Multilevel Monte Carlo Approaches for Numerical Homogenization
Efendiev, Yalchin R.
2015-10-01
In this article, we study the application of multilevel Monte Carlo (MLMC) approaches to numerical random homogenization. Our objective is to compute the expectation of some functionals of the homogenized coefficients, or of the homogenized solutions. This is accomplished within MLMC by considering different sizes of representative volumes (RVEs). Many inexpensive computations with the smallest RVE size are combined with fewer expensive computations performed on larger RVEs. Likewise, when it comes to homogenized solutions, different levels of coarse-grid meshes are used to solve the homogenized equation. We show that, by carefully selecting the number of realizations at each level, we can achieve a speed-up in the computations in comparison to a standard Monte Carlo method. Numerical results are presented for both one-dimensional and two-dimensional test-cases that illustrate the efficiency of the approach.
Monte Carlo 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
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...
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
Application of advanced Monte Carlo Methods in numerical dosimetry.
Reichelt, U; Henniger, J; Lange, C
2006-01-01
Many tasks in different sectors of dosimetry are very complex and highly sensitive to changes in the radiation field. Often, only the simulation of radiation transport is capable of describing the radiation field completely. Down to sub-cellular dimensions the energy deposition by cascades of secondary electrons is the main pathway for damage induction in matter. A large number of interactions take place until such electrons are slowed down to thermal energies. Also for some problems of photon transport a large number of photon histories need to be processed. Thus the efficient non-analogue Monte Carlo program, AMOS, has been developed for photon and electron transport. Various applications and benchmarks are presented showing its ability. For radiotherapy purposes the radiation field of a brachytherapy source is calculated according to the American Association of Physicists in Medicine Task Group Report 43 (AAPM/TG43). As additional examples, results for the detector efficiency of a high-purity germanium (HPGe) detector and a dose estimation for an X-ray shielding for radiation protection are shown.
Cluster Monte Carlo and numerical mean field analysis for the water liquid-liquid phase transition
Mazza, Marco G.; Stokely, Kevin; Strekalova, Elena G.; Stanley, H. Eugene; Franzese, Giancarlo
2009-04-01
Using Wolff's cluster Monte Carlo simulations and numerical minimization within a mean field approach, we study the low temperature phase diagram of water, adopting a cell model that reproduces the known properties of water in its fluid phases. Both methods allow us to study the thermodynamic behavior of water at temperatures, where other numerical approaches - both Monte Carlo and molecular dynamics - are seriously hampered by the large increase of the correlation times. The cluster algorithm also allows us to emphasize that the liquid-liquid phase transition corresponds to the percolation transition of tetrahedrally ordered water molecules.
Monte Carlo transition probabilities
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...
Versluis, R.; Dorsman, R.; Thielen, L.; Roos, M.E.
2009-01-01
A new approach for performing numerical direct simulation Monte Carlo (DSMC) simulations on turbomolecular pumps in the free molecular and transitional flow regimes is described. The chosen approach is to use surfaces that move relative to the grid to model the effect of rotors and stators on a gas
Takahashi, F; Endo, A
2007-01-01
A system utilising radiation transport codes has been developed to derive accurate dose distributions in a human body for radiological accidents. A suitable model is quite essential for a numerical analysis. Therefore, two tools were developed to setup a 'problem-dependent' input file, defining a radiation source and an exposed person to simulate the radiation transport in an accident with the Monte Carlo calculation codes-MCNP and MCNPX. Necessary resources are defined by a dialogue method with a generally used personal computer for both the tools. The tools prepare human body and source models described in the input file format of the employed Monte Carlo codes. The tools were validated for dose assessment in comparison with a past criticality accident and a hypothesized exposure.
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...
A numerical study of rays in random media. [Monte Carlo method simulation
Youakim, M. Y.; Liu, C. H.; Yeh, K. C.
1973-01-01
Statistics of electromagnetic rays in a random medium are studied numerically by the Monte Carlo method. Two dimensional random surfaces with prescribed correlation functions are used to simulate the random media. Rays are then traced in these sample media. Statistics of the ray properties such as the ray positions and directions are computed. Histograms showing the distributions of the ray positions and directions at different points along the ray path as well as at given points in space are given. The numerical experiment is repeated for different cases corresponding to weakly and strongly random media with isotropic and anisotropic irregularities. Results are compared with those derived from theoretical investigations whenever possible.
Monte Carlo and nonlinearities
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...
Development of numerical models for Monte Carlo simulations of Th-Pb fuel assembly
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Oettingen Mikołaj
2017-01-01
Full Text Available The thorium-uranium fuel cycle is a promising alternative against uranium-plutonium fuel cycle, but it demands many advanced research before starting its industrial application in commercial nuclear reactors. The paper presents the development of the thorium-lead (Th-Pb fuel assembly numerical models for the integral irradiation experiments. The Th-Pb assembly consists of a hexagonal array of ThO2 fuel rods and metallic Pb rods. The design of the assembly allows different combinations of rods for various types of irradiations and experimental measurements. The numerical model of the Th-Pb assembly was designed for the numerical simulations with the continuous energy Monte Carlo Burnup code (MCB implemented on the supercomputer Prometheus of the Academic Computer Centre Cyfronet AGH.
System Level Numerical Analysis of a Monte Carlo Simulation of the E. Coli Chemotaxis
Siettos, Constantinos I
2010-01-01
Over the past few years it has been demonstrated that "coarse timesteppers" establish a link between traditional numerical analysis and microscopic/ stochastic simulation. The underlying assumption of the associated lift-run-restrict-estimate procedure is that macroscopic models exist and close in terms of a few governing moments of microscopically evolving distributions, but they are unavailable in closed form. This leads to a system identification based computational approach that sidesteps the necessity of deriving explicit closures. Two-level codes are constructed; the outer code performs macroscopic, continuum level numerical tasks, while the inner code estimates -through appropriately initialized bursts of microscopic simulation- the quantities required for continuum numerics. Such quantities include residuals, time derivatives, and the action of coarse slow Jacobians. We demonstrate how these coarse timesteppers can be applied to perform equation-free computations of a kinetic Monte Carlo simulation of...
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 KAPL`s RACER Monte Carlo code, cover the fundamental theory, concepts, and practices for Monte Carlo analysis. In particular, a thorough grounding in the basic fundamentals of Monte Carlo methods is presented, including random number generation, random sampling, the Monte Carlo approach to solving transport problems, computational geometry, collision physics, tallies, and eigenvalue calculations. Furthermore, modern computational algorithms for vector and parallel approaches to Monte Carlo calculations are covered in detail, including fundamental parallel and vector concepts, the event-based algorithm, master/slave schemes, parallel scaling laws, and portability issues.
(U) Introduction to Monte Carlo Methods
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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.
Quasi-Monte Carlo numerical integration on $\\mathbb{R}^s$: digital nets and worst-case error
Dick, Josef
2010-01-01
Quasi-Monte Carlo rules are equal weight quadrature rules defined over the domain $[0,1]^s$. Here we introduce quasi-Monte Carlo type rules for numerical integration of functions defined on $\\mathbb{R}^s$. These rules are obtained by way of some transformation of digital nets such that locally one obtains qMC rules, but at the same time, globally one also has the required distribution. We prove that these rules are optimal for numerical integration in fractional Besov type spaces. The analysis is based on certain tilings of the Walsh phase plane.
