenuation as the distance to the detector increases. This importance function is generated on a three-dimensional mesh including geometry and with graph theory algorithms. This scheme is currently being implemented in the third version of the neutron and gamma ray transport code TRIPOLI-3. (author).

10. MORSE Monte Carlo code

Energy Technology Data Exchange (ETDEWEB)

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.

11. Quantum Monte Carlo simulation

OpenAIRE

Wang, Yazhen

2011-01-01

Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating analytically intractable quantities. We derive the bias and variance for the proposed Monte Carlo quantum simulation estimator and establish the asymptotic theory for the estimator. The theory is used to design a computational scheme for minimizing the mean square er...

12. Monte Carlo transition probabilities

OpenAIRE

Lucy, L. B.

2001-01-01

Transition probabilities governing the interaction of energy packets and matter are derived that allow Monte Carlo NLTE transfer codes to be constructed without simplifying the treatment of line formation. These probabilities are such that the Monte Carlo calculation asymptotically recovers the local emissivity of a gas in statistical equilibrium. Numerical experiments with one-point statistical equilibrium problems for Fe II and Hydrogen confirm this asymptotic behaviour. In addition, the re...

13. Monte Carlo importance sampling for the MCNP{trademark} general source

Energy Technology Data Exchange (ETDEWEB)

Lichtenstein, H.

1996-01-09

Research was performed to develop an importance sampling procedure for a radiation source. The procedure was developed for the MCNP radiation transport code, but the approach itself is general and can be adapted to other Monte Carlo codes. The procedure, as adapted to MCNP, relies entirely on existing MCNP capabilities. It has been tested for very complex descriptions of a general source, in the context of the design of spent-reactor-fuel storage casks. Dramatic improvements in calculation efficiency have been observed in some test cases. In addition, the procedure has been found to provide an acceleration to acceptable convergence, as well as the benefit of quickly identifying user specified variance-reduction in the transport that effects unstable convergence.

14. The Virtual Monte Carlo

CERN Document Server

Hrivnacova, I; Berejnov, V V; Brun, R; Carminati, F; Fassò, A; Futo, E; Gheata, A; Caballero, I G; Morsch, Andreas

2003-01-01

The concept of Virtual Monte Carlo (VMC) has been developed by the ALICE Software Project to allow different Monte Carlo simulation programs to run without changing the user code, such as the geometry definition, the detector response simulation or input and output formats. Recently, the VMC classes have been integrated into the ROOT framework, and the other relevant packages have been separated from the AliRoot framework and can be used individually by any other HEP project. The general concept of the VMC and its set of base classes provided in ROOT will be presented. Existing implementations for Geant3, Geant4 and FLUKA and simple examples of usage will be described.

15. The importance of axonal undulation in diffusion MR measurements: a Monte Carlo simulation study.

Science.gov (United States)

Nilsson, Markus; Lätt, Jimmy; Ståhlberg, Freddy; van Westen, Danielle; Hagslätt, Håkan

2012-05-01

Many axons follow wave-like undulating courses. This is a general feature of extracranial nerve segments, but is also found in some intracranial nervous tissue. The importance of axonal undulation has previously been considered, for example, in the context of biomechanics, where it has been shown that posture affects undulation properties. However, the importance of axonal undulation in the context of diffusion MR measurements has not been investigated. Using an analytical model and Monte Carlo simulations of water diffusion, this study compared undulating and straight axons in terms of diffusion propagators, diffusion-weighted signal intensities and parameters derived from diffusion tensor imaging, such as the mean diffusivity (MD), the eigenvalues and the fractional anisotropy (FA). All parameters were strongly affected by the presence of undulation. The diffusivity perpendicular to the undulating axons increased with the undulation amplitude, thus resembling that of straight axons with larger diameters. Consequently, models assuming straight axons for the estimation of the axon diameter from diffusion MR measurements might overestimate the diameter if undulation is present. FA decreased from approximately 0.7 to 0.5 when axonal undulation was introduced into the simulation model structure. Our results indicate that axonal undulation may play a role in diffusion measurements when investigating, for example, the optic and sciatic nerves and the spinal cord. The simulations also demonstrate that the stretching or compression of neuronal tissue comprising undulating axons alters the observed water diffusivity, suggesting that posture may be of importance for the outcome of diffusion MRI measurements.

16. Equilibrium Statistics: Monte Carlo Methods

Science.gov (United States)

Kröger, Martin

Monte Carlo methods use random numbers, or ‘random’ sequences, to sample from a known shape of a distribution, or to extract distribution by other means. and, in the context of this book, to (i) generate representative equilibrated samples prior being subjected to external fields, or (ii) evaluate high-dimensional integrals. Recipes for both topics, and some more general methods, are summarized in this chapter. It is important to realize, that Monte Carlo should be as artificial as possible to be efficient and elegant. Advanced Monte Carlo ‘moves’, required to optimize the speed of algorithms for a particular problem at hand, are outside the scope of this brief introduction. One particular modern example is the wavelet-accelerated MC sampling of polymer chains [406].

17. Monte Carlo Option Princing

Directory of Open Access Journals (Sweden)

Cecilia Maya

2004-12-01

Full Text Available El método Monte Carlo se aplica a varios casos de valoración de opciones financieras. El método genera una buena aproximación al comparar su precisión con la de otros métodos numéricos. La estimación que produce la versión Cruda de Monte Carlo puede ser aún más exacta si se recurre a metodologías de reducción de la varianza entre las cuales se sugieren la variable antitética y de la variable de control. Sin embargo, dichas metodologías requieren un esfuerzo computacional mayor por lo cual las mismas deben ser evaluadas en términos no sólo de su precisión sino también de su eficiencia.

18. Monte Carlo and nonlinearities

CERN Document Server

Dauchet, Jérémi; Blanco, Stéphane; Caliot, Cyril; Charon, Julien; Coustet, Christophe; Hafi, Mouna El; Eymet, Vincent; Farges, Olivier; Forest, Vincent; Fournier, Richard; Galtier, Mathieu; Gautrais, Jacques; Khuong, Anaïs; Pelissier, Lionel; Piaud, Benjamin; Roger, Maxime; Terrée, Guillaume; Weitz, Sebastian

2016-01-01

The Monte Carlo method is widely used to numerically predict systems behaviour. However, its powerful incremental design assumes a strong premise which has severely limited application so far: the estimation process must combine linearly over dimensions. Here we show that this premise can be alleviated by projecting nonlinearities on a polynomial basis and increasing the configuration-space dimension. Considering phytoplankton growth in light-limited environments, radiative transfer in planetary atmospheres, electromagnetic scattering by particles and concentrated-solar-power-plant productions, we prove the real world usability of this advance on four test-cases that were so far regarded as impracticable by Monte Carlo approaches. We also illustrate an outstanding feature of our method when applied to sharp problems with interacting particles: handling rare events is now straightforward. Overall, our extension preserves the features that made the method popular: addressing nonlinearities does not compromise o...

19. Fundamentals of Monte Carlo

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.

20. LMC: Logarithmantic Monte Carlo

Science.gov (United States)

2017-06-01

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

1. Density matrix quantum Monte Carlo

CERN Document Server

Blunt, N S; Spencer, J S; Foulkes, W M C

2013-01-01

This paper describes a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system, thus granting access to arbitrary reduced density matrices and allowing expectation values of complicated non-local operators to be evaluated easily. The direct sampling of the density matrix also raises the possibility of calculating previously inaccessible entanglement measures. The algorithm closely resembles the recently introduced full configuration interaction quantum Monte Carlo method, but works all the way from infinite to zero temperature. We explain the theory underlying the method, describe the algorithm, and introduce an importance-sampling procedure to improve the stochastic efficiency. To demonstrate the potential of our approach, the energy and staggered magnetization of the isotropic antiferromagnetic Heisenberg model on small lattices and the concurrence of one-dimensional spin rings are compared to exact or well-established results. Finally, the nature of the sign problem...

2. MCMini: Monte Carlo on GPGPU

Energy Technology Data Exchange (ETDEWEB)

Marcus, Ryan C. [Los Alamos National Laboratory

2012-07-25

MCMini is a proof of concept that demonstrates the possibility for Monte Carlo neutron transport using OpenCL with a focus on performance. This implementation, written in C, shows that tracing particles and calculating reactions on a 3D mesh can be done in a highly scalable fashion. These results demonstrate a potential path forward for MCNP or other Monte Carlo codes.

3. Monte Carlo methods for electromagnetics

CERN Document Server

2009-01-01

Until now, novices had to painstakingly dig through the literature to discover how to use Monte Carlo techniques for solving electromagnetic problems. Written by one of the foremost researchers in the field, Monte Carlo Methods for Electromagnetics provides a solid understanding of these methods and their applications in electromagnetic computation. Including much of his own work, the author brings together essential information from several different publications.Using a simple, clear writing style, the author begins with a historical background and review of electromagnetic theory. After addressing probability and statistics, he introduces the finite difference method as well as the fixed and floating random walk Monte Carlo methods. The text then applies the Exodus method to Laplace's and Poisson's equations and presents Monte Carlo techniques for handing Neumann problems. It also deals with whole field computation using the Markov chain, applies Monte Carlo methods to time-varying diffusion problems, and ...

4. Metropolis Methods for Quantum Monte Carlo Simulations

OpenAIRE

Ceperley, D. M.

2003-01-01

Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector monte carlo ({\\it i.e.} diffusion Monte Carlo with rejection), multilevel sampling in path integral Monte Carlo, the sampling of permutations, ...

5. Lectures on Monte Carlo methods

CERN Document Server

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

6. 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.

7. Lattice gauge theories and Monte Carlo simulations

CERN Document Server

Rebbi, Claudio

1983-01-01

This volume is the most up-to-date review on Lattice Gauge Theories and Monte Carlo Simulations. It consists of two parts. Part one is an introductory lecture on the lattice gauge theories in general, Monte Carlo techniques and on the results to date. Part two consists of important original papers in this field. These selected reprints involve the following: Lattice Gauge Theories, General Formalism and Expansion Techniques, Monte Carlo Simulations. Phase Structures, Observables in Pure Gauge Theories, Systems with Bosonic Matter Fields, Simulation of Systems with Fermions.

8. Monte Carlo integration on GPU

OpenAIRE

Kanzaki, J.

2010-01-01

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

9. The Feynman Path Goes Monte Carlo

OpenAIRE

Sauer, Tilman

2001-01-01

Path integral Monte Carlo (PIMC) simulations have become an important tool for the investigation of the statistical mechanics of quantum systems. I discuss some of the history of applying the Monte Carlo method to non-relativistic quantum systems in path-integral representation. The principle feasibility of the method was well established by the early eighties, a number of algorithmic improvements have been introduced in the last two decades.

10. Monte Carlo Hamiltonian:Inverse Potential

Institute of Scientific and Technical Information of China (English)

LUO Xiang-Qian; CHENG Xiao-Ni; Helmut KR(O)GER

2004-01-01

The Monte Carlo Hamiltonian method developed recently allows to investigate the ground state and low-lying excited states of a quantum system,using Monte Carlo(MC)algorithm with importance sampling.However,conventional MC algorithm has some difficulties when applied to inverse potentials.We propose to use effective potential and extrapolation method to solve the problem.We present examples from the hydrogen system.

11. Monte Carlo simulations for plasma physics

Energy Technology Data Exchange (ETDEWEB)

Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X. [National Inst. for Fusion Science, Toki, Gifu (Japan)

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)

12. Monte Carlo methods for particle transport

CERN Document Server

Haghighat, Alireza

2015-01-01

The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...

13. Multilevel sequential Monte Carlo samplers

KAUST Repository

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.

14. Monte Carlo Hamiltonian: Linear Potentials

Institute of Scientific and Technical Information of China (English)

LUO Xiang-Qian; LIU Jin-Jiang; HUANG Chun-Qing; JIANG Jun-Qin; Helmut KROGER

2002-01-01

We further study the validity of the Monte Carlo Hamiltonian method. The advantage of the method,in comparison with the standard Monte Carlo Lagrangian approach, is its capability to study the excited states. Weconsider two quantum mechanical models: a symmetric one V(x) = |x|/2; and an asymmetric one V(x) = ∞, forx ＜ 0 and V(x) = x, for x ≥ 0. The results for the spectrum, wave functions and thermodynamical observables are inagreement with the analytical or Runge-Kutta calculations.

15. Proton Upset Monte Carlo Simulation

Science.gov (United States)

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

2009-01-01

The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.

16. Monte Carlo Particle Lists: MCPL

CERN Document Server

Kittelmann, Thomas; Knudsen, Erik B; Willendrup, Peter; Cai, Xiao Xiao; Kanaki, Kalliopi

2016-01-01

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.

17. CosmoPMC: Cosmology Population Monte Carlo

CERN Document Server

Kilbinger, Martin; Cappe, Olivier; Cardoso, Jean-Francois; Fort, Gersende; Prunet, Simon; Robert, Christian P; Wraith, Darren

2011-01-01

We present the public release of the Bayesian sampling algorithm for cosmology, CosmoPMC (Cosmology Population Monte Carlo). CosmoPMC explores the parameter space of various cosmological probes, and also provides a robust estimate of the Bayesian evidence. CosmoPMC is based on an adaptive importance sampling method called Population Monte Carlo (PMC). Various cosmology likelihood modules are implemented, and new modules can be added easily. The importance-sampling algorithm is written in C, and fully parallelised using the Message Passing Interface (MPI). Due to very little overhead, the wall-clock time required for sampling scales approximately with the number of CPUs. The CosmoPMC package contains post-processing and plotting programs, and in addition a Monte-Carlo Markov chain (MCMC) algorithm. The sampling engine is implemented in the library pmclib, and can be used independently. The software is available for download at http://www.cosmopmc.info.

18. Applications of Monte Carlo Methods in Calculus.

Science.gov (United States)

Gordon, Sheldon P.; Gordon, Florence S.

1990-01-01

Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)

19. Random Numbers and Monte Carlo Methods

Science.gov (United States)

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.

20. Quantum speedup of Monte Carlo methods.

Science.gov (United States)

Montanaro, Ashley

2015-09-08

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.

1. (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.

2. Monte Carlo dose distributions for radiosurgery

Energy Technology Data Exchange (ETDEWEB)

Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E. [Sevilla Univ. (Spain). Dept. Fisiologia Medica y Biofisica; Sanchez-Doblado, F. [Sevilla Univ. (Spain). Dept. Fisiologia Medica y Biofisica]|[Hospital Univ. Virgen Macarena, Sevilla (Spain). Servicio de Oncologia Radioterapica; Nunez, L. [Clinica Puerta de Hierro, Madrid (Spain). Servicio de Radiofisica; Arrans, R.; Sanchez-Calzado, J.A.; Errazquin, L. [Hospital Univ. Virgen Macarena, Sevilla (Spain). Servicio de Oncologia Radioterapica; Sanchez-Nieto, B. [Royal Marsden NHS Trust (United Kingdom). Joint Dept. of Physics]|[Inst. of Cancer Research, Sutton, Surrey (United Kingdom)

2001-07-01

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.)

3. Monte carlo simulations of organic photovoltaics.

Science.gov (United States)

Groves, Chris; Greenham, Neil C

2014-01-01

Monte Carlo simulations are a valuable tool to model the generation, separation, and collection of charges in organic photovoltaics where charges move by hopping in a complex nanostructure and Coulomb interactions between charge carriers are important. We review the Monte Carlo techniques that have been applied to this problem, and describe the results of simulations of the various recombination processes that limit device performance. We show how these processes are influenced by the local physical and energetic structure of the material, providing information that is useful for design of efficient photovoltaic systems.

4. Alternative Monte Carlo Approach for General Global Illumination

Institute of Scientific and Technical Information of China (English)

徐庆; 李朋; 徐源; 孙济洲

2004-01-01

An alternative Monte Carlo strategy for the computation of global illumination problem was presented.The proposed approach provided a new and optimal way for solving Monte Carlo global illumination based on the zero variance importance sampling procedure. A new importance driven Monte Carlo global illumination algorithm in the framework of the new computing scheme was developed and implemented. Results, which were obtained by rendering test scenes, show that this new framework and the newly derived algorithm are effective and promising.

5. Efficient kinetic Monte Carlo simulation

Science.gov (United States)

Schulze, Tim P.

2008-02-01

This paper concerns kinetic Monte Carlo (KMC) algorithms that have a single-event execution time independent of the system size. Two methods are presented—one that combines the use of inverted-list data structures with rejection Monte Carlo and a second that combines inverted lists with the Marsaglia-Norman-Cannon algorithm. The resulting algorithms apply to models with rates that are determined by the local environment but are otherwise arbitrary, time-dependent and spatially heterogeneous. While especially useful for crystal growth simulation, the algorithms are presented from the point of view that KMC is the numerical task of simulating a single realization of a Markov process, allowing application to a broad range of areas where heterogeneous random walks are the dominate simulation cost.

6. Adaptive Multilevel Monte Carlo Simulation

KAUST Repository

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).

7. Monte Carlo Tools

CERN Document Server

Sjöstrand, Torbjörn

2009-01-01

Given the current landscape in experimental high-energy physics, these lectures are focused on applications of event generators for hadron colliders like the Tevatron and LHC. Section 2 contains a first overview of the physics picture and the generator landscape. Thereafter section 3 describes the usage of matrix elements, section 4 the important topics of initial- and final-state showers, and section 5 how showers can be matched to different hard processes. The issue of multiparton interactions and their role in mimimum-bias and underlying-event physics is introduced in section 6, followed by some comments on hadronization in section 7. The article concludes with an outlook on the ongoing generator-development work in section 8.

8. Monte Carlo approach to turbulence

Energy Technology Data Exchange (ETDEWEB)

Dueben, P.; Homeier, D.; Muenster, G. [Muenster Univ. (Germany). Inst. fuer Theoretische Physik; Jansen, K. [DESY, Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Mesterhazy, D. [Humboldt Univ., Berlin (Germany). Inst. fuer Physik

2009-11-15

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

9. MONTE CARLO SIMULATION: IMPORTANT MANAGEMENT TOOL IN EVALUATING DECISIONS UNDER RISK. CASE STUDY: LAUNCH A NEW PRODUCT OF SHOES

Directory of Open Access Journals (Sweden)

Veres Vincentiu

2013-07-01

Full Text Available Decisions are a result of choices made between several alternatives and will affect all participants in the decision-making process. In this paper we analyze the Monte Carlo simulation as an important management tool in evaluating decisions under risk. The method is particularly useful in simulating decision problems. For example, the profit that could be achieved if a company launches a new product may depend on a number of factors (market share, advertising, production costs, launch costs, the lifetime of the product, etc. The company manager should identify all factors that could affect profit and then to consider the large number of ways in which these factors may interrelate. In such situations it is recommended company manager to divide the problem into smaller parts, asking him to estimate the probability distribution for market share, for advertising, for the cost of launch. Once they were obtained it can be determined their combined effect in order to obtain the probability distribution of profit. Through computer can generate a large number of possible combinations of situations where you choose a particular course of action. Upon completion of the simulation possible combination will be generated mostly while the least possible combination will be generated less frequently. For exemplification we selected a company producing shoes in Cluj market who wants to launch a new model for autumn-winter 2013-2014. In the current period the company has limited production capacity, has a number of additional contracts honored and general economic crisis situation makes money availability to be extremely limited. Accordingly, the company will have to choose a single product to be launched next season. The company will have to decide which of the two new products to be launched on the market: a model of boots for men in business class or a new model of women\\'s boots of the same class business. The company is not sure either production costs or

10. Monte Carlo techniques in radiation therapy

CERN Document Server

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...

11. Approaching Chemical Accuracy with Quantum Monte Carlo

OpenAIRE

Petruzielo, Frank R.; Toulouse, Julien; Umrigar, C. J.

2012-01-01

International audience; A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction formed from Hartree-Fock orbitals. With the largest basis set, the mean absolute deviation from experimental atomization energies for the G2 set is 3.0 kcal/mol. Optimizing the orbitals within variational Monte Carlo improves the agreem...

12. Mean field simulation for Monte Carlo integration

CERN Document Server

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

13. Monte Carlo Treatment Planning for Advanced Radiotherapy

DEFF Research Database (Denmark)

Cronholm, Rickard

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...... previous algorithms since it uses delineations of structures in order to include and/or exclude certain media in various anatomical regions. This method has the potential to reduce anatomically irrelevant media assignment. In house MATLAB scripts translating the treatment plan parameters to Monte Carlo...

14. 1-D EQUILIBRIUM DISCRETE DIFFUSION MONTE CARLO

Energy Technology Data Exchange (ETDEWEB)

T. EVANS; ET AL

2000-08-01

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

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

OpenAIRE

Kleiss, R. H. P.; Lazopoulos, A.

2006-01-01

While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of each other and, therefore, fails to account for the error improvement advertised by the Quasi-Monte Carlo method. We advocate the construction o...

16. Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy

Science.gov (United States)

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

2012-03-01

Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.

17. Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method

CERN Document Server

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.

18. Composite biasing in Monte Carlo radiative transfer

CERN Document Server

Baes, Maarten; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf

2016-01-01

Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the potential introduction of large weight factors. We discuss a general strategy, composite biasing, to suppress the appearance of large weight factors. We use this composite biasing approach for two different problems faced by current state-of-the-art Monte Carlo radiative transfer codes: the generation of photon packages from multiple components, and the penetration of radiation through high optical depth barriers. In both cases, the implementation of the relevant algorithms is trivial and does not interfere with any other optimisation techniques. Through simple test models, we demonstrate the general applicability, accuracy and efficiency of the composite biasing approach. In particular, for the penetration of high optical depths, the gain in efficiency is spectacular for the spe...

19. Langevin Monte Carlo filtering for target tracking

NARCIS (Netherlands)

Iglesias Garcia, Fernando; Bocquel, Melanie; Driessen, Hans

2015-01-01

This paper introduces the Langevin Monte Carlo Filter (LMCF), a particle filter with a Markov chain Monte Carlo algorithm which draws proposals by simulating Hamiltonian dynamics. This approach is well suited to non-linear filtering problems in high dimensional state spaces where the bootstrap filte

20. An introduction to Monte Carlo methods

NARCIS (Netherlands)

Walter, J. -C.; Barkema, G. T.

2015-01-01

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim

1. An introduction to Monte Carlo methods

NARCIS (Netherlands)

Walter, J. -C.; Barkema, G. T.

2015-01-01

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim

2. Challenges of Monte Carlo Transport

Energy Technology Data Exchange (ETDEWEB)

Long, Alex Roberts [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-10

These are slides from a presentation for Parallel Summer School at Los Alamos National Laboratory. Solving discretized partial differential equations (PDEs) of interest can require a large number of computations. We can identify concurrency to allow parallel solution of discrete PDEs. Simulated particles histories can be used to solve the Boltzmann transport equation. Particle histories are independent in neutral particle transport, making them amenable to parallel computation. Physical parameters and method type determine the data dependencies of particle histories. Data requirements shape parallel algorithms for Monte Carlo. Then, Parallel Computational Physics and Parallel Monte Carlo are discussed and, finally, the results are given. The mesh passing method greatly simplifies the IMC implementation and allows simple load-balancing. Using MPI windows and passive, one-sided RMA further simplifies the implementation by removing target synchronization. The author is very interested in implementations of PGAS that may allow further optimization for one-sided, read-only memory access (e.g. Open SHMEM). The MPICH_RMA_OVER_DMAPP option and library is required to make one-sided messaging scale on Trinitite - Moonlight scales poorly. Interconnect specific libraries or functions are likely necessary to ensure performance. BRANSON has been used to directly compare the current standard method to a proposed method on idealized problems. The mesh passing algorithm performs well on problems that are designed to show the scalability of the particle passing method. BRANSON can now run load-imbalanced, dynamic problems. Potential avenues of improvement in the mesh passing algorithm will be implemented and explored. A suite of test problems that stress DD methods will elucidate a possible path forward for production codes.

3. The MC21 Monte Carlo Transport Code

Energy Technology Data Exchange (ETDEWEB)

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

2007-01-09

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.

4. An introduction to Monte Carlo methods

Science.gov (United States)

Walter, J.-C.; Barkema, G. T.

2015-01-01

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo simulations are ergodicity and detailed balance. The Ising model is a lattice spin system with nearest neighbor interactions that is appropriate to illustrate different examples of Monte Carlo simulations. It displays a second order phase transition between disordered (high temperature) and ordered (low temperature) phases, leading to different strategies of simulations. The Metropolis algorithm and the Glauber dynamics are efficient at high temperature. Close to the critical temperature, where the spins display long range correlations, cluster algorithms are more efficient. We introduce the rejection free (or continuous time) algorithm and describe in details an interesting alternative representation of the Ising model using graphs instead of spins with the so-called Worm algorithm. We conclude with an important discussion of the dynamical effects such as thermalization and correlation time.

5. Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods

OpenAIRE

NeuroData; Paninski, L

2015-01-01

Vogelstein JT, Paninski L. Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods. Statistical and Applied Mathematical Sciences Institute (SAMSI) Program on Sequential Monte Carlo Methods, 2008

6. Monte carlo simulation for soot dynamics

KAUST Repository

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.

7. Quantum Monte Carlo for minimum energy structures

CERN Document Server

Wagner, Lucas K

2010-01-01

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

8. Fast quantum Monte Carlo on a GPU

CERN Document Server

Lutsyshyn, Y

2013-01-01

We present a scheme for the parallelization of quantum Monte Carlo on graphical processing units, focusing on bosonic systems and variational Monte Carlo. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent acceleration. Comparing with single core execution, GPU-accelerated code runs over x100 faster. The CUDA code is provided along with the package that is necessary to execute variational Monte Carlo for a system representing liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the latest Kepler architecture K20 GPU. Kepler-specific optimization is discussed.

9. MONTE CARLO SIMULATION OF CHARGED PARTICLE IN AN ELECTRONEGATIVE PLASMA

Directory of Open Access Journals (Sweden)

L SETTAOUTI

2003-12-01

Full Text Available Interest in radio frequency (rf discharges has grown tremendously in recent years due to their importance in microelectronic technologies. Especially interesting are the properties of discharges in electronegative gases which are most frequently used for technological applications. Monte Carlo simulation have become increasingly important as a simulation tool particularly in the area of plasma physics. In this work, we present some detailed properties of rf plasmas obtained by Monte Carlo simulation code, in SF6

10. 11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

CERN Document Server

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.

11. Simulation and the Monte Carlo method

CERN Document Server

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...

12. Quantum Monte Carlo Calculations of Light Nuclei

CERN Document Server

Pieper, Steven C

2007-01-01

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

13. Improved Monte Carlo Renormalization Group Method

Science.gov (United States)

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

1985-01-01

An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.

14. Smart detectors for Monte Carlo radiative transfer

CERN Document Server

Baes, Maarten

2008-01-01

Many optimization techniques have been invented to reduce the noise that is inherent in Monte Carlo radiative transfer simulations. As the typical detectors used in Monte Carlo simulations do not take into account all the information contained in the impacting photon packages, there is still room to optimize this detection process and the corresponding estimate of the surface brightness distributions. We want to investigate how all the information contained in the distribution of impacting photon packages can be optimally used to decrease the noise in the surface brightness distributions and hence to increase the efficiency of Monte Carlo radiative transfer simulations. We demonstrate that the estimate of the surface brightness distribution in a Monte Carlo radiative transfer simulation is similar to the estimate of the density distribution in an SPH simulation. Based on this similarity, a recipe is constructed for smart detectors that take full advantage of the exact location of the impact of the photon pack...

15. Quantum Monte Carlo approaches for correlated systems

CERN Document Server

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 ...

16. Using Supervised Learning to Improve Monte Carlo Integral Estimation

CERN Document Server

Tracey, Brendan; Alonso, Juan J

2011-01-01

Monte Carlo (MC) techniques are often used to estimate integrals of a multivariate function using randomly generated samples of the function. In light of the increasing interest in uncertainty quantification and robust design applications in aerospace engineering, the calculation of expected values of such functions (e.g. performance measures) becomes important. However, MC techniques often suffer from high variance and slow convergence as the number of samples increases. In this paper we present Stacked Monte Carlo (StackMC), a new method for post-processing an existing set of MC samples to improve the associated integral estimate. StackMC is based on the supervised learning techniques of fitting functions and cross validation. It should reduce the variance of any type of Monte Carlo integral estimate (simple sampling, importance sampling, quasi-Monte Carlo, MCMC, etc.) without adding bias. We report on an extensive set of experiments confirming that the StackMC estimate of an integral is more accurate than ...

17. LCG Monte-Carlo Data Base

CERN Document Server

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.

18. Monte Carlo Algorithms for Linear Problems

OpenAIRE

DIMOV, Ivan

2000-01-01

MSC Subject Classification: 65C05, 65U05. Monte Carlo methods are a powerful tool in many fields of mathematics, physics and engineering. It is known, that these methods give statistical estimates for the functional of the solution by performing random sampling of a certain chance variable whose mathematical expectation is the desired functional. Monte Carlo methods are methods for solving problems using random variables. In the book [16] edited by Yu. A. Shreider one can find the followin...

19. Self-consistent kinetic lattice Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Horsfield, A.; Dunham, S.; Fujitani, Hideaki

1999-07-01

The authors present a brief description of a formalism for modeling point defect diffusion in crystalline systems using a Monte Carlo technique. The main approximations required to construct a practical scheme are briefly discussed, with special emphasis on the proper treatment of charged dopants and defects. This is followed by tight binding calculations of the diffusion barrier heights for charged vacancies. Finally, an application of the kinetic lattice Monte Carlo method to vacancy diffusion is presented.

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

CERN Document Server

Kleiss, R H

2006-01-01

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

1. Monte Carlo techniques for analyzing deep penetration problems

Energy Technology Data Exchange (ETDEWEB)

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.

2. Perturbation Monte Carlo methods for tissue structure alterations.

Science.gov (United States)

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

2013-01-01

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

3. Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Issaid, Chaouki Ben

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.

4. Approaching Chemical Accuracy with Quantum Monte Carlo

CERN Document Server

Petruzielo, F R; Umrigar, C J

2012-01-01

A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction formed from Hartree-Fock orbitals. With the largest basis set, the mean absolute deviation from experimental atomization energies for the G2 set is 3.0 kcal/mol. Optimizing the orbitals within variational Monte Carlo improves the agreement between diffusion Monte Carlo and experiment, reducing the mean absolute deviation to 2.1 kcal/mol. Moving beyond a single determinant Slater-Jastrow trial wavefunction, diffusion Monte Carlo with a small complete active space Slater-Jastrow trial wavefunction results in near chemical accuracy. In this case, the mean absolute deviation from experimental atomization energies is 1.2 kcal/mol. It is shown from calculations on systems containing phosphorus that the accuracy can be further improved by employing a larger active space.

5. Monte Carlo EM加速算法%Acceleration of Monte Carlo EM Algorithm

Institute of Scientific and Technical Information of China (English)

罗季

2008-01-01

EM算法是近年来常用的求后验众数的估计的一种数据增广算法,但由于求出其E步中积分的显示表达式有时很困难,甚至不可能,限制了其应用的广泛性.而Monte Carlo EM算法很好地解决了这个问题,将EM算法中E步的积分用Monte Carlo模拟来有效实现,使其适用性大大增强.但无论是EM算法,还是Monte Carlo EM算法,其收敛速度都是线性的,被缺损信息的倒数所控制,当缺损数据的比例很高时,收敛速度就非常缓慢.而Newton-Raphson算法在后验众数的附近具有二次收敛速率.本文提出Monte Carlo EM加速算法,将Monte Carlo EM算法与Newton-Raphson算法结合,既使得EM算法中的E步用Monte Carlo模拟得以实现,又证明了该算法在后验众数附近具有二次收敛速度.从而使其保留了Monte Carlo EM算法的优点,并改进了Monte Carlo EM算法的收敛速度.本文通过数值例子,将Monte Carlo EM加速算法的结果与EM算法、Monte Carlo EM算法的结果进行比较,进一步说明了Monte Carlo EM加速算法的优良性.

6. Quantum Monte Carlo Endstation for Petascale Computing

Energy Technology Data Exchange (ETDEWEB)

Lubos Mitas

2011-01-26

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

7. SMCTC: Sequential Monte Carlo in C++

Directory of Open Access Journals (Sweden)

2009-04-01

Full Text Available Sequential Monte Carlo methods are a very general class of Monte Carlo methodsfor sampling from sequences of distributions. Simple examples of these algorithms areused very widely in the tracking and signal processing literature. Recent developmentsillustrate that these techniques have much more general applicability, and can be appliedvery eectively to statistical inference problems. Unfortunately, these methods are oftenperceived as being computationally expensive and dicult to implement. This articleseeks to address both of these problems.A C++ template class library for the ecient and convenient implementation of verygeneral Sequential Monte Carlo algorithms is presented. Two example applications areprovided: a simple particle lter for illustrative purposes and a state-of-the-art algorithmfor rare event estimation.