Numerical study of the systematic error in Monte Carlo schemes for semiconductors
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Muscato, Orazio [Univ. degli Studi di Catania (Italy). Dipt. di Matematica e Informatica; Di Stefano, Vincenza [Univ. degli Studi di Messina (Italy). Dipt. di Matematica; Wagner, Wolfgang [Weierstrass-Institut fuer Angewandte Analysis und Stochastik (WIAS) im Forschungsverbund Berlin e.V. (Germany)
2008-07-01
The paper studies the convergence behavior of Monte Carlo schemes for semiconductors. A detailed analysis of the systematic error with respect to numerical parameters is performed. Different sources of systematic error are pointed out and illustrated in a spatially one-dimensional test case. The error with respect to the number of simulation particles occurs during the calculation of the internal electric field. The time step error, which is related to the splitting of transport and electric field calculations, vanishes sufficiently fast. The error due to the approximation of the trajectories of particles depends on the ODE solver used in the algorithm. It is negligible compared to the other sources of time step error, when a second order Runge-Kutta solver is used. The error related to the approximate scattering mechanism is the most significant source of error with respect to the time step. (orig.)
Numerical study of reflectance imaging using a parallel Monte Carlo method.
Chen, Cheng; Lu, Jun Q; Li, Kai; Zhao, Suisheng; Brock, R Scott; Hu, Xin-Hua
2007-07-01
Reflectance imaging of biological tissues with visible and near-infrared light has the significant potential to provide a noninvasive and safe imaging modality for diagnosis of dysplastic and malignant lesions in the superficial tissue layers. The difficulty in the extraction of optical and structural parameters lies in the lack of efficient methods for accurate modeling of light scattering in biological tissues of turbid nature. We present a parallel Monte Carlo method for accurate and efficient modeling of reflectance images from turbid tissue phantoms. A parallel Monte Carlo code has been developed with the message passing interface and evaluated on a computing cluster with 16 processing elements. The code was validated against the solutions of the radiative transfer equation on the bidirectional reflection and transmission functions. With this code we investigated numerically the dependence of reflectance image on the imaging system and phantom parameters. The contrasts of reflectance images were found to be nearly independent of the numerical aperture (NA) of the imaging camera despite the fact that reflectance depends on the NA. This enables efficient simulations of the reflectance images using an NA at 1.00. Using heterogeneous tissue phantoms with an embedded region simulating a lesion, we investigated the correlation between the reflectance image profile or contrast and the phantom parameters. It has been shown that the image contrast approaches 0 when the single-scattering albedos of the two regions in the heterogeneous phantoms become matched. Furthermore, a zone of detection has been demonstrated for determination of the thickness of the embedded region and optical parameters from the reflectance image profile and contrast. Therefore, the utility of the reflectance imaging method with visible and near-infrared light has been firmly established. We conclude from these results that the optical parameters of the embedded region can be determined inversely
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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.
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Walsh, Jonathan A., E-mail: walshjon@mit.edu [Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 24-107, Cambridge, MA 02139 (United States); Palmer, Todd S. [Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, 116 Radiation Center, Corvallis, OR 97331 (United States); Urbatsch, Todd J. [XTD-IDA: Theoretical Design, Integrated Design and Assessment, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2015-12-15
Highlights: • Generation of discrete differential scattering angle and energy loss cross sections. • Gauss–Radau quadrature utilizing numerically computed cross section moments. • Development of a charged particle transport capability in the Milagro IMC code. • Integration of cross section generation and charged particle transport capabilities. - Abstract: We investigate a method for numerically generating discrete scattering cross sections for use in charged particle transport simulations. We describe the cross section generation procedure and compare it to existing methods used to obtain discrete cross sections. The numerical approach presented here is generalized to allow greater flexibility in choosing a cross section model from which to derive discrete values. Cross section data computed with this method compare favorably with discrete data generated with an existing method. Additionally, a charged particle transport capability is demonstrated in the time-dependent Implicit Monte Carlo radiative transfer code, Milagro. We verify the implementation of charged particle transport in Milagro with analytic test problems and we compare calculated electron depth–dose profiles with another particle transport code that has a validated electron transport capability. Finally, we investigate the integration of the new discrete cross section generation method with the charged particle transport capability in Milagro.
Quantum Monte Carlo simulation
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...
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros
2016-08-29
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Error in Monte Carlo, quasi-error in Quasi-Monte Carlo
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...
Numerical simulations of blast-impact problems using the direct simulation Monte Carlo method
Sharma, Anupam
There is an increasing need to design protective structures that can withstand or mitigate the impulsive loading due to the impact of a blast or a shock wave. A preliminary step in designing such structures is the prediction of the pressure loading on the structure. This is called the "load definition." This thesis is focused on a numerical approach to predict the load definition on arbitrary geometries for a given strength of the incident blast/shock wave. A particle approach, namely the Direct Simulation Monte Carlo (DSMC) method, is used as the numerical model. A three-dimensional, time-accurate DSMC flow solver is developed as a part of this study. Embedded surfaces, modeled as triangulations, are used to represent arbitrary-shaped structures. Several techniques to improve the computational efficiency of the algorithm of particle-structure interaction are presented. The code is designed using the Object Oriented Programming (OOP) paradigm. Domain decomposition with message passing is used to solve large problems in parallel. The solver is extensively validated against analytical results and against experiments. Two kinds of geometries, a box and an I-shaped beam are investigated for blast impact. These simulations are performed in both two- and three-dimensions. A major portion of the thesis is dedicated to studying the uncoupled fluid dynamics problem where the structure is assumed to remain stationary and intact during the simulation. A coupled, fluid-structure dynamics problem is solved in one spatial dimension using a simple, spring-mass-damper system to model the dynamics of the structure. A parametric study, by varying the mass, spring constant, and the damping coefficient, to study their effect on the loading and the displacement of the structure is also performed. Finally, the parallel performance of the solver is reported for three sample-size problems on two Beowulf clusters.
Numerical Study of Light Transport in Apple Models Based on Monte Carlo Simulations
Directory of Open Access Journals (Sweden)
Mohamed Lamine Askoura
2015-12-01
Full Text Available This paper reports on the quantification of light transport in apple models using Monte Carlo simulations. To this end, apple was modeled as a two-layer spherical model including skin and flesh bulk tissues. The optical properties of both tissue types used to generate Monte Carlo data were collected from the literature, and selected to cover a range of values related to three apple varieties. Two different imaging-tissue setups were simulated in order to show the role of the skin on steady-state backscattering images, spatially-resolved reflectance profiles, and assessment of flesh optical properties using an inverse nonlinear least squares fitting algorithm. Simulation results suggest that apple skin cannot be ignored when a Visible/Near-Infrared (Vis/NIR steady-state imaging setup is used for investigating quality attributes of apples. They also help to improve optical inspection techniques in the horticultural products.
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.
Sharma, Anupam; Long, Lyle N.
2004-10-01
A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented.
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.
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.
Efficient kinetic Monte Carlo simulation
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.
LMC: Logarithmantic Monte Carlo
Mantz, Adam B.
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).
Adaptive Multilevel Monte Carlo Simulation
Hoel, H
2011-08-23
This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).
Error in Monte Carlo, quasi-error in Quasi-Monte Carlo
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.
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.
Monte Carlo methods for electromagnetics
Sadiku, Matthew NO
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 ...