8. 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.

9. Quantum Monte Carlo with variable spins.

Science.gov (United States)

Melton, Cody A; Bennett, M Chandler; Mitas, Lubos

2016-06-28

We investigate the inclusion of variable spins in electronic structure quantum Monte Carlo, with a focus on diffusion Monte Carlo with Hamiltonians that include spin-orbit interactions. Following our previous introduction of fixed-phase spin-orbit diffusion Monte Carlo, we thoroughly discuss the details of the method and elaborate upon its technicalities. We present a proof for an upper-bound property for complex nonlocal operators, which allows for the implementation of T-moves to ensure the variational property. We discuss the time step biases associated with our particular choice of spin representation. Applications of the method are also presented for atomic and molecular systems. We calculate the binding energies and geometry of the PbH and Sn2 molecules, as well as the electron affinities of the 6p row elements in close agreement with experiments.

10. A brief introduction to Monte Carlo simulation.

Science.gov (United States)

Bonate, P L

2001-01-01

Simulation affects our life every day through our interactions with the automobile, airline and entertainment industries, just to name a few. The use of simulation in drug development is relatively new, but its use is increasing in relation to the speed at which modern computers run. One well known example of simulation in drug development is molecular modelling. Another use of simulation that is being seen recently in drug development is Monte Carlo simulation of clinical trials. Monte Carlo simulation differs from traditional simulation in that the model parameters are treated as stochastic or random variables, rather than as fixed values. The purpose of this paper is to provide a brief introduction to Monte Carlo simulation methods.

11. Quantum Monte Carlo with Variable Spins

CERN Document Server

Melton, Cody A; Mitas, Lubos

2016-01-01

We investigate the inclusion of variable spins in electronic structure quantum Monte Carlo, with a focus on diffusion Monte Carlo with Hamiltonians that include spin-orbit interactions. Following our previous introduction of fixed-phase spin-orbit diffusion Monte Carlo (FPSODMC), we thoroughly discuss the details of the method and elaborate upon its technicalities. We present a proof for an upper-bound property for complex nonlocal operators, which allows for the implementation of T-moves to ensure the variational property. We discuss the time step biases associated with our particular choice of spin representation. Applications of the method are also presented for atomic and molecular systems. We calculate the binding energies and geometry of the PbH and Sn$_2$ molecules, as well as the electron affinities of the 6$p$ row elements in close agreement with experiments.

12. Adiabatic optimization versus diffusion Monte Carlo methods

Science.gov (United States)

Jarret, Michael; Jordan, Stephen P.; Lackey, Brad

2016-10-01

Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .

13. Self-learning Monte Carlo method

Science.gov (United States)

Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang

2017-01-01

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of a general and efficient update algorithm for large size systems close to the phase transition, for which local updates perform badly. In this Rapid Communication, we propose a general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup.

14. Monte Carlo strategies in scientific computing

CERN Document Server

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...

15. Parallel Markov chain Monte Carlo simulations.

Science.gov (United States)

Ren, Ruichao; Orkoulas, G

2007-06-07

With strict detailed balance, parallel Monte Carlo simulation through domain decomposition cannot be validated with conventional Markov chain theory, which describes an intrinsically serial stochastic process. In this work, the parallel version of Markov chain theory and its role in accelerating Monte Carlo simulations via cluster computing is explored. It is shown that sequential updating is the key to improving efficiency in parallel simulations through domain decomposition. A parallel scheme is proposed to reduce interprocessor communication or synchronization, which slows down parallel simulation with increasing number of processors. Parallel simulation results for the two-dimensional lattice gas model show substantial reduction of simulation time for systems of moderate and large size.

16. Monte Carlo Hamiltonian：Linear Potentials

Institute of Scientific and Technical Information of China (English)

LUOXiang－Qian; HelmutKROEGER; 等

2002-01-01

We further study the validity of the Monte Carlo Hamiltonian method .The advantage of the method,in comparison with the standard Monte Carlo Lagrangian approach,is its capability to study the excited states.We consider two quantum mechanical models:a symmetric one V(x)=/x/2;and an asymmetric one V(x)==∞,for x<0 and V(x)=2,for x≥0.The results for the spectrum,wave functions and thermodynamical observables are in agreement with the analytical or Runge-Kutta calculations.

17. Monte Carlo simulation of neutron scattering instruments

Energy Technology Data Exchange (ETDEWEB)

Seeger, P.A.

1995-12-31

A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width.

18. The Rational Hybrid Monte Carlo Algorithm

CERN Document Server

Clark, M A

2006-01-01

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

19. The Rational Hybrid Monte Carlo algorithm

Science.gov (United States)

Clark, Michael

2006-12-01

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

20. Lunar Regolith Albedos Using Monte Carlos

Science.gov (United States)

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

2003-01-01

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

1. Fast sequential Monte Carlo methods for counting and optimization

CERN Document Server

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

2. Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules

CERN Document Server

Lester, William A; Reynolds, PJ

1994-01-01

This book presents the basic theory and application of the Monte Carlo method to the electronic structure of atoms and molecules. It assumes no previous knowledge of the subject, only a knowledge of molecular quantum mechanics at the first-year graduate level. A working knowledge of traditional ab initio quantum chemistry is helpful, but not essential.Some distinguishing features of this book are: Clear exposition of the basic theory at a level to facilitate independent study. Discussion of the various versions of the theory: diffusion Monte Carlo, Green's function Monte Carlo, and release n

3. Use of Monte Carlo Methods in brachytherapy; Uso del metodo de Monte Carlo en braquiterapia

Energy Technology Data Exchange (ETDEWEB)

Granero Cabanero, D.

2015-07-01

The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)

4. On the use of stochastic approximation Monte Carlo for Monte Carlo integration

KAUST Repository

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.

5. A comparison of Monte Carlo generators

CERN Document Server

Golan, Tomasz

2014-01-01

A comparison of GENIE, NEUT, NUANCE, and NuWro Monte Carlo neutrino event generators is presented using a set of four observables: protons multiplicity, total visible energy, most energetic proton momentum, and $\\pi^+$ two-dimensional energy vs cosine distribution.

6. Monte Carlo Tools for Jet Quenching

OpenAIRE

Zapp, Korinna

2011-01-01

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

7. An Introduction to Monte Carlo Methods

Science.gov (United States)

Raeside, D. E.

1974-01-01

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

8. Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

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 intr

9. 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.

10. Monte Carlo methods beyond detailed balance

NARCIS (Netherlands)

Schram, Raoul D.; Barkema, Gerard T.

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

11. Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

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 intr

12. An analysis of Monte Carlo tree search

CSIR Research Space (South Africa)

James, S

2017-02-01

Full Text Available Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in recent years. Despite the vast amount of research into MCTS, the effect of modifications on the algorithm, as well as the manner...

13. Monte Carlo Simulation of Counting Experiments.

Science.gov (United States)

Ogden, Philip M.

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

14. Monte Carlo radiation transport in external beam radiotherapy

OpenAIRE

Çeçen, Yiğit

2013-01-01

The use of Monte Carlo in radiation transport is an effective way to predict absorbed dose distributions. Monte Carlo modeling has contributed to a better understanding of photon and electron transport by radiotherapy physicists. The aim of this review is to introduce Monte Carlo as a powerful radiation transport tool. In this review, photon and electron transport algorithms for Monte Carlo techniques are investigated and a clinical linear accelerator model is studied for external beam radiot...

15. Properties of Reactive Oxygen Species by Quantum Monte Carlo

CERN Document Server

Zen, Andrea; Guidoni, Leonardo

2014-01-01

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

16. The Monte Carlo method in quantum field theory

CERN Document Server

Morningstar, C

2007-01-01

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

17. Efficiency of Monte Carlo sampling in chaotic systems.

Science.gov (United States)

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

2014-11-01

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

18. Introduction to the variational and diffusion Monte Carlo methods

CERN Document Server

Toulouse, Julien; Umrigar, C J

2015-01-01

We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on the subject, we review in depth the Metropolis-Hastings algorithm used in VMC for sampling the square of an approximate wave function, discussing details important for applications to electronic systems. We also review in detail the more sophisticated DMC algorithm within the fixed-node approximation, introduced to avoid the infamous Fermionic sign problem, which allows one to sample a more accurate approximation to the ground-state wave function. Throughout this review, we discuss the statistical methods used for evaluating expectation values and statistical uncertainties. In particular, we show how to estimate nonlinear functions of expectation values and their statistical uncertainties.

19. Green's function monte carlo and the many-fermion problem

Science.gov (United States)

Kalos, M. H.

The application of Green's function Monte Carlo to many body problems is outlined. For boson problems, the method is well developed and practical. An "efficiency principle",importance sampling, can be used to reduce variance. Fermion problems are more difficult because spatially antisymmetric functions must be represented as a difference of two density functions. Naively treated, this leads to a rapid growth of Monte Carlo error. Methods for overcoming the difficulty are discussed. Satisfactory algorithms exist for few-body problems; for many-body problems more work is needed, but it is likely that adequate methods will soon be available.

20. Monte Carlo studies of nuclei and quantum liquid drops

Energy Technology Data Exchange (ETDEWEB)

Pandharipande, V.R.; Pieper, S.C.

1989-01-01

The progress in application of variational and Green's function Monte Carlo methods to nuclei is reviewed. The nature of single-particle orbitals in correlated quantum liquid drops is discussed, and it is suggested that the difference between quasi-particle and mean-field orbitals may be of importance in nuclear structure physics. 27 refs., 7 figs., 2 tabs.

1. Monte Carlo simulation of magnetic nanostructured thin films

Institute of Scientific and Technical Information of China (English)

Guan Zhi-Qiang; Yutaka Abe; Jiang Dong-Hua; Lin Hai; Yoshitake Yamazakia; Wu Chen-Xu

2004-01-01

@@ Using Monte Carlo simulation, we have compared the magnetic properties between nanostructured thin films and two-dimensional crystalline solids. The dependence of nanostructured properties on the interaction between particles that constitute the nanostructured thin films is also studied. The result shows that the parameters in the interaction potential have an important effect on the properties of nanostructured thin films at the transition temperatures.

2. Play It Again: Teaching Statistics with Monte Carlo Simulation

Science.gov (United States)

Sigal, Matthew J.; Chalmers, R. Philip

2016-01-01

Monte Carlo simulations (MCSs) provide important information about statistical phenomena that would be impossible to assess otherwise. This article introduces MCS methods and their applications to research and statistical pedagogy using a novel software package for the R Project for Statistical Computing constructed to lessen the often steep…

3. Research of Monte Carlo Simulation in Commercial Bank Risk Management

Institute of Scientific and Technical Information of China (English)

BeimingXiao

2004-01-01

Simulation method is an important-tool in financial risk management. It can simulate financial variable or economic wriable and deal with non-linear or non-nominal issue. This paper analyzes the usage of "Monte Carlo" approach in commercial bank risk management.

4. Hybrid Monte Carlo with Chaotic Mixing

CERN Document Server

2016-01-01

We propose a hybrid Monte Carlo (HMC) technique applicable to high-dimensional multivariate normal distributions that effectively samples along chaotic trajectories. The method is predicated on the freedom of choice of the HMC momentum distribution, and due to its mixing properties, exhibits sample-to-sample autocorrelations that decay far faster than those in the traditional hybrid Monte Carlo algorithm. We test the methods on distributions of varying correlation structure, finding that the proposed technique produces superior covariance estimates, is less reliant on step-size tuning, and can even function with sparse or no momentum re-sampling. The method presented here is promising for more general distributions, such as those that arise in Bayesian learning of artificial neural networks and in the state and parameter estimation of dynamical systems.

5. Monte Carlo study of real time dynamics

CERN Document Server

Alexandru, Andrei; Bedaque, Paulo F; Vartak, Sohan; Warrington, Neill C

2016-01-01

Monte Carlo studies involving real time dynamics are severely restricted by the sign problem that emerges from highly oscillatory phase of the path integral. In this letter, we present a new method to compute real time quantities on the lattice using the Schwinger-Keldysh formalism via Monte Carlo simulations. The key idea is to deform the path integration domain to a complex manifold where the phase oscillations are mild and the sign problem is manageable. We use the previously introduced "contraction algorithm" to create a Markov chain on this alternative manifold. We substantiate our approach by analyzing the quantum mechanical anharmonic oscillator. Our results are in agreement with the exact ones obtained by diagonalization of the Hamiltonian. The method we introduce is generic and in principle applicable to quantum field theory albeit very slow. We discuss some possible improvements that should speed up the algorithm.

6. Multilevel sequential Monte-Carlo samplers

KAUST Repository

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.

7. Monte Carlo Simulation for Particle Detectors

CERN Document Server

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...

8. An enhanced Monte Carlo outlier detection method.

Science.gov (United States)

Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi

2015-09-30

Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc.

9. Multilevel Monte Carlo Approaches for Numerical Homogenization

KAUST Repository

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.

10. Monte Carlo simulations on SIMD computer architectures

Energy Technology Data Exchange (ETDEWEB)

Burmester, C.P.; Gronsky, R. [Lawrence Berkeley Lab., CA (United States); Wille, L.T. [Florida Atlantic Univ., Boca Raton, FL (United States). Dept. of Physics

1992-03-01

Algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SMM) 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 Carlo updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures.

11. Rare event simulation using Monte Carlo methods

CERN Document Server

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. ...

12. Handbook of Markov chain Monte Carlo

CERN Document Server

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.

13. Accelerated Monte Carlo by Embedded Cluster Dynamics

Science.gov (United States)

Brower, R. C.; Gross, N. A.; Moriarty, K. J. M.

1991-07-01

We present an overview of the new methods for embedding Ising spins in continuous fields to achieve accelerated cluster Monte Carlo algorithms. The methods of Brower and Tamayo and Wolff are summarized and variations are suggested for the O( N) models based on multiple embedded Z2 spin components and/or correlated projections. Topological features are discussed for the XY model and numerical simulations presented for d=2, d=3 and mean field theory lattices.

14. Diffusion Monte Carlo in internal coordinates.

Science.gov (United States)

Petit, Andrew S; McCoy, Anne B

2013-08-15

An internal coordinate extension of diffusion Monte Carlo (DMC) is described as a first step toward a generalized reduced-dimensional DMC approach. The method places no constraints on the choice of internal coordinates other than the requirement that they all be independent. Using H(3)(+) and its isotopologues as model systems, the methodology is shown to be capable of successfully describing the ground state properties of molecules that undergo large amplitude, zero-point vibrational motions. Combining the approach developed here with the fixed-node approximation allows vibrationally excited states to be treated. Analysis of the ground state probability distribution is shown to provide important insights into the set of internal coordinates that are less strongly coupled and therefore more suitable for use as the nodal coordinates for the fixed-node DMC calculations. In particular, the curvilinear normal mode coordinates are found to provide reasonable nodal surfaces for the fundamentals of H(2)D(+) and D(2)H(+) despite both molecules being highly fluxional.

15. Monte Carlo models of dust coagulation

CERN Document Server

Zsom, Andras

2010-01-01

The thesis deals with the first stage of planet formation, namely dust coagulation from micron to millimeter sizes in circumstellar disks. For the first time, we collect and compile the recent laboratory experiments on dust aggregates into a collision model that can be implemented into dust coagulation models. We put this model into a Monte Carlo code that uses representative particles to simulate dust evolution. Simulations are performed using three different disk models in a local box (0D) located at 1 AU distance from the central star. We find that the dust evolution does not follow the previously assumed growth-fragmentation cycle, but growth is halted by bouncing before the fragmentation regime is reached. We call this the bouncing barrier which is an additional obstacle during the already complex formation process of planetesimals. The absence of the growth-fragmentation cycle and the halted growth has two important consequences for planet formation. 1) It is observed that disk atmospheres are dusty thr...

16. Measuring Berry curvature with quantum Monte Carlo

CERN Document Server

Kolodrubetz, Michael

2014-01-01

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

17. Thermodynamic properties of van der Waals fluids from Monte Carlo simulations and perturbative Monte Carlo theory.

Science.gov (United States)

Díez, A; Largo, J; Solana, J R

2006-08-21

Computer simulations have been performed for fluids with van der Waals potential, that is, hard spheres with attractive inverse power tails, to determine the equation of state and the excess energy. On the other hand, the first- and second-order perturbative contributions to the energy and the zero- and first-order perturbative contributions to the compressibility factor have been determined too from Monte Carlo simulations performed on the reference hard-sphere system. The aim was to test the reliability of this "exact" perturbation theory. It has been found that the results obtained from the Monte Carlo perturbation theory for these two thermodynamic properties agree well with the direct Monte Carlo simulations. Moreover, it has been found that results from the Barker-Henderson [J. Chem. Phys. 47, 2856 (1967)] perturbation theory are in good agreement with those from the exact perturbation theory.

18. Observations on variational and projector Monte Carlo methods.

Science.gov (United States)

Umrigar, C J

2015-10-28

Variational Monte Carlo and various projector Monte Carlo (PMC) methods are presented in a unified manner. Similarities and differences between the methods and choices made in designing the methods are discussed. Both methods where the Monte Carlo walk is performed in a discrete space and methods where it is performed in a continuous space are considered. It is pointed out that the usual prescription for importance sampling may not be advantageous depending on the particular quantum Monte Carlo method used and the observables of interest, so alternate prescriptions are presented. The nature of the sign problem is discussed for various versions of PMC methods. A prescription for an exact PMC method in real space, i.e., a method that does not make a fixed-node or similar approximation and does not have a finite basis error, is presented. This method is likely to be practical for systems with a small number of electrons. Approximate PMC methods that are applicable to larger systems and go beyond the fixed-node approximation are also discussed.

19. Direct Monte Carlo simulation of nanoscale mixed gas bearings

Directory of Open Access Journals (Sweden)

Kyaw Sett Myo

2015-06-01

Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.

20. On a full Monte Carlo approach to quantum mechanics

Science.gov (United States)

Sellier, J. M.; Dimov, I.

2016-12-01

The Monte Carlo approach to numerical problems has shown to be remarkably efficient in performing very large computational tasks since it is an embarrassingly parallel technique. Additionally, Monte Carlo methods are well known to keep performance and accuracy with the increase of dimensionality of a given problem, a rather counterintuitive peculiarity not shared by any known deterministic method. Motivated by these very peculiar and desirable computational features, in this work we depict a full Monte Carlo approach to the problem of simulating single- and many-body quantum systems by means of signed particles. In particular we introduce a stochastic technique, based on the strategy known as importance sampling, for the computation of the Wigner kernel which, so far, has represented the main bottleneck of this method (it is equivalent to the calculation of a multi-dimensional integral, a problem in which complexity is known to grow exponentially with the dimensions of the problem). The introduction of this stochastic technique for the kernel is twofold: firstly it reduces the complexity of a quantum many-body simulation from non-linear to linear, secondly it introduces an embarassingly parallel approach to this very demanding problem. To conclude, we perform concise but indicative numerical experiments which clearly illustrate how a full Monte Carlo approach to many-body quantum systems is not only possible but also advantageous. This paves the way towards practical time-dependent, first-principle simulations of relatively large quantum systems by means of affordable computational resources.

1. Status of Monte-Carlo Event Generators

Energy Technology Data Exchange (ETDEWEB)

Hoeche, Stefan; /SLAC

2011-08-11

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

2. Quantum Monte Carlo for vibrating molecules

Energy Technology Data Exchange (ETDEWEB)

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

1996-08-01

Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H{sub 2}O and C{sub 3} vibrational states, using 7 PESs, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H{sub 2}O and C{sub 3}. In order to construct accurate trial wavefunctions for C{sub 3}, the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C{sub 3} the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C{sub 3} PESs 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.

3. A Monte Carlo algorithm for degenerate plasmas

Energy Technology Data Exchange (ETDEWEB)

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

2013-09-15

A procedure for performing Monte Carlo calculations of plasmas with an arbitrary level of degeneracy is outlined. It has possible applications in inertial confinement fusion and astrophysics. Degenerate particles are initialised according to the Fermi–Dirac distribution function, and scattering is via a Pauli blocked binary collision approximation. The algorithm is tested against degenerate electron–ion equilibration, and the degenerate resistivity transport coefficient from unmagnetised first order transport theory. The code is applied to the cold fuel shell and alpha particle equilibration problem of inertial confinement fusion.

4. 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....

5. Archimedes, the Free Monte Carlo simulator

CERN Document Server

Sellier, Jean Michel D

2012-01-01

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

6. Cluster hybrid Monte Carlo simulation algorithms

Science.gov (United States)

Plascak, J. A.; Ferrenberg, Alan M.; Landau, D. P.

2002-06-01

We show that addition of Metropolis single spin flips to the Wolff cluster-flipping Monte Carlo procedure leads to a dramatic increase in performance for the spin-1/2 Ising model. We also show that adding Wolff cluster flipping to the Metropolis or heat bath algorithms in systems where just cluster flipping is not immediately obvious (such as the spin-3/2 Ising model) can substantially reduce the statistical errors of the simulations. A further advantage of these methods is that systematic errors introduced by the use of imperfect random-number generation may be largely healed by hybridizing single spin flips with cluster flipping.

7. Introduction to Cluster Monte Carlo Algorithms

Science.gov (United States)

Luijten, E.

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

8. 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.

9. Mosaic crystal algorithm for Monte Carlo simulations

CERN Document Server

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.)

10. Diffusion quantum Monte Carlo for molecules

Energy Technology Data Exchange (ETDEWEB)

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/sup 2/) as a density of ''walks.'' The walks undergo an exponential birth and death as given by the rate term. 16 refs., 2 tabs.

11. Exascale Monte Carlo R&D

Energy Technology Data Exchange (ETDEWEB)

Marcus, Ryan C. [Los Alamos National Laboratory

2012-07-24

Overview of this presentation is (1) Exascale computing - different technologies, getting there; (2) high-performance proof-of-concept MCMini - features and results; and (3) OpenCL toolkit - Oatmeal (OpenCL Automatic Memory Allocation Library) - purpose and features. Despite driver issues, OpenCL seems like a good, hardware agnostic tool. MCMini demonstrates the possibility for GPGPU-based Monte Carlo methods - it shows great scaling for HPC application and algorithmic equivalence. Oatmeal provides a flexible framework to aid in the development of scientific OpenCL codes.

12. State-of-the-art Monte Carlo 1988

Energy Technology Data Exchange (ETDEWEB)

Soran, P.D.

1988-06-28

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

13. Stochastic Engine Final Report: Applying Markov Chain Monte Carlo Methods with Importance Sampling to Large-Scale Data-Driven Simulation

Energy Technology Data Exchange (ETDEWEB)

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

2004-03-11

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

14. Monte Carlo Simulations: Number of Iterations and Accuracy

Science.gov (United States)

2015-07-01

Jessica Schultheis for her editorial review. vi INTENTIONALLY LEFT BLANK. 1 1. Introduction Monte Carlo (MC) methods1 are often used...ARL-TN-0684 ● JULY 2015 US Army Research Laboratory Monte Carlo Simulations: Number of Iterations and Accuracy by William...needed. Do not return it to the originator. ARL-TN-0684 ● JULY 2015 US Army Research Laboratory Monte Carlo Simulations: Number

15. Discrete diffusion Monte Carlo for frequency-dependent radiative transfer

Energy Technology Data Exchange (ETDEWEB)

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

2010-11-17

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

16. Validation of Compton Scattering Monte Carlo Simulation Models

CERN Document Server

Weidenspointner, Georg; Hauf, Steffen; Hoff, Gabriela; Kuster, Markus; Pia, Maria Grazia; Saracco, Paolo

2014-01-01

Several models for the Monte Carlo simulation of Compton scattering on electrons are quantitatively evaluated with respect to a large collection of experimental data retrieved from the literature. Some of these models are currently implemented in general purpose Monte Carlo systems; some have been implemented and evaluated for possible use in Monte Carlo particle transport for the first time in this study. Here we present first and preliminary results concerning total and differential Compton scattering cross sections.

17. 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......The rank envelope test (Myllym\\"aki et al., Global envelope tests for spatial processes, arXiv:1307.0239 [stat.ME]) is proposed as a solution to multiple testing problem for Monte Carlo tests. Three different situations are recognized: 1) a few univariate Monte Carlo tests, 2) a Monte Carlo test...

18. THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE

Energy Technology Data Exchange (ETDEWEB)

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

2007-01-10

MCNPX (Monte Carlo N-Particle eXtended) is a general-purpose Monte Carlo radiation transport code with three-dimensional geometry and continuous-energy transport of 34 particles and light ions. It contains flexible source and tally options, interactive graphics, and support for both sequential and multi-processing computer platforms. MCNPX is based on MCNP4B, and has been upgraded to most MCNP5 capabilities. MCNP is a highly stable code tracking neutrons, photons and electrons, and using evaluated nuclear data libraries for low-energy interaction probabilities. MCNPX has extended this base to a comprehensive set of particles and light ions, with heavy ion transport in development. Models have been included to calculate interaction probabilities when libraries are not available. Recent additions focus on the time evolution of residual nuclei decay, allowing calculation of transmutation and delayed particle emission. MCNPX is now a code of great dynamic range, and the excellent neutronics capabilities allow new opportunities to simulate devices of interest to experimental particle physics; particularly calorimetry. This paper describes the capabilities of the current MCNPX version 2.6.C, and also discusses ongoing code development.

19. Multi-Index Monte Carlo (MIMC)

KAUST Repository

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.

20. Chemical application of diffusion quantum Monte Carlo

Science.gov (United States)

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

1983-10-01

The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. As an example the singlet-triplet splitting of the energy of the methylene molecule CH2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on our VAX 11/780, and second by explicitly writing vector code for all loops longer than a crossover length C. The speed of the codes relative to one another as a function of C, and relative to the VAX is discussed. Since CH2 has only eight electrons, most of the loops in this application are fairly short. The longest inner loops run over the set of atomic basis functions. The CPU time dependence obtained versus the number of basis functions is discussed and compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures. Finally, preliminary work on restructuring the algorithm to compute the separate Monte Carlo realizations in parallel is discussed.

1. Multi-Index Monte Carlo (MIMC)

KAUST Repository

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).

2. Discrete range clustering using Monte Carlo methods

Science.gov (United States)

Chatterji, G. B.; Sridhar, B.

1993-01-01

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

3. Quantum Monte Carlo Calculations of Neutron Matter

CERN Document Server

Carlson, J; Ravenhall, D G

2003-01-01

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

4. Information Geometry and Sequential Monte Carlo

CERN Document Server

Sim, Aaron; Stumpf, Michael P H

2012-01-01

This paper explores the application of methods from information geometry to the sequential Monte Carlo (SMC) sampler. In particular the Riemannian manifold Metropolis-adjusted Langevin algorithm (mMALA) is adapted for the transition kernels in SMC. Similar to its function in Markov chain Monte Carlo methods, the mMALA is a fully adaptable kernel which allows for efficient sampling of high-dimensional and highly correlated parameter spaces. We set up the theoretical framework for its use in SMC with a focus on the application to the problem of sequential Bayesian inference for dynamical systems as modelled by sets of ordinary differential equations. In addition, we argue that defining the sequence of distributions on geodesics optimises the effective sample sizes in the SMC run. We illustrate the application of the methodology by inferring the parameters of simulated Lotka-Volterra and Fitzhugh-Nagumo models. In particular we demonstrate that compared to employing a standard adaptive random walk kernel, the SM...

5. Monte Carlo uncertainty analyses for integral beryllium experiments

CERN Document Server

Fischer, U; Tsige-Tamirat, H

2000-01-01

The novel Monte Carlo technique for calculating point detector sensitivities has been applied to two representative beryllium transmission experiments with the objective to investigate the sensitivity of important responses such as the neutron multiplication and to assess the related uncertainties due to the underlying cross-section data uncertainties. As an important result, it has been revealed that the neutron multiplication power of beryllium can be predicted with good accuracy using state-of-the-art nuclear data evaluations. Severe discrepancies do exist for the spectral neutron flux distribution that would transmit into significant uncertainties of the calculated neutron spectra and of the nuclear blanket performance in blanket design calculations. With regard to this, it is suggested to re-analyse the secondary energy and angle distribution data of beryllium by means of Monte Carlo based sensitivity and uncertainty calculations. Related code development work is underway.

6. Monte Carlo simulation of NSE at reactor and spallation sources

Energy Technology Data Exchange (ETDEWEB)

Zsigmond, G.; Wechsler, D.; Mezei, F. [Hahn-Meitner-Institut Berlin, Berlin (Germany)

2001-03-01

A MC (Monte Carlo) computation study of NSE (Neutron Spin Echo) has been performed by means of VITESS investigating the classic and TOF-NSE options at spallation sources. The use of white beams in TOF-NSE makes the flipper efficiency in function of the neutron wavelength an important issue. The emphasis was put on exact evaluation of flipper efficiencies for wide wavelength-band instruments. (author)

7. Planning Tunnel Construction Using Markov Chain Monte Carlo (MCMC)

OpenAIRE

Vargas, Juan P.; Koppe,Jair C.; Sebastián Pérez; Hurtado, Juan P.

2015-01-01

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 ope...

8. An Introduction to Monte Carlo Simulation of Statistical physics Problem

OpenAIRE

Murthy, K. P. N.

2001-01-01

A brief introduction to the technique of Monte Carlo simulations in statistical physics is presented. The topics covered include statistical ensembles random and pseudo random numbers, random sampling techniques, importance sampling, Markov chain, Metropolis algorithm, continuous phase transition, statistical errors from correlated and uncorrelated data, finite size scaling, n-fold way, critical slowing down, blocking technique,percolation, cluster algorithms, cluster counting, histogram tech...

9. On adaptive resampling strategies for sequential Monte Carlo methods

OpenAIRE

Del Moral, Pierre; Doucet, Arnaud; Jasra, Ajay

2012-01-01

Sequential Monte Carlo (SMC) methods are a class of techniques to sample approximately from any sequence of probability distributions using a combination of importance sampling and resampling steps. This paper is concerned with the convergence analysis of a class of SMC methods where the times at which resampling occurs are computed online using criteria such as the effective sample size. This is a popular approach amongst practitioners but there are very few convergence results available for...

10. Finding organic vapors - a Monte Carlo approach

Science.gov (United States)

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

2010-05-01

drawbacks in accuracy, the inability to find diurnal variation and the lack of size resolution. Here, we aim to shed some light onto the problem by applying an ad hoc Monte Carlo algorithm to a well established aerosol dynamical model, the University of Helsinki Multicomponent Aerosol model (UHMA). By performing a side-by-side comparison with measurement data within the algorithm, this approach has the significant advantage of decreasing the amount of manual labor. But more importantly, by basing the comparison on particle number size distribution data - a quantity that can be quite reliably measured - the accuracy of the results is good.

11. Visibility assessment : Monte Carlo characterization of temporal variability.

Energy Technology Data Exchange (ETDEWEB)

Laulainen, N.; Shannon, J.; Trexler, E. C., Jr.

1997-12-12

Current techniques for assessing the benefits of certain anthropogenic emission reductions are largely influenced by limitations in emissions data and atmospheric modeling capability and by the highly variant nature of meteorology. These data and modeling limitations are likely to continue for the foreseeable future, during which time important strategic decisions need to be made. Statistical atmospheric quality data and apportionment techniques are used in Monte-Carlo models to offset serious shortfalls in emissions, entrainment, topography, statistical meteorology data and atmospheric modeling. This paper describes the evolution of Department of Energy (DOE) Monte-Carlo based assessment models and the development of statistical inputs. A companion paper describes techniques which are used to develop the apportionment factors used in the assessment models.

12. Monte Carlo methods for pricing ﬁnancial options

Indian Academy of Sciences (India)

N Bolia; S Juneja

2005-04-01

Pricing ﬁnancial options is amongst the most important and challenging problems in the modern ﬁnancial industry. Except in the simplest cases, the prices of options do not have a simple closed form solution and efﬁcient computational methods are needed to determine them. Monte Carlo methods have increasingly become a popular computational tool to price complex ﬁnancial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the ‘curse of dimensionality’. However, even Monte-Carlo techniques can be quite slow as the problem-size increases, motivating research in variance reduction techniques to increase the efﬁciency of the simulations. In this paper, we review some of the popular variance reduction techniques and their application to pricing options. We particularly focus on the recent Monte-Carlo techniques proposed to tackle the difﬁcult problem of pricing American options. These include: regression-based methods, random tree methods and stochastic mesh methods. Further, we show how importance sampling, a popular variance reduction technique, may be combined with these methods to enhance their effectiveness. We also brieﬂy review the evolving options market in India.