Kovtanyuk, Andrey E.
2012-01-01
Radiative-conductive heat transfer in a medium bounded by two reflecting and radiating plane surfaces is considered. This process is described by a nonlinear system of two differential equations: an equation of the radiative heat transfer and an equation of the conductive heat exchange. The problem is characterized by anisotropic scattering of the medium and by specularly and diffusely reflecting boundaries. For the computation of solutions of this problem, two approaches based on iterative techniques are considered. First, a recursive algorithm based on some modification of the Monte Carlo method is proposed. Second, the diffusion approximation of the radiative transfer equation is utilized. Numerical comparisons of the approaches proposed are given in the case of isotropic scattering. © 2011 Elsevier Ltd. All rights reserved.
Metropolis Methods for Quantum Monte Carlo Simulations
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, ...
Lectures on Monte Carlo methods
Madras, Neal
2001-01-01
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati
Broecker, Peter; Trebst, Simon
2016-12-01
In the absence of a fermion sign problem, auxiliary-field (or determinantal) quantum Monte Carlo (DQMC) approaches have long been the numerical method of choice for unbiased, large-scale simulations of interacting many-fermion systems. More recently, the conceptual scope of this approach has been expanded by introducing ingenious schemes to compute entanglement entropies within its framework. On a practical level, these approaches, however, suffer from a variety of numerical instabilities that have largely impeded their applicability. Here we report on a number of algorithmic advances to overcome many of these numerical instabilities and significantly improve the calculation of entanglement measures in the zero-temperature projective DQMC approach, ultimately allowing us to reach similar system sizes as for the computation of conventional observables. We demonstrate the applicability of this improved DQMC approach by providing an entanglement perspective on the quantum phase transition from a magnetically ordered Mott insulator to a band insulator in the bilayer square lattice Hubbard model at half filling.
Monte Carlo integration on GPU
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...
Numerical calculation of radiation protective clothing efficiency by using Monte Carlo method
Моргунов, Владимир Викторович; Диденко, Наталья Викторовна; Трищ, Роман Михайлович
2016-01-01
The article presents the results of numerical experiments on modeling of absorption of gamma-radiation with/without using the proposed radiation-protective suit and radiation-shielding material (lead glass in the form of microspheres). The proposed method numerical experiments leads to the reduction of human, time and financial resources. When conducting numerical experiments we used the software package GEANT4. When conducting numerical experiments, we used a phantom of the human body (total...
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Liang, Faming
2009-03-01
The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.
Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.
2010-10-01
Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.
Institute of Scientific and Technical Information of China (English)
Shi Feng; Zhang Li-Li; Wang De-Zhen
2009-01-01
This paper reports that a simulation of glow discharge in pure helium gas at the pressure of 1.333×103 Pa under a high-voltage nanosecond pulse is performed by using a one-dimensional particle-in-cell Monte Carlo collisions (PIC-MCC) model. Numerical modelling results show that the cathode sheath is much thicker than that of anode during the pulse discharge, and that there exists the phenomenon of field reversal at relative high pressures near the end of the pulse, which results from the cumulative positive charges due to their finite mobility during the cathode sheath expansion. Moreover, electron energy distribution function (EEDF) and ion energy distribution function (IEDF) have been also observed. In the early stage of the pulse, a large amount of electrons can be accelerated above the ionization threshold energy. However, in the second half of the pulse, as the field in bulk plasma decreases and thereafter the reverse field forms due to the excessive charges in cathode sheath, although the plasma density grows, the high energy part of EEDF decreases. It concludes that the large volume non-equilibrium plasmas can be obtained with high-voltage nanosecond pulse discharges.
Cepeda, Jose; Luna, Byron Quan; Nadim, Farrokh
2013-04-01
An essential component of a quantitative landslide hazard assessment is establishing the extent of the endangered area. This task requires accurate prediction of the run-out behaviour of a landslide, which includes the estimation of the run-out distance, run-out width, velocities, pressures, and depth of the moving mass and the final configuration of the deposits. One approach to run-out modelling is to reproduce accurately the dynamics of the propagation processes. A number of dynamic numerical models are able to compute the movement of the flow over irregular topographic terrains (3-D) controlled by a complex interaction between mechanical properties that may vary in space and time. Given the number of unknown parameters and the fact that most of the rheological parameters cannot be measured in the laboratory or field, the parametrization of run-out models is very difficult in practice. For this reason, the application of run-out models is mostly used for back-analysis of past events and very few studies have attempted to achieve forward predictions. Consequently all models are based on simplified descriptions that attempt to reproduce the general features of the failed mass motion through the use of parameters (mostly controlling shear stresses at the base of the moving mass) which account for aspects not explicitly described or oversimplified. The uncertainties involved in the run-out process have to be approached in a stochastic manner. It is of significant importance to develop methods for quantifying and properly handling the uncertainties in dynamic run-out models, in order to allow a more comprehensive approach to quantitative risk assessment. A method was developed to compute the variation in run-out intensities by using a dynamic run-out model (MassMov2D) and a probabilistic framework based on a Monte Carlo simulation in order to analyze the effect of the uncertainty of input parameters. The probability density functions of the rheological parameters
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
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.
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
Quasi-Monte Carlo rules for numerical integration over the unit sphere $\\mathbb{S}^2$
Brauchart, Johann S
2011-01-01
We study numerical integration on the unit sphere $\\mathbb{S}^2 \\subset \\mathbb{R}^3$ using equal weight quadrature rules, where the weights are such that constant functions are integrated exactly. The quadrature points are constructed by lifting a $(0,m,2)$-net given in the unit square $[0,1]^2$ to the sphere $\\mathbb{S}^2$ by means of an area preserving map. A similar approach has previously been suggested by Cui and Freeden [SIAM J. Sci. Comput. 18 (1997), no. 2]. We prove three results. The first one is that the construction is (almost) optimal with respect to discrepancies based on spherical rectangles. Further we prove that the point set is asymptotically uniformly distributed on $\\mathbb{S}^2$. And finally, we prove an upper bound on the spherical cap $L_2$-discrepancy of order $N^{-1/2} (\\log N)^{1/2}$ (where $N$ denotes the number of points). Numerical results suggest that the $(0,m,2)$-nets lifted to the sphere $\\mathbb{S}^2$ have spherical cap $L_2$-discrepancy converging with the optimal order of ...
Equilibrium Statistics: Monte Carlo Methods
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].
Quantum speedup of Monte Carlo methods.
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.
Self-learning Monte Carlo method
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.
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.
Proton Upset Monte Carlo Simulation
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.
Monte Carlo Particle Lists: MCPL
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.
Applications of Monte Carlo Methods in Calculus.
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)
Density matrix quantum Monte Carlo
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...
Zhang, Yong; Chen, Bin; Li, Dong
2016-04-01
To investigate the influence of polarization on the polarized light propagation in biological tissue, a polarized geometric Monte Carlo method is developed. The Stokes-Mueller formalism is expounded to describe the shifting of light polarization during propagation events, including scattering and interface interaction. The scattering amplitudes and optical parameters of different tissue structures are obtained using Mie theory. Through simulations of polarized light (pulsed dye laser at wavelength of 585 nm) propagation in an infinite slab tissue model and a discrete vessel tissue model, energy depositions in tissue structures are calculated and compared with those obtained through general geometric Monte Carlo simulation under the same parameters but without consideration of polarization effect. It is found that the absorption depth of the polarized light is about one half of that determined by conventional simulations. In the discrete vessel model, low penetrability manifests in three aspects: diffuse reflection became the main contributor to the energy escape, the proportion of epidermal energy deposition increased significantly, and energy deposition in the blood became weaker and more uneven. This may indicate that the actual thermal damage of epidermis during the real-world treatment is higher and the deep buried blood vessels are insufficiently damaged by consideration of polarization effect, compared with the conventional prediction.