13. Morse Monte Carlo Radiation Transport Code System

Energy Technology Data Exchange (ETDEWEB)

Emmett, M.B.

1975-02-01

The report contains sections containing descriptions of the MORSE and PICTURE codes, input descriptions, sample problems, deviations of the physical equations and explanations of the various error messages. The MORSE code is a multipurpose neutron and gamma-ray transport Monte Carlo code. Time dependence for both shielding and criticality problems is provided. General three-dimensional geometry may be used with an albedo option available at any material surface. The PICTURE code provide aid in preparing correct input data for the combinatorial geometry package CG. It provides a printed view of arbitrary two-dimensional slices through the geometry. By inspecting these pictures one may determine if the geometry specified by the input cards is indeed the desired geometry. 23 refs. (WRF)

14. 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.

15. Monte Carlo simulation of neutron scattering instruments

Energy Technology Data Exchange (ETDEWEB)

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

1998-12-01

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.

16. Atomistic Monte Carlo simulation of lipid membranes

DEFF Research Database (Denmark)

Wüstner, Daniel; Sklenar, Heinz

2014-01-01

, 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......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...

17. Experimental Monte Carlo Quantum Process Certification

CERN Document Server

Steffen, L; Fedorov, A; Baur, M; Wallraff, A

2012-01-01

Experimental implementations of quantum information processing have now reached a level of sophistication where quantum process tomography is impractical. The number of experimental settings as well as the computational cost of the data post-processing now translates to days of effort to characterize even experiments with as few as 8 qubits. Recently a more practical approach to determine the fidelity of an experimental quantum process has been proposed, where the experimental data is compared directly to an ideal process using Monte Carlo sampling. Here we present an experimental implementation of this scheme in a circuit quantum electrodynamics setup to determine the fidelity of two qubit gates, such as the cphase and the cnot gate, and three qubit gates, such as the Toffoli gate and two sequential cphase gates.

18. Gas discharges modeling by Monte Carlo technique

Directory of Open Access Journals (Sweden)

Savić Marija

2010-01-01

Full Text Available The basic assumption of the Townsend theory - that ions produce secondary electrons - is valid only in a very narrow range of the reduced electric field E/N. In accordance with the revised Townsend theory that was suggested by Phelps and Petrović, secondary electrons are produced in collisions of ions, fast neutrals, metastable atoms or photons with the cathode, or in gas phase ionizations by fast neutrals. In this paper we tried to build up a Monte Carlo code that can be used to calculate secondary electron yields for different types of particles. The obtained results are in good agreement with the analytical results of Phelps and. Petrović [Plasma Sourc. Sci. Technol. 8 (1999 R1].

19. On nonlinear Markov chain Monte Carlo

CERN Document Server

Andrieu, Christophe; Doucet, Arnaud; Del Moral, Pierre; 10.3150/10-BEJ307

2011-01-01

Let $\\mathscr{P}(E)$ be the space of probability measures on a measurable space $(E,\\mathcal{E})$. In this paper we introduce a class of nonlinear Markov chain Monte Carlo (MCMC) methods for simulating from a probability measure $\\pi\\in\\mathscr{P}(E)$. Nonlinear Markov kernels (see [Feynman--Kac Formulae: Genealogical and Interacting Particle Systems with Applications (2004) Springer]) $K:\\mathscr{P}(E)\\times E\\rightarrow\\mathscr{P}(E)$ can be constructed to, in some sense, improve over MCMC methods. However, such nonlinear kernels cannot be simulated exactly, so approximations of the nonlinear kernels are constructed using auxiliary or potentially self-interacting chains. Several nonlinear kernels are presented and it is demonstrated that, under some conditions, the associated approximations exhibit a strong law of large numbers; our proof technique is via the Poisson equation and Foster--Lyapunov conditions. We investigate the performance of our approximations with some simulations.

20. Monte Carlo exploration of warped Higgsless models

Energy Technology Data Exchange (ETDEWEB)

Hewett, JoAnne L.; Lillie, Benjamin; Rizzo, Thomas Gerard [Stanford Linear Accelerator Center, 2575 Sand Hill Rd., Menlo Park, CA, 94025 (United States)]. E-mail: rizzo@slac.stanford.edu

2004-10-01

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

1. Monte Carlo Exploration of Warped Higgsless Models

CERN Document Server

Hewett, J L; Rizzo, T G

2004-01-01

We have performed a detailed Monte Carlo exploration of the parameter space for a warped Higgsless model of electroweak symmetry breaking in 5 dimensions. This model is based on the $SU(2)_L\\times SU(2)_R\\times U(1)_{B-L}$ gauge group in an AdS$_5$ bulk with arbitrary gauge kinetic terms on both the Planck and TeV branes. Constraints arising from precision electroweak measurements and collider data are found to be relatively easy to satisfy. We show, however, that the additional requirement of perturbative unitarity up to the cut-off, $\\simeq 10$ TeV, in $W_L^+W_L^-$ elastic scattering in the absence of dangerous tachyons eliminates all models. If successful models of this class exist, they must be highly fine-tuned.

2. Monte Carlo Implementation of Polarized Hadronization

CERN Document Server

Matevosyan, Hrayr H; Thomas, Anthony W

2016-01-01

We study the polarized quark hadronization in a Monte Carlo (MC) framework based on the recent extension of the quark-jet framework, where a self-consistent treatment of the quark polarization transfer in a sequential hadronization picture has been presented. Here, we first adopt this approach for MC simulations of hadronization process with finite number of produced hadrons, expressing the relevant probabilities in terms of the eight leading twist quark-to-quark transverse momentum dependent (TMD) splitting functions (SFs) for elementary $q \\to q'+h$ transition. We present explicit expressions for the unpolarized and Collins fragmentation functions (FFs) of unpolarized hadrons emitted at rank two. Further, we demonstrate that all the current spectator-type model calculations of the leading twist quark-to-quark TMD SFs violate the positivity constraints, and propose quark model based ansatz for these input functions that circumvents the problem. We validate our MC framework by explicitly proving the absence o...

3. Commensurabilities between ETNOs: a Monte Carlo survey

CERN Document Server

Marcos, C de la Fuente

2016-01-01

Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nin...

4. Variable length trajectory compressible hybrid Monte Carlo

CERN Document Server

Nishimura, Akihiko

2016-01-01

Hybrid Monte Carlo (HMC) generates samples from a prescribed probability distribution in a configuration space by simulating Hamiltonian dynamics, followed by the Metropolis (-Hastings) acceptance/rejection step. Compressible HMC (CHMC) generalizes HMC to a situation in which the dynamics is reversible but not necessarily Hamiltonian. This article presents a framework to further extend the algorithm. Within the existing framework, each trajectory of the dynamics must be integrated for the same amount of (random) time to generate a valid Metropolis proposal. Our generalized acceptance/rejection mechanism allows a more deliberate choice of the integration time for each trajectory. The proposed algorithm in particular enables an effective application of variable step size integrators to HMC-type sampling algorithms based on reversible dynamics. The potential of our framework is further demonstrated by another extension of HMC which reduces the wasted computations due to unstable numerical approximations and corr...

5. Nuclear reactions in Monte Carlo codes.

Science.gov (United States)

Ferrari, A; Sala, P R

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.

6. 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......, 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....

7. Geometric Monte Carlo and Black Janus Geometries

CERN Document Server

Bak, Dongsu; Kim, Kyung Kiu; Min, Hyunsoo; Song, Jeong-Pil

2016-01-01

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.

8. Modeling neutron guides using Monte Carlo simulations

CERN Document Server

Wang, D Q; Crow, M L; Wang, X L; Lee, W T; Hubbard, C R

2002-01-01

Four neutron guide geometries, straight, converging, diverging and curved, were characterized using Monte Carlo ray-tracing simulations. The main areas of interest are the transmission of the guides at various neutron energies and the intrinsic time-of-flight (TOF) peak broadening. Use of a delta-function time pulse from a uniform Lambert neutron source allows one to quantitatively simulate the effect of guides' geometry on the TOF peak broadening. With a converging guide, the intensity and the beam divergence increases while the TOF peak width decreases compared with that of a straight guide. By contrast, use of a diverging guide decreases the intensity and the beam divergence, and broadens the width (in TOF) of the transmitted neutron pulse.

9. Accurate barrier heights using diffusion Monte Carlo

CERN Document Server

Krongchon, Kittithat; Wagner, Lucas K

2016-01-01

Fixed node diffusion Monte Carlo (DMC) has been performed on a test set of forward and reverse barrier heights for 19 non-hydrogen-transfer reactions, and the nodal error has been assessed. The DMC results are robust to changes in the nodal surface, as assessed by using different mean-field techniques to generate single determinant wave functions. Using these single determinant nodal surfaces, DMC results in errors of 1.5(5) kcal/mol on barrier heights. Using the large data set of DMC energies, we attempted to find good descriptors of the fixed node error. It does not correlate with a number of descriptors including change in density, but does correlate with the gap between the highest occupied and lowest unoccupied orbital energies in the mean-field calculation.

10. Recent Developments in Quantum Monte Carlo: Methods and Applications

Science.gov (United States)

Aspuru-Guzik, Alan; Austin, Brian; Domin, Dominik; Galek, Peter T. A.; Handy, Nicholas; Prasad, Rajendra; Salomon-Ferrer, Romelia; Umezawa, Naoto; Lester, William A.

2007-12-01

The quantum Monte Carlo method in the diffusion Monte Carlo form has become recognized for its capability of describing the electronic structure of atomic, molecular and condensed matter systems to high accuracy. This talk will briefly outline the method with emphasis on recent developments connected with trial function construction, linear scaling, and applications to selected systems.

11. QUANTUM MONTE-CARLO SIMULATIONS - ALGORITHMS, LIMITATIONS AND APPLICATIONS

NARCIS (Netherlands)

DERAEDT, H

1992-01-01

A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown

12. QWalk: A Quantum Monte Carlo Program for Electronic Structure

CERN Document Server

Wagner, Lucas K; Mitas, Lubos

2007-01-01

We describe QWalk, a new computational package capable of performing Quantum Monte Carlo electronic structure calculations for molecules and solids with many electrons. We describe the structure of the program and its implementation of Quantum Monte Carlo methods. It is open-source, licensed under the GPL, and available at the web site http://www.qwalk.org

13. Quantum Monte Carlo Simulations : Algorithms, Limitations and Applications

NARCIS (Netherlands)

Raedt, H. De

1992-01-01

A survey is given of Quantum Monte Carlo methods currently used to simulate quantum lattice models. The formalisms employed to construct the simulation algorithms are sketched. The origin of fundamental (minus sign) problems which limit the applicability of the Quantum Monte Carlo approach is shown

14. Reporting Monte Carlo Studies in Structural Equation Modeling

NARCIS (Netherlands)

Boomsma, Anne

2013-01-01

In structural equation modeling, Monte Carlo simulations have been used increasingly over the last two decades, as an inventory from the journal Structural Equation Modeling illustrates. Reaching out to a broad audience, this article provides guidelines for reporting Monte Carlo studies in that fiel

15. Practical schemes for accurate forces in quantum Monte Carlo

NARCIS (Netherlands)

Moroni, S.; Saccani, S.; Filippi, Claudia

2014-01-01

While the computation of interatomic forces has become a well-established practice within variational Monte Carlo (VMC), the use of the more accurate Fixed-Node Diffusion Monte Carlo (DMC) method is still largely limited to the computation of total energies on structures obtained at a lower level of

16. The Monte Carlo Method. Popular Lectures in Mathematics.

Science.gov (United States)

Sobol', I. M.

The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…

17. Forest canopy BRDF simulation using Monte Carlo method

NARCIS (Netherlands)

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.

18. Sensitivity of Monte Carlo simulations to input distributions

Energy Technology Data Exchange (ETDEWEB)

RamoRao, B. S.; Srikanta Mishra, S.; McNeish, J.; Andrews, R. W.

2001-07-01

The sensitivity of the results of a Monte Carlo simulation to the shapes and moments of the probability distributions of the input variables is studied. An economical computational scheme is presented as an alternative to the replicate Monte Carlo simulations and is explained with an illustrative example. (Author) 4 refs.

19. Quantum Monte Carlo using a Stochastic Poisson Solver

Energy Technology Data Exchange (ETDEWEB)

Das, D; Martin, R M; Kalos, M H

2005-05-06

Quantum Monte Carlo (QMC) is an extremely powerful method to treat many-body systems. Usually quantum Monte Carlo has been applied in cases where the interaction potential has a simple analytic form, like the 1/r Coulomb potential. However, in a complicated environment as in a semiconductor heterostructure, the evaluation of the interaction itself becomes a non-trivial problem. Obtaining the potential from any grid-based finite-difference method, for every walker and every step is unfeasible. We demonstrate an alternative approach of solving the Poisson equation by a classical Monte Carlo within the overall quantum Monte Carlo scheme. We have developed a modified ''Walk On Spheres'' algorithm using Green's function techniques, which can efficiently account for the interaction energy of walker configurations, typical of quantum Monte Carlo algorithms. This stochastically obtained potential can be easily incorporated within popular quantum Monte Carlo techniques like variational Monte Carlo (VMC) or diffusion Monte Carlo (DMC). We demonstrate the validity of this method by studying a simple problem, the polarization of a helium atom in the electric field of an infinite capacitor.

20. Further experience in Bayesian analysis using Monte Carlo Integration

NARCIS (Netherlands)

H.K. van Dijk (Herman); T. Kloek (Teun)

1980-01-01

textabstractAn earlier paper [Kloek and Van Dijk (1978)] is extended in three ways. First, Monte Carlo integration is performed in a nine-dimensional parameter space of Klein's model I [Klein (1950)]. Second, Monte Carlo is used as a tool for the elicitation of a uniform prior on a finite region by

1. 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.

2. Forest canopy BRDF simulation using Monte Carlo method

NARCIS (Netherlands)

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.

3. Practical schemes for accurate forces in quantum Monte Carlo

NARCIS (Netherlands)

Moroni, S.; Saccani, S.; Filippi, C.

2014-01-01

While the computation of interatomic forces has become a well-established practice within variational Monte Carlo (VMC), the use of the more accurate Fixed-Node Diffusion Monte Carlo (DMC) method is still largely limited to the computation of total energies on structures obtained at a lower level of

4. CERN Summer Student Report 2016 Monte Carlo Data Base Improvement

CERN Document Server

Caciulescu, Alexandru Razvan

2016-01-01

During my Summer Student project I worked on improving the Monte Carlo Data Base and MonALISA services for the ALICE Collaboration. The project included learning the infrastructure for tracking and monitoring of the Monte Carlo productions as well as developing a new RESTful API for seamless integration with the JIRA issue tracking framework.

5. Accelerated GPU based SPECT Monte Carlo simulations

Science.gov (United States)

Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

2016-06-01

Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency

6. Monte Carlo modelling of TRIGA research reactor

Science.gov (United States)

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.

7. Accelerated GPU based SPECT Monte Carlo simulations.

Science.gov (United States)

Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

2016-06-07

Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational

8. Monte Carlo scatter correction for SPECT

Science.gov (United States)

Liu, Zemei

The goal of this dissertation is to present a quantitatively accurate and computationally fast scatter correction method that is robust and easily accessible for routine applications in SPECT imaging. A Monte Carlo based scatter estimation method is investigated and developed further. The Monte Carlo simulation program SIMIND (Simulating Medical Imaging Nuclear Detectors), was specifically developed to simulate clinical SPECT systems. The SIMIND scatter estimation (SSE) method was developed further using a multithreading technique to distribute the scatter estimation task across multiple threads running concurrently on multi-core CPU's to accelerate the scatter estimation process. An analytical collimator that ensures less noise was used during SSE. The research includes the addition to SIMIND of charge transport modeling in cadmium zinc telluride (CZT) detectors. Phenomena associated with radiation-induced charge transport including charge trapping, charge diffusion, charge sharing between neighboring detector pixels, as well as uncertainties in the detection process are addressed. Experimental measurements and simulation studies were designed for scintillation crystal based SPECT and CZT based SPECT systems to verify and evaluate the expanded SSE method. Jaszczak Deluxe and Anthropomorphic Torso Phantoms (Data Spectrum Corporation, Hillsborough, NC, USA) were used for experimental measurements and digital versions of the same phantoms employed during simulations to mimic experimental acquisitions. This study design enabled easy comparison of experimental and simulated data. The results have consistently shown that the SSE method performed similarly or better than the triple energy window (TEW) and effective scatter source estimation (ESSE) methods for experiments on all the clinical SPECT systems. The SSE method is proven to be a viable method for scatter estimation for routine clinical use.

9. Fission Matrix Capability for MCNP Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

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

2012-09-05

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

10. Vectorized Monte Carlo methods for reactor lattice analysis

Science.gov (United States)

Brown, F. B.

1984-01-01

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

11. Quantum Monte Carlo methods algorithms for lattice models

CERN Document Server

Gubernatis, James; Werner, Philipp

2016-01-01

Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in ...

12. Monte Carlo 2000 Conference : Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications

CERN Document Server

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.

13. A semianalytic Monte Carlo code for modelling LIDAR measurements

Science.gov (United States)

Palazzi, Elisa; Kostadinov, Ivan; Petritoli, Andrea; Ravegnani, Fabrizio; Bortoli, Daniele; Masieri, Samuele; Premuda, Margherita; Giovanelli, Giorgio

2007-10-01

LIDAR (LIght Detection and Ranging) is an optical active remote sensing technology with many applications in atmospheric physics. Modelling of LIDAR measurements appears useful approach for evaluating the effects of various environmental variables and scenarios as well as of different measurement geometries and instrumental characteristics. In this regard a Monte Carlo simulation model can provide a reliable answer to these important requirements. A semianalytic Monte Carlo code for modelling LIDAR measurements has been developed at ISAC-CNR. The backscattered laser signal detected by the LIDAR system is calculated in the code taking into account the contributions due to the main atmospheric molecular constituents and aerosol particles through processes of single and multiple scattering. The contributions by molecular absorption, ground and clouds reflection are evaluated too. The code can perform simulations of both monostatic and bistatic LIDAR systems. To enhance the efficiency of the Monte Carlo simulation, analytical estimates and expected value calculations are performed. Artificial devices (such as forced collision, local forced collision, splitting and russian roulette) are moreover foreseen by the code, which can enable the user to drastically reduce the variance of the calculation.

14. Stock Price Simulation Using Bootstrap and Monte Carlo

Directory of Open Access Journals (Sweden)

Pažický Martin

2017-06-01

Full Text Available In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.

15. Monte Carlo Simulation as a Research Management Tool

Energy Technology Data Exchange (ETDEWEB)

Douglas, L. J.

1986-06-01

Monte Carlo simulation provides a research manager with a performance monitoring tool to supplement the standard schedule- and resource-based tools such as the Program Evaluation and Review Technique (PERT) and Critical Path Method (CPM). The value of the Monte Carlo simulation in a research environment is that it 1) provides a method for ranking competing processes, 2) couples technical improvements to the process economics, and 3) provides a mechanism to determine the value of research dollars. In this paper the Monte Carlo simulation approach is developed and applied to the evaluation of three competing processes for converting lignocellulosic biomass to ethanol. The technique is shown to be useful for ranking the processes and illustrating the importance of the timeframe of the analysis on the decision process. The results show that acid hydrolysis processes have higher potential for near-term application (2-5 years), while the enzymatic hydrolysis approach has an equal chance to be competitive in the long term (beyond 10 years).

16. Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo

Energy Technology Data Exchange (ETDEWEB)

Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)

2011-07-01

This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)

17. Monte Carlo Numerical Models for Nuclear Logging Applications

Directory of Open Access Journals (Sweden)

Fusheng Li

2012-06-01

Full Text Available Nuclear logging is one of most important logging services provided by many oil service companies. The main parameters of interest are formation porosity, bulk density, and natural radiation. Other services are also provided from using complex nuclear logging tools, such as formation lithology/mineralogy, etc. Some parameters can be measured by using neutron logging tools and some can only be measured by using a gamma ray tool. To understand the response of nuclear logging tools, the neutron transport/diffusion theory and photon diffusion theory are needed. Unfortunately, for most cases there are no analytical answers if complex tool geometry is involved. For many years, Monte Carlo numerical models have been used by nuclear scientists in the well logging industry to address these challenges. The models have been widely employed in the optimization of nuclear logging tool design, and the development of interpretation methods for nuclear logs. They have also been used to predict the response of nuclear logging systems for forward simulation problems. In this case, the system parameters including geometry, materials and nuclear sources, etc., are pre-defined and the transportation and interactions of nuclear particles (such as neutrons, photons and/or electrons in the regions of interest are simulated according to detailed nuclear physics theory and their nuclear cross-section data (probability of interacting. Then the deposited energies of particles entering the detectors are recorded and tallied and the tool responses to such a scenario are generated. A general-purpose code named Monte Carlo N– Particle (MCNP has been the industry-standard for some time. In this paper, we briefly introduce the fundamental principles of Monte Carlo numerical modeling and review the physics of MCNP. Some of the latest developments of Monte Carlo Models are also reviewed. A variety of examples are presented to illustrate the uses of Monte Carlo numerical models

18. 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.

19. Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions

Directory of Open Access Journals (Sweden)

Samuel Livingstone

2014-06-01

Full Text Available Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo simulation for statistical inference and molecular dynamics is provided, with particular emphasis on methods based on Langevin diffusions. After this, geometric concepts in Markov chain Monte Carlo are introduced. A full derivation of the Langevin diffusion on a Riemannian manifold is given, together with a discussion of the appropriate Riemannian metric choice for different problems. A survey of applications is provided, and some open questions are discussed.

20. The Monte Carlo method the method of statistical trials

CERN Document Server

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

1. 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.)

2. A continuation multilevel Monte Carlo algorithm

KAUST Repository

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.

3. Monte Carlo Simulations of the Photospheric Process

CERN Document Server

Santana, Rodolfo; Hernandez, Roberto A; Kumar, Pawan

2015-01-01

We present a Monte Carlo (MC) code we wrote to simulate the photospheric process and to study the photospheric spectrum above the peak energy. Our simulations were performed with a photon to electron ratio $N_{\\gamma}/N_{e} = 10^{5}$, as determined by observations of the GRB prompt emission. We searched an exhaustive parameter space to determine if the photospheric process can match the observed high-energy spectrum of the prompt emission. If we do not consider electron re-heating, we determined that the best conditions to produce the observed high-energy spectrum are low photon temperatures and high optical depths. However, for these simulations, the spectrum peaks at an energy below 300 keV by a factor $\\sim 10$. For the cases we consider with higher photon temperatures and lower optical depths, we demonstrate that additional energy in the electrons is required to produce a power-law spectrum above the peak-energy. By considering electron re-heating near the photosphere, the spectrum for these simulations h...

4. Finding Planet Nine: a Monte Carlo approach

CERN Document Server

Marcos, C de la Fuente

2016-01-01

Planet Nine is a hypothetical planet located well beyond Pluto that has been proposed in an attempt to explain the observed clustering in physical space of the perihelia of six extreme trans-Neptunian objects or ETNOs. The predicted approximate values of its orbital elements include a semimajor axis of 700 au, an eccentricity of 0.6, an inclination of 30 degrees, and an argument of perihelion of 150 degrees. Searching for this putative planet is already under way. Here, we use a Monte Carlo approach to create a synthetic population of Planet Nine orbits and study its visibility statistically in terms of various parameters and focusing on the aphelion configuration. Our analysis shows that, if Planet Nine exists and is at aphelion, it might be found projected against one out of four specific areas in the sky. Each area is linked to a particular value of the longitude of the ascending node and two of them are compatible with an apsidal antialignment scenario. In addition and after studying the current statistic...

5. Atomistic Monte Carlo simulation of lipid membranes.

Science.gov (United States)

Wüstner, Daniel; Sklenar, Heinz

2014-01-24

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.

6. Parallel Monte Carlo Simulation of Aerosol Dynamics

Directory of Open Access Journals (Sweden)

Kun Zhou

2014-02-01

Full Text Available 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.

7. Monte Carlo simulations of Protein Adsorption

Science.gov (United States)

Sharma, Sumit; Kumar, Sanat K.; Belfort, Georges

2008-03-01

Amyloidogenic diseases, such as, Alzheimer's are caused by adsorption and aggregation of partially unfolded proteins. Adsorption of proteins is a concern in design of biomedical devices, such as dialysis membranes. Protein adsorption is often accompanied by conformational rearrangements in protein molecules. Such conformational rearrangements are thought to affect many properties of adsorbed protein molecules such as their adhesion strength to the surface, biological activity, and aggregation tendency. It has been experimentally shown that many naturally occurring proteins, upon adsorption to hydrophobic surfaces, undergo a helix to sheet or random coil secondary structural rearrangement. However, to better understand the equilibrium structural complexities of this phenomenon, we have performed Monte Carlo (MC) simulations of adsorption of a four helix bundle, modeled as a lattice protein, and studied the adsorption behavior and equilibrium protein conformations at different temperatures and degrees of surface hydrophobicity. To study the free energy and entropic effects on adsorption, Canonical ensemble MC simulations have been combined with Weighted Histogram Analysis Method(WHAM). Conformational transitions of proteins on surfaces will be discussed as a function of surface hydrophobicity and compared to analogous bulk transitions.

8. Monte Carlo simulations of the NIMROD diffractometer

Energy Technology Data Exchange (ETDEWEB)

Botti, A. [University of Roma TRE, Rome (Italy)]. E-mail: botti@fis.uniroma3.it; Ricci, M.A. [University of Roma TRE, Rome (Italy); Bowron, D.T. [ISIS-Rutherford Appleton Laboratory, Chilton (United Kingdom); Soper, A.K. [ISIS-Rutherford Appleton Laboratory, Chilton (United Kingdom)

2006-11-15

The near and intermediate range order diffractometer (NIMROD) has been selected as a day one instrument on the second target station at ISIS. Uniquely, NIMROD will provide continuous access to particle separations ranging from the interatomic (<1A) to the mesoscopic (<300A). This instrument is mainly designed for structural investigations, although the possibility of putting a Fermi chopper (and corresponding NIMONIC chopper) in the incident beam line, will potentially allow the performance of low resolution inelastic scattering measurements. The performance characteristics of the TOF diffractometer have been simulated by means of a series of Monte Carlo calculations. In particular, the flux as a function of the transferred momentum Q as well as the resolution in Q and transferred energy have been estimated. Moreover, the possibility of including a honeycomb collimator in order to achieve better resolution has been tested. Here, we want to present the design of this diffractometer that will bridge the gap between wide- and small-angle neutron scattering experiments.

9. Monte Carlo Simulation of River Meander Modelling

Science.gov (United States)

Posner, A. J.; Duan, J. G.

2010-12-01

This study first compares the first order analytical solutions for flow field by Ikeda et. al. (1981) and Johanesson and Parker (1989b). Ikeda et. al.’s (1981) linear bank erosion model was implemented to predict the rate of bank erosion in which the bank erosion coefficient is treated as a stochastic variable that varies with physical properties of the bank (e.g. cohesiveness, stratigraphy, vegetation density). The developed model was used to predict the evolution of meandering planforms. Then, the modeling results were analyzed and compared to the observed data. Since the migration of meandering channel consists of downstream translation, lateral expansion, and downstream or upstream rotations. Several measures are formulated in order to determine which of the resulting planform is closest to the experimental measured one. Results from the deterministic model highly depend on the calibrated erosion coefficient. Since field measurements are always limited, the stochastic model yielded more realistic predictions of meandering planform evolutions. Due to the random nature of bank erosion coefficient, the meandering planform evolution is a stochastic process that can only be accurately predicted by a stochastic model. Quasi-2D Ikeda (1989) flow solution with Monte Carlo Simulation of Bank Erosion Coefficient.

10. Commensurabilities between ETNOs: a Monte Carlo survey

Science.gov (United States)

de la Fuente Marcos, C.; de la Fuente Marcos, R.

2016-07-01

Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nine hypothesis; in particular, a number of objects may be trapped in the 5:3 and 3:1 mean motion resonances with a putative Planet Nine with semimajor axis ˜700 au.

11. Monte Carlo simulations for focusing elliptical guides

Energy Technology Data Exchange (ETDEWEB)

Valicu, Roxana [FRM2 Garching, Muenchen (Germany); Boeni, Peter [E20, TU Muenchen (Germany)

2009-07-01

The aim of the Monte Carlo simulations using McStas Programme was to improve the focusing of the neutron beam existing at PGAA (FRM II) by prolongation of the existing elliptic guide (coated now with supermirrors with m=3) with a new part. First we have tried with an initial length of the additional guide of 7,5cm and coatings for the neutron guide of supermirrors with m=4,5 and 6. The gain (calculated by dividing the intensity in the focal point after adding the guide by the intensity at the focal point with the initial guide) obtained for this coatings indicated that a coating with m=5 would be appropriate for a first trial. The next step was to vary the length of the additional guide for this m value and therefore choosing the appropriate length for the maximal gain. With the m value and the length of the guide fixed we have introduced an aperture 1 cm before the focal point and we have varied the radius of this aperture in order to obtain a focused beam. We have observed a dramatic decrease in the size of the beam in the focal point after introducing this aperture. The simulation results, the gains obtained and the evolution of the beam size will be presented.

12. Monte Carlo Production Management at CMS

CERN Document Server

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...

13. 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.

14. Parallel Monte Carlo simulation of aerosol dynamics

KAUST Repository

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.

15. Highly Efficient Monte-Carlo for Estimating the Unavailability of Markov Dynamic System1）

Institute of Scientific and Technical Information of China (English)

XIAOGang; DENGLi; ZHANGBen-Ai; ZHUJian-Shi

2004-01-01

Monte Carlo simulation has become an important tool for estimating the reliability andavailability of dynamic system, since conventional numerical methods are no longer efficient whenthe size of the system to solve is large. However, evaluating by a simulation the probability of oc-currence of very rare events means playing a very large number of histories of the system, whichleads to unacceptable computing time. Highly efficient Monte Carlo should be worked out. In thispaper, based on the integral equation describing state transitions of Markov dynamic system, a u-niform Monte Carlo for estimating unavailability is presented. Using free-flight estimator, directstatistical estimation Monte Carlo is achieved. Using both free-flight estimator and biased proba-bility space of sampling, weighted statistical estimation Monte Carlo is also achieved. Five MonteCarlo schemes, including crude simulation, analog simulation, statistical estimation based oncrude and analog simulation, and weighted statistical estimation, are used for calculating the un-availability of a repairable Con/3/30 : F system. Their efficiencies are compared with each other.The results show the weighted statistical estimation Monte Carlo has the smallest variance and thehighest efficiency in very rare events simulation.

16. On adaptive resampling strategies for sequential Monte Carlo methods

CERN Document Server

Del Moral, Pierre; Jasra, Ajay; 10.3150/10-BEJ335

2012-01-01

Sequential Monte Carlo (SMC) methods are a class of techniques to sample approximately from any sequence of probability distributions using a combination of importance sampling and resampling steps. This paper is concerned with the convergence analysis of a class of SMC methods where the times at which resampling occurs are computed online using criteria such as the effective sample size. This is a popular approach amongst practitioners but there are very few convergence results available for these methods. By combining semigroup techniques with an original coupling argument, we obtain functional central limit theorems and uniform exponential concentration estimates for these algorithms.

17. TRIPOLI-3: a neutron/photon Monte Carlo transport code

Energy Technology Data Exchange (ETDEWEB)

Nimal, J.C.; Vergnaud, T. [Commissariat a l' Energie Atomique, Gif-sur-Yvette (France). Service d' Etudes de Reacteurs et de Mathematiques Appliquees

2001-07-01

The present version of TRIPOLI-3 solves the transport equation for coupled neutron and gamma ray problems in three dimensional geometries by using the Monte Carlo method. This code is devoted both to shielding and criticality problems. The most important feature for particle transport equation solving is the fine treatment of the physical phenomena and sophisticated biasing technics useful for deep penetrations. The code is used either for shielding design studies or for reference and benchmark to validate cross sections. Neutronic studies are essentially cell or small core calculations and criticality problems. TRIPOLI-3 has been used as reference method, for example, for resonance self shielding qualification. (orig.)

18. Probabilistic Assessments of the Plate Using Monte Carlo Simulation

Energy Technology Data Exchange (ETDEWEB)

Ismail, A E [Department of Mechanical Engineering, Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Batu Pahat, 86400 Johor (Malaysia); Ariffin, A K; Abdullah, S; Ghazali, M J, E-mail: kamal@eng.ukm.my, E-mail: shahrum@eng.ukm.my, E-mail: maryam@eng.ukm.my, E-mail: emran@uthm.edu.my [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)

2011-02-15

This paper presents the probabilistic analysis of the plate with a hole using several multiaxial high cycle fatigue criteria (MHFC). Dang Van, Sines, Crossland criteria were used and von Mises criterion was also considered for comparison purpose. Parametric finite element model of the plate was developed and several important random variable parameters were selected and Latin Hypercube Sampling Monte-Carlo Simulation (LHS-MCS) was used for probabilistic analysis tool. It was found that, different structural reliability and sensitivity factors were obtained using different failure criteria. According to the results multiaxial fatigue criteria are the most significant criteria need to be considered in assessing all the structural behavior especially under complex loadings.

19. Probabilistic Assessments of the Plate Using Monte Carlo Simulation

Science.gov (United States)

Ismail, A. E.; Ariffin, A. K.; Abdullah, S.; Ghazali, M. J.

2011-02-01

This paper presents the probabilistic analysis of the plate with a hole using several multiaxial high cycle fatigue criteria (MHFC). Dang Van, Sines, Crossland criteria were used and von Mises criterion was also considered for comparison purpose. Parametric finite element model of the plate was developed and several important random variable parameters were selected and Latin Hypercube Sampling Monte-Carlo Simulation (LHS-MCS) was used for probabilistic analysis tool. It was found that, different structural reliability and sensitivity factors were obtained using different failure criteria. According to the results multiaxial fatigue criteria are the most significant criteria need to be considered in assessing all the structural behavior especially under complex loadings.

20. Monte Carlo simulation of radiation heat transfer in arrays of fixed discrete surfaces using cell-to-cell photon transport

Energy Technology Data Exchange (ETDEWEB)

Drost, M.K. (Pacific Northwest Lab., Richland, WA (United States)); Welty, J.R. (Oregon State Univ., Corvallis, OR (United States))

1992-08-01

Radiation heat transfer in an array of fixed discrete surfaces is an important problem that is particularly difficult to analyze because of the nonhomogeneous and anisotropic optical properties involved. This article presents an efficient Monte Carlo method for evaluating radiation heat transfer in arrays of fixed discrete surfaces. This Monte Carlo model has been optimized to take advantage of the regular arrangement of surfaces often encountered in these arrays. Monte Carlo model predictions have been compared with analytical and experimental results.

1. Monte Carlo simulation of radiation heat transfer in arrays of fixed discrete surfaces using cell-to-cell photon transport

Energy Technology Data Exchange (ETDEWEB)

Drost, M.K. [Pacific Northwest Lab., Richland, WA (United States); Welty, J.R. [Oregon State Univ., Corvallis, OR (United States)

1992-08-01

Radiation heat transfer in an array of fixed discrete surfaces is an important problem that is particularly difficult to analyze because of the nonhomogeneous and anisotropic optical properties involved. This article presents an efficient Monte Carlo method for evaluating radiation heat transfer in arrays of fixed discrete surfaces. This Monte Carlo model has been optimized to take advantage of the regular arrangement of surfaces often encountered in these arrays. Monte Carlo model predictions have been compared with analytical and experimental results.

2. Monte-Carlo simulation-based statistical modeling

CERN Document Server

Chen, John

2017-01-01

This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.

3. EXTENDED MONTE CARLO LOCALIZATION ALGORITHM FOR MOBILE SENSOR NETWORKS

Institute of Scientific and Technical Information of China (English)

2008-01-01

A real-world localization system for wireless sensor networks that adapts for mobility and irregular radio propagation model is considered.The traditional range-based techniques and recent range-free localization schemes are not welt competent for localization in mobile sensor networks,while the probabilistic approach of Bayesian filtering with particle-based density representations provides a comprehensive solution to such localization problem.Monte Carlo localization is a Bayesian filtering method that approximates the mobile node’S location by a set of weighted particles.In this paper,an enhanced Monte Carlo localization algorithm-Extended Monte Carlo Localization (Ext-MCL) is suitable for the practical wireless network environment where the radio propagation model is irregular.Simulation results show the proposal gets better localization accuracy and higher localizable node number than previously proposed Monte Carlo localization schemes not only for ideal radio model,but also for irregular one.

4. On the Markov Chain Monte Carlo (MCMC) method

Indian Academy of Sciences (India)

Rajeeva L Karandikar

2006-04-01

Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be speciﬁed indirectly. In this article, we give an introduction to this method along with some examples.

5. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

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.

6. Bayesian phylogeny analysis via stochastic approximation Monte Carlo.

Science.gov (United States)

Cheon, Sooyoung; Liang, Faming

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.

7. Monte Carlo simulations: Hidden errors from good'' random number generators

Science.gov (United States)

Ferrenberg, Alan M.; Landau, D. P.; Wong, Y. Joanna

1992-12-01

The Wolff algorithm is now accepted as the best cluster-flipping Monte Carlo algorithm for beating critical slowing down.'' We show how this method can yield incorrect answers due to subtle correlations in `high quality'' random number generators.

8. An Introduction to Multilevel Monte Carlo for Option Valuation

CERN Document Server

Higham, Desmond J

2015-01-01

Monte Carlo is a simple and flexible tool that is widely used in computational finance. In this context, it is common for the quantity of interest to be the expected value of a random variable defined via a stochastic differential equation. In 2008, Giles proposed a remarkable improvement to the approach of discretizing with a numerical method and applying standard Monte Carlo. His multilevel Monte Carlo method offers an order of speed up given by the inverse of epsilon, where epsilon is the required accuracy. So computations can run 100 times more quickly when two digits of accuracy are required. The multilevel philosophy has since been adopted by a range of researchers and a wealth of practically significant results has arisen, most of which have yet to make their way into the expository literature. In this work, we give a brief, accessible, introduction to multilevel Monte Carlo and summarize recent results applicable to the task of option evaluation.

9. MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD

Science.gov (United States)

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

10. A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

NARCIS (Netherlands)

MIKOSCH, T; WANG, QA

1995-01-01

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.

11. A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

NARCIS (Netherlands)

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.

12. Accelerating Monte Carlo Renderers by Ray Histogram Fusion

Directory of Open Access Journals (Sweden)

Mauricio Delbracio

2015-03-01

Full Text Available This paper details the recently introduced Ray Histogram Fusion (RHF filter for accelerating Monte Carlo renderers [M. Delbracio et al., Boosting Monte Carlo Rendering by Ray Histogram Fusion, ACM Transactions on Graphics, 33 (2014]. In this filter, each pixel in the image is characterized by the colors of the rays that reach its surface. Pixels are compared using a statistical distance on the associated ray color distributions. Based on this distance, it decides whether two pixels can share their rays or not. The RHF filter is consistent: as the number of samples increases, more evidence is required to average two pixels. The algorithm provides a significant gain in PSNR, or equivalently accelerates the rendering process by using many fewer Monte Carlo samples without observable bias. Since the RHF filter depends only on the Monte Carlo samples color values, it can be naturally combined with all rendering effects.

13. MCOR - Monte Carlo depletion code for reference LWR calculations

Energy Technology Data Exchange (ETDEWEB)

Puente Espel, Federico, E-mail: fup104@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Tippayakul, Chanatip, E-mail: cut110@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Ivanov, Kostadin, E-mail: kni1@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Misu, Stefan, E-mail: Stefan.Misu@areva.com [AREVA, AREVA NP GmbH, Erlangen (Germany)

2011-04-15

Research highlights: > Introduction of a reference Monte Carlo based depletion code with extended capabilities. > Verification and validation results for MCOR. > Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations. Additionally

14. 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.

15. Public Infrastructure for Monte Carlo Simulation: publicMC@BATAN

CERN Document Server

Waskita, A A; Akbar, Z; Handoko, L T; 10.1063/1.3462759

2010-01-01

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

16. Radiative Equilibrium and Temperature Correction in Monte Carlo Radiation Transfer

OpenAIRE

Bjorkman, J. E.; Wood, Kenneth

2001-01-01

We describe a general radiative equilibrium and temperature correction procedure for use in Monte Carlo radiation transfer codes with sources of temperature-independent opacity, such as astrophysical dust. The technique utilizes the fact that Monte Carlo simulations track individual photon packets, so we may easily determine where their energy is absorbed. When a packet is absorbed, it heats a particular cell within the envelope, raising its temperature. To enforce radiative equilibrium, the ...

17. Chemical accuracy from quantum Monte Carlo for the Benzene Dimer

OpenAIRE

Azadi, Sam; Cohen, R. E

2015-01-01

We report an accurate study of interactions between Benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory (DFT) using different van der Waals (vdW) functionals. In our QMC calculations, we use accurate correlated trial wave functions including three-body Jastrow factors, and backflow transformations. We consider two benzene molecules in the parallel displaced (PD) geometry, and fin...

18. de Finetti Priors using Markov chain Monte Carlo computations.

Science.gov (United States)

Bacallado, Sergio; Diaconis, Persi; Holmes, Susan

2015-07-01

Recent advances in Monte Carlo methods allow us to revisit work by de Finetti who suggested the use of approximate exchangeability in the analyses of contingency tables. This paper gives examples of computational implementations using Metropolis Hastings, Langevin and Hamiltonian Monte Carlo to compute posterior distributions for test statistics relevant for testing independence, reversible or three way models for discrete exponential families using polynomial priors and Gröbner bases.

19. Event-chain Monte Carlo for classical continuous spin models

Science.gov (United States)

Michel, Manon; Mayer, Johannes; Krauth, Werner

2015-10-01

We apply the event-chain Monte Carlo algorithm to classical continuum spin models on a lattice and clarify the condition for its validity. In the two-dimensional XY model, it outperforms the local Monte Carlo algorithm by two orders of magnitude, although it remains slower than the Wolff cluster algorithm. In the three-dimensional XY spin glass model at low temperature, the event-chain algorithm is far superior to the other algorithms.

20. Confidence and efficiency scaling in Variational Quantum Monte Carlo calculations

CERN Document Server

Delyon, François; Holzmann, Markus

2016-01-01

Based on the central limit theorem, we discuss the problem of evaluation of the statistical error of Monte Carlo calculations using a time discretized diffusion process. We present a robust and practical method to determine the effective variance of general observables and show how to verify the equilibrium hypothesis by the Kolmogorov-Smirnov test. We then derive scaling laws of the efficiency illustrated by Variational Monte Carlo calculations on the two dimensional electron gas.

1. Study of the Transition Flow Regime using Monte Carlo Methods

Science.gov (United States)

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.

2. Monte Carlo Simulation of Optical Properties of Wake Bubbles

Institute of Scientific and Technical Information of China (English)

CAO Jing; WANG Jiang-An; JIANG Xing-Zhou; SHI Sheng-Wei

2007-01-01

Based on Mie scattering theory and the theory of multiple light scattering, the light scattering properties of air bubbles in a wake are analysed by Monte Carlo simulation. The results show that backscattering is enhanced obviously due to the existence of bubbles, especially with the increase of bubble density, and that it is feasible to use the Monte Carlo method to study the properties of light scattering by air bubbles.

3. Successful combination of the stochastic linearization and Monte Carlo methods

Science.gov (United States)

Elishakoff, I.; Colombi, P.

1993-01-01

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

4. Confidence and efficiency scaling in variational quantum Monte Carlo calculations

Science.gov (United States)

Delyon, F.; Bernu, B.; Holzmann, Markus

2017-02-01

Based on the central limit theorem, we discuss the problem of evaluation of the statistical error of Monte Carlo calculations using a time-discretized diffusion process. We present a robust and practical method to determine the effective variance of general observables and show how to verify the equilibrium hypothesis by the Kolmogorov-Smirnov test. We then derive scaling laws of the efficiency illustrated by variational Monte Carlo calculations on the two-dimensional electron gas.

5. Monte Carlo methods for light propagation in biological tissues

OpenAIRE

Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine

2016-01-01

Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis–Hastings algori...

6. Multiscale Monte Carlo equilibration: pure Yang-Mills theory

CERN Document Server

Endres, Michael G; Detmold, William; Orginos, Kostas; Pochinsky, Andrew V

2015-01-01

We present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.

7. Geometrical and Monte Carlo projectors in 3D PET reconstruction

OpenAIRE

Aguiar, Pablo; Rafecas López, Magdalena; Ortuno, Juan Enrique; Kontaxakis, George; Santos, Andrés; Pavía, Javier; Ros, Domènec

2010-01-01

Purpose: In the present work, the authors compare geometrical and Monte Carlo projectors in detail. The geometrical projectors considered were the conventional geometrical Siddon ray-tracer (S-RT) and the orthogonal distance-based ray-tracer (OD-RT), based on computing the orthogonal distance from the center of image voxel to the line-of-response. A comparison of these geometrical projectors was performed using different point spread function (PSF) models. The Monte Carlo-based method under c...

8. 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.

9. Monte Carlo study for γ+N→π+N at a new compound target

Institute of Scientific and Technical Information of China (English)

2008-01-01

An inbuilt compound target composed of carbon and tungsten is designed,and optimized by realistic GEANT4 Monte Carlo simulation.Also,we do a Monte Carlo study for single-pion photoproduction at the target.The results are presented from the simulation of pion yield,angular distribution and spectrum (at θ1ab,θcm=41°).These efforts are important to the coming measurement of the differential cross section for γ+N→π+N.

10. Monte Carlo Volcano Seismic Moment Tensors

Science.gov (United States)

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.

11. Quantum Monte Carlo with directed loops.

Science.gov (United States)

Syljuåsen, Olav F; Sandvik, Anders W

2002-10-01

We introduce the concept of directed loops in stochastic series expansion and path-integral quantum Monte Carlo methods. Using the detailed balance rules for directed loops, we show that it is possible to smoothly connect generally applicable simulation schemes (in which it is necessary to include backtracking processes in the loop construction) to more restricted loop algorithms that can be constructed only for a limited range of Hamiltonians (where backtracking can be avoided). The "algorithmic discontinuities" between general and special points (or regions) in parameter space can hence be eliminated. As a specific example, we consider the anisotropic S=1/2 Heisenberg antiferromagnet in an external magnetic field. We show that directed-loop simulations are very efficient for the full range of magnetic fields (zero to the saturation point) and anisotropies. In particular, for weak fields and anisotropies, the autocorrelations are significantly reduced relative to those of previous approaches. The back-tracking probability vanishes continuously as the isotropic Heisenberg point is approached. For the XY model, we show that back tracking can be avoided for all fields extending up to the saturation field. The method is hence particularly efficient in this case. We use directed-loop simulations to study the magnetization process in the two-dimensional Heisenberg model at very low temperatures. For LxL lattices with L up to 64, we utilize the step structure in the magnetization curve to extract gaps between different spin sectors. Finite-size scaling of the gaps gives an accurate estimate of the transverse susceptibility in the thermodynamic limit: chi( perpendicular )=0.0659+/-0.0002.

12. Monte Carlo simulation of large electron fields

Science.gov (United States)

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

2008-03-01

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

13. Dosimetry applications in GATE Monte Carlo toolkit.

Science.gov (United States)

2017-02-21

14. Monte Carlo implementation of polarized hadronization

Science.gov (United States)

Matevosyan, Hrayr H.; Kotzinian, Aram; Thomas, Anthony W.

2017-01-01

We study the polarized quark hadronization in a Monte Carlo (MC) framework based on the recent extension of the quark-jet framework, where a self-consistent treatment of the quark polarization transfer in a sequential hadronization picture has been presented. Here, we first adopt this approach for MC simulations of the hadronization process with a finite number of produced hadrons, expressing the relevant probabilities in terms of the eight leading twist quark-to-quark transverse-momentum-dependent (TMD) splitting functions (SFs) for elementary q →q'+h transition. We present explicit expressions for the unpolarized and Collins fragmentation functions (FFs) of unpolarized hadrons emitted at rank 2. Further, we demonstrate that all the current spectator-type model calculations of the leading twist quark-to-quark TMD SFs violate the positivity constraints, and we propose a quark model based ansatz for these input functions that circumvents the problem. We validate our MC framework by explicitly proving the absence of unphysical azimuthal modulations of the computed polarized FFs, and by precisely reproducing the earlier derived explicit results for rank-2 pions. Finally, we present the full results for pion unpolarized and Collins FFs, as well as the corresponding analyzing powers from high statistics MC simulations with a large number of produced hadrons for two different model input elementary SFs. The results for both sets of input functions exhibit the same general features of an opposite signed Collins function for favored and unfavored channels at large z and, at the same time, demonstrate the flexibility of the quark-jet framework by producing significantly different dependences of the results at mid to low z for the two model inputs.

15. kmos: A lattice kinetic Monte Carlo framework

Science.gov (United States)

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

2014-07-01

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

16. A Survey on Multilevel Monte Carlo for European Options

Directory of Open Access Journals (Sweden)

2016-03-01

Full Text Available One of the most applicable and common methods for pricing options is the Monte Carlo simulation. Among the advantages of this method we can name ease of use, being suitable for different types of options including vanilla options and exotic options. On one hand, convergence rate of Monte Carlo's variance is , which has a slow convergence in responding problems, such that for achieving accuracy of ε for a d dimensional problem, computation complexity would be . Thus, various methods have been proposed in Monte Carlo framework to increase the convergence rate of variance as variance reduction methods. One of the recent methods was proposed by Gills in 2006, is the multilevel Monte Carlo method. This method besides reducing the computationcomplexity to while being used in Euler discretizing and to while being used in Milsteindiscretizing method, has the capacity to be combined with other variance reduction methods. In this article, multilevel Monte Carlo using Euler and Milsteindiscretizing methods is adopted for comparing computation complexity with standard Monte Carlo method in pricing European call options.

17. Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments

Energy Technology Data Exchange (ETDEWEB)

Pevey, Ronald E.

2005-09-15

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.

18. Monte Carlo simulation experiments on box-type radon dosimeter

Science.gov (United States)

Jamil, Khalid; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid

2014-11-01

Epidemiological studies show that inhalation of radon gas (222Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the 222Rn concentrations (Bq/m3) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter's dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (ηint) and alpha hit efficiency (ηhit). The ηint depends upon only on the dimensions of the dosimeter and ηhit depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper explains that how radon concentration from the

19. PREFACE: First European Workshop on Monte Carlo Treatment Planning

Science.gov (United States)

Reynaert, Nick

2007-07-01

The "First European Workshop on Monte Carlo treatment planning", was an initiative of the European working group on Monte Carlo treatment planning (EWG-MCTP). It was organised at Ghent University (Belgium) on 22-25October 2006. The meeting was very successful and was attended by 150 participants. The impressive list of invited speakers and the scientific contributions (posters and oral presentations) have led to a very interesting program, that was well appreciated by all attendants. In addition, the presence of seven vendors of commercial MCTP software systems provided serious added value to the workshop. For each vendor, a representative has given a presentation in a dedicated session, explaining the current status of their system. It is clear that, for "traditional" radiotherapy applications (using photon or electron beams), Monte Carlo dose calculations have become the state of the art, and are being introduced into almost all commercial treatment planning systems. Invited lectures illustrated that scientific challenges are currently associated with 4D applications (e.g. respiratory motion) and the introduction of MC dose calculations in inverse planning. But it was striking that the Monte Carlo technique is also becoming very important in more novel treatment modalities such as BNCT, hadron therapy, stereotactic radiosurgery, Tomotherapy, etc. This emphasizes the continuous growing interest in MCTP. The people who attended the dosimetry session will certainly remember the high level discussion on the determination of correction factors for different ion chambers, used in small fields. The following proceedings will certainly confirm the high scientific level of the meeting. I would like to thank the members of the local organizing committee for all the hard work done before, during and after this meeting. The organisation of such an event is not a trivial task and it would not have been possible without the help of all my colleagues. I would also like to thank

20. Monte Carlo simulation experiments on box-type radon dosimeter

Energy Technology Data Exchange (ETDEWEB)

Jamil, Khalid, E-mail: kjamil@comsats.edu.pk; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid

2014-11-11

Epidemiological studies show that inhalation of radon gas ({sup 222}Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the {sup 222}Rn concentrations (Bq/m{sup 3}) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter’s dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (η{sub int}) and alpha hit efficiency (η{sub hit}). The η{sub int} depends upon only on the dimensions of the dosimeter and η{sub hit} depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper

1. A pure-sampling quantum Monte Carlo algorithm.

Science.gov (United States)

Ospadov, Egor; Rothstein, Stuart M

2015-01-14

The objective of pure-sampling quantum Monte Carlo is to calculate physical properties that are independent of the importance sampling function being employed in the calculation, save for the mismatch of its nodal hypersurface with that of the exact wave function. To achieve this objective, we report a pure-sampling algorithm that combines features of forward walking methods of pure-sampling and reptation quantum Monte Carlo (RQMC). The new algorithm accurately samples properties from the mixed and pure distributions simultaneously in runs performed at a single set of time-steps, over which extrapolation to zero time-step is performed. In a detailed comparison, we found RQMC to be less efficient. It requires different sets of time-steps to accurately determine the energy and other properties, such as the dipole moment. We implement our algorithm by systematically increasing an algorithmic parameter until the properties converge to statistically equivalent values. As a proof in principle, we calculated the fixed-node energy, static α polarizability, and other one-electron expectation values for the ground-states of LiH and water molecules. These quantities are free from importance sampling bias, population control bias, time-step bias, extrapolation-model bias, and the finite-field approximation. We found excellent agreement with the accepted values for the energy and a variety of other properties for those systems.

2. Infinite variance in fermion quantum Monte Carlo calculations.

Science.gov (United States)

Shi, Hao; Zhang, Shiwei

2016-03-01

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

3. Infinite Variance in Fermion Quantum Monte Carlo Calculations

CERN Document Server

Shi, Hao

2015-01-01

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, lattice QCD calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied upon to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple sub-areas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations turn out to have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calc...

4. Infinite variance in fermion quantum Monte Carlo calculations

Science.gov (United States)

Shi, Hao; Zhang, Shiwei

2016-03-01

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.

5. 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

6. 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

7. Reducing quasi-ergodicity in a double well potential by Tsallis Monte Carlo simulation

OpenAIRE

Iwamatsu, Masao; Okabe, Yutaka

2000-01-01

A new Monte Carlo scheme based on the system of Tsallis's generalized statistical mechanics is applied to a simple double well potential to calculate the canonical thermal average of potential energy. Although we observed serious quasi-ergodicity when using the standard Metropolis Monte Carlo algorithm, this problem is largely reduced by the use of the new Monte Carlo algorithm. Therefore the ergodicity is guaranteed even for short Monte Carlo steps if we use this new canonical Monte Carlo sc...

8. Coherent Scattering Imaging Monte Carlo Simulation

Science.gov (United States)

Hassan, Laila Abdulgalil Rafik

Conventional mammography has poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter potentially provides more information because interference of coherently scattered radiation depends on the average intermolecular spacing, and can be used to characterize tissue types. However, typical coherent scatter analysis techniques are not compatible with rapid low dose screening techniques. Coherent scatter slot scan imaging is a novel imaging technique which provides new information with higher contrast. In this work a simulation of coherent scatter was performed for slot scan imaging to assess its performance and provide system optimization. In coherent scatter imaging, the coherent scatter is exploited using a conventional slot scan mammography system with anti-scatter grids tilted at the characteristic angle of cancerous tissues. A Monte Carlo simulation was used to simulate the coherent scatter imaging. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The contrast increased as the grid tilt angle increased beyond the characteristic angle for the modeled carcinoma. A grid tilt angle of 16 degrees yielded the highest contrast and signal to noise ratio (SNR). Also, contrast increased as the source voltage increased. Increasing grid ratio improved contrast at the expense of decreasing SNR. A grid ratio of 10:1 was sufficient to give a good contrast without reducing the intensity to a noise level. The optimal source to sample distance was determined to be such that the source should be located at the focal distance of the grid. A carcinoma lump of 0.5x0.5x0.5 cm3 in size was detectable which is reasonable considering the high noise due to the usage of relatively small number of incident photons for computational reasons. A further study is needed to study the effect of breast density and breast thickness

9. Monte Carlo simulation for simultaneous particle coagulation and deposition

Institute of Scientific and Technical Information of China (English)

ZHAO; Haibo; ZHENG; Chuguang

2006-01-01

The process of dynamic evolution in dispersed systems due to simultaneous particle coagulation and deposition is described mathematically by general dynamic equation (GDE). Monte Carlo (MC) method is an important approach of numerical solutions of GDE. However, constant-volume MC method exhibits the contradictory of low computation cost and high computation precision owing to the fluctuation of the number of simulation particles; constant-number MC method can hardly be applied to engineering application and general scientific quantitative analysis due to the continual contraction or expansion of computation domain. In addition, the two MC methods depend closely on the "subsystem" hypothesis, which constraints their expansibility and the scope of application. A new multi-Monte Carlo (MMC) method is promoted to take account of GDE for simultaneous particle coagulation and deposition. MMC method introduces the concept of "weighted fictitious particle" and is based on the "time-driven" technique. Furthermore MMC method maintains synchronously the computational domain and the total number of fictitious particles, which results in the latent expansibility of simulation for boundary condition, the space evolution of particle size distribution and even particle dynamics. The simulation results of MMC method for two special cases in which analytical solutions exist agree with analytical solutions well, which proves that MMC method has high and stable computational precision and low computation cost because of the constant and limited number of fictitious particles. Lastly the source of numerical error and the relative error of MMC method are analyzed, respectively.

10. Optimization of Monte Carlo dose calculations: The interface problem

Science.gov (United States)

Soudentas, Edward

1998-05-01

High energy photon beams are widely used for radiation treatment of deep-seated tumors. The human body contains many types of interfaces between dissimilar materials that affect dose distribution in radiation therapy. Experimentally, significant radiation dose perturbations has been observed at such interfaces. The EGS4 Monte Carlo code was used to calculate dose perturbations at boundaries between dissimilar materials (such as bone/water) for 60Co and 6 MeV linear accelerator beams using a UNIX workstation. A simple test of the reliability of a random number generator was also developed. A systematic study of the adjustable parameters in EGS4 was performed in order to minimize calculational artifacts at boundaries. Calculations of dose perturbations at boundaries between different materials showed that there is a 12% increase in dose at water/bone interface, and a 44% increase in dose at water/copper interface. with the increase mainly due to electrons produced in water and backscattered from the high atomic number material. The dependence of the dose increase on the atomic number was also investigated. The clinically important case of using two parallel opposed beams for radiation therapy was investigated where increased doses at boundaries has been observed. The Monte Carlo calculations can provide accurate dosimetry data under conditions of electronic non-equilibrium at tissue interfaces.

11. pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis

Science.gov (United States)

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.

12. Monte Carlo simulation on teaching of luminescence and excited states decay kinetics; Simulacao Monte Carlo no ensino de luminescencia e cinetica de decaimento de estado excitado

Energy Technology Data Exchange (ETDEWEB)

Winnischofer, Herbert; Araujo, Marcio Peres de; Dias Junior, Lauro Camargo; Novo, Joao Batista Marques [Universidade Federal do Parana (UFPR), Curitiba, PR (Brazil)

2010-07-01

A software based in the Monte Carlo method have been developed aiming the teaching of important cases of mechanisms found in luminescence and in excited states decay kinetics, including: multiple decays, consecutive decays and coupled systems decays. The Monte Carlo Method allows the student to easily simulate and visualize the luminescence mechanisms, focusing on the probabilities of the related steps. The software CINESTEX was written for FreeBASIC compiler; it assumes first-order kinetics and any number of excited states, where the pathways are allowed with probabilities assigned by the user. (author)

13. An unbiased Hessian representation for Monte Carlo PDFs

Energy Technology Data Exchange (ETDEWEB)

Carrazza, Stefano; Forte, Stefano [Universita di Milano, TIF Lab, Dipartimento di Fisica, Milan (Italy); INFN, Sezione di Milano (Italy); Kassabov, Zahari [Universita di Milano, TIF Lab, Dipartimento di Fisica, Milan (Italy); Universita di Torino, Dipartimento di Fisica, Turin (Italy); INFN, Sezione di Torino (Italy); Latorre, Jose Ignacio [Universitat de Barcelona, Departament d' Estructura i Constituents de la Materia, Barcelona (Spain); Rojo, Juan [University of Oxford, Rudolf Peierls Centre for Theoretical Physics, Oxford (United Kingdom)

2015-08-15

We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set. (orig.)

14. An Unbiased Hessian Representation for Monte Carlo PDFs

CERN Document Server

Carrazza, Stefano; Kassabov, Zahari; Latorre, Jose Ignacio; Rojo, Juan

2015-01-01

We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (CMC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available togethe...

15. Monte Carlo evaluation of kerma in an HDR brachytherapy bunker

Energy Technology Data Exchange (ETDEWEB)

Perez-Calatayud, J [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Granero, D [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Ballester, F [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Casal, E [Department of Atomic, Molecular and Nuclear Physics, and IFIC, CSIC-University of Valencia, Burjassot (Spain); Crispin, V [FIVO, Fundacion Instituto Valenciano De OncologIa, Valencia (Spain); Puchades, V [Grupo IMO-SFA, Madrid (Spain); Leon, A [Department of Chemistry and Nuclear Engineering, Polytechnic University of Valencia, Valencia (Spain); Verdu, G [Department of Chemistry and Nuclear Engineering, Polytechnic University of Valencia, Valencia (Spain)

2004-12-21

In recent years, the use of high dose rate (HDR) after-loader machines has greatly increased due to the shift from traditional Cs-137/Ir-192 low dose rate (LDR) to HDR brachytherapy. The method used to calculate the required concrete and, where appropriate, lead shielding in the door is based on analytical methods provided by documents published by the ICRP, the IAEA and the NCRP. The purpose of this study is to perform a more realistic kerma evaluation at the entrance maze door of an HDR bunker using the Monte Carlo code GEANT4. The Monte Carlo results were validated experimentally. The spectrum at the maze entrance door, obtained with Monte Carlo, has an average energy of about 110 keV, maintaining a similar value along the length of the maze. The comparison of results from the aforementioned values with the Monte Carlo ones shows that results obtained using the albedo coefficient from the ICRP document more closely match those given by the Monte Carlo method, although the maximum value given by MC calculations is 30% greater. (note)

16. Monte Carlo studies of model Langmuir monolayers.

Science.gov (United States)

Opps, S B; Yang, B; Gray, C G; Sullivan, D E

2001-04-01

This paper examines some of the basic properties of a model Langmuir monolayer, consisting of surfactant molecules deposited onto a water subphase. The surfactants are modeled as rigid rods composed of a head and tail segment of diameters sigma(hh) and sigma(tt), respectively. The tails consist of n(t) approximately 4-7 effective monomers representing methylene groups. These rigid rods interact via site-site Lennard-Jones potentials with different interaction parameters for the tail-tail, head-tail, and head-head interactions. In a previous paper, we studied the ground-state properties of this system using a Landau approach. In the present paper, Monte Carlo simulations were performed in the canonical ensemble to elucidate the finite-temperature behavior of this system. Simulation techniques, incorporating a system of dynamic filters, allow us to decrease CPU time with negligible statistical error. This paper focuses on several of the key parameters, such as density, head-tail diameter mismatch, and chain length, responsible for driving transitions from uniformly tilted to untilted phases and between different tilt-ordered phases. Upon varying the density of the system, with sigma(hh)=sigma(tt), we observe a transition from a tilted (NNN)-condensed phase to an untilted-liquid phase and, upon comparison with recent experiments with fatty acid-alcohol and fatty acid-ester mixtures [M. C. Shih, M. K. Durbin, A. Malik, P. Zschack, and P. Dutta, J. Chem. Phys. 101, 9132 (1994); E. Teer, C. M. Knobler, C. Lautz, S. Wurlitzer, J. Kildae, and T. M. Fischer, J. Chem. Phys. 106, 1913 (1997)], we identify this as the L'(2)/Ov-L1 phase boundary. By varying the head-tail diameter ratio, we observe a decrease in T(c) with increasing mismatch. However, as the chain length was increased we observed that the transition temperatures increased and differences in T(c) due to head-tail diameter mismatch were diminished. In most of the present research, the water was treated as a hard

17. Calibration and Monte Carlo modelling of neutron long counters

CERN Document Server

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...

18. Vectorizing and macrotasking Monte Carlo neutral particle algorithms

Energy Technology Data Exchange (ETDEWEB)

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.

19. LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events

CERN Document Server

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.