Accelerated Monte Carlo by Embedded Cluster Dynamics
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.
Directory of Open Access Journals (Sweden)
Giuliano Carrozza Uzêda Iorio de Souza
2011-08-01
Full Text Available This article presents a practical case in which two of the most efficient numerical procedures developed for derivative analysis are applied to evaluate the POP (Investment Protection with Participation, a structured operation created by São Paulo Stock Exchange - BM&FBOVESPA. The first procedure solves the differential equation through the use of implicit finite differences method. Due to its characteristics, the approach makes it possible to run sensitivity analysis as well as price estimation. In the second, the problem is solved by Monte Carlo simulation, which facilitates the identification of the probability related to the exercise of the embedded options.
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.
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.)
Monte Carlo techniques in radiation therapy
Verhaegen, Frank
2013-01-01
Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...
Approaching Chemical Accuracy with Quantum Monte Carlo
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...
Mean field simulation for Monte Carlo integration
Del Moral, Pierre
2013-01-01
In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko
Monte Carlo 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...
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.
Langevin Monte Carlo filtering for target tracking
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
An introduction to Monte Carlo methods
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
An introduction to Monte Carlo methods
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
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.
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.
Spike Inference from Calcium Imaging using Sequential Monte Carlo Methods
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
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung
2009-11-01
Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.
Bayesian phylogeny analysis via stochastic approximation Monte Carlo.
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.
An Introduction to Multilevel Monte Carlo for Option Valuation
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.
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.
Monte carlo simulation for soot dynamics
Zhou, Kun
2012-01-01
A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.
Lattice gauge theories and Monte Carlo simulations
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.
Quantum Monte Carlo for minimum energy structures
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.
Fast quantum Monte Carlo on a GPU
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.
Geometric Monte Carlo and Black Janus Geometries
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.
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Simulation and the Monte Carlo method
Rubinstein, Reuven Y
2016-01-01
Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...
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)
Quantum Monte Carlo Calculations of Light Nuclei
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.
Improved Monte Carlo Renormalization Group Method
Gupta, R.; Wilson, K. G.; Umrigar, C.
1985-01-01
An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.
Monte Carlo methods for particle transport
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 ...
Smart detectors for Monte Carlo radiative transfer
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...
Quantum Monte Carlo approaches for correlated systems
Becca, Federico
2017-01-01
Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
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.
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.
Monte Carlo Algorithms for Linear Problems
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...
The Feynman Path Goes Monte Carlo
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.
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.
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.
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.
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.
Variable length trajectory compressible hybrid Monte Carlo
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...
Approaching Chemical Accuracy with Quantum Monte Carlo
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.
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.
Ivančič, Matic; Naglič, Peter; Likar, Boštjan; Pernuš, Franjo; Bürmen, Miran
2017-02-01
For a given experimental setting, the measured spatially resolved reflectance rapidly drops with decreasing numerical aperture of the detection scheme. Consequently, for detection schemes with small numerical apertures, the computational time of MC simulations required to obtain adequate signal-to-noise ratio of the spatially resolved reflectance can become very long. We mitigate the issue by virtually increasing the numerical aperture of the detection scheme in MC simulations and devise a criterion for robust estimation of its maximum value. By using the proposed methodology, we show that the acceptance angle of a selected imaging system can be virtually increased from 3 to 11 while preserving a low relative error of the simulated spatially resolved reflectance over a wide range of tissue-like optical properties. As a result, a more than eightfold improvement in the computation time is attained.
Schoups, G.H.W.; Vrugt, J.A.; Fenicia, F.; Van de Giesen, N.C.
2010-01-01
Conceptual rainfall‐runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first‐order, explicit, fixed‐step integration methods leads to computationally cheap simulation models that are e
Schoups, G.; Vrugt, J.A.; Fenicia, F.; van de Giesen, N.C.
2010-01-01
Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are e
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.
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.
Parallel Monte Carlo simulation of aerosol dynamics
Zhou, K.
2014-01-01
A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
SMCTC: Sequential Monte Carlo in C++
Directory of Open Access Journals (Sweden)
Adam M. Johansen
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.
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.
Quantum Monte Carlo with variable spins.
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.
A brief introduction to Monte Carlo simulation.
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.
Quantum Monte Carlo with Variable Spins
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.
CosmoPMC: Cosmology Population Monte Carlo
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.
Adiabatic optimization versus diffusion Monte Carlo methods
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 .
Monte Carlo strategies in scientific computing
Liu, Jun S
2008-01-01
This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...
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.
Parallel Markov chain Monte Carlo simulations.
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.
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.
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.)
Monte carlo simulations of organic photovoltaics.
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.
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.
The Rational Hybrid Monte Carlo Algorithm
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.
The Rational Hybrid Monte Carlo algorithm
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.
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules
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
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)
A comparison of Monte Carlo generators
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.
Monte Carlo Tools for Jet Quenching
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.
An Introduction to Monte Carlo Methods
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)
Monte Carlo methods beyond detailed balance
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
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...
Monte Carlo Simulation of Counting Experiments.
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…
On a full Monte Carlo approach to quantum mechanics
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.
Monte Carlo radiation transport in external beam radiotherapy
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...
A continuation multilevel Monte Carlo algorithm
Collier, Nathan
2014-09-05
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. © 2014, Springer Science+Business Media Dordrecht.
Measuring Berry curvature with quantum Monte Carlo
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...
A separable shadow Hamiltonian hybrid Monte Carlo method.
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).
Monte Carlo methods for multidimensional integration for European option pricing
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.
Institute of Scientific and Technical Information of China (English)
Wang Yang; Cheng Tianle; Xia Yuanming; Jiang Dazhi
2001-01-01
In this paper, the fracture process of a unidirectional CF/SiC single edge-notched beam (SENB) under three-point bending (TPB) is studied by means of macro/micro-statistical Monte Carlo simulation. The simulated p-△ curves are in agreement with the experimental results before the peaks of curves, and the simulated microevolution patterns are in agreement with the patterns of the crack surfaces, which have verified this method. It is preliminarily demonstrated that the second turning point in the compliance changing rate curve corresponds to the fracture initiation for experiments on SENB under TPB of unidirectional CF/SiC composites.
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.
Hybrid Monte Carlo with Chaotic Mixing
Kadakia, Nirag
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.
Monte Carlo study of real time dynamics
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.
Multilevel sequential Monte-Carlo samplers
Jasra, Ajay
2016-01-05
Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.
Monte Carlo Simulation for Particle Detectors
Pia, Maria Grazia
2012-01-01
Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc.
Composite biasing in Monte Carlo radiative transfer
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...
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.
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.
Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy
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.
Handbook of Markov chain Monte Carlo
Brooks, Steve
2011-01-01
""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.
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.)
An introduction to Monte Carlo methods
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.
Planning Tunnel Construction Using Markov Chain Monte Carlo (MCMC)
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...
Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method
2002-01-01
This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.
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.
Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations
Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias
2015-01-01
Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.
Convergence Studies on Monte Carlo Methods for Pricing Mortgage-Backed Securities
National Research Council Canada - National Science Library
Tao Pang; Yipeng Yang; Dai Zhao
2015-01-01
.... When pricing complex instruments, like mortgage-backed securities (MBS), strong path-dependency and high dimensionality make the Monte Carlo method the most suitable, if not the only, numerical method...
Firstenberg, H.
1971-01-01
The statistics are considered of the Monte Carlo method relative to the interpretation of the NUGAM2 and NUGAM3 computer code results. A numerical experiment using the NUGAM2 code is presented and the results are statistically interpreted.
Research on GPU Acceleration for Monte Carlo Criticality Calculation
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.
A Monte Carlo algorithm for simulating fermions on Lefschetz thimbles
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...
Monte Carlo Euler approximations of HJM term structure financial models
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.
Cluster Monte Carlo methods for the FePt Hamiltonian
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.
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.)
Quantum Monte Carlo study of the protonated water dimer
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...
Application of Monte Carlo Simulations to Improve Basketball Shooting Strategy
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.
Bayesian Monte Carlo method for nuclear data evaluation
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.
Institute of Scientific and Technical Information of China (English)
梁铭辉; 郑飞虎; 安振连; 张冶文
2016-01-01
Thermal-pulse method is a powerful tool for measuring space charge distributions in polymer films. The data analysis for thermal-pulse method involves the Fredholm integral equation of the first kind, which requires an appropriate numerical procedure to obtain a solution. Various numerical techniques, including scale transformation and regulation method, are proposed. Of those numerical methods, the scale transformation (ST) is the simplest and the most widely used method. However, it presents a high spatial resolution only near the sample surface. Monte Carlo (MC) method is one of the recently proposed ways to solve the equation numerically and has been successfully applied to the analysis of laser intensity modulation method data, which also involves the Fredholm integral equation of the first kind. In this paper we attempt to analyze thermal-pulse data in frequency domain with the MC method and discuss its effectiveness based on some numerical simulations. The simulation results indicate that the electric field profiles can be effectively extracted by the MC method. The computed profiles by the MC method consist well with the supposed distributions in the entire thickness of the sample, while the profiles reconstructed by the ST method fit very well to the supposed one at the vicinity of the target surface and distort sharply along the direction of the thermal pulse propagation in the sample bulk. On the other hand, the oscillations in the computed results by the MC method could deteriorate its accuracy in this study. The influence of noise level on the analysis based on the MC method is also tested by the use of the simulated data. The results show that the computed profiles would become more fluctuant as the noise level increases. This problem can be solved by selecting a larger value of tolerance during the singular value decomposition procedure. Thus, the value of tolerance is considered to be one of the key parameters in this algorithm, which is actually
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.
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 PES`s, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H{sub 2}O and C{sub 3}. In order to construct accurate trial wavefunctions for C{sub 3}, the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C{sub 3} the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C{sub 3} PES`s suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies.
An Overview of the Monte Carlo Application ToolKit (MCATK)
Energy Technology Data Exchange (ETDEWEB)
Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-01-07
MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library designed to build specialized applications and designed to provide new functionality in existing general-purpose Monte Carlo codes like MCNP; it was developed with Agile software engineering methodologies under the motivation to reduce costs. The characteristics of MCATK can be summarized as follows: MCATK physics – continuous energy neutron-gamma transport with multi-temperature treatment, static eigenvalue (k and α) algorithms, time-dependent algorithm, fission chain algorithms; MCATK geometry – mesh geometries, solid body geometries. MCATK provides verified, unit-tested Monte Carlo components, flexibility in Monte Carlo applications development, and numerous tools such as geometry and cross section plotters. Recent work has involved deterministic and Monte Carlo analysis of stochastic systems. Static and dynamic analysis is discussed, and the results of a dynamic test problem are given.
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.
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....
Archimedes, the Free Monte Carlo simulator
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.
Cluster hybrid Monte Carlo simulation algorithms
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.
Introduction to Cluster Monte Carlo Algorithms
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.
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.
Mosaic crystal algorithm for Monte Carlo simulations
Seeger, P A
2002-01-01
An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)
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.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Richet, Y
2006-12-15
Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)
Monte Carlo Simulations: Number of Iterations and Accuracy
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
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.
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.
Validation of Compton Scattering Monte Carlo Simulation Models
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.
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...
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.
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2015-01-07
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.
Chemical application of diffusion quantum Monte Carlo
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.
Multi-Index Monte Carlo (MIMC)
Haji Ali, Abdul Lateef
2016-01-06
We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).
Discrete range clustering using Monte Carlo methods
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.
Quantum Monte Carlo Calculations of Neutron Matter
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 ...
Information Geometry and Sequential Monte Carlo
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...
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.
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.
MCNP{trademark} Monte Carlo: A precis of MCNP
Energy Technology Data Exchange (ETDEWEB)
Adams, K.J.
1996-06-01
MCNP{trademark} is a general purpose three-dimensional time-dependent neutron, photon, and electron transport code. It is highly portable and user-oriented, and backed by stringent software quality assurance practices and extensive experimental benchmarks. The cross section database is based upon the best evaluations available. MCNP incorporates state-of-the-art analog and adaptive Monte Carlo techniques. The code is documented in a 600 page manual which is augmented by numerous Los Alamos technical reports which detail various aspects of the code. MCNP represents over a megahour of development and refinement over the past 50 years and an ongoing commitment to excellence.
Monte Carlo Simulation of Kinesin Movement with a Lattice Model
Institute of Scientific and Technical Information of China (English)
WANG Hong; DOU Shuo-Xing; WANG Peng-Ye
2005-01-01
@@ Kinesin is a processive double-headed molecular motor that moves along a microtubule by taking about 8nm steps. It generally hydrolyzes one ATP molecule for taking each forward step. The processive movement of the kinesin molecular motors is numerically simulated with a lattice model. The motors are considered as Brownian particles and the ATPase processes of both heads are taken into account. The Monte Carlo simulation results agree well with recent experimental observations, especially on the relation of velocity versus ATP and ADP concentrations.
Communication: Variation after response in quantum Monte Carlo
Neuscamman, Eric
2016-08-01
We present a new method for modeling electronically excited states that overcomes a key failing of linear response theory by allowing the underlying ground state ansatz to relax in the presence of an excitation. The method is variational, has a cost similar to ground state variational Monte Carlo, and admits both open and periodic boundary conditions. We present preliminary numerical results showing that, when paired with the Jastrow antisymmetric geminal power ansatz, the variation-after-response formalism delivers accuracies for valence and charge transfer single excitations on par with equation of motion coupled cluster, while surpassing coupled cluster's accuracy for excitations with significant doubly excited character.
Gauge Potts model with generalized action: A Monte Carlo analysis
Energy Technology Data Exchange (ETDEWEB)
Fanchiotti, H.; Canal, C.A.G.; Sciutto, S.J.
1985-08-15
Results of a Monte Carlo calculation on the q-state gauge Potts model in d dimensions with a generalized action involving planar 1 x 1, plaquette, and 2 x 1, fenetre, loop interactions are reported. For d = 3 and q = 2, first- and second-order phase transitions are detected. The phase diagram for q = 3 presents only first-order phase transitions. For d = 2, a comparison with analytical results is made. Here also, the behavior of the numerical simulation in the vicinity of a second-order transition is analyzed.