20. TAKING THE NEXT STEP WITH INTELLIGENT MONTE CARLO

Energy Technology Data Exchange (ETDEWEB)

Booth, T.E.; Carlson, J.A. [and others

2000-10-01

For many scientific calculations, Monte Carlo is the only practical method available. Unfortunately, standard Monte Carlo methods converge slowly as the square root of the computer time. We have shown, both numerically and theoretically, that the convergence rate can be increased dramatically if the Monte Carlo algorithm is allowed to adapt based on what it has learned from previous samples. As the learning continues, computational efficiency increases, often geometrically fast. The particle transport work achieved geometric convergence for a two-region problem as well as for problems with rapidly changing nuclear data. The statistics work provided theoretical proof of geometic convergence for continuous transport problems and promising initial results for airborne migration of particles. The statistical physics work applied adaptive methods to a variety of physical problems including the three-dimensional Ising glass, quantum scattering, and eigenvalue problems.

1. Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

Science.gov (United States)

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.

2. Monte Carlo tests of the ELIPGRID-PC algorithm

Energy Technology Data Exchange (ETDEWEB)

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 {plus_minus}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.

3. Sequential Monte Carlo on large binary sampling spaces

CERN Document Server

Schäfer, Christian

2011-01-01

A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for a good performance. In this paper, we present such a parametric family for adaptive sampling on high-dimensional binary spaces. A practical motivation for this problem is variable selection in a linear regression context. We want to sample from a Bayesian posterior distribution on the model space using an appropriate version of Sequential Monte Carlo. Raw versions of Sequential Monte Carlo are easily implemented using binary vectors with independent components. For high-dimensional problems, however, these simple proposals do not yield satisfactory results. The key to an efficient adaptive algorithm are binary parametric families which take correlations into account, analogously to the multivariate normal distribution on continuous spaces. We provide a review of models for binar...

4. Monte Carlo simulation of laser attenuation characteristics in fog

Science.gov (United States)

Wang, Hong-Xia; Sun, Chao; Zhu, You-zhang; Sun, Hong-hui; Li, Pan-shi

2011-06-01

Based on the Mie scattering theory and the gamma size distribution model, the scattering extinction parameter of spherical fog-drop is calculated. For the transmission attenuation of the laser in the fog, a Monte Carlo simulation model is established, and the impact of attenuation ratio on visibility and field angle is computed and analysed using the program developed by MATLAB language. The results of the Monte Carlo method in this paper are compared with the results of single scattering method. The results show that the influence of multiple scattering need to be considered when the visibility is low, and single scattering calculations have larger errors. The phenomenon of multiple scattering can be interpreted more better when the Monte Carlo is used to calculate the attenuation ratio of the laser transmitting in the fog.

5. VARIATIONAL MONTE-CARLO APPROACH FOR ARTICULATED OBJECT TRACKING

Directory of Open Access Journals (Sweden)

Kartik Dwivedi

2013-12-01

Full Text Available In this paper, we describe a novel variational Monte Carlo approach for modeling and tracking body parts of articulated objects. An articulated object (human target is represented as a dynamic Markov network of the different constituent parts. The proposed approach combines local information of individual body parts and other spatial constraints influenced by neighboring parts. The movement of the relative parts of the articulated body is modeled with local information of displacements from the Markov network and the global information from other neighboring parts. We explore the effect of certain model parameters (including the number of parts tracked; number of Monte-Carlo cycles, etc. on system accuracy and show that ourvariational Monte Carlo approach achieves better efficiency and effectiveness compared to other methods on a number of real-time video datasets containing single targets.

6. Meaningful timescales from Monte Carlo simulations of molecular systems

CERN Document Server

Costa, Liborio I

2016-01-01

A new Markov Chain Monte Carlo method for simulating the dynamics of molecular systems with atomistic detail is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.

7. Monte Carlo Methods for Tempo Tracking and Rhythm Quantization

CERN Document Server

Cemgil, A T; 10.1613/jair.1121

2011-01-01

We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. Exact computation of posterior features such as the MAP state is intractable in this model class, so we introduce Monte Carlo methods for integration and optimization. We compare Markov Chain Monte Carlo (MCMC) methods (such as Gibbs sampling, simulated annealing and iterative improvement) and sequential Monte Carlo methods (particle filters). Our simulation results suggest better results with sequential methods. The methods can be applied in both online and batch scenarios such as tempo tracking and transcr...

8. Monte Carlo Simulation in Statistical Physics An Introduction

CERN Document Server

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 ...

9. Applicability of Quasi-Monte Carlo for lattice systems

CERN Document Server

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

2013-01-01

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.

10. 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...

11. Implementation of Monte Carlo Simulations for the Gamma Knife System

Energy Technology Data Exchange (ETDEWEB)

Xiong, W [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Huang, D [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Lee, L [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Feng, J [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Morris, K [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Calugaru, E [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Burman, C [Memorial Sloan-Kettering Cancer Center/Mercy Medical Center, 1000 N Village Ave., Rockville Centre, NY 11570 (United States); Li, J [Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 17111 (United States); Ma, C-M [Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 17111 (United States)

2007-06-15

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

12. A standard Event Class for Monte Carlo Generators

Institute of Scientific and Technical Information of China (English)

L.A.Gerren; M.Fischler

2001-01-01

StdHepC++[1]is a CLHEP[2] Monte Carlo event class library which provides a common interface to Monte Carlo Event Generators,This work is an extensive redesign of the StdHep Fortran interface to use the full power of object oriented design,A generated event maps naturally onto the Directed Acyclic Graph concept and we have used the HepMC classes to implement this.The full implementation allows the user to combine events to simulate beam pileup and access them transparently as though they were a single event.

13. Parallelization of Monte Carlo codes MVP/GMVP

Energy Technology Data Exchange (ETDEWEB)

Nagaya, Yasunobu; Mori, Takamasa; Nakagawa, Masayuki [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Sasaki, Makoto

1998-03-01

General-purpose Monte Carlo codes MVP/GMVP are well-vectorized and thus enable us to perform high-speed Monte Carlo calculations. In order to achieve more speedups, we parallelized the codes on the different types of the parallel processing platforms. The platforms reported are a distributed-memory vector-parallel computer Fujitsu VPP500, a distributed-memory massively parallel computer Intel Paragon and a distributed-memory scalar-parallel computer Hitachi SR2201. As mentioned generally, ideal speedup could be obtained for large-scale problems but parallelization efficiency got worse as the batch size per a processing element (PE) was smaller. (author)

14. Parton distribution functions in Monte Carlo factorisation scheme

Science.gov (United States)

Jadach, S.; Płaczek, W.; Sapeta, S.; Siódmok, A.; Skrzypek, M.

2016-12-01

A next step in development of the KrkNLO method of including complete NLO QCD corrections to hard processes in a LO parton-shower Monte Carlo is presented. It consists of a generalisation of the method, previously used for the Drell-Yan process, to Higgs-boson production. This extension is accompanied with the complete description of parton distribution functions in a dedicated, Monte Carlo factorisation scheme, applicable to any process of production of one or more colour-neutral particles in hadron-hadron collisions.

15. Kinetic Monte Carlo method applied to nucleic acid hairpin folding.

Science.gov (United States)

Sauerwine, Ben; Widom, Michael

2011-12-01

Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure, is advantageous for being able to access behavior at long time scales, even minutes or hours. Transition rates between coarse-grained states depend upon intermediate barriers, which are not directly simulated. We propose an Arrhenius rate model and an intermediate energy model that incorporates the effects of the barrier between simulated states without enlarging the state space itself. Applying our Arrhenius rate model to DNA hairpin folding, we demonstrate improved agreement with experiment compared to the usual kinetic Monte Carlo model. Further improvement results from including rigidity of single-stranded stacking.

16. Quasi-Monte Carlo methods for the Heston model

OpenAIRE

Jan Baldeaux; Dale Roberts

2012-01-01

In this paper, we discuss the application of quasi-Monte Carlo methods to the Heston model. We base our algorithms on the Broadie-Kaya algorithm, an exact simulation scheme for the Heston model. As the joint transition densities are not available in closed-form, the Linear Transformation method due to Imai and Tan, a popular and widely applicable method to improve the effectiveness of quasi-Monte Carlo methods, cannot be employed in the context of path-dependent options when the underlying pr...

17. Modelling hadronic interactions in cosmic ray Monte Carlo generators

Directory of Open Access Journals (Sweden)

Pierog Tanguy

2015-01-01

Full Text Available Currently the uncertainty in the prediction of shower observables for different primary particles and energies is dominated by differences between hadronic interaction models. The LHC data on minimum bias measurements can be used to test Monte Carlo generators and these new constraints will help to reduce the uncertainties in air shower predictions. In this article, after a short introduction on air showers and Monte Carlo generators, we will show the results of the comparison between the updated version of high energy hadronic interaction models EPOS LHC and QGSJETII-04 with LHC data. Results for air shower simulations and their consequences on comparisons with air shower data will be discussed.

18. An overview of Monte Carlo treatment planning for radiotherapy.

Science.gov (United States)

Spezi, Emiliano; Lewis, Geraint

2008-01-01

The implementation of Monte Carlo dose calculation algorithms in clinical radiotherapy treatment planning systems has been anticipated for many years. Despite a continuous increase of interest in Monte Carlo Treatment Planning (MCTP), its introduction into clinical practice has been delayed by the extent of calculation time required. The development of newer and faster MC codes is behind the commercialisation of the first MC-based treatment planning systems. The intended scope of this article is to provide the reader with a compact 'primer' on different approaches to MCTP with particular attention to the latest developments in the field.

19. Applications of quantum Monte Carlo methods in condensed systems

CERN Document Server

Kolorenc, Jindrich

2010-01-01

The quantum Monte Carlo methods represent a powerful and broadly applicable computational tool for finding very accurate solutions of the stationary Schroedinger equation for atoms, molecules, solids and a variety of model systems. The algorithms are intrinsically parallel and are able to take full advantage of the present-day high-performance computing systems. This review article concentrates on the fixed-node/fixed-phase diffusion Monte Carlo method with emphasis on its applications to electronic structure of solids and other extended many-particle systems.

20. Monte Carlo simulation of electron slowing down in indium

Energy Technology Data Exchange (ETDEWEB)

Rouabah, Z.; Hannachi, M. [Materials and Electronic Systems Laboratory (LMSE), University of Bordj Bou Arreridj, Bordj Bou Arreridj (Algeria); Champion, C. [Université de Bordeaux 1, CNRS/IN2P3, Centre d’Etudes Nucléaires de Bordeaux-Gradignan, (CENBG), Gradignan (France); Bouarissa, N., E-mail: n_bouarissa@yahoo.fr [Laboratory of Materials Physics and its Applications, University of M' sila, 28000 M' sila (Algeria)

2015-07-15

Highlights: • Electron scattering in indium targets. • Modeling of elastic cross-sections. • Monte Carlo simulation of low energy electrons. - Abstract: In the current study, we aim at simulating via a detailed Monte Carlo code, the electron penetration in a semi-infinite indium medium for incident energies ranging from 0.5 to 5 keV. Electron range, backscattering coefficients, mean penetration depths as well as stopping profiles are then reported. The results may be seen as the first predictions for low-energy electron penetration in indium target.

1. Monte Carlo methods and models in finance and insurance

CERN Document Server

Korn, Ralf

2010-01-01

Offering a unique balance between applications and calculations, this book 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 book enables readers to find the right algorithm for a desired application and illustrates complicated methods and algorithms with simple applicat

2. Utilising Monte Carlo Simulation for the Valuation of Mining Concessions

Directory of Open Access Journals (Sweden)

Rosli Said

2005-12-01

Full Text Available Valuation involves the analyses of various input data to produce an estimated value. Since each input is itself often an estimate, there is an element of uncertainty in the input. This leads to uncertainty in the resultant output value. It is argued that a valuation must also convey information on the uncertainty, so as to be more meaningful and informative to the user. The Monte Carlo simulation technique can generate the information on uncertainty and is therefore potentially useful to valuation. This paper reports on the investigation that has been conducted to apply Monte Carlo simulation technique in mineral valuation, more specifically, in the valuation of a quarry concession.

3. PEPSI — a Monte Carlo generator for polarized leptoproduction

Science.gov (United States)

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.

4. THE APPLICATION OF MONTE CARLO SIMULATION FOR A DECISION PROBLEM

Directory of Open Access Journals (Sweden)

Çiğdem ALABAŞ

2001-01-01

Full Text Available The ultimate goal of the standard decision tree approach is to calculate the expected value of a selected performance measure. In the real-world situations, the decision problems become very complex as the uncertainty factors increase. In such cases, decision analysis using standard decision tree approach is not useful. One way of overcoming this difficulty is the Monte Carlo simulation. In this study, a Monte Carlo simulation model is developed for a complex problem and statistical analysis is performed to make the best decision.

5. Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations

Institute of Scientific and Technical Information of China (English)

仲昕; 杨汝清; 周兵

2003-01-01

Monte Carlo simulation was applied to Assembly Success Rate (ASR) analyses.ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes,manufacturing tolerances and robot repeatability into account.A statistic arithmetic expression was proposed and deduced in this paper,which offers an alternative method of estimating the accuracy of ASR,without having to repeat the simulations.This statistic method also helps to choose a suitable sample size,if error reduction is desired.Monte Carlo simulation results demonstrated the feasibility of the method.

6. Novel Quantum Monte Carlo Approaches for Quantum Liquids

Science.gov (United States)

Rubenstein, Brenda M.

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

7. Fission source sampling in coupled Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Olsen, Boerge; Dufek, Jan [KTH Royal Inst. of Technology, Stockholm (Sweden). Div. of Nuclear Research Technology

2017-05-15

We study fission source sampling methods suitable for the iterative way of solving coupled Monte Carlo neutronics problems. Specifically, we address the question as to how the initial Monte Carlo fission source should be optimally sampled at the beginning of each iteration step. We compare numerically two approaches of sampling the initial fission source; the tested techniques are derived from well-known methods for iterating the neutron flux in coupled simulations. The first technique samples the initial fission source using the source from the previous iteration step, while the other technique uses a combination of all previous steps for this purpose. We observe that the previous-step approach performs the best.

8. Monte Carlo simulation of electrons in dense gases

Science.gov (United States)

Tattersall, Wade; Boyle, Greg; Cocks, Daniel; Buckman, Stephen; White, Ron

2014-10-01

We implement a Monte-Carlo simulation modelling the transport of electrons and positrons in dense gases and liquids, by using a dynamic structure factor that allows us to construct structure-modified effective cross sections. These account for the coherent effects caused by interactions with the relatively dense medium. The dynamic structure factor also allows us to model thermal gases in the same manner, without needing to directly sample the velocities of the neutral particles. We present the results of a series of Monte Carlo simulations that verify and apply this new technique, and make comparisons with macroscopic predictions and Boltzmann equation solutions. Financial support of the Australian Research Council.

9. Cosmological Markov Chain Monte Carlo simulation with Cmbeasy

CERN Document Server

Müller, C M

2004-01-01

We introduce a Markov Chain Monte Carlo simulation and data analysis package for the cosmological computation package Cmbeasy. We have taken special care in implementing an adaptive step algorithm for the Markov Chain Monte Carlo in order to improve convergence. Data analysis routines are provided which allow to test models of the Universe against up-to-date measurements of the Cosmic Microwave Background, Supernovae Ia and Large Scale Structure. The observational data is provided with the software for convenient usage. The package is publicly available as part of the Cmbeasy software at www.cmbeasy.org.

10. A Monte Carlo implementation of the BDMPS-Z formalism

Energy Technology Data Exchange (ETDEWEB)

Wiedemann, Urs Achim [CERN PH-TH Department, CH-1211 Geneva (Switzerland); Zapp, Korinna Christine [Institute for Particle Physics Phenomenology, Durham University, Durham DH1 3LE (United Kingdom); Stachel, Johanna [Physikalisches Institut, Universitaet Heidelberg, Philosophenweg 12, D-69120 Heidelberg (Germany)

2011-04-01

We present preliminary results of a Monte Carlo algorithm that provides a faithful representation of the BDMPS-Z formalism for highly energetic partons interacting in dense QCD matter. In the incoherent limit, the evolution is governed by the probabilities for elastic and inelastic scattering of the highly energetic parton with target constituents in the dense QCD matter. A dynamically evolving formation time encodes coherence effects in such a way that a probabilistic implementation of the BDMPS-Z formalism is obtained. Since the scattering probabilities of the proposed algorithm depend on the total elastic and inelastic cross sections presented by target constituents, they will be sensitive to the IR and UV regulators of these cross sections. In this proceedings article, we highlight only one important feature of the algorithm, namely that the physical output is insensitive to these regulators. A complete description of the algorithm will be given in an upcoming publication.

11. Bayesian Inference in Monte-Carlo Tree Search

CERN Document Server

Tesauro, Gerald; Segal, Richard

2012-01-01

Monte-Carlo Tree Search (MCTS) methods are drawing great interest after yielding breakthrough results in computer Go. This paper proposes a Bayesian approach to MCTS that is inspired by distributionfree approaches such as UCT [13], yet significantly differs in important respects. The Bayesian framework allows potentially much more accurate (Bayes-optimal) estimation of node values and node uncertainties from a limited number of simulation trials. We further propose propagating inference in the tree via fast analytic Gaussian approximation methods: this can make the overhead of Bayesian inference manageable in domains such as Go, while preserving high accuracy of expected-value estimates. We find substantial empirical outperformance of UCT in an idealized bandit-tree test environment, where we can obtain valuable insights by comparing with known ground truth. Additionally we rigorously prove on-policy and off-policy convergence of the proposed methods.

12. Last-passage Monte Carlo algorithm for mutual capacitance.

Science.gov (United States)

Hwang, Chi-Ok; Given, James A

2006-08-01

We develop and test the last-passage diffusion algorithm, a charge-based Monte Carlo algorithm, for the mutual capacitance of a system of conductors. The first-passage algorithm is highly efficient because it is charge based and incorporates importance sampling; it averages over the properties of Brownian paths that initiate outside the conductor and terminate on its surface. However, this algorithm does not seem to generalize to mutual capacitance problems. The last-passage algorithm, in a sense, is the time reversal of the first-passage algorithm; it involves averages over particles that initiate on an absorbing surface, leave that surface, and diffuse away to infinity. To validate this algorithm, we calculate the mutual capacitance matrix of the circular-disk parallel-plate capacitor and compare with the known numerical results. Good agreement is obtained.

13. Monte Carlo Simulation of Diamond Deposition at Low Temperature

Institute of Scientific and Technical Information of China (English)

董丽芳; 张玉红

2001-01-01

Diamond deposition at low temperatures is investigated and the relationship between substrate temperature for diamond growth and the energy of the carbonaceous species is given. The electron energy distribution and velocity distribution during the electron assisted chemical vapour deposition have been obtained by using Monte Carlo simulation. The main results obtained are as follows. (1) The substrate temperature for diamond growth will be lower than 800 C when the carbonaceous species on the substrate have mobility energy. For example, if the energy of the carbonaceous species is 0. 75 eV, the substrate temperature will be 380℃-600℃. (2) The greatnumber of atomic H on the substrate is of importance to the growth of diamond films.

14. Monte Carlo Simulation of Magnetization Behaviour of Co Nanowires

Institute of Scientific and Technical Information of China (English)

ZHONG Ke-Hua; HUANG Zhi-Gao; FENG Qian; JIANG Li-Qin; YANG Yan-Min; CHEN Zhi-Gao

2006-01-01

Based on the Monte Carlo method, we simulate the magnetization curves with various magnetic field orientations for various single Co nanowires at room temperature. The simulated switching field as a function of angle θ between the field and the wire axis is consistent well with the experimental data. Correspondingly, the coercivity as a function of angle θ is presented, which together with the switching field plays an important role on explaining the magnetic reversal mechanism. It is found that the angular dependence of coercivity depends on the diameter of nanowires, and the coercivity and switching field versus θ deviate markedly from the prediction from the classical uniform rotation mode in the chain-of-sphere model. Furthermore, the magnetic reversal configurations display that magnetization reversal in the wires with small diameters is a nucleation-propagation process, and it is similar to the curling spread process in the larger wires.

15. Modelling a gamma irradiation process using the Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Soares, Gabriela A.; Pereira, Marcio T., E-mail: gas@cdtn.br, E-mail: mtp@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

2011-07-01

In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)

16. Monte Carlo simulations and benchmark studies at CERN's accelerator chain

CERN Document Server

AUTHOR|(CDS)2083190; Brugger, Markus

2016-01-01

Mixed particle and energy radiation fields present at the Large Hadron Collider (LHC) and its accelerator chain are responsible for failures on electronic devices located in the vicinity of the accelerator beam lines. These radiation effects on electronics and, more generally, the overall radiation damage issues have a direct impact on component and system lifetimes, as well as on maintenance requirements and radiation exposure to personnel who have to intervene and fix existing faults. The radiation environments and respective radiation damage issues along the CERN’s accelerator chain were studied in the framework of the CERN Radiation to Electronics (R2E) project and are hereby presented. The important interplay between Monte Carlo simulations and radiation monitoring is also highlighted.

17. Particle acceleration at shocks - A Monte Carlo method

Science.gov (United States)

Kirk, J. G.; Schneider, P.

1987-01-01

A Monte Carlo method is presented for the problem of acceleration of test particles at relativistic shocks. The particles are assumed to diffuse in pitch angle as a result of scattering off magnetic irregularities frozen into the fluid. Several tests are performed using the analytic results available for both relativistic and nonrelativistic shock speeds. The acceleration at relativistic shocks under the influence of radiation losses is investigated, including the effects of a momentum dependence in the diffusion coefficient. The results demonstrate the usefulness of the technique in those situations in which the diffusion approximation cannot be employed, such as when relativistic bulk motion is considered, when particles are permitted to escape at the boundaries, and when the effects of the finite length of the particle mean free path are important.

18. Monte Carlo simulation of electrical corona discharge in air

Energy Technology Data Exchange (ETDEWEB)

Settaouti, A.; Settaouti, L. [Electrotechnic Department, University of Sciences and Technology, P.O. Box 1505, El-M' naouar, Oran (Algeria)

2011-01-15

Electrical discharges play a key role in technologies; there are many industrial applications where the corona discharge is used. Air as insulator is probably the best compromise solution for many applications. All of this reflects on the great importance of the evaluation of the corona performance characteristics. Numerical simulation of the corona discharge helps to better understand the involved phenomena and optimize the corona devices. This paper is aimed at calculating the corona discharge in negative point-plane air gaps. To describe the non-equilibrium behavior of the electronic avalanches and to simulate the development of corona discharge the method of Monte Carlo has been used. This model provides the spatial-temporal local field and particles charged densities variations as well as the ionization front velocity. (author)

19. Quantum Monte Carlo calculations of two neutrons in finite volume

CERN Document Server

Klos, P; Tews, I; Gandolfi, S; Gezerlis, A; Hammer, H -W; Hoferichter, M; Schwenk, A

2016-01-01

Ab initio calculations provide direct access to the properties of pure neutron systems that are challenging to study experimentally. In addition to their importance for fundamental physics, their properties are required as input for effective field theories of the strong interaction. In this work, we perform auxiliary-field diffusion Monte Carlo calculations of the ground and first excited state of two neutrons in a finite box, considering a simple contact potential as well as chiral effective field theory interactions. We compare the results against exact diagonalizations and present a detailed analysis of the finite-volume effects, whose understanding is crucial for determining observables from the calculated energies. Using the L\\"uscher formula, we extract the low-energy S-wave scattering parameters from ground- and excited-state energies for different box sizes.

20. Accelerating particle-in-cell simulations using multilevel Monte Carlo

Science.gov (United States)

Ricketson, Lee

2015-11-01

Particle-in-cell (PIC) simulations have been an important tool in understanding plasmas since the dawn of the digital computer. Much more recently, the multilevel Monte Carlo (MLMC) method has accelerated particle-based simulations of a variety of systems described by stochastic differential equations (SDEs), from financial portfolios to porous media flow. The fundamental idea of MLMC is to perform correlated particle simulations using a hierarchy of different time steps, and to use these correlations for variance reduction on the fine-step result. This framework is directly applicable to the Langevin formulation of Coulomb collisions, as demonstrated in previous work, but in order to apply to PIC simulations of realistic scenarios, MLMC must be generalized to incorporate self-consistent evolution of the electromagnetic fields. We present such a generalization, with rigorous results concerning its accuracy and efficiency. We present examples of the method in the collisionless, electrostatic context, and discuss applications and extensions for the future.

1. Neutron monitor generated data distributions in quantum variational Monte Carlo

Science.gov (United States)

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.

2. Final Report: 06-LW-013, Nuclear Physics the Monte Carlo Way

Energy Technology Data Exchange (ETDEWEB)

Ormand, W E

2009-03-01

This is document reports the progress and accomplishments achieved in 2006-2007 with LDRD funding under the proposal 06-LW-013, 'Nuclear Physics the Monte Carlo Way'. The project was a theoretical study to explore a novel approach to dealing with a persistent problem in Monte Carlo approaches to quantum many-body systems. The goal was to implement a solution to the notorious 'sign-problem', which if successful, would permit, for the first time, exact solutions to quantum many-body systems that cannot be addressed with other methods. In this document, we outline the progress and accomplishments achieved during FY2006-2007 with LDRD funding in the proposal 06-LW-013, 'Nuclear Physics the Monte Carlo Way'. This project was funded under the Lab Wide LDRD competition at Lawrence Livermore National Laboratory. The primary objective of this project was to test the feasibility of implementing a novel approach to solving the generic quantum many-body problem, which is one of the most important problems being addressed in theoretical physics today. Instead of traditional methods based matrix diagonalization, this proposal focused a Monte Carlo method. The principal difficulty with Monte Carlo methods, is the so-called 'sign problem'. The sign problem, which will discussed in some detail later, is endemic to Monte Carlo approaches to the quantum many-body problem, and is the principal reason that they have not been completely successful in the past. Here, we outline our research in the 'shifted-contour method' applied the Auxiliary Field Monte Carlo (AFMC) method.

3. Pseudopotentials for quantum-Monte-Carlo-calculations; Pseudopotentiale fuer Quanten-Monte-Carlo-Rechnungen

Energy Technology Data Exchange (ETDEWEB)

Burkatzki, Mark Thomas

2008-07-01

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.)

4. Monte Carlo autofluorescence modeling of cervical intraepithelial neoplasm progression

Science.gov (United States)

Chu, S. C.; Chiang, H. K.; Wu, C. E.; He, S. Y.; Wang, D. Y.

2006-02-01

Monte Carlo fluorescence model has been developed to estimate the autofluorescent spectra associated with the progression of the Exo-Cervical Intraepithelial Neoplasm (CIN). We used double integrating spheres system and a tunable light source system, 380 to 600 nm, to measure the reflection and transmission spectra of a 50 μm thick tissue, and used Inverse Adding-Doubling (IAD) method to estimate the absorption (μa) and scattering (μs) coefficients. Human cervical tissue samples were sliced vertically (longitudinal) by the frozen section method. The results show that the absorption and scattering coefficients of cervical neoplasia are 2~3 times higher than normal tissues. We applied Monte Carlo method to estimate photon distribution and fluorescence emission in the tissue. By combining the intrinsic fluorescence information (collagen, NADH, and FAD), the anatomical information of the epithelium, CIN, stroma layers, and the fluorescence escape function, the autofluorescence spectra of CIN at different development stages were obtained.We have observed that the progression of the CIN results in gradually decreasing of the autofluorescence intensity of collagen peak intensity. In addition, the existence of the CIN layer formeda barrier that blocks the autofluorescence escaping from the stroma layer due to the strong extinction(scattering and absorption) of the CIN layer. To our knowledge, this is the first study measuring the CIN optical properties in the visible range; it also successfully demonstrates the fluorescence model forestimating autofluorescence spectra of cervical tissue associated with the progression of the CIN tissue;this model is very important in assisting the CIN diagnosis and treatment in clinical medicine.

5. Complete Monte Carlo Simulation of Neutron Scattering Experiments

Science.gov (United States)

Drosg, M.

2011-12-01

In the far past, it was not possible to accurately correct for the finite geometry and the finite sample size of a neutron scattering set-up. The limited calculation power of the ancient computers as well as the lack of powerful Monte Carlo codes and the limitation in the data base available then prevented a complete simulation of the actual experiment. Using e.g. the Monte Carlo neutron transport code MCNPX [1], neutron scattering experiments can be simulated almost completely with a high degree of precision using a modern PC, which has a computing power that is ten thousand times that of a super computer of the early 1970s. Thus, (better) corrections can also be obtained easily for previous published data provided that these experiments are sufficiently well documented. Better knowledge of reference data (e.g. atomic mass, relativistic correction, and monitor cross sections) further contributes to data improvement. Elastic neutron scattering experiments from liquid samples of the helium isotopes performed around 1970 at LANL happen to be very well documented. Considering that the cryogenic targets are expensive and complicated, it is certainly worthwhile to improve these data by correcting them using this comparatively straightforward method. As two thirds of all differential scattering cross section data of 3He(n,n)3He are connected to the LANL data, it became necessary to correct the dependent data measured in Karlsruhe, Germany, as well. A thorough simulation of both the LANL experiments and the Karlsruhe experiment is presented, starting from the neutron production, followed by the interaction in the air, the interaction with the cryostat structure, and finally the scattering medium itself. In addition, scattering from the hydrogen reference sample was simulated. For the LANL data, the multiple scattering corrections are smaller by a factor of five at least, making this work relevant. Even more important are the corrections to the Karlsruhe data due to the

6. Effective quantum Monte Carlo algorithm for modeling strongly correlated systems

NARCIS (Netherlands)

Kashurnikov, V. A.; Krasavin, A. V.

2007-01-01

A new effective Monte Carlo algorithm based on principles of continuous time is presented. It allows calculating, in an arbitrary discrete basis, thermodynamic quantities and linear response of mixed boson-fermion, spin-boson, and other strongly correlated systems which admit no analytic description

7. Time management for Monte-Carlo tree search in Go

NARCIS (Netherlands)

Baier, Hendrik; Winands, Mark H M

2012-01-01

The dominant approach for programs playing the game of Go is nowadays Monte-Carlo Tree Search (MCTS). While MCTS allows for fine-grained time control, little has been published on time management for MCTS programs under tournament conditions. This paper investigates the effects that various time-man

8. Variational Monte Carlo calculations of few-body nuclei

Energy Technology Data Exchange (ETDEWEB)

Wiringa, R.B.

1986-01-01

The variational Monte Carlo method is described. Results for the binding energies, density distributions, momentum distributions, and static longitudinal structure functions of the /sup 3/H, /sup 3/He, and /sup 4/He ground states, and for the energies of the low-lying scattering states in /sup 4/He are presented. 25 refs., 3 figs.

9. Determining MTF of digital detector system with Monte Carlo simulation

Science.gov (United States)

Jeong, Eun Seon; Lee, Hyung Won; Nam, Sang Hee

2005-04-01

We have designed a detector based on a-Se(amorphous Selenium) and done simulation the detector with Monte Carlo method. We will apply the cascaded linear system theory to determine the MTF for whole detector system. For direct comparison with experiment, we have simulated 139um pixel pitch and used simulated X-ray tube spectrum.

10. Data libraries as a collaborative tool across Monte Carlo codes

CERN Document Server

Augelli, Mauro; Han, Mincheol; Hauf, Steffen; Kim, Chan-Hyeung; Kuster, Markus; Pia, Maria Grazia; Quintieri, Lina; Saracco, Paolo; Seo, Hee; Sudhakar, Manju; Eidenspointner, Georg; Zoglauer, Andreas

2010-01-01

The role of data libraries in Monte Carlo simulation is discussed. A number of data libraries currently in preparation are reviewed; their data are critically examined with respect to the state-of-the-art in the respective fields. Extensive tests with respect to experimental data have been performed for the validation of their content.

11. A separable shadow Hamiltonian hybrid Monte Carlo method.

Science.gov (United States)

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

2009-11-07

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

12. Quantum Monte Carlo diagonalization method as a variational calculation

Energy Technology Data Exchange (ETDEWEB)

Mizusaki, Takahiro; Otsuka, Takaharu [Tokyo Univ. (Japan). Dept. of Physics; Honma, Michio

1997-05-01

A stochastic method for performing large-scale shell model calculations is presented, which utilizes the auxiliary field Monte Carlo technique and diagonalization method. This method overcomes the limitation of the conventional shell model diagonalization and can extremely widen the feasibility of shell model calculations with realistic interactions for spectroscopic study of nuclear structure. (author)

13. Monte Carlo simulation of quantum statistical lattice models

NARCIS (Netherlands)

Raedt, Hans De; Lagendijk, Ad

1985-01-01

In this article we review recent developments in computational methods for quantum statistical lattice problems. We begin by giving the necessary mathematical basis, the generalized Trotter formula, and discuss the computational tools, exact summations and Monte Carlo simulation, that will be used t

14. Distributed and Adaptive Darting Monte Carlo through Regenerations

NARCIS (Netherlands)

Ahn, S.; Chen, Y.; Welling, M.

2013-01-01

Darting Monte Carlo (DMC) is a MCMC procedure designed to effectively mix between multiple modes of a probability distribution. We propose an adaptive and distributed version of this method by using regenerations. This allows us to run multiple chains in parallel and adapt the shape of the jump regi

15. A novel Monte Carlo approach to hybrid local volatility models

NARCIS (Netherlands)

A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

2017-01-01

textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

16. SPANDY: a Monte Carlo program for gas target scattering geometry

Energy Technology Data Exchange (ETDEWEB)

Jarmie, N.; Jett, J.H.; Niethammer, A.C.

1977-02-01

A Monte Carlo computer program is presented that simulates a two-slit gas target scattering geometry. The program is useful in estimating effects due to finite geometry and multiple scattering in the target foil. Details of the program are presented and experience with a specific example is discussed.

17. Monte Carlo Simulation of Partially Confined Flexible Polymers

NARCIS (Netherlands)

Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias

2002-01-01

We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the por

18. Tackling the premature convergence problem in Monte-Carlo localization

NARCIS (Netherlands)

Kootstra, G.; de Boer, B.

2009-01-01

Monte-Carlo localization uses particle filtering to estimate the position of the robot. The method is known to suffer from the loss of potential positions when there is ambiguity present in the environment. Since many indoor environments are highly symmetric, this problem of premature convergence is

19. Nonequilibrium Candidate Monte Carlo Simulations with Configurational Freezing Schemes.

Science.gov (United States)

Giovannelli, Edoardo; Gellini, Cristina; Pietraperzia, Giangaetano; Cardini, Gianni; Chelli, Riccardo

2014-10-14

Nonequilibrium Candidate Monte Carlo simulation [Nilmeier et al., Proc. Natl. Acad. Sci. U.S.A. 2011, 108, E1009-E1018] is a tool devised to design Monte Carlo moves with high acceptance probabilities that connect uncorrelated configurations. Such moves are generated through nonequilibrium driven dynamics, producing candidate configurations accepted with a Monte Carlo-like criterion that preserves the equilibrium distribution. The probability of accepting a candidate configuration as the next sample in the Markov chain basically depends on the work performed on the system during the nonequilibrium trajectory and increases with decreasing such a work. It is thus strategically relevant to find ways of producing nonequilibrium moves with low work, namely moves where dissipation is as low as possible. This is the goal of our methodology, in which we combine Nonequilibrium Candidate Monte Carlo with Configurational Freezing schemes developed by Nicolini et al. (J. Chem. Theory Comput. 2011, 7, 582-593). The idea is to limit the configurational sampling to particles of a well-established region of the simulation sample, namely the region where dissipation occurs, while leaving fixed the other particles. This allows to make the system relaxation faster around the region perturbed by the finite-time switching move and hence to reduce the dissipated work, eventually enhancing the probability of accepting the generated move. Our combined approach enhances significantly configurational sampling, as shown by the case of a bistable dimer immersed in a dense fluid.

20. Multi-microcomputer system for Monte-Carlo calculations

CERN Document Server

Berg, B; Krasemann, H

1981-01-01

The authors propose a microcomputer system that allows parallel processing for Monte Carlo calculations in lattice gauge theories, simulations of high energy physics experiments and many other fields of current interest. The master-n-slave multiprocessor system is based on the Motorola MC 6800 microprocessor. One attraction of this processor is that it allows up to 16 M Byte random access memory.

1. Criticality benchmarks validation of the Monte Carlo code TRIPOLI-2

Energy Technology Data Exchange (ETDEWEB)

Maubert, L. (Commissariat a l' Energie Atomique, Inst. de Protection et de Surete Nucleaire, Service d' Etudes de Criticite, 92 - Fontenay-aux-Roses (France)); Nouri, A. (Commissariat a l' Energie Atomique, Inst. de Protection et de Surete Nucleaire, Service d' Etudes de Criticite, 92 - Fontenay-aux-Roses (France)); Vergnaud, T. (Commissariat a l' Energie Atomique, Direction des Reacteurs Nucleaires, Service d' Etudes des Reacteurs et de Mathematique Appliquees, 91 - Gif-sur-Yvette (France))

1993-04-01

The three-dimensional energy pointwise Monte-Carlo code TRIPOLI-2 includes metallic spheres of uranium and plutonium, nitrate plutonium solutions, square and triangular pitch assemblies of uranium oxide. Results show good agreements between experiments and calculations, and avoid a part of the code and its ENDF-B4 library validation. (orig./DG)

2. Strain in the mesoscale kinetic Monte Carlo model for sintering

DEFF Research Database (Denmark)

Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.

2014-01-01

Shrinkage strains measured from microstructural simulations using the mesoscale kinetic Monte Carlo (kMC) model for solid state sintering are discussed. This model represents the microstructure using digitized discrete sites that are either grain or pore sites. The algorithm used to simulate...

3. Monte Carlo estimation of the conditional Rasch model

NARCIS (Netherlands)

Akkermans, Wies M.W.

1994-01-01

In order to obtain conditional maximum likelihood estimates, the so-called conditioning estimates have to be calculated. In this paper a method is examined that does not calculate these constants exactly, but approximates them using Monte Carlo Markov Chains. As an example, the method is applied to

4. Monte Carlo estimation of the conditional Rasch model

NARCIS (Netherlands)

Akkermans, W.

1998-01-01

In order to obtain conditional maximum likelihood estimates, the conditioning constants are needed. Geyer and Thompson (1992) proposed a Markov chain Monte Carlo method that can be used to approximate these constants when they are difficult to calculate exactly. In the present paper, their method is

5. Nanoporous gold formation by dealloying : A Metropolis Monte Carlo study

NARCIS (Netherlands)

Zinchenko, O.; De Raedt, H. A.; Detsi, E.; Onck, P. R.; De Hosson, J. T. M.

2013-01-01

A Metropolis Monte Carlo study of the dealloying mechanism leading to the formation of nanoporous gold is presented. A simple lattice-gas model for gold, silver and acid particles, vacancies and products of chemical reactions is adopted. The influence of temperature, concentration and lattice defect

6. Quantum Monte Carlo simulation of topological phase transitions

Science.gov (United States)

Yamamoto, Arata; Kimura, Taro

2016-12-01

We study the electron-electron interaction effects on topological phase transitions by the ab initio quantum Monte Carlo simulation. We analyze two-dimensional class A topological insulators and three-dimensional Weyl semimetals with the long-range Coulomb interaction. The direct computation of the Chern number shows the electron-electron interaction modifies or extinguishes topological phase transitions.

7. Calculating coherent pair production with Monte Carlo methods

Energy Technology Data Exchange (ETDEWEB)

Bottcher, C.; Strayer, M.R.

1989-01-01

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

8. A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods

NARCIS (Netherlands)

Bijmolt, T.H.A.; Wedel, M.

1996-01-01

We compare three alternative Maximum Likelihood Multidimensional Scaling methods for pairwise dissimilarity ratings, namely MULTISCALE, MAXSCAL, and PROSCAL in a Monte Carlo study.The three MLMDS methods recover the true con gurations very well.The recovery of the true dimensionality depends on the

9. Direct determination of liquid phase coexistence by Monte Carlo simulations

NARCIS (Netherlands)

Zweistra, H.J.A.; Besseling, N.A.M.

2006-01-01

A formalism to determine coexistence points by means of Monte Carlo simulations is presented. The general idea of the method is to perform a simulation simultaneously in several unconnected boxes which can exchange particles. At equilibrium, most of the boxes will be occupied by a homogeneous phase.

10. Monte Carlo methods for multidimensional integration for European option pricing

Science.gov (United States)

Todorov, V.; Dimov, I. T.

2016-10-01

In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.

11. Monte Carlo Simulation Optimizing Design of Grid Ionization Chamber

Institute of Scientific and Technical Information of China (English)

ZHENG; Yu-lai; WANG; Qiang; YANG; Lu

2013-01-01

The grid ionization chamber detector is often used for measuring charged particles.Based on Monte Carlo simulation method,the energy loss distribution and electron ion pairs of alpha particle with different energy have been calculated to determine suitable filling gas in the ionization chamber filled with

12. Optimization of sequential decisions by least squares Monte Carlo method

DEFF Research Database (Denmark)

Nishijima, Kazuyoshi; Anders, Annett

change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...

13. Testing Dependent Correlations with Nonoverlapping Variables: A Monte Carlo Simulation

Science.gov (United States)

Silver, N. Clayton; Hittner, James B.; May, Kim

2004-01-01

The authors conducted a Monte Carlo simulation of 4 test statistics or comparing dependent correlations with no variables in common. Empirical Type 1 error rates and power estimates were determined for K. Pearson and L. N. G. Filon's (1898) z, O. J. Dunn and V. A. Clark's (1969) z, J. H. Steiger's (1980) original modification of Dunn and Clark's…

14. Bayesian Monte Carlo Method for Nuclear Data Evaluation

Energy Technology Data Exchange (ETDEWEB)

Koning, A.J., E-mail: koning@nrg.eu

2015-01-15

A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using TALYS. The result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by an experiment based weight.

15. Auxiliary-field quantum Monte Carlo methods in nuclei

CERN Document Server

Alhassid, Y

2016-01-01

Auxiliary-field quantum Monte Carlo methods enable the calculation of thermal and ground state properties of correlated quantum many-body systems in model spaces that are many orders of magnitude larger than those that can be treated by conventional diagonalization methods. We review recent developments and applications of these methods in nuclei using the framework of the configuration-interaction shell model.

16. Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm

Science.gov (United States)

Gubernatis, James

2014-03-01

A common computational task is solving a set of ordinary differential equations (o.d.e.'s). A little known theorem says that the solution of any set of o.d.e.'s is exactly solved by the expectation value over a set of arbitary Poisson processes of a particular function of the elements of the matrix that defines the o.d.e.'s. The theorem thus provides a new starting point to develop real and imaginary-time continous-time solvers for quantum Monte Carlo algorithms, and several simple observations enable various quantum Monte Carlo techniques and variance reduction methods to transfer to a new context. I will state the theorem, note a transformation to a very simple computational scheme, and illustrate the use of some techniques from the directed-loop algorithm in context of the wavefunction Monte Carlo method that is used to solve the Lindblad master equation for the dynamics of open quantum systems. I will end by noting that as the theorem does not depend on the source of the o.d.e.'s coming from quantum mechanics, it also enables the transfer of continuous-time methods from quantum Monte Carlo to the simulation of various classical equations of motion heretofore only solved deterministically.

17. Monte Carlo method for magnetic impurities in metals

Science.gov (United States)

Hirsch, J. E.; Fye, R. M.

1986-01-01

The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.

18. Improved Monte Carlo model for multiple scattering calculations

Institute of Scientific and Technical Information of China (English)

Weiwei Cai; Lin Ma

2012-01-01

The coupling between the Monte Carlo (MC) method and geometrical optics to improve accuracy is investigated.The results obtained show improved agreement with previous experimental data,demonstrating that the MC method,when coupled with simple geometrical optics,can simulate multiple scattering with enhanced fidelity.

19. Simulating Strongly Correlated Electron Systems with Hybrid Monte Carlo

Institute of Scientific and Technical Information of China (English)

LIU Chuan

2000-01-01

Using the path integral representation, the Hubbard and the periodic Anderson model on D-dimensional cubic lattice are transformed into field theories of fermions in D + 1 dimensions. These theories at half-filling possess a positive definite real symmetry fermion matrix and can be simulated using the hybrid Monte Carlo method.

20. Monte-carlo calculations for some problems of quantum mechanics

Energy Technology Data Exchange (ETDEWEB)

Novoselov, A. A., E-mail: novoselov@goa.bog.msu.ru; Pavlovsky, O. V.; Ulybyshev, M. V. [Moscow State University (Russian Federation)

2012-09-15

The Monte-Carlo technique for the calculations of functional integral in two one-dimensional quantum-mechanical problems had been applied. The energies of the bound states in some potential wells were obtained using this method. Also some peculiarities in the calculation of the kinetic energy in the ground state had been studied.

1. Quantum Monte Carlo simulation of topological phase transitions

CERN Document Server

Yamamoto, Arata

2016-01-01

We study the electron-electron interaction effects on topological phase transitions by the ab-initio quantum Monte Carlo simulation. We analyze two-dimensional class A topological insulators and three-dimensional Weyl semimetals with the long-range Coulomb interaction. The direct computation of the Chern number shows the electron-electron interaction modifies or extinguishes topological phase transitions.

2. Exploring Mass Perception with Markov Chain Monte Carlo

Science.gov (United States)

Cohen, Andrew L.; Ross, Michael G.

2009-01-01

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

3. CMS Monte Carlo production operations in a distributed computing environment

CERN Document Server

Mohapatra, A; Khomich, A; Lazaridis, C; Hernández, J M; Caballero, J; Hof, C; Kalinin, S; Flossdorf, A; Abbrescia, M; De Filippis, N; Donvito, G; Maggi, G; My, S; Pompili, A; Sarkar, S; Maes, J; Van Mulders, P; Villella, I; De Weirdt, S; Hammad, G; Wakefield, S; Guan, W; Lajas, J A S; Elmer, P; Evans, D; Fanfani, A; Bacchi, W; Codispoti, G; Van Lingen, F; Kavka, C; Eulisse, G

2008-01-01

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

4. A Variational Monte Carlo Approach to Atomic Structure

Science.gov (United States)

Davis, Stephen L.

2007-01-01

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

5. Monte Carlo Simulation on Glueball Search at BESⅢ

Institute of Scientific and Technical Information of China (English)

QIN Hu; SHEN Xiao-Yan

2007-01-01

The J/ψ radiative decays are suggested as promising modes for glueball search. A full Monte Carlo simulation of J/ψ→γηη and γηη', based on the design of BESⅢ detector, is performed to study the sensitivity of searching for a possible tensor glueball at BESⅢ.

6. The Metropolis Monte Carlo Method in Statistical Physics

Science.gov (United States)

Landau, David P.

2003-11-01

A brief overview is given of some of the advances in statistical physics that have been made using the Metropolis Monte Carlo method. By complementing theory and experiment, these have increased our understanding of phase transitions and other phenomena in condensed matter systems. A brief description of a new method, commonly known as "Wang-Landau sampling," will also be presented.

7. Exploring Mass Perception with Markov Chain Monte Carlo

Science.gov (United States)

Cohen, Andrew L.; Ross, Michael G.

2009-01-01

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

8. An Overview of the Monte Carlo Methods, Codes, & Applications Group

Energy Technology Data Exchange (ETDEWEB)

Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-08-30

This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.

9. Monte Carlo Simulation of Partially Confined Flexible Polymers

NARCIS (Netherlands)

Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias

2002-01-01

We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the

10. Monte Carlo: in the beginning and some great expectations

Energy Technology Data Exchange (ETDEWEB)

Metropolis, N.

1985-01-01

The central theme will be on the historical setting and origins of the Monte Carlo Method. The scene was post-war Los Alamos Scientific Laboratory. There was an inevitability about the Monte Carlo Event: the ENIAC had recently enjoyed its meteoric rise (on a classified Los Alamos problem); Stan Ulam had returned to Los Alamos; John von Neumann was a frequent visitor. Techniques, algorithms, and applications developed rapidly at Los Alamos. Soon, the fascination of the Method reached wider horizons. The first paper was submitted for publication in the spring of 1949. In the summer of 1949, the first open conference was held at the University of California at Los Angeles. Of some interst perhaps is an account of Fermi's earlier, independent application in neutron moderation studies while at the University of Rome. The quantum leap expected with the advent of massively parallel processors will provide stimuli for very ambitious applications of the Monte Carlo Method in disciplines ranging from field theories to cosmology, including more realistic models in the neurosciences. A structure of multi-instruction sets for parallel processing is ideally suited for the Monte Carlo approach. One may even hope for a modest hardening of the soft sciences.

11. Monte Carlo analysis of radiative transport in oceanographic lidar measurements

Energy Technology Data Exchange (ETDEWEB)

Cupini, E.; Ferro, G. [ENEA, Divisione Fisica Applicata, Centro Ricerche Ezio Clementel, Bologna (Italy); Ferrari, N. [Bologna Univ., Bologna (Italy). Dipt. Ingegneria Energetica, Nucleare e del Controllo Ambientale

2001-07-01

The analysis of oceanographic lidar systems measurements is often carried out with semi-empirical methods, since there is only a rough understanding of the effects of many environmental variables. The development of techniques for interpreting the accuracy of lidar measurements is needed to evaluate the effects of various environmental situations, as well as of different experimental geometric configurations and boundary conditions. A Monte Carlo simulation model represents a tool that is particularly well suited for answering these important questions. The PREMAR-2F Monte Carlo code has been developed taking into account the main molecular and non-molecular components of the marine environment. The laser radiation interaction processes of diffusion, re-emission, refraction and absorption are treated. In particular are considered: the Rayleigh elastic scattering, produced by atoms and molecules with small dimensions with respect to the laser emission wavelength (i.e. water molecules), the Mie elastic scattering, arising from atoms or molecules with dimensions comparable to the laser wavelength (hydrosols), the Raman inelastic scattering, typical of water, the absorption of water, inorganic (sediments) and organic (phytoplankton and CDOM) hydrosols, the fluorescence re-emission of chlorophyll and yellow substances. PREMAR-2F is an extension of a code for the simulation of the radiative transport in atmospheric environments (PREMAR-2). The approach followed in PREMAR-2 was to combine conventional Monte Carlo techniques with analytical estimates of the probability of the receiver to have a contribution from photons coming back after an interaction in the field of view of the lidar fluorosensor collecting apparatus. This offers an effective mean for modelling a lidar system with realistic geometric constraints. The retrieved semianalytic Monte Carlo radiative transfer model has been developed in the frame of the Italian Research Program for Antarctica (PNRA) and it is

12. Development of ray tracing visualization program by Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro

1997-09-01

Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)

13. Development of ray tracing visualization program by Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro

1997-09-01

Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)

14. The Specific Bias in Dynamic Monte Carlo Simulations of Nuclear Reactor

Science.gov (United States)

Yamamoto, Toshihisa; Endo, Hiroshi; Ishizu, Tomoko; Tatewaki, Isao

2014-06-01

During the development of Monte-Carlo-based dynamic code system, we have encountered two major Monte-Carlo-specific problems. One is the break down due to "false super-criticality" which is caused by an accidentally large eigenvalue due to statistical error in spite of the fact that the reactor is actually not. The other problem, which is the main topic in this paper, is that the statistical error in power level using the reactivity calculated with Monte Carlo code is not symmetric about its mean but always positively biased. This signifies that the bias is accumulated as the calculation proceeds and consequently results in over-estimation of the final power level. It should be noted that the bias will not eliminated by refining time step as long as the variance is not zero. A preliminary investigation on this matter using the one-group-precursor point kinetic equations was made and it was concluded that the bias in power level is approximately proportional to the product of variance in Monte Carlo calculation and elapsed time. This conclusion was verified with some numerical experiments. This outcome is important in quantifying the required precision of the Monte-Carlo-based reactivity calculations.

15. Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement.

Science.gov (United States)

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.

16. Clinical implementation of the Peregrine Monte Carlo dose calculations system for photon beam therapy

Energy Technology Data Exchange (ETDEWEB)

Albright, N; Bergstrom, P M; Daly, T P; Descalle, M; Garrett, D; House, R K; Knapp, D K; May, S; Patterson, R W; Siantar, C L; Verhey, L; Walling, R S; Welczorek, D

1999-07-01

PEREGRINE is a 3D Monte Carlo dose calculation system designed to serve as a dose calculation engine for clinical radiation therapy treatment planning systems. Taking advantage of recent advances in low-cost computer hardware, modern multiprocessor architectures and optimized Monte Carlo transport algorithms, PEREGRINE performs mm-resolution Monte Carlo calculations in times that are reasonable for clinical use. PEREGRINE has been developed to simulate radiation therapy for several source types, including photons, electrons, neutrons and protons, for both teletherapy and brachytherapy. However the work described in this paper is limited to linear accelerator-based megavoltage photon therapy. Here we assess the accuracy, reliability, and added value of 3D Monte Carlo transport for photon therapy treatment planning. Comparisons with clinical measurements in homogeneous and heterogeneous phantoms demonstrate PEREGRINE's accuracy. Studies with variable tissue composition demonstrate the importance of material assignment on the overall dose distribution. Detailed analysis of Monte Carlo results provides new information for radiation research by expanding the set of observables.

17. Direct aperture optimization for IMRT using Monte Carlo generated beamlets.

Science.gov (United States)

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

2006-10-01

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

18. Global Monte Carlo Simulation with High Order Polynomial Expansions

Energy Technology Data Exchange (ETDEWEB)

William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin

2007-12-13

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

19. Multiple-time-stepping generalized hybrid Monte Carlo methods

Energy Technology Data Exchange (ETDEWEB)

Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)

2015-01-01

Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.

20. Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls)

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...

1. Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls).xml

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...

2. Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls).

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...

3. Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls)

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — Monte Carlo programs described in chapter MC, Monte Carlo Simulation Method. Emc2.xls was the program used to calculate the estimates of undiscovered resources for...

4. TRIPOLI: a general Monte Carlo code, present state and future prospects. [Neutron and gamma ray transport

Energy Technology Data Exchange (ETDEWEB)

Nimal, J.C.; Vergnaud, T. (CEA Centre d' Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette (France))

1990-01-01

This paper describes the most important features of the Monte Carlo code TRIPOLI-2. This code solves the Boltzmann equation in three-dimensional geometries for coupled neutron and gamma rays problems. A particular emphasis is devoted to the biasing techniques, which are very important for deep penetration. Future developments in TRIPOLI are described in the conclusion. (author).

5. A simple new way to help speed up Monte Carlo convergence rates: Energy-scaled displacement Monte Carlo

Science.gov (United States)

Goldman, Saul

1983-10-01

A method we call energy-scaled displacement Monte Carlo (ESDMC) whose purpose is to improve sampling efficiency and thereby speed up convergence rates in Monte Carlo calculations is presented. The method involves scaling the maximum displacement a particle may make on a trial move to the particle's configurational energy. The scaling is such that on the average, the most stable particles make the smallest moves and the most energetic particles the largest moves. The method is compared to Metropolis Monte Carlo (MMC) and Force Bias Monte Carlo of (FBMC) by applying all three methods to a dense Lennard-Jones fluid at two temperatures, and to hot ST2 water. The functions monitored as the Markov chains developed were, for the Lennard-Jones case: melting, radial distribution functions, internal energies, and heat capacities. For hot ST2 water, we monitored energies and heat capacities. The results suggest that ESDMC samples configuration space more efficiently than either MMC or FBMC in these systems for the biasing parameters used here. The benefit from using ESDMC seemed greatest for the Lennard-Jones systems.

6. TRIPOLI-4: Monte Carlo transport code functionalities and applications; TRIPOLI-4: code de transport Monte Carlo fonctionnalites et applications

Energy Technology Data Exchange (ETDEWEB)

Both, J.P.; Lee, Y.K.; Mazzolo, A.; Peneliau, Y.; Petit, O.; Roesslinger, B. [CEA Saclay, Dir. de l' Energie Nucleaire (DEN), Service d' Etudes de Reacteurs et de Modelisation Avancee, 91 - Gif sur Yvette (France)

2003-07-01

Tripoli-4 is a three dimensional calculations code using the Monte Carlo method to simulate the transport of neutrons, photons, electrons and positrons. This code is used in four application fields: the protection studies, the criticality studies, the core studies and the instrumentation studies. Geometry, cross sections, description of sources, principle. (N.C.)

7. Monte Carlo Radiation Hydrodynamics: Methods, Tests and Application to Supernova Type Ia Ejecta

CERN Document Server

Noebauer, U M; Kromer, M; Röpke, F K; Hillebrandt, W

2012-01-01

In astrophysical systems, radiation-matter interactions are important in transferring energy and momentum between the radiation field and the surrounding material. This coupling often makes it necessary to consider the role of radiation when modelling the dynamics of astrophysical fluids. During the last few years, there have been rapid developments in the use of Monte Carlo methods for numerical radiative transfer simulations. Here, we present an approach to radiation hydrodynamics that is based on coupling Monte Carlo radiative transfer techniques with finite-volume hydrodynamical methods in an operator-split manner. In particular, we adopt an indivisible packet formalism to discretize the radiation field into an ensemble of Monte Carlo packets and employ volume-based estimators to reconstruct the radiation field characteristics. In this paper the numerical tools of this method are presented and their accuracy is verified in a series of test calculations. Finally, as a practical example, we use our approach...

8. Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks

Directory of Open Access Journals (Sweden)

Gareth W. Peters

2017-09-01

Full Text Available The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under the new solvency regulations. In particular, a novel Monte Carlo method to calculate capital allocations for a general insurance company is developed, with a focus on coherent capital allocation that is compliant with the Swiss Solvency Test. The data used is based on the balance sheet of a representative stylized company. For each line of business in that company, allocations are calculated for the one-year risk with dependencies based on correlations given by the Swiss Solvency Test. Two different approaches for dealing with parameter uncertainty are discussed and simulation algorithms based on (pseudo-marginal Sequential Monte Carlo algorithms are described and their efficiency is analysed.

9. Quantum Monte Carlo with reoptimized perturbatively selected configuration-interaction wave functions

CERN Document Server

Giner, Emmanuel; Toulouse, Julien

2016-01-01

We explore the use in quantum Monte Carlo (QMC) of trial wave functions consisting of a Jastrow factor multiplied by a truncated configuration-interaction (CI) expansion in Slater determinants obtained from a CI perturbatively selected iteratively (CIPSI) calculation. In the CIPSI algorithm, the CI expansion is iteratively enlarged by selecting the best determinants using perturbation theory, which provides an optimal and automatic way of constructing truncated CI expansions approaching the full CI limit. We perform a systematic study of variational Monte Carlo (VMC) and fixed-node diffusion Monte Carlo (DMC) total energies of first-row atoms from B to Ne with different levels of optimization of the parameters (Jastrow parameters, coefficients of the determinants, and orbital parameters) in these trial wave functions. The results show that the reoptimization of the coefficients of the determinants in VMC (together with the Jastrow factor) leads to an important lowering of both VMC and DMC total energies, and ...

10. Markov chain Monte Carlo and importance sampling for multiple targets tracking%马尔可夫链蒙特卡洛重要度采样与多目标跟踪

Institute of Scientific and Technical Information of China (English)

龙云利; 徐晖; 安玮

2011-01-01

针对强杂波环境下的多目标跟踪问题，提出一种基于马尔可夫链蒙特卡洛重要度采样的跟踪方法．通过马尔可夫链蒙特卡洛实现对联合关联事件的采样，据此计算目标可关联量测数据的边缘关联概率．在联合关联事件求解中利用单目标量测的概率密度进行重要度采样，提高采样效率．马尔可夫链蒙特卡洛重要度采样方法克服了联合概率数据关联中的“组合爆炸”问题，能够在强杂波干扰下较好地实现多目标实时跟踪．通过仿真实验对比分析了算法的跟踪精度和处理的时效性，验证了方法的有效性．%This paper presents an algorithm based on Markov chain Monte Carlo and importance sampling（MCMCIS） for tracking multi-target in a dense environment. The joint associated events are sampled by the Markov chain Monte Carlo and the marginal association probability of the measurement to the target is calculated. The probabilistic density is utilized when sampling the associated events as to improve the efficiency. Although the joint probabilistic data association（JPDA） is NP-hard, the MCMCIS provides the ability to track multi-target timely in a dense environment. The simulation experiments are implemented to analyze the tracking precision and processing time, which shows the effectiveness of the algorithm.

11. Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications

CERN Document Server

Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne

2014-01-01

The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.

12. The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature

CERN Document Server

Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V

2010-01-01

A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.

13. Fast orthogonal transforms for multi-level quasi-Monte Carlo integration

OpenAIRE

Irrgeher, Christian; Leobacher, Gunther

2015-01-01

We combine a generic method for finding fast orthogonal transforms for a given quasi-Monte Carlo integration problem with the multilevel Monte Carlo method. It is shown by example that this combined method can vastly improve the efficiency of quasi-Monte Carlo.

14. Markov chain Monte Carlo methods for state-space models with point process observations.

Science.gov (United States)

Yuan, Ke; Girolami, Mark; Niranjan, Mahesan

2012-06-01

This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations. We quantified the efficiencies of these MCMC methods on synthetic data, and our results suggest that the Reimannian manifold Hamiltonian Monte Carlo method offers the best performance. We further compared such a method with a previously tested variational Bayes method on two experimental data sets. Results indicate similar performance on the large data sets and superior performance on small ones. The work offers an extensive suite of MCMC algorithms evaluated on an important class of models for physiological signal analysis.

15. B-splines smoothed rejection sampling method and its applications in quasi-Monte Carlo integration

Institute of Scientific and Technical Information of China (English)

雷桂媛

2002-01-01

The rejection sampling method is one of the most popular methods used in Monte Carlo methods. It turns out that the standard rejection method is closely related to the problem of quasi-Monte Carlo integration of characteristic functions, whose accuracy may be lost due to the discontinuity of the characteristic functions. We proposed a B-splines smoothed rejection sampling method, which smoothed the characteristic function by B-splines smoothing technique without changing the integral quantity. Numerical experiments showed that the convergence rate of nearly O(N-1) is regained by using the B-splines smoothed rejection method in importance sampling.

16. B-splines smoothed rejection sampling method and its applications in quasi-Monte Carlo integration

Institute of Scientific and Technical Information of China (English)

雷桂媛

2002-01-01

The rejection sampling method is one of the most popular methods used in Monte Carlo methods. It turns out that the standard rejection method is closely related to the problem of quasi-Monte Carlo integration of characteristic functions, whose accuracy may be lost due to the discontinuity of the characteristic functions. We proposed a B-splines smoothed rejection sampling method, which smoothed the characteristic function by B-splines smoothing technique without changing the integral quantity. Numerical experiments showed that the convergence rate of nearly O( N-1 ) is regained by using the B-splines smoothed rejection method in importance sampling.

17. Artificial neural networks, a new alternative to Monte Carlo calculations for radiotherapy; Les Reseaux de Neurones Artificiels, une nouvelle alternative aux calculs Monte-Carlo pour la radiotherapie

Energy Technology Data Exchange (ETDEWEB)

Martin, E.; Gschwind, R.; Henriet, J.; Sauget, M.; Makovicka, L. [IRMA/Enisys/FEMTO-ST, Pole universitaire des Portes du Jura, place Tharradin, BP 71427, 2521 1 - Montbeliard cedex (France)

2010-07-01

In order to reduce the computing time needed by Monte Carlo codes in the field of irradiation physics, notably in dosimetry, the authors report the use of artificial neural networks in combination with preliminary Monte Carlo calculations. During the learning phase, Monte Carlo calculations are performed in homogeneous media to allow the building up of the neural network. Then, dosimetric calculations (in heterogeneous media, unknown by the network) can be performed by the so-learned network. Results with an equivalent precision can be obtained within less than one minute on a simple PC whereas several days are needed with a Monte Carlo calculation

18. Advanced Mesh-Enabled Monte carlo capability for Multi-Physics Reactor Analysis

Energy Technology Data Exchange (ETDEWEB)

Wilson, Paul; Evans, Thomas; Tautges, Tim

2012-12-24

This project will accumulate high-precision fluxes throughout reactor geometry on a non- orthogonal grid of cells to support multi-physics coupling, in order to more accurately calculate parameters such as reactivity coefficients and to generate multi-group cross sections. This work will be based upon recent developments to incorporate advanced geometry and mesh capability in a modular Monte Carlo toolkit with computational science technology that is in use in related reactor simulation software development. Coupling this capability with production-scale Monte Carlo radiation transport codes can provide advanced and extensible test-beds for these developments. Continuous energy Monte Carlo methods are generally considered to be the most accurate computational tool for simulating radiation transport in complex geometries, particularly neutron transport in reactors. Nevertheless, there are several limitations for their use in reactor analysis. Most significantly, there is a trade-off between the fidelity of results in phase space, statistical accuracy, and the amount of computer time required for simulation. Consequently, to achieve an acceptable level of statistical convergence in high-fidelity results required for modern coupled multi-physics analysis, the required computer time makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. More subtly, the statistical uncertainty is typically not uniform throughout the domain, and the simulation quality is limited by the regions with the largest statistical uncertainty. In addition, the formulation of neutron scattering laws in continuous energy Monte Carlo methods makes it difficult to calculate adjoint neutron fluxes required to properly determine important reactivity parameters. Finally, most Monte Carlo codes available for reactor analysis have relied on orthogonal hexahedral grids for tallies that do not conform to the geometric boundaries and are thus generally not well

19. Teaching Markov Chain Monte Carlo: Revealing the Basic Ideas behind the Algorithm

Science.gov (United States)

Stewart, Wayne; Stewart, Sepideh

2014-01-01

For many scientists, researchers and students Markov chain Monte Carlo (MCMC) simulation is an important and necessary tool to perform Bayesian analyses. The simulation is often presented as a mathematical algorithm and then translated into an appropriate computer program. However, this can result in overlooking the fundamental and deeper…

20. Speed-up of Monte Carlo simulations by sampling of rejected states

NARCIS (Netherlands)

Frenkel, D.