Monte Carlo Frameworks Building Customisable High-performance C++ Applications
Duffy, Daniel J
2011-01-01
This is one of the first books that describe all the steps that are needed in order to analyze, design and implement Monte Carlo applications. It discusses the financial theory as well as the mathematical and numerical background that is needed to write flexible and efficient C++ code using state-of-the art design and system patterns, object-oriented and generic programming models in combination with standard libraries and tools. Includes a CD containing the source code for all examples. It is strongly advised that you experiment with the code by compiling it and extending it to suit your ne
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)
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.
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...
Experimental Monte Carlo Quantum Process Certification
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.
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].
On nonlinear Markov chain Monte Carlo
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.
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)
Monte Carlo Exploration of Warped Higgsless Models
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.
Monte Carlo Implementation of Polarized Hadronization
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...
Commensurabilities between ETNOs: a Monte Carlo survey
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...
Lunar Regolith Albedos Using Monte Carlos
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.
Nuclear reactions in Monte Carlo codes.
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.
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....
Modeling neutron guides using Monte Carlo simulations
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.
Accurate barrier heights using diffusion Monte Carlo
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.
Recent Developments in Quantum Monte Carlo: Methods and Applications
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.
QUANTUM MONTE-CARLO SIMULATIONS - ALGORITHMS, LIMITATIONS AND APPLICATIONS
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
QWalk: A Quantum Monte Carlo Program for Electronic Structure
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
Quantum Monte Carlo Simulations : Algorithms, Limitations and Applications
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
Reporting Monte Carlo Studies in Structural Equation Modeling
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
Practical schemes for accurate forces in quantum Monte Carlo
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
Efficiency and accuracy of Monte Carlo (importance) sampling
Waarts, P.H.
2003-01-01
Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed
The Monte Carlo Method. Popular Lectures in Mathematics.
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…
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
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.
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.
Further experience in Bayesian analysis using Monte Carlo Integration
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
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.
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
Practical schemes for accurate forces in quantum Monte Carlo
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
CERN Summer Student Report 2016 Monte Carlo Data Base Improvement
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.
Energy Technology Data Exchange (ETDEWEB)
Noelle, P
2006-12-15
In vivo lung counting, one of the preferred methods for monitoring people exposed to the risk of actinide inhalation, is nevertheless limited by the use of physical calibration phantoms which, for technical reasons, can only provide a rough representation of human tissue. A new approach to in vivo measurements has been developed to take advantage of advances in medical imaging and computing; this consists of numerical phantoms based on tomographic images (CT) or magnetic resonance images (R.M.I.) combined with Monte Carlo computing techniques. Under laboratory implementation of this innovative method using specific software called O.E.D.I.P.E., the main thrust of this thesis was to provide answers to the following question: what do numerical phantoms and new techniques like O.E.D.I.P.E. contribute to the improvement in calibration of low-energy in vivo counting systems? After a few developments of the O.E.D.I.P.E. interface, the numerical method was validated for systems composed of four germanium detectors, the most widespread configuration in radio bioassay laboratories (a good match was found, with less than 10% variation). This study represents the first step towards a person-specific numerical calibration of counting systems, which will improve assessment of the activity retained. A second stage focusing on an exhaustive evaluation of uncertainties encountered in in vivo lung counting was possible thanks to the approach offered by the previously-validated O.E.D.I.P.E. software. It was shown that the uncertainties suggested by experiments in a previous study were underestimated, notably morphological differences between the physical phantom and the measured person. Some improvements in the measurement procedure were then proposed, particularly new bio-metric equations specific to French measurement configurations that allow a more sensible choice of the calibration phantom, directly assessing the thickness of the torso plate to be added to the Livermore phantom
Accelerated GPU based SPECT Monte Carlo simulations
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
Monte Carlo modelling of TRIGA research reactor
El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.
2010-10-01
The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.
Accelerated GPU based SPECT Monte Carlo simulations.
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-07
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
Monte Carlo scatter correction for SPECT
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.
Chen, Hsing-Ta; Cohen, Guy; Reichman, David R.
2017-02-01
In this second paper of a two part series, we present extensive benchmark results for two different inchworm Monte Carlo expansions for the spin-boson model. Our results are compared to previously developed numerically exact approaches for this problem. A detailed discussion of convergence and error propagation is presented. Our results and analysis allow for an understanding of the benefits and drawbacks of inchworm Monte Carlo compared to other approaches for exact real-time non-adiabatic quantum dynamics.
Chen, Hsing-Ta; Reichman, David R
2016-01-01
In this second paper of a two part series, we present extensive benchmark results for two different inchworm Monte Carlo expansions for the spin-boson model. Our results are compared to previously developed numerically exact approaches for this problem. A detailed discussion of convergence and error propagation is presented. Our results and analysis allow for an understanding of the benefits and drawbacks of inchworm Monte Carlo compared to other approaches for exact real-time non-adiabatic quantum dynamics.
Grand Canonical Ensemble Monte Carlo Simulation of Depletion Interactions in Colloidal Suspensions
Institute of Scientific and Technical Information of China (English)
GUO Ji-Yuan; XIAO Chang-Ming
2008-01-01
Depletion interactions in colloidal suspensions confined between two parallel plates are investigated by using acceptance ratio method with grand canonical ensemble Monte Carlo simulation.The numerical results show that both the depletion potential and depletion force are affected by the confinement from the two parallel plates.Furthermore,it is found that in the grand canonical ensemble Monte Carlo simulation,the depletion interactions are strongly affected by the generalized chemical potential.
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
Vectorized Monte Carlo methods for reactor lattice analysis
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.
Quantum Monte Carlo methods algorithms for lattice models
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 ...
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.
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.
Kong, Linghan; Wang, Weizong; Murphy, Anthony B.; Xia, Guangqing
2017-04-01
Microdischarges are an important type of plasma discharge that possess several unique characteristics, such as the presence of a stable glow discharge, high plasma density and intense excimer radiation, leading to several potential applications. The intense and controllable gas heating within the extremely small dimensions of microdischarges has been exploited in micro-thruster technologies by incorporating a micro-nozzle to generate the thrust. This kind of micro-thruster has a significantly improved specific impulse performance compared to conventional cold gas thrusters, and can meet the requirements arising from the emerging development and application of micro-spacecraft. In this paper, we performed a self-consistent 2D particle-in-cell simulation, with a Monte Carlo collision model, of a microdischarge operating in a prototype micro-plasma thruster with a hollow cylinder geometry and a divergent micro-nozzle. The model takes into account the thermionic electron emission including the Schottky effect, the secondary electron emission due to cathode bombardment by the plasma ions, several different collision processes, and a non-uniform argon background gas density in the cathode–anode gap. Results in the high-pressure (several hundreds of Torr), high-current (mA) operating regime showing the behavior of the plasma density, potential distribution, and energy flux towards the hollow cathode and anode are presented and discussed. In addition, the results of simulations showing the effect of different argon gas pressures, cathode material work function and discharge voltage on the operation of the microdischarge thruster are presented. Our calculated properties are compared with experimental data under similar conditions and qualitative and quantitative agreements are reached.
Ku, B.; Nam, M.
2012-12-01
Neutron logging has been widely used to estimate neutron porosity to evaluate formation properties in oil industry. More recently, neutron logging has been highlighted for monitoring the behavior of CO2 injected into reservoir for geological CO2 sequestration. For a better understanding of neutron log interpretation, Monte Carlo N-Particle (MCNP) algorithm is used to illustrate the response of a neutron tool. In order to obtain calibration curves for the neutron tool, neutron responses are simulated in water-filled limestone, sandstone and dolomite formations of various porosities. Since the salinities (concentration of NaCl) of borehole fluid and formation water are important factors for estimating formation porosity, we first compute and analyze neutron responses for brine-filled formations with different porosities. Further, we consider changes in brine saturation of a reservoir due to hydrocarbon production or geological CO2 sequestration to simulate corresponding neutron logging data. As gas saturation decreases, measured neutron porosity confirms gas effects on neutron logging, which is attributed to the fact that gas has slightly smaller number of hydrogen than brine water. In the meantime, increase in CO2 saturation due to CO2 injection reduces measured neutron porosity giving a clue to estimation the CO2 saturation, since the injected CO2 substitute for the brine water. A further analysis on the reduction gives a strategy for estimating CO2 saturation based on time-lapse neutron logging. This strategy can help monitoring not only geological CO2 sequestration but also CO2 flood for enhanced-oil-recovery. Acknowledgements: This work was supported by the Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (No. 2012T100201588). Myung Jin Nam was partially supported by the National Research Foundation of Korea(NRF) grant funded by the Korea
Energy Technology Data Exchange (ETDEWEB)
Baeza, J. A.; Ureba, A.; Jimenez-Ortega, E.; Pereira-Barbeiro, A. R.; Leal, A.
2013-07-01
A new platform for the full Monte Carlo planning and an independent experimental evaluation that it can be integrated into clinical practice. The tool has proved its usefulness and efficiency and now forms part of the flow of work of our research group, the tool used for the generation of results, which are to be suitably revised and are being published. This software is an effort of integration of numerous algorithms of image processing, along with planning optimization algorithms, allowing the process of MCTP planning from a single interface. In addition, becomes a flexible and accurate tool for the evaluation of experimental dosimetric data for the quality control of actual treatments. (Author)
Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran
2017-01-01
Analytical expressions for sampling the scattering angle from a phase function in Monte Carlo simulations of light propagation are available only for a limited number of phase functions. Consequently, numerical sampling methods based on tabulated values are often required instead. By using Monte Carlo simulated reflectance, we compare two existing and propose an improved numerical sampling method and show that both the number of the tabulated values and the numerical sampling method significantly influence the accuracy of the simulated reflectance. The provided results and guidelines should serve as a good starting point for conducting computationally efficient Monte Carlo simulations with numerical phase function sampling. PMID:28663872
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.
Fourier Monte Carlo renormalization-group approach to crystalline membranes.
Tröster, A
2015-02-01
The computation of the critical exponent η characterizing the universal elastic behavior of crystalline membranes in the flat phase continues to represent challenges to theorists as well as computer simulators that manifest themselves in a considerable spread of numerical results for η published in the literature. We present additional insight into this problem that results from combining Wilson's momentum shell renormalization-group method with the power of modern computer simulations based on the Fourier Monte Carlo algorithm. After discussing the ideas and difficulties underlying this combined scheme, we present a calculation of the renormalization-group flow of the effective two-dimensional Young modulus for momentum shells of different thickness. Extrapolation to infinite shell thickness allows us to produce results in reasonable agreement with those obtained by functional renormalization group or by Fourier Monte Carlo simulations in combination with finite-size scaling. Moreover, our method allows us to obtain a decent estimate for the value of the Wegner exponent ω that determines the leading correction to scaling, which in turn allows us to refine our numerical estimate for η previously obtained from precise finite-size scaling data.
Non-Boltzmann Ensembles and Monte Carlo Simulations
Murthy, K. P. N.
2016-10-01
Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc. This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g(E, M), as a function of both energy E, and order parameter M. This is carried out in two stages. We estimate g(E) in the first stage. Employing g
Optical coherence tomography: Monte Carlo simulation and improvement by optical amplification
DEFF Research Database (Denmark)
Tycho, Andreas
2002-01-01
An advanced novel Monte Carlo simulation model of the detection process of an optical coherence tomography (OCT) system is presented. For the first time it is shown analytically that the applicability of the incoherent Monte Carlo approach to model the heterodyne detection process of an OCT system...... model of the OCT signal. The OCT signal from a scattering medium are obtained for several beam and sample geometries using the new Monte Carlo model, and when comparing to results of an analytical model based on the extended Huygens-Fresnel principle excellent agreement is obtained. With the greater...... flexibility of Monte Carlo simulations, this new model is demonstrated to be excellent as a numerical phantom, i.e., as a substitute for otherwise difficult experiments. Finally, a new model of the signal-to-noise ratio (SNR) of an OCT system with optical amplification of the light reflected from the sample...
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.
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.
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio
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.)
Rare event simulation using Monte Carlo methods
Rubino, Gerardo
2009-01-01
In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...
Monte Carlo Simulations of the Photospheric Process
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...
Finding Planet Nine: a Monte Carlo approach
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...
Atomistic Monte Carlo simulation of lipid membranes.
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.
Monte Carlo simulations of Protein Adsorption
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.
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.
Monte Carlo Simulation of River Meander Modelling
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.
Commensurabilities between ETNOs: a Monte Carlo survey
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.
Diffusion Monte Carlo in internal coordinates.
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.
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.
Monte Carlo Production Management at CMS
Boudoul, G.; Pol, A; Srimanobhas, P; Vlimant, J R; Franzoni, Giovanni
2015-01-01
The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events.During the runI of LHC (2010-2012), CMS has produced over 12 Billion simulated events,organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up).In order toaggregate the information needed for the configuration and prioritization of the events production,assure the book-keeping and of all the processing requests placed by the physics analysis groups,and to interface with the CMS production infrastructure,the web-based service Monte Carlo Management (McM) has been developed and put in production in 2012.McM is based on recent server infrastructure technology (CherryPy + java) and relies on a CouchDB database back-end.This contribution will coverthe one and half year of operational experience managing samples of simulated events for CMS,the evolution of its functionalitiesand the extension of its capabi...
Monte Carlo models of dust coagulation
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...
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.
Radiative heat transfer by the Monte Carlo method
Hartnett †, James P; Cho, Young I; Greene, George A; Taniguchi, Hiroshi; Yang, Wen-Jei; Kudo, Kazuhiko
1995-01-01
This book presents the basic principles and applications of radiative heat transfer used in energy, space, and geo-environmental engineering, and can serve as a reference book for engineers and scientists in researchand development. A PC disk containing software for numerical analyses by the Monte Carlo method is included to provide hands-on practice in analyzing actual radiative heat transfer problems.Advances in Heat Transfer is designed to fill the information gap between regularly scheduled journals and university level textbooks by providing in-depth review articles over a broader scope than journals or texts usually allow.Key Features* Offers solution methods for integro-differential formulation to help avoid difficulties* Includes a computer disk for numerical analyses by PC* Discusses energy absorption by gas and scattering effects by particles* Treats non-gray radiative gases* Provides example problems for direct applications in energy, space, and geo-environmental engineering
Monte Carlo simulation of classical spin models with chaotic billiards.