2004-01-01

The Markov chain Monte Carlo method is an important tool to estimate the average properties of systems with a very large number of accessible states. This technique is used extensively in fields ranging from physics to genetics and economics. The rejection of trial configurations is a central

1. Using Monte Carlo Software to Teach Abstract Statistical Concepts: A Case Study

Science.gov (United States)

Raffle, Holly; Brooks, Gordon P.

2005-01-01

Violations of assumptions, inflated Type I error rates, and robustness are important concepts for students to learn in an introductory statistics course. However, these abstract ideas can be difficult for students to understand. Monte Carlo simulation methods can provide a concrete way for students to learn abstract statistical concepts. This…

2. JEWEL - a Monte Carlo Model for Jet Quenching

CERN Document Server

Zapp, Korinna; Wiedemann, Urs Achim

2009-01-01

The Monte Carlo model JEWEL 1.0 (Jet Evolution With Energy Loss) simulates parton shower evolution in the presence of a dense QCD medium. In its current form medium interactions are modelled as elastic scattering based on perturbative matrix elements and a simple prescription for medium induced gluon radiation. The parton shower is interfaced with a hadronisation model. In the absence of medium effects JEWEL is shown to reproduce jet measurements at LEP. The collisional energy loss is consistent with analytic calculations, but with JEWEL we can go a step further and characterise also jet-induced modifications of the medium. Elastic and inelastic medium interactions are shown to lead to distinctive modifications of the jet fragmentation pattern, which should allow to experimentally distinguish between collisional and radiative energy loss mechanisms. In these proceedings the main JEWEL results are summarised and a Monte Carlo algorithm is outlined that allows to include the Landau-Pomerantschuk-Migdal effect i...

3. Research on GPU Acceleration for Monte Carlo Criticality Calculation

Science.gov (United States)

Xu, Qi; Yu, Ganglin; Wang, Kan

2014-06-01

The Monte Carlo neutron transport method can be naturally parallelized by multi-core architectures due to the dependency between particles during the simulation. The GPU+CPU heterogeneous parallel mode has become an increasingly popular way of parallelism in the field of scientific supercomputing. Thus, this work focuses on the GPU acceleration method for the Monte Carlo criticality simulation, as well as the computational efficiency that GPUs can bring. The "neutron transport step" is introduced to increase the GPU thread occupancy. In order to test the sensitivity of the MC code's complexity, a 1D one-group code and a 3D multi-group general purpose code are respectively transplanted to GPUs, and the acceleration effects are compared. The result of numerical experiments shows considerable acceleration effect of the "neutron transport step" strategy. However, the performance comparison between the 1D code and the 3D code indicates the poor scalability of MC codes on GPUs.

4. Applying polynomial filtering to mass preconditioned Hybrid Monte Carlo

CERN Document Server

Haar, Taylor; Zanotti, James; Nakamura, Yoshifumi

2016-01-01

The use of mass preconditioning or Hasenbusch filtering in modern Hybrid Monte Carlo simulations is common. At light quark masses, multiple filters (three or more) are typically used to reduce the cost of generating dynamical gauge fields; however, the task of tuning a large number of Hasenbusch mass terms is non-trivial. The use of short polynomial approximations to the inverse has been shown to provide an effective UV filter for HMC simulations. In this work we investigate the application of polynomial filtering to the mass preconditioned Hybrid Monte Carlo algorithm as a means of introducing many time scales into the molecular dynamics integration with a simplified parameter tuning process. A generalized multi-scale integration scheme that permits arbitrary step- sizes and can be applied to Omelyan-style integrators is also introduced. We find that polynomial-filtered mass-preconditioning (PF-MP) performs as well as or better than standard mass preconditioning, with significantly less fine tuning required.

5. A Monte Carlo algorithm for simulating fermions on Lefschetz thimbles

CERN Document Server

Alexandru, Andrei; Bedaque, Paulo

2016-01-01

A possible solution of the notorious sign problem preventing direct Monte Carlo calculations for systems with non-zero chemical potential is to deform the integration region in the complex plane to a Lefschetz thimble. We investigate this approach for a simple fermionic model. We introduce an easy to implement Monte Carlo algorithm to sample the dominant thimble. Our algorithm relies only on the integration of the gradient flow in the numerically stable direction, which gives it a distinct advantage over the other proposed algorithms. We demonstrate the stability and efficiency of the algorithm by applying it to an exactly solvable fermionic model and compare our results with the analytical ones. We report a very good agreement for a certain region in the parameter space where the dominant contribution comes from a single thimble, including a region where standard methods suffer from a severe sign problem. However, we find that there are also regions in the parameter space where the contribution from multiple...

6. Monte Carlo Euler approximations of HJM term structure financial models

KAUST Repository

Björk, Tomas

2012-11-22

We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.

7. Kinetic Monte Carlo Studies of Hydrogen Abstraction from Graphite

CERN Document Server

Cuppen, H M

2008-01-01

We present Monte Carlo simulations on Eley-Rideal abstraction reactions of atomic hydrogen chemisorbed on graphite. The results are obtained via a hybrid approach where energy barriers derived from density functional theory calculations are used as input to Monte Carlo simulations. By comparing with experimental data, we discriminate between contributions from different Eley-Rideal mechanisms. A combination of two different mechanisms yields good quantitative and qualitative agreement between the experimentally derived and the simulated Eley-Rideal abstraction cross sections and surface configurations. These two mechanisms include a direct Eley-Rideal reaction with fast diffusing H atoms and a dimer mediated Eley-Rideal mechanism with increased cross section at low coverage. Such a dimer mediated Eley-Rideal mechanism has not previously been proposed and serves as an alternative explanation to the steering behavior often given as the cause of the coverage dependence observed in Eley-Rideal reaction cross sect...

8. Minimising biases in full configuration interaction quantum Monte Carlo

Science.gov (United States)

Vigor, W. A.; Spencer, J. S.; Bearpark, M. J.; Thom, A. J. W.

2015-03-01

We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to, in general, minimise the bias. We show a reweight ing scheme to remove the bias caused by population control commonly used in diffusion Monte Carlo [Umrigar et al., J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step.

9. Sign problem and Monte Carlo calculations beyond Lefschetz thimbles

CERN Document Server

Alexandru, Andrei; Bedaque, Paulo F; Ridgway, Gregory W; Warrington, Neill C

2015-01-01

We point out that Monte Carlo simulations of theories with severe sign problems can be profitably performed over manifolds in complex space different from the one with fixed imaginary part of the action. We describe a family of such manifolds that interpolate between the tangent space at one critical point, where the sign problem is milder compared to the real plane but in some cases still severe, and the union of relevant thimbles, where the sign problem is mild but a multimodal distribution function complicates the Monte Carlo sampling. We exemplify this approach using a simple 0 + 1 dimensional fermion model previously used on sign problem studies and show that it can solve the model for some parameter values where a solution using Lefshetz thimbles was elusive.

10. Minimising biases in full configuration interaction quantum Monte Carlo.

Science.gov (United States)

Vigor, W A; Spencer, J S; Bearpark, M J; Thom, A J W

2015-03-14

We show that Full Configuration Interaction Quantum Monte Carlo (FCIQMC) is a Markov chain in its present form. We construct the Markov matrix of FCIQMC for a two determinant system and hence compute the stationary distribution. These solutions are used to quantify the dependence of the population dynamics on the parameters defining the Markov chain. Despite the simplicity of a system with only two determinants, it still reveals a population control bias inherent to the FCIQMC algorithm. We investigate the effect of simulation parameters on the population control bias for the neon atom and suggest simulation setups to, in general, minimise the bias. We show a reweight ing scheme to remove the bias caused by population control commonly used in diffusion Monte Carlo [Umrigar et al., J. Chem. Phys. 99, 2865 (1993)] is effective and recommend its use as a post processing step.

11. Subtle Monte Carlo Updates in Dense Molecular Systems

DEFF Research Database (Denmark)

Bottaro, Sandro; Boomsma, Wouter; Johansson, Kristoffer E.;

2012-01-01

Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce...... as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results...... a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule...

12. Monte Carlo Study of Real Time Dynamics on the Lattice

Science.gov (United States)

Alexandru, Andrei; Başar, Gökçe; Bedaque, Paulo F.; Vartak, Sohan; Warrington, Neill C.

2016-08-01

Monte Carlo studies involving real time dynamics are severely restricted by the sign problem that emerges from a highly oscillatory phase of the path integral. In this Letter, we present a new method to compute real time quantities on the lattice using the Schwinger-Keldysh formalism via Monte Carlo simulations. The key idea is to deform the path integration domain to a complex manifold where the phase oscillations are mild and the sign problem is manageable. We use the previously introduced "contraction algorithm" to create a Markov chain on this alternative manifold. We substantiate our approach by analyzing the quantum mechanical anharmonic oscillator. Our results are in agreement with the exact ones obtained by diagonalization of the Hamiltonian. The method we introduce is generic and, in principle, applicable to quantum field theory albeit very slow. We discuss some possible improvements that should speed up the algorithm.

13. Fixed-Node Diffusion Monte Carlo of Lithium Systems

CERN Document Server

Rasch, Kevin

2015-01-01

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to avoid any possible impact by pseudo potentials. The focus of the study is the fixed-node errors, and for that purpose we test several orbital sets in order to provide the most accurate nodal hyper surfaces. We compare our results to other high accuracy calculations wherever available and to experimental results so as to quantify the the fixed-node errors. The results for these Li systems show that fixed-node quantum Monte Carlo achieves remarkably high accuracy total energies and recovers 97-99 % of the correlation energy.

14. Monte Carlo Methods in ICF (LIRPP Vol. 13)

Science.gov (United States)

Zimmerman, George B.

2016-10-01

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 SOX 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.

15. A Monte Carlo Model of Light Propagation in Nontransparent Tissue

Institute of Scientific and Technical Information of China (English)

姚建铨; 朱水泉; 胡海峰; 王瑞康

2004-01-01

To sharpen the imaging of structures, it is vital to develop a convenient and efficient quantitative algorithm of the optical coherence tomography (OCT) sampling. In this paper a new Monte Carlo model is set up and how light propagates in bio-tissue is analyzed in virtue of mathematics and physics equations. The relations,in which light intensity of Class 1 and Class 2 light with different wavelengths changes with their permeation depth,and in which Class 1 light intensity (signal light intensity) changes with the probing depth, and in which angularly resolved diffuse reflectance and diffuse transmittance change with the exiting angle, are studied. The results show that Monte Carlo simulation results are consistent with the theory data.

16. Cluster Monte Carlo methods for the FePt Hamiltonian

Science.gov (United States)

Lyberatos, A.; Parker, G. J.

2016-02-01

Cluster Monte Carlo methods for the classical spin Hamiltonian of FePt with long range exchange interactions are presented. We use a combination of the Swendsen-Wang (or Wolff) and Metropolis algorithms that satisfies the detailed balance condition and ergodicity. The algorithms are tested by calculating the temperature dependence of the magnetization, susceptibility and heat capacity of L10-FePt nanoparticles in a range including the critical region. The cluster models yield numerical results in good agreement within statistical error with the standard single-spin flipping Monte Carlo method. The variation of the spin autocorrelation time with grain size is used to deduce the dynamic exponent of the algorithms. Our cluster models do not provide a more accurate estimate of the magnetic properties at equilibrium.

17. Efficient Word Alignment with Markov Chain Monte Carlo

Directory of Open Access Journals (Sweden)

Östling Robert

2016-10-01

Full Text Available We present EFMARAL, a new system for efficient and accurate word alignment using a Bayesian model with Markov Chain Monte Carlo (MCMC inference. Through careful selection of data structures and model architecture we are able to surpass the fast_align system, commonly used for performance-critical word alignment, both in computational efficiency and alignment accuracy. Our evaluation shows that a phrase-based statistical machine translation (SMT system produces translations of higher quality when using word alignments from EFMARAL than from fast_align, and that translation quality is on par with what is obtained using GIZA++, a tool requiring orders of magnitude more processing time. More generally we hope to convince the reader that Monte Carlo sampling, rather than being viewed as a slow method of last resort, should actually be the method of choice for the SMT practitioner and others interested in word alignment.

18. Adaptive Monte Carlo on multivariate binary sampling spaces

CERN Document Server

Schäfer, Christian

2010-01-01

A Monte Carlo algorithm is said to be adaptive if it can adjust automatically its current proposal distribution, using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for a good performance. We treat the problem of constructing such parametric families for adaptive sampling on multivariate binary spaces. A practical motivation for this problem is variable selection in a linear regression context, where we need to either find the best model, with respect to some criterion, or to sample from a Bayesian posterior distribution on the model space. In terms of adaptive algorithms, we focus on the Cross-Entropy (CE) method for optimisation, and the Sequential Monte Carlo (SMC) methods for sampling. Raw versions of both SMC and CE algorithms are easily implemented using binary vectors with independent components. However, for high-dimensional model choice problems, these straightforward proposals do not yields satisfactory results. The key to advanced a...

19. Estimation of beryllium ground state energy by Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Kabir, K. M. Ariful [Department of Physical Sciences, School of Engineering and Computer Science, Independent University, Bangladesh (IUB) Dhaka (Bangladesh); Halder, Amal [Department of Mathematics, University of Dhaka Dhaka (Bangladesh)

2015-05-15

Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.

20. Quantum Monte Carlo calculations with chiral effective field theory interactions.

Science.gov (United States)

Gezerlis, A; Tews, I; Epelbaum, E; Gandolfi, S; Hebeler, K; Nogga, A; Schwenk, A

2013-07-19

We present the first quantum Monte Carlo (QMC) calculations with chiral effective field theory (EFT) interactions. To achieve this, we remove all sources of nonlocality, which hamper the inclusion in QMC calculations, in nuclear forces to next-to-next-to-leading order. We perform auxiliary-field diffusion Monte Carlo (AFDMC) calculations for the neutron matter energy up to saturation density based on local leading-order, next-to-leading order, and next-to-next-to-leading order nucleon-nucleon interactions. Our results exhibit a systematic order-by-order convergence in chiral EFT and provide nonperturbative benchmarks with theoretical uncertainties. For the softer interactions, perturbative calculations are in excellent agreement with the AFDMC results. This work paves the way for QMC calculations with systematic chiral EFT interactions for nuclei and nuclear matter, for testing the perturbativeness of different orders, and allows for matching to lattice QCD results by varying the pion mass.

1. Bayesian Monte Carlo method for nuclear data evaluation

Energy Technology Data Exchange (ETDEWEB)

Koning, A.J. [Nuclear Research and Consultancy Group NRG, P.O. Box 25, ZG Petten (Netherlands)

2015-12-15

A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using the nuclear model code TALYS and the experimental nuclear reaction database EXFOR. The method is applied to all nuclides at the same time. First, the global predictive power of TALYS is numerically assessed, which enables to set the prior space of nuclear model solutions. Next, the method gradually zooms in on particular experimental data per nuclide, until for each specific target nuclide its existing experimental data can be used for weighted Monte Carlo sampling. To connect to the various different schools of uncertainty propagation in applied nuclear science, the result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by the EXFOR-based weight. (orig.)

2. Monte Carlo Simulations of Arterial Imaging with Optical Coherence Tomography

Energy Technology Data Exchange (ETDEWEB)

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

2000-02-01

The laser-tissue interaction code LATIS [London et al., Appl. Optics 36, 9068 ( 1998)] is used to analyze photon scattering histories representative of optical coherence tomography (OCT) experiment performed at Lawrence Livermore National Laboratory. Monte Carlo photonics with Henyey-Greenstein anisotropic scattering is implemented and used to simulate signal discrimination of intravascular structure. An analytic model is developed and used to obtain a scaling law relation for optimization of the OCT signal and to validate Monte Carlo photonics. The appropriateness of the Henyey-Greenstein phase function is studied by direct comparison with more detailed Mie scattering theory using an ensemble of spherical dielectric scatterers. Modest differences are found between the two prescriptions for describing photon angular scattering in tissue. In particular, the Mie scattering phase functions provide less overall reflectance signal but more signal contrast compared to the Henyey-Greenstein formulation.

3. Monte Carlo methods for light propagation in biological tissues.

Science.gov (United States)

Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine

2015-11-01

Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis-Hastings algorithm. The resulting estimating methods are then compared to the so-called Wang-Prahl (or Wang) method. Finally, the formal representation allows to derive a non-linear optimization algorithm close to Levenberg-Marquardt that is used for the estimation of the scattering and absorption coefficients of the tissue from measurements.

4. Monte Carlo simulation of quantum Zeno effect in the brain

CERN Document Server

Georgiev, Danko

2014-01-01

Environmental decoherence appears to be the biggest obstacle for successful construction of quantum mind theories. Nevertheless, the quantum physicist Henry Stapp promoted the view that the mind could utilize quantum Zeno effect to influence brain dynamics and that the efficacy of such mental efforts would not be undermined by environmental decoherence of the brain. To address the physical plausibility of Stapp's claim, we modeled the brain using quantum tunneling of an electron in a multiple-well structure such as the voltage sensor in neuronal ion channels and performed Monte Carlo simulations of quantum Zeno effect exerted by the mind upon the brain in the presence or absence of environmental decoherence. The simulations unambiguously showed that the quantum Zeno effect breaks down for timescales greater than the brain decoherence time. To generalize the Monte Carlo simulation results for any n-level quantum system, we further analyzed the change of brain entropy due to the mind probing actions and proved ...

5. Monte Carlo Simulations of Neutron Oil well Logging Tools

CERN Document Server

Azcurra, M

2002-01-01

Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented.The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively.The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation.The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B.Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation.In particular, the ratio C/O was analyzed as an indicator of oil saturation.Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition

6. Quantum Monte Carlo study of the protonated water dimer

CERN Document Server

Dagrada, Mario; Saitta, Antonino M; Sorella, Sandro; Mauri, Francesco

2013-01-01

We report an extensive theoretical study of the protonated water dimer (Zundel ion) by means of the highly correlated variational Monte Carlo and lattice regularized Monte Carlo approaches. This system represents the simplest model for proton transfer (PT) and a correct description of its properties is essential in order to understand the PT mechanism in more complex acqueous systems. Our Jastrow correlated AGP wave function ensures an accurate treatment of electron correlations. Exploiting the advantages of contracting the primitive basis set over atomic hybrid orbitals, we are able to limit dramatically the number of variational parameters with a systematic control on the numerical precision, crucial in order to simulate larger systems. We investigate energetics and geometrical properties of the Zundel ion as a function of the oxygen-oxygen distance, taken as reaction coordinate. In both cases, our QMC results are found in excellent agreement with coupled cluster CCSD(T) technique, the quantum chemistry "go...

7. Monte Carlo simulations of the Galileo energetic particle detector

CERN Document Server

Jun, I; Garrett, H B; McEntire, R W

2002-01-01

Monte Carlo radiation transport studies have been performed for the Galileo spacecraft energetic particle detector (EPD) in order to study its response to energetic electrons and protons. Three-dimensional Monte Carlo radiation transport codes, MCNP version 4B (for electrons) and MCNPX version 2.2.3 (for protons), were used throughout the study. The results are presented in the form of 'geometric factors' for the high-energy channels studied in this paper: B1, DC2, and DC3 for electrons and B0, DC0, and DC1 for protons. The geometric factor is the energy-dependent detector response function that relates the incident particle fluxes to instrument count rates. The trend of actual data measured by the EPD was successfully reproduced using the geometric factors obtained in this study.

8. Application of Monte Carlo Simulations to Improve Basketball Shooting Strategy

CERN Document Server

Min, Byeong June

2016-01-01

The underlying physics of basketball shooting seems to be a straightforward example of the Newtonian mechanics that can easily be traced by numerical methods. However, a human basketball player does not make use of all the possible basketball trajectories. Instead, a basketball player will build up a database of successful shots and select the trajectory that has the greatest tolerance to small variations of the real world. We simulate the basketball player's shooting training as a Monte Carlo sequence to build optimal shooting strategies, such as the launch speed and angle of the basketball, and whether to take a direct shot or a bank shot, as a function of the player's court positions and height. The phase space volume that belongs to the successful launch velocities generated by Monte Carlo simulations are then used as the criterion to optimize a shooting strategy that incorporates not only mechanical, but human factors as well.

9. Bayesian Monte Carlo method for nuclear data evaluation

Science.gov (United States)

Koning, A. J.

2015-12-01

A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using the nuclear model code TALYS and the experimental nuclear reaction database EXFOR. The method is applied to all nuclides at the same time. First, the global predictive power of TALYS is numerically assessed, which enables to set the prior space of nuclear model solutions. Next, the method gradually zooms in on particular experimental data per nuclide, until for each specific target nuclide its existing experimental data can be used for weighted Monte Carlo sampling. To connect to the various different schools of uncertainty propagation in applied nuclear science, the result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by the EXFOR-based weight.

10. A Monte Carlo code for ion beam therapy

CERN Multimedia

Anaïs Schaeffer

2012-01-01

Initially developed for applications in detector and accelerator physics, the modern Fluka Monte Carlo code is now used in many different areas of nuclear science. Over the last 25 years, the code has evolved to include new features, such as ion beam simulations. Given the growing use of these beams in cancer treatment, Fluka simulations are being used to design treatment plans in several hadron-therapy centres in Europe.   Fluka calculates the dose distribution for a patient treated at CNAO with proton beams. The colour-bar displays the normalized dose values. Fluka is a Monte Carlo code that very accurately simulates electromagnetic and nuclear interactions in matter. In the 1990s, in collaboration with NASA, the code was developed to predict potential radiation hazards received by space crews during possible future trips to Mars. Over the years, it has become the standard tool to investigate beam-machine interactions, radiation damage and radioprotection issues in the CERN accelerator com...

11. Monte Carlo Methods for Bridging the Timescale Gap

Science.gov (United States)

Wilding, Nigel; Landau, David P.

We identify the origin, and elucidate the character of the extended time-scales that plague computer simulation studies of first and second order phase transitions. A brief survey is provided of a number of new and existing techniques that attempt to circumvent these problems. Attention is then focused on two novel methods with which we have particular experience: “Wang-Landau sampling” and Phase Switch Monte Carlo. Detailed case studies are made of the application of the Wang-Landau approach to calculate the density of states of the 2D Ising model and the Edwards-Anderson spin glass. The principles and operation of Phase Switch Monte Carlo are described and its utility in tackling ‘difficult’ first order phase transitions is illustrated via a case study of hard-sphere freezing. We conclude with a brief overview of promising new methods for the improvement of deterministic, spin dynamics simulations.

12. Monte Carlo evaluation of derivative-based global sensitivity measures

Energy Technology Data Exchange (ETDEWEB)

Kucherenko, S. [Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)], E-mail: s.kucherenko@ic.ac.uk; Rodriguez-Fernandez, M. [Process Engineering Group, Instituto de Investigaciones Marinas, Spanish Council for Scientific Research (C.S.I.C.), C/ Eduardo Cabello, 6, 36208 Vigo (Spain); Pantelides, C.; Shah, N. [Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)

2009-07-15

A novel approach for evaluation of derivative-based global sensitivity measures (DGSM) is presented. It is compared with the Morris and the Sobol' sensitivity indices methods. It is shown that there is a link between DGSM and Sobol' sensitivity indices. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is many orders of magnitude lower than that for estimation of the Sobol' sensitivity indices. It is also lower than that for the Morris method. Efficiencies of Monte Carlo (MC) and quasi-Monte Carlo (QMC) sampling methods for calculation of DGSM are compared. It is shown that the superiority of QMC over MC depends on the problem's effective dimension, which can also be estimated using DGSM.

13. Accelerated Monte Carlo simulations with restricted Boltzmann machines

Science.gov (United States)

Huang, Li; Wang, Lei

2017-01-01

Despite their exceptional flexibility and popularity, Monte Carlo methods often suffer from slow mixing times for challenging statistical physics problems. We present a general strategy to overcome this difficulty by adopting ideas and techniques from the machine learning community. We fit the unnormalized probability of the physical model to a feed-forward neural network and reinterpret the architecture as a restricted Boltzmann machine. Then, exploiting its feature detection ability, we utilize the restricted Boltzmann machine to propose efficient Monte Carlo updates to speed up the simulation of the original physical system. We implement these ideas for the Falicov-Kimball model and demonstrate an improved acceptance ratio and autocorrelation time near the phase transition point.

14. Accelerate Monte Carlo Simulations with Restricted Boltzmann Machines

CERN Document Server

Huang, Li

2016-01-01

Despite their exceptional flexibility and popularity, the Monte Carlo methods often suffer from slow mixing times for challenging statistical physics problems. We present a general strategy to overcome this difficulty by adopting ideas and techniques from the machine learning community. We fit the unnormalized probability of the physical model to a feedforward neural network and reinterpret the architecture as a restricted Boltzmann machine. Then, exploiting its feature detection ability, we utilize the restricted Boltzmann machine for efficient Monte Carlo updates and to speed up the simulation of the original physical system. We implement these ideas for the Falicov-Kimball model and demonstrate improved acceptance ratio and autocorrelation time near the phase transition point.

15. Forward Monte Carlo Computations of Polarized Microwave Radiation

Science.gov (United States)

Battaglia, A.; Kummerow, C.

2000-01-01

Microwave radiative transfer computations continue to acquire greater importance as the emphasis in remote sensing shifts towards the understanding of microphysical properties of clouds and with these to better understand the non linear relation between rainfall rates and satellite-observed radiance. A first step toward realistic radiative simulations has been the introduction of techniques capable of treating 3-dimensional geometry being generated by ever more sophisticated cloud resolving models. To date, a series of numerical codes have been developed to treat spherical and randomly oriented axisymmetric particles. Backward and backward-forward Monte Carlo methods are, indeed, efficient in this field. These methods, however, cannot deal properly with oriented particles, which seem to play an important role in polarization signatures over stratiform precipitation. Moreover, beyond the polarization channel, the next generation of fully polarimetric radiometers challenges us to better understand the behavior of the last two Stokes parameters as well. In order to solve the vector radiative transfer equation, one-dimensional numerical models have been developed, These codes, unfortunately, consider the atmosphere as horizontally homogeneous with horizontally infinite plane parallel layers. The next development step for microwave radiative transfer codes must be fully polarized 3-D methods. Recently a 3-D polarized radiative transfer model based on the discrete ordinate method was presented. A forward MC code was developed that treats oriented nonspherical hydrometeors, but only for plane-parallel situations.

16. Non-analogue Monte Carlo method, application to neutron simulation; Methode de Monte Carlo non analogue, application a la simulation des neutrons

Energy Technology Data Exchange (ETDEWEB)

Morillon, B.

1996-12-31

With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.

17. Instantaneous GNSS attitude determination: A Monte Carlo sampling approach

Science.gov (United States)

Sun, Xiucong; Han, Chao; Chen, Pei

2017-04-01

A novel instantaneous GNSS ambiguity resolution approach which makes use of only single-frequency carrier phase measurements for ultra-short baseline attitude determination is proposed. The Monte Carlo sampling method is employed to obtain the probability density function of ambiguities from a quaternion-based GNSS-attitude model and the LAMBDA method strengthened with a screening mechanism is then utilized to fix the integer values. Experimental results show that 100% success rate could be achieved for ultra-short baselines.

18. Quantum Monte Carlo Study of Random Antiferromagnetic Heisenberg Chain

OpenAIRE

Todo, Synge; Kato, Kiyoshi; Takayama, Hajime

1998-01-01

Effects of randomness on the spin-1/2 and 1 antiferromagnetic Heisenberg chains are studied using the quantum Monte Carlo method with the continuous-time loop algorithm. We precisely calculated the uniform susceptibility, string order parameter, spatial and temporal correlation length, and the dynamical exponent, and obtained a phase diagram. The generalization of the continuous-time loop algorithm for the systems with higher-S spins is also presented.

19. Monte Carlo Simulation of Argon in Nano-Space

Institute of Scientific and Technical Information of China (English)

CHEN Min; YANG Chun; GUO Zeng-Yuan

2000-01-01

Monte Carlo simulations are performed to investigate the thermodynamic properties of argon confined in nano-scale cubes constructed of graphite walls. A remarkable depression of the system pressures is observed. The simulations reveal that the length-scale of the cube, the magnitude of the interaction between the fluid and the graphite wall and the density of the fluid exhibit reasonable effects on the thermodynamic property shifts of the luid.

20. A simple introduction to Markov Chain Monte-Carlo sampling.

Science.gov (United States)

van Ravenzwaaij, Don; Cassey, Pete; Brown, Scott D

2016-03-11

Markov Chain Monte-Carlo (MCMC) is an increasingly popular method for obtaining information about distributions, especially for estimating posterior distributions in Bayesian inference. This article provides a very basic introduction to MCMC sampling. It describes what MCMC is, and what it can be used for, with simple illustrative examples. Highlighted are some of the benefits and limitations of MCMC sampling, as well as different approaches to circumventing the limitations most likely to trouble cognitive scientists.

1. Conceptual design and Monte Carlo simulations of the AGATA array

Energy Technology Data Exchange (ETDEWEB)

Farnea, E., E-mail: Enrico.Farnea@pd.infn.i [Istituto Nazionale di Fisica Nucleare, Sezione di Padova, Padova (Italy); Recchia, F.; Bazzacco, D. [Istituto Nazionale di Fisica Nucleare, Sezione di Padova, Padova (Italy); Kroell, Th. [Institut fuer Kernphysik, Technische Universitaet Darmstadt, Darmstadt (Germany); Podolyak, Zs. [Department of Physics, University of Surrey, Guildford (United Kingdom); Quintana, B. [Departamento de Fisica Fundamental, Universidad de Salamanca, Salamanca (Spain); Gadea, A. [Instituto de Fisica Corpuscular, CSIC-Universidad de Valencia, Valencia (Spain)

2010-09-21

The aim of the Advanced GAmma Tracking Array (AGATA) project is the construction of an array based on the novel concepts of pulse shape analysis and {gamma}-ray tracking with highly segmented Ge semiconductor detectors. The conceptual design of AGATA and its performance evaluation under different experimental conditions has required the development of a suitable Monte Carlo code. In this article, the description of the code as well as simulation results relevant for AGATA, are presented.

2. Monte Carlo calculations for r-process nucleosynthesis

Energy Technology Data Exchange (ETDEWEB)

Mumpower, Matthew Ryan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-11-12

A Monte Carlo framework is developed for exploring the impact of nuclear model uncertainties on the formation of the heavy elements. Mass measurements tightly constrain the macroscopic sector of FRDM2012. For r-process nucleosynthesis, it is necessary to understand the microscopic physics of the nuclear model employed. A combined approach of measurements and a deeper understanding of the microphysics is thus warranted to elucidate the site of the r-process.

3. Cassandra: An open source Monte Carlo package for molecular simulation.

Science.gov (United States)

Shah, Jindal K; Marin-Rimoldi, Eliseo; Mullen, Ryan Gotchy; Keene, Brian P; Khan, Sandip; Paluch, Andrew S; Rai, Neeraj; Romanielo, Lucienne L; Rosch, Thomas W; Yoo, Brian; Maginn, Edward J

2017-07-15

Cassandra is an open source atomistic Monte Carlo software package that is effective in simulating the thermodynamic properties of fluids and solids. The different features and algorithms used in Cassandra are described, along with implementation details and theoretical underpinnings to various methods used. Benchmark and example calculations are shown, and information on how users can obtain the package and contribute to it are provided. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

4. The CCFM Monte Carlo generator CASCADE 2.2.0

CERN Document Server

Jung, H; Deak, M; Grebenyuk, A; Hautmann, F; Hentschinski, M; Knutsson, A; Kraemer, M; Kutak, K; Lipatov, A; Zotov, N

2010-01-01

CASCADE is a full hadron level Monte Carlo event generator for ep, \\gamma p and p\\bar{p} and pp processes, which uses the CCFM evolution equation for the initial state cascade in a backward evolution approach supplemented with off - shell matrix elements for the hard scattering. A detailed program description is given, with emphasis on parameters the user wants to change and variables which completely specify the generated events.

5. Monte Carlo physical dosimetry for small photon beams

Energy Technology Data Exchange (ETDEWEB)

Perucha, M.; Rincon, M.; Leal, A.; Carrasco, E. [Sevilla Univ. (Spain). Dept. Fisiologia Medica y Biofisica; Sanchez-Doblado, F. [Sevilla Univ. (Spain). Dept. Fisiologia Medica y Biofisica]|[Hospital Univ. Virgen Macarena, Sevilla (Spain). Servicio de Oncologia Radioterapica; Nunez, L. [Clinica Puerta de Hierro, Madrid (Spain). Servicio de Radiofisica; Arrans, R.; Sanchez-Calzado, J.A.; Errazquin, L. [Hospital Univ. Virgen Macarena, Sevilla (Spain). Servicio de Oncologia Radioterapica

2001-07-01

Small field dosimetry is complicated due to the lack of electronic equilibrium and to the high steep dose gradients. This works compares PDD curves, profiles and output factors measured with conventional detectors (film, diode, TLD and ionisation chamber) and calculated with Monte Carlo. The 6 MV nominal energy from a Philips SL-18 linac has been simulated by using the OMEGA code. MC calculation reveals itself as a convenient method to validate OF and profiles in special conditions, such as small fields. (orig.)

6. Probabilistic fire simulator - Monte Carlo simulation tool for fire scenarios

Energy Technology Data Exchange (ETDEWEB)

Hostikka, S.; Keski-Rahkonen, O. [VTT Building and Transport, Espoo (Finland)

2002-11-01

Risk analysis tool is developed for computing of the distributions of fire model output variables. The tool, called Probabilistic Fire Simulator, combines Monte Carlo simulation and CFAST two-zone fire model. In this work, it is used to calculate failure probability of redundant cables and fire detector activation times in a cable tunnel fire. Sensitivity of the output variables to the input variables is calculated in terms of the rank order correlations. (orig.)

7. CMS Monte Carlo production in the WLCG computing grid

CERN Document Server

Hernández, J M; Mohapatra, A; Filippis, N D; Weirdt, S D; Hof, C; Wakefield, S; Guan, W; Khomitch, A; Fanfani, A; Evans, D; Flossdorf, A; Maes, J; van Mulders, P; Villella, I; Pompili, A; My, S; Abbrescia, M; Maggi, G; Donvito, G; Caballero, J; Sanches, J A; Kavka, C; Van Lingen, F; Bacchi, W; Codispoti, G; Elmer, P; Eulisse, G; Lazaridis, C; Kalini, S; Sarkar, S; Hammad, G

2008-01-01

Monte Carlo production in CMS has received a major boost in performance and scale since the past CHEP06 conference. The production system has been re-engineered in order to incorporate the experience gained in running the previous system and to integrate production with the new CMS event data model, data management system and data processing framework. The system is interfaced to the two major computing Grids used by CMS, the LHC Computing Grid (LCG) and the Open Science Grid (OSG).

8. Monte Carlo simulations to replace film dosimetry in IMRT verification

OpenAIRE

Goetzfried, Thomas; Rickhey, Mark; Treutwein, Marius; Koelbl, Oliver; Bogner, Ludwig

2011-01-01

Patient-specific verification of intensity-modulated radiation therapy (IMRT) plans can be done by dosimetric measurements or by independent dose or monitor unit calculations. The aim of this study was the clinical evaluation of IMRT verification based on a fast Monte Carlo (MC) program with regard to possible benefits compared to commonly used film dosimetry. 25 head-and-neck IMRT plans were recalculated by a pencil beam based treatment planning system (TPS) using an appropriate quality assu...

9. Two Dimensional Nucleation Process by Monte Carlo Simulation

OpenAIRE

T., Irisawa; K., Matsumoto; Y., Arima; T., Kan; Computer Center, Gakushuin University; Department of Physics, Gakushuin University

1997-01-01

Two dimensional nucleation process on substrate is investigated by Monte Carlo simulation, and the critical nucleus size and its waiting time are measured with a high accuracy. In order to measure the critical nucleus with a high accuracy, we calculate the attachment and the detachment rate to the nucleus directly, and define the critical nucleus size when both rate are equal. Using the kinematical nucleation theory by Nishioka, it is found that, our obtained kinematical two dimensional criti...

10. Monte Carlo simulation of photon migration path in turbid media

Institute of Scientific and Technical Information of China (English)

2008-01-01

A new method of Monte Carlo simulation is developed to simulate the photon migration path in a scattering medium after an ultrashort-pulse laser beam comes into the medium.The most probable trajectory of photons at an instant can be obtained with this method.How the photon migration paths are affected by the optical parameters of the scattering medium is analyzed.It is also concluded that the absorption coefficient has no effect on the most probable trajectory of photons.

11. Continuous Time Quantum Monte Carlo simulation of Kondo shuttling

Science.gov (United States)

Zhang, Peng; Assaad, Fakher; Jarrell, Mark

2010-03-01

The Kondo shuttling problem is investigated by using the Continuous Time Quantum Monte Carlo method in both the anti-adiabatic limit φTK and the intermediate regime φ˜TK, where φ is the phonon modulation frequency and TK is the Kondo temperature. We investigate the potential emergence of Kondo effect or Kondo breakdown as a function of the phonon modulation frequency and electron-phonon coupling. This research is supported by grant OISE-0952300.

12. Monte Carlo methods in continuous time for lattice Hamiltonians

CERN Document Server

Huffman, Emilie

2016-01-01

We solve a variety of sign problems for models in lattice field theory using the Hamiltonian formulation, including Yukawa models and simple lattice gauge theories. The solutions emerge naturally in continuous time and use the dual representation for the bosonic fields. These solutions allow us to construct quantum Monte Carlo methods for these problems. The methods could provide an alternative approach to understanding non-perturbative dynamics of some lattice field theories.

13. Assessing Excel VBA Suitability for Monte Carlo Simulation

OpenAIRE

2015-01-01

Monte Carlo (MC) simulation includes a wide range of stochastic techniques used to quantitatively evaluate the behavior of complex systems or processes. Microsoft Excel spreadsheets with Visual Basic for Applications (VBA) software is, arguably, the most commonly employed general purpose tool for MC simulation. Despite the popularity of the Excel in many industries and educational institutions, it has been repeatedly criticized for its flaws and often described as questionable, if not complet...

14. Monte Carlo simulation of proton track structure in biological matter

Science.gov (United States)

Quinto, Michele A.; Monti, Juan M.; Weck, Philippe F.; Fojón, Omar A.; Hanssen, Jocelyn; Rivarola, Roberto D.; Senot, Philippe; Champion, Christophe

2017-05-01

Understanding the radiation-induced effects at the cellular and subcellular levels remains crucial for predicting the evolution of irradiated biological matter. In this context, Monte Carlo track-structure simulations have rapidly emerged among the most suitable and powerful tools. However, most existing Monte Carlo track-structure codes rely heavily on the use of semi-empirical cross sections as well as water as a surrogate for biological matter. In the current work, we report on the up-to-date version of our homemade Monte Carlo code TILDA-V - devoted to the modeling of the slowing-down of 10 keV-100 MeV protons in both water and DNA - where the main collisional processes are described by means of an extensive set of ab initio differential and total cross sections. Contribution to the Topical Issue "Many Particle Spectroscopy of Atoms, Molecules, Clusters and Surfaces", edited by A.N. Grum-Grzhimailo, E.V. Gryzlova, Yu V. Popov, and A.V. Solov'yov.

15. Chemical accuracy from quantum Monte Carlo for the benzene dimer

Energy Technology Data Exchange (ETDEWEB)

Azadi, Sam, E-mail: s.azadi@ucl.ac.uk [Department of Earth Science and Thomas Young Centre, University College London, London WC1E 6BT (United Kingdom); Cohen, R. E. [London Centre for Nanotechnology, University College London, London WC1E 6BT, United Kingdom and Extreme Materials Initiative, Geophysical Laboratory, Carnegie Institution of Washington, Washington, D.C. 20015 (United States)

2015-09-14

We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of −2.3(4) and −2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is −2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.

16. Valence-bond quantum Monte Carlo algorithms defined on trees.

Science.gov (United States)

Deschner, Andreas; Sørensen, Erik S

2014-09-01

We present a class of algorithms for performing valence-bond quantum Monte Carlo of quantum spin models. Valence-bond quantum Monte Carlo is a projective T=0 Monte Carlo method based on sampling of a set of operator strings that can be viewed as forming a treelike structure. The algorithms presented here utilize the notion of a worm that moves up and down this tree and changes the associated operator string. In quite general terms, we derive a set of equations whose solutions correspond to a whole class of algorithms. As specific examples of this class of algorithms, we focus on two cases. The bouncing worm algorithm, for which updates are always accepted by allowing the worm to bounce up and down the tree, and the driven worm algorithm, where a single parameter controls how far up the tree the worm reaches before turning around. The latter algorithm involves only a single bounce where the worm turns from going up the tree to going down. The presence of the control parameter necessitates the introduction of an acceptance probability for the update.

17. Estimating return period of landslide triggering by Monte Carlo simulation

Science.gov (United States)

Peres, D. J.; Cancelliere, A.

2016-10-01

Assessment of landslide hazard is a crucial step for landslide mitigation planning. Estimation of the return period of slope instability represents a quantitative method to map landslide triggering hazard on a catchment. The most common approach to estimate return periods consists in coupling a triggering threshold equation, derived from an hydrological and slope stability process-based model, with a rainfall intensity-duration-frequency (IDF) curve. Such a traditional approach generally neglects the effect of rainfall intensity variability within events, as well as the variability of initial conditions, which depend on antecedent rainfall. We propose a Monte Carlo approach for estimating the return period of shallow landslide triggering which enables to account for both variabilities. Synthetic hourly rainfall-landslide data generated by Monte Carlo simulations are analysed to compute return periods as the mean interarrival time of a factor of safety less than one. Applications are first conducted to map landslide triggering hazard in the Loco catchment, located in highly landslide-prone area of the Peloritani Mountains, Sicily, Italy. Then a set of additional simulations are performed in order to evaluate the traditional IDF-based method by comparison with the Monte Carlo one. Results show that return period is affected significantly by variability of both rainfall intensity within events and of initial conditions, and that the traditional IDF-based approach may lead to an overestimation of the return period of landslide triggering, or, in other words, a non-conservative assessment of landslide hazard.

18. FAST CONVERGENT MONTE CARLO RECEIVER FOR OFDM SYSTEMS

Institute of Scientific and Technical Information of China (English)

Wu Lili; Liao Guisheng; Bao Zheng; Shang Yong

2005-01-01

The paper investigates the problem of the design of an optimal Orthogonal Frequency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is proposed. In the proposed method, the Markov Chain Monte Carlo (MCMC) methods are employed for the blind Bayesian detection without channel estimation. Meanwhile, with the exploitation of the characteristics of OFDM systems, two methods are employed to improve the convergence rate and enhance the efficiency of MCMC algorithms.One is the integration of the posterior distribution function with respect to the associated channel parameters, which is involved in the derivation of the objective distribution function; the other is the intra-symbol differential coding for the elimination of the bimodality problem resulting from the presence of unknown fading channels. Moreover, no matrix inversion is needed with the use of the orthogonality property of OFDM modulation and hence the computational load is significantly reduced. Computer simulation results show the effectiveness of the fast convergent Monte Carlo receiver.

19. Geometric Templates for Improved Tracking Performance in Monte Carlo Codes

Science.gov (United States)

Nease, Brian R.; Millman, David L.; Griesheimer, David P.; Gill, Daniel F.

2014-06-01

One of the most fundamental parts of a Monte Carlo code is its geometry kernel. This kernel not only affects particle tracking (i.e., run-time performance), but also shapes how users will input models and collect results for later analyses. A new framework based on geometric templates is proposed that optimizes performance (in terms of tracking speed and memory usage) and simplifies user input for large scale models. While some aspects of this approach currently exist in different Monte Carlo codes, the optimization aspect has not been investigated or applied. If Monte Carlo codes are to be realistically used for full core analysis and design, this type of optimization will be necessary. This paper describes the new approach and the implementation of two template types in MC21: a repeated ellipse template and a box template. Several different models are tested to highlight the performance gains that can be achieved using these templates. Though the exact gains are naturally problem dependent, results show that runtime and memory usage can be significantly reduced when using templates, even as problems reach realistic model sizes.

20. Monte Carlo Simulation for Statistical Decay of Compound Nucleus

Directory of Open Access Journals (Sweden)

2012-02-01

Full Text Available We perform Monte Carlo simulations for neutron and γ-ray emissions from a compound nucleus based on the Hauser-Feshbach statistical theory. This Monte Carlo Hauser-Feshbach (MCHF method calculation, which gives us correlated information between emitted particles and γ-rays. It will be a powerful tool in many applications, as nuclear reactions can be probed in a more microscopic way. We have been developing the MCHF code, CGM, which solves the Hauser-Feshbach theory with the Monte Carlo method. The code includes all the standard models that used in a standard Hauser-Feshbach code, namely the particle transmission generator, the level density module, interface to the discrete level database, and so on. CGM can emit multiple neutrons, as long as the excitation energy of the compound nucleus is larger than the neutron separation energy. The γ-ray competition is always included at each compound decay stage, and the angular momentum and parity are conserved. Some calculations for a fission fragment 140Xe are shown as examples of the MCHF method, and the correlation between the neutron and γ-ray is discussed.

1. Cluster Monte Carlo methods for the FePt Hamiltonian

Energy Technology Data Exchange (ETDEWEB)

Lyberatos, A., E-mail: lyb@materials.uoc.gr [Materials Science and Technology Department, P.O. Box 2208, 71003 Heraklion (Greece); Parker, G.J. [HGST, A Western Digital Company, 3403 Yerba Buena Road, San Jose, CA 95135 (United States)

2016-02-15

Cluster Monte Carlo methods for the classical spin Hamiltonian of FePt with long range exchange interactions are presented. We use a combination of the Swendsen–Wang (or Wolff) and Metropolis algorithms that satisfies the detailed balance condition and ergodicity. The algorithms are tested by calculating the temperature dependence of the magnetization, susceptibility and heat capacity of L1{sub 0}-FePt nanoparticles in a range including the critical region. The cluster models yield numerical results in good agreement within statistical error with the standard single-spin flipping Monte Carlo method. The variation of the spin autocorrelation time with grain size is used to deduce the dynamic exponent of the algorithms. Our cluster models do not provide a more accurate estimate of the magnetic properties at equilibrium. - Highlights: • A new cluster Monte Carlo algorithm was applied to FePt nanoparticles. • Magnetic anisotropy imposes a restriction on cluster moves. • Inclusion of Metropolis steps is required to satisfy ergodicity. • In the critical region a percolating cluster occurs for any grain size. • Critical slowing down is not solved by the new cluster algorithms.

2. A New Approach to Monte Carlo Simulations in Statistical Physics

Science.gov (United States)

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).

3. Monte Carlo modelling of positron transport in real world applications

Science.gov (United States)

Marjanović, S.; Banković, A.; Šuvakov, M.; Petrović, Z. Lj

2014-05-01

Due to the unstable nature of positrons and their short lifetime, it is difficult to obtain high positron particle densities. This is why the Monte Carlo simulation technique, as a swarm method, is very suitable for modelling most of the current positron applications involving gaseous and liquid media. The ongoing work on the measurements of cross-sections for positron interactions with atoms and molecules and swarm calculations for positrons in gasses led to the establishment of good cross-section sets for positron interaction with gasses commonly used in real-world applications. Using the standard Monte Carlo technique and codes that can follow both low- (down to thermal energy) and high- (up to keV) energy particles, we are able to model different systems directly applicable to existing experimental setups and techniques. This paper reviews the results on modelling Surko-type positron buffer gas traps, application of the rotating wall technique and simulation of positron tracks in water vapor as a substitute for human tissue, and pinpoints the challenges in and advantages of applying Monte Carlo simulations to these systems.

4. Stabilization effect of fission source in coupled Monte Carlo simulations

Directory of Open Access Journals (Sweden)

Börge Olsen

2017-08-01

Full Text Available 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.

5. Quantum Monte Carlo Calculations Applied to Magnetic Molecules

Energy Technology Data Exchange (ETDEWEB)

Engelhardt, Larry [Iowa State Univ., Ames, IA (United States)

2006-01-01

We have calculated the equilibrium thermodynamic properties of Heisenberg spin systems using a quantum Monte Carlo (QMC) method. We have used some of these systems as models to describe recently synthesized magnetic molecules, and-upon comparing the results of these calculations with experimental data-have obtained accurate estimates for the basic parameters of these models. We have also performed calculations for other systems that are of more general interest, being relevant both for existing experimental data and for future experiments. Utilizing the concept of importance sampling, these calculations can be carried out in an arbitrarily large quantum Hilbert space, while still avoiding any approximations that would introduce systematic errors. The only errors are statistical in nature, and as such, their magnitudes are accurately estimated during the course of a simulation. Frustrated spin systems present a major challenge to the QMC method, nevertheless, in many instances progress can be made. In this chapter, the field of magnetic molecules is introduced, paying particular attention to the characteristics that distinguish magnetic molecules from other systems that are studied in condensed matter physics. We briefly outline the typical path by which we learn about magnetic molecules, which requires a close relationship between experiments and theoretical calculations. The typical experiments are introduced here, while the theoretical methods are discussed in the next chapter. Each of these theoretical methods has a considerable limitation, also described in Chapter 2, which together serve to motivate the present work. As is shown throughout the later chapters, the present QMC method is often able to provide useful information where other methods fail. In Chapter 3, the use of Monte Carlo methods in statistical physics is reviewed, building up the fundamental ideas that are necessary in order to understand the method that has been used in this work. With these

6. 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...

7. Use of Monte Carlo simulations in the assessment of calibration strategies-Part I: an introduction to Monte Carlo mathematics.

Science.gov (United States)

Burrows, John

2013-04-01

An introduction to the use of the mathematical technique of Monte Carlo simulations to evaluate least squares regression calibration is described. Monte Carlo techniques involve the repeated sampling of data from a population that may be derived from real (experimental) data, but is more conveniently generated by a computer using a model of the analytical system and a randomization process to produce a large database. Datasets are selected from this population and fed into the calibration algorithms under test, thus providing a facile way of producing a sufficiently large number of assessments of the algorithm to enable a statically valid appraisal of the calibration process to be made. This communication provides a description of the technique that forms the basis of the results presented in Parts II and III of this series, which follow in this issue, and also highlights the issues arising from the use of small data populations in bioanalysis.

8. Gas Swing Options: Introduction and Pricing using Monte Carlo Methods

Directory of Open Access Journals (Sweden)

Václavík Tomáš

2016-02-01

Full Text Available Motivated by the changing nature of the natural gas industry in the European Union, driven by the liberalisation process, we focus on the introduction and pricing of gas swing options. These options are embedded in typical gas sales agreements in the form of offtake flexibility concerning volume and time. The gas swing option is actually a set of several American puts on a spread between prices of two or more energy commodities. This fact, together with the fact that the energy markets are fundamentally different from traditional financial security markets, is important for our choice of valuation technique. Due to the specific features of the energy markets, the existing analytic approximations for spread option pricing are hardly applicable to our framework. That is why we employ Monte Carlo methods to model the spot price dynamics of the underlying commodities. The price of an arbitrarily chosen gas swing option is then computed in accordance with the concept of risk-neutral expectations. Finally, our result is compared with the real payoff from the option realised at the time of the option execution and the maximum ex-post payoff that the buyer could generate in case he knew the future, discounted to the original time of the option pricing.

9. Evaluation of Monte Carlo tools for high energy atmospheric physics

Science.gov (United States)

Rutjes, Casper; Sarria, David; Broberg Skeltved, Alexander; Luque, Alejandro; Diniz, Gabriel; Østgaard, Nikolai; Ebert, Ute

2016-11-01

The emerging field of high energy atmospheric physics (HEAP) includes terrestrial gamma-ray flashes, electron-positron beams and gamma-ray glows from thunderstorms. Similar emissions of high energy particles occur in pulsed high voltage discharges. Understanding these phenomena requires appropriate models for the interaction of electrons, positrons and photons of up to 40 MeV energy with atmospheric air. In this paper, we benchmark the performance of the Monte Carlo codes Geant4, EGS5 and FLUKA developed in other fields of physics and of the custom-made codes GRRR and MC-PEPTITA against each other within the parameter regime relevant for high energy atmospheric physics. We focus on basic tests, namely on the evolution of monoenergetic and directed beams of electrons, positrons and photons with kinetic energies between 100 keV and 40 MeV through homogeneous air in the absence of electric and magnetic fields, using a low energy cutoff of 50 keV. We discuss important differences between the results of the different codes and provide plausible explanations. We also test the computational performance of the codes. The Supplement contains all results, providing a first benchmark for present and future custom-made codes that are more flexible in including electrodynamic interactions.

10. Monte Carlo calculations of the properties of solid nitromethane

Science.gov (United States)

Rice, Betsy M.; Trevino, Samuel F.

1991-09-01

Pairwise additive potential energy functions for H-O, H-H, and O-O intermolecular interactions are presented; methods by which these functions were developed are discussed, and preliminary Monte Carlo calculations of the crystal lattice parameters using these functions are presented. The results indicate that these potential energy functions correctly reproduce the lattice parameters measured by neutron diffraction at 4.2 K, ambient pressure, and at pressures below 1.0 GPa, room temperature. It is our intention in this and future work to obtain sufficient information concerning the intermolecular interactions between molecules of nitromethane (CH3NO2) in order to produce, via computer simulation, a reliable equation of state and other related properties in the condensed phase. For this purpose, substantial experimental investigations have been performed in the past on several properties of the crystal. For the present study, the most important of these are the determination of the crystal structure at ambient pressure, from 4.2 K to 228 K (Trevino, Prince, and Hubbard 1980) and neutron spectroscopic determination of the rotational properties of the methyl group (Trevino and Rymes 1980; Alefeld et al. 1982; Cavagnat et al. 1985).

11. Bayesian adaptive Markov chain Monte Carlo estimation of genetic parameters.

Science.gov (United States)

Mathew, B; Bauer, A M; Koistinen, P; Reetz, T C; Léon, J; Sillanpää, M J

2012-10-01

Accurate and fast estimation of genetic parameters that underlie quantitative traits using mixed linear models with additive and dominance effects is of great importance in both natural and breeding populations. Here, we propose a new fast adaptive Markov chain Monte Carlo (MCMC) sampling algorithm for the estimation of genetic parameters in the linear mixed model with several random effects. In the learning phase of our algorithm, we use the hybrid Gibbs sampler to learn the covariance structure of the variance components. In the second phase of the algorithm, we use this covariance structure to formulate an effective proposal distribution for a Metropolis-Hastings algorithm, which uses a likelihood function in which the random effects have been integrated out. Compared with the hybrid Gibbs sampler, the new algorithm had better mixing properties and was approximately twice as fast to run. Our new algorithm was able to detect different modes in the posterior distribution. In addition, the posterior mode estimates from the adaptive MCMC method were close to the REML (residual maximum likelihood) estimates. Moreover, our exponential prior for inverse variance components was vague and enabled the estimated mode of the posterior variance to be practically zero, which was in agreement with the support from the likelihood (in the case of no dominance). The method performance is illustrated using simulated data sets with replicates and field data in barley.

12. Monte-Carlo Tree Search in Settlers of Catan

Science.gov (United States)

Szita, István; Chaslot, Guillaume; Spronck, Pieter

Games are considered important benchmark opportunities for artificial intelligence research. Modern strategic board games can typically be played by three or more people, which makes them suitable test beds for investigating multi-player strategic decision making. Monte-Carlo Tree Search (MCTS) is a recently published family of algorithms that achieved successful results with classical, two-player, perfect-information games such as Go. In this paper we apply MCTS to the multi-player, non-deterministic board game Settlers of Catan. We implemented an agent that is able to play against computer-controlled and human players. We show that MCTS can be adapted successfully to multi-agent environments, and present two approaches of providing the agent with a limited amount of domain knowledge. Our results show that the agent has a considerable playing strength when compared to game implementation with existing heuristics. So, we may conclude that MCTS is a suitable tool for achieving a strong Settlers of Catan player.

13. Monte Carlo calculation of radiation energy absorbed in plastic scintillators

Energy Technology Data Exchange (ETDEWEB)

Mainardi, R.T.; Bonzi, E.V. [Universidad Nacional de Cordoba (Argentina). Facultad de Matematica, Astronomia y Fisica

1995-05-01

Monte Carlo calculations of the rate of absorbed energy from a photon beam were carried out to compare the response of commercial plastic scintillators with that of air in the energy region below 1 MeV. We have found that for photon energies above 100 keV, the response of different kinds of plastics is proportional to that of air, while below this value of energy, we have obtained differences between the responses of plastics and air. In a literature search, we have also found discrepancies with other authors as well as among them. In this paper, we investigate the possibilities of eliminating these differences and explaining discrepancies. We found that doping a plastic scintillator with silicon makes the composite materials behave like air from 2 keV up to 600 keV, making the ratio of absorbed energy constant. This energy region is of interest in radiology and surface radiotherapy and we conclude that a plastic scintillator with truly air-equivalent behavior is of importance to carry out more precise dosimetry. Other elements such as fluorine and magnesium were also considered, but silicon was found to be more appropriate due to its greater atomic number and its interchangeability with carbon in hydrocarbon molecules. (author).

14. Monte Carlo Sampling of Negative-temperature Plasma States

Energy Technology Data Exchange (ETDEWEB)

John A. Krommes; Sharadini Rath

2002-07-19

A Monte Carlo procedure is used to generate N-particle configurations compatible with two-temperature canonical equilibria in two dimensions, with particular attention to nonlinear plasma gyrokinetics. An unusual feature of the problem is the importance of a nontrivial probability density function R0(PHI), the probability of realizing a set {Phi} of Fourier amplitudes associated with an ensemble of uniformly distributed, independent particles. This quantity arises because the equilibrium distribution is specified in terms of {Phi}, whereas the sampling procedure naturally produces particles states gamma; {Phi} and gamma are related via a gyrokinetic Poisson equation, highly nonlinear in its dependence on gamma. Expansion and asymptotic methods are used to calculate R0(PHI) analytically; excellent agreement is found between the large-N asymptotic result and a direct numerical calculation. The algorithm is tested by successfully generating a variety of states of both positive and negative temperature, including ones in which either the longest- or shortest-wavelength modes are excited to relatively very large amplitudes.

15. Lattice gauge theories and Monte Carlo algorithms

Energy Technology Data Exchange (ETDEWEB)

Creutz, M. (Brookhaven National Lab., Upton, NY (USA). Physics Dept.)

1989-07-01

Lattice gauge theory has become the primary tool for non-perturbative calculations in quantum field theory. These lectures review some of the foundations of this subject. The first lecture reviews the basic definition of the theory in terms of invariant integrals over group elements on lattice bonds. The lattice represents an ultraviolet cutoff, and renormalization group arguments show how the bare coupling must be varied to obtain the continuum limit. Expansions in the inverse of the coupling constant demonstrate quark confinement in the strong coupling limit. The second lecture turns to numerical simulation, which has become an important approach to calculating hadronic properties. Here I discuss the basic algorithms for obtaining appropriately weighted gauge field configurations. The third lecture turns to algorithms for treating fermionic fields, which still require considerably more computer time than needed for purely bosonic simulations. Some particularly promising recent approaches are based on global accept-reject steps and should display a rather favorable dependence of computer time on the system volume. (orig.).

16. Application of Monte Carlo Technique for Determining Maneuvering Loads from Statistical Information on Airplane Motions

Science.gov (United States)

Hamer, Harold A.; Mayer, John P.; Huston, Wilber B.

1961-01-01

17. CloudMC: a cloud computing application for Monte Carlo simulation.

Science.gov (United States)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-04-21

This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

18. Applications of the Monte Carlo simulation in dosimetry and medical physics problems; Aplicaciones de la simulacion Monte Carlo en dosimetria y problemas de fisica medica

Energy Technology Data Exchange (ETDEWEB)

Rojas C, E. L., E-mail: leticia.rojas@inin.gob.m [ININ, Gerencia de Ciencias Ambientales, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)

2010-07-01

At the present time the computers use to solve important problems extends to all the areas. These areas can be of social, economic, of engineering, of basic and applied science, etc. With and appropriate handling of computation programs and information can be carried out calculations and simulations of real models, to study them and to solve theoretical or application problems. The processes that contain random variables are susceptible of being approached with the Monte Carlo method. This is a numeric method that, thanks to the improvements in the processors of the computers, it can apply in many tasks more than what was made in the principles of their practical application (at the beginning of the decade of 1950). In this work the application of the Monte Carlo method will be approached in the simulation of the radiation interaction with the matter, to investigate dosimetric aspects of some problems that exist in the medical physics area. Also, contain an introduction about some historical data and some general concepts related with the Monte Carlo simulation are revised. (Author)

19. Time-step limits for a Monte Carlo Compton-scattering method

Energy Technology Data Exchange (ETDEWEB)

Densmore, Jeffery D [Los Alamos National Laboratory; Warsa, James S [Los Alamos National Laboratory; Lowrie, Robert B [Los Alamos National Laboratory

2008-01-01

Compton scattering is an important aspect of radiative transfer in high energy density applications. In this process, the frequency and direction of a photon are altered by colliding with a free electron. The change in frequency of a scattered photon results in an energy exchange between the photon and target electron and energy coupling between radiation and matter. Canfield, Howard, and Liang have presented a Monte Carlo method for simulating Compton scattering that models the photon-electron collision kinematics exactly. However, implementing their technique in multiphysics problems that include the effects of radiation-matter energy coupling typically requires evaluating the material temperature at its beginning-of-time-step value. This explicit evaluation can lead to unstable and oscillatory solutions. In this paper, we perform a stability analysis of this Monte Carlo method and present time-step limits that avoid instabilities and nonphysical oscillations by considering a spatially independent, purely scattering radiative-transfer problem. Examining a simplified problem is justified because it isolates the effects of Compton scattering, and existing Monte Carlo techniques can robustly model other physics (such as absorption, emission, sources, and photon streaming). Our analysis begins by simplifying the equations that are solved via Monte Carlo within each time step using the Fokker-Planck approximation. Next, we linearize these approximate equations about an equilibrium solution such that the resulting linearized equations describe perturbations about this equilibrium. We then solve these linearized equations over a time step and determine the corresponding eigenvalues, quantities that can predict the behavior of solutions generated by a Monte Carlo simulation as a function of time-step size and other physical parameters. With these results, we develop our time-step limits. This approach is similar to our recent investigation of time discretizations for the

20. An introduction to applied quantum mechanics in the Wigner Monte Carlo formalism

Energy Technology Data Exchange (ETDEWEB)

Sellier, J.M., E-mail: jeanmichel.sellier@parallel.bas.bg [IICT, Bulgarian Academy of Sciences, Acad. G. Bonchev str. 25A, 1113 Sofia (Bulgaria); Nedjalkov, M. [IICT, Bulgarian Academy of Sciences, Acad. G. Bonchev str. 25A, 1113 Sofia (Bulgaria); Institute for Microelectronics, TU Wien, Gußhausstraße 27-29/E360, 1040 Wien (Austria); Dimov, I. [IICT, Bulgarian Academy of Sciences, Acad. G. Bonchev str. 25A, 1113 Sofia (Bulgaria)

2015-05-12

The Wigner formulation of quantum mechanics is a very intuitive approach which allows the comprehension and prediction of quantum mechanical phenomena in terms of quasi-distribution functions. In this review, our aim is to provide a detailed introduction to this theory along with a Monte Carlo method for the simulation of time-dependent quantum systems evolving in a phase-space. This work consists of three main parts. First, we introduce the Wigner formalism, then we discuss in detail the Wigner Monte Carlo method and, finally, we present practical applications. In particular, the Wigner model is first derived from the Schrödinger equation. Then a generalization of the formalism due to Moyal is provided, which allows to recover important mathematical properties of the model. Next, the Wigner equation is further generalized to the case of many-body quantum systems. Finally, a physical interpretation of the negative part of a quasi-distribution function is suggested. In the second part, the Wigner Monte Carlo method, based on the concept of signed (virtual) particles, is introduced in detail for the single-body problem. Two extensions of the Wigner Monte Carlo method to quantum many-body problems are introduced, in the frameworks of time-dependent density functional theory and ab-initio methods. Finally, in the third and last part of this paper, applications to single- and many-body problems are performed in the context of quantum physics and quantum chemistry, specifically focusing on the hydrogen, lithium and boron atoms, the H{sub 2} molecule and a system of two identical Fermions. We conclude this work with a discussion on the still unexplored directions the Wigner Monte Carlo method could take in the next future.