Suzuki, Hideyuki
2013-11-01
It has recently been shown that the computing abilities of Boltzmann machines, or Ising spin-glass models, can be implemented by chaotic billiard dynamics without any use of random numbers. In this paper, we further numerically investigate the capabilities of the chaotic billiard dynamics as a deterministic alternative to random Monte Carlo methods by applying it to classical spin models in statistical physics. First, we verify that the billiard dynamics can yield samples that converge to the true distribution of the Ising model on a small lattice, and we show that it appears to have the same convergence rate as random Monte Carlo sampling. Second, we apply the billiard dynamics to finite-size scaling analysis of the critical behavior of the Ising model and show that the phase-transition point and the critical exponents are correctly obtained. Third, we extend the billiard dynamics to spins that take more than two states and show that it can be applied successfully to the Potts model. We also discuss the possibility of extensions to continuous-valued models such as the XY model.
Proton therapy Monte Carlo SRNA-VOX code
Directory of Open Access Journals (Sweden)
Ilić Radovan D.
2012-01-01
Full Text Available The most powerful feature of the Monte Carlo method is the possibility of simulating all individual particle interactions in three dimensions and performing numerical experiments with a preset error. These facts were the motivation behind the development of a general-purpose Monte Carlo SRNA program for proton transport simulation in technical systems described by standard geometrical forms (plane, sphere, cone, cylinder, cube. Some of the possible applications of the SRNA program are: (a a general code for proton transport modeling, (b design of accelerator-driven systems, (c simulation of proton scattering and degrading shapes and composition, (d research on proton detectors; and (e radiation protection at accelerator installations. This wide range of possible applications of the program demands the development of various versions of SRNA-VOX codes for proton transport modeling in voxelized geometries and has, finally, resulted in the ISTAR package for the calculation of deposited energy distribution in patients on the basis of CT data in radiotherapy. All of the said codes are capable of using 3-D proton sources with an arbitrary energy spectrum in an interval of 100 keV to 250 MeV.
Flow in Random Microstructures: a Multilevel Monte Carlo Approach
Icardi, Matteo
2016-01-06
In this work we are interested in the fast estimation of effective parameters of random heterogeneous materials using Multilevel Monte Carlo (MLMC). MLMC is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrisation of the input randomness is not available or too expensive. We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations (PDEs) on random heterogeneous materials. We make use of the key idea of MLMC, based on different discretization levels, extending it in a more general context, making use of a hierarchy of physical resolution scales, solvers, models and other numerical/geometrical discretisation parameters. Modifications of the classical MLMC estimators are proposed to further reduce variance in cases where analytical convergence rates and asymptotic regimes are not available. Spheres, ellipsoids and general convex-shaped grains are placed randomly in the domain with different placing/packing algorithms and the effective properties of the heterogeneous medium are computed. These are, for example, effective diffusivities, conductivities, and reaction rates. The implementation of the Monte-Carlo estimators, the statistical samples and each single solver is done efficiently in parallel. The method is tested and applied for pore-scale simulations of random sphere packings.
Evolutionary Sequential Monte Carlo Samplers for Change-Point Models
Directory of Open Access Journals (Sweden)
Arnaud Dufays
2016-03-01
Full Text Available Sequential Monte Carlo (SMC methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC methods. Not only do SMC algorithms draw posterior distributions of static or dynamic parameters but additionally they provide an estimate of the marginal likelihood. The tempered and time (TNT algorithm, developed in this paper, combines (off-line tempered SMC inference with on-line SMC inference for drawing realizations from many sequential posterior distributions without experiencing a particle degeneracy problem. Furthermore, it introduces a new MCMC rejuvenation step that is generic, automated and well-suited for multi-modal distributions. As this update relies on the wide heuristic optimization literature, numerous extensions are readily available. The algorithm is notably appropriate for estimating change-point models. As an example, we compare several change-point GARCH models through their marginal log-likelihoods over time.
Monte Carlo model for electron degradation in methane
Bhardwaj, Anil
2015-01-01
We present a Monte Carlo model for degradation of 1-10,000 eV electrons in an atmosphere of methane. The electron impact cross sections for CH4 are compiled and analytical representations of these cross sections are used as input to the model.model.Yield spectra, which provides information about the number of inelastic events that have taken place in each energy bin, is used to calculate the yield (or population) of various inelastic processes. The numerical yield spectra, obtained from the Monte Carlo simulations, is represented analytically, thus generating the Analytical Yield Spectra (AYS). AYS is employed to obtain the mean energy per ion pair and efficiencies of various inelastic processes.Mean energy per ion pair for neutral CH4 is found to be 26 (27.8) eV at 10 (0.1) keV. Efficiency calculation showed that ionization is the dominant process at energies >50 eV, for which more than 50% of the incident electron energy is used. Above 25 eV, dissociation has an efficiency of 27%. Below 10 eV, vibrational e...
Monte-Carlo simulation-based statistical modeling
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.
EXTENDED MONTE CARLO LOCALIZATION ALGORITHM FOR MOBILE SENSOR NETWORKS
Institute of Scientific and Technical Information of China (English)
无
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.
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.
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.
Monte Carlo simulations: Hidden errors from ``good'' random number generators
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.
MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD
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 ...
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
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.
Using Supervised Learning to Improve Monte Carlo Integral Estimation
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 ...
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
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.
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.
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.
Public Infrastructure for Monte Carlo Simulation: publicMC@BATAN
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.
Radiative Equilibrium and Temperature Correction in Monte Carlo Radiation Transfer
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 ...
Chemical accuracy from quantum Monte Carlo for the Benzene Dimer
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...
de Finetti Priors using Markov chain Monte Carlo computations.
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.
Event-chain Monte Carlo for classical continuous spin models
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.
Confidence and efficiency scaling in Variational Quantum Monte Carlo calculations
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.
Study of the Transition Flow Regime using Monte Carlo Methods
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
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.
Successful combination of the stochastic linearization and Monte Carlo methods
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.
Confidence and efficiency scaling in variational quantum Monte Carlo calculations
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.
Monte Carlo methods for light propagation in biological tissues
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...
Multiscale Monte Carlo equilibration: pure Yang-Mills theory
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.
Geometrical and Monte Carlo projectors in 3D PET reconstruction
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...
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
Monte Carlo Volcano Seismic Moment Tensors
Waite, G. P.; Brill, K. A.; Lanza, F.
2015-12-01
Inverse modeling of volcano seismic sources can provide insight into the geometry and dynamics of volcanic conduits. But given the logistical challenges of working on an active volcano, seismic networks are typically deficient in spatial and temporal coverage; this potentially leads to large errors in source models. In addition, uncertainties in the centroid location and moment-tensor components, including volumetric components, are difficult to constrain from the linear inversion results, which leads to a poor understanding of the model space. In this study, we employ a nonlinear inversion using a Monte Carlo scheme with the objective of defining robustly resolved elements of model space. The model space is randomized by centroid location and moment tensor eigenvectors. Point sources densely sample the summit area and moment tensors are constrained to a randomly chosen geometry within the inversion; Green's functions for the random moment tensors are all calculated from modeled single forces, making the nonlinear inversion computationally reasonable. We apply this method to very-long-period (VLP) seismic events that accompany minor eruptions at Fuego volcano, Guatemala. The library of single force Green's functions is computed with a 3D finite-difference modeling algorithm through a homogeneous velocity-density model that includes topography, for a 3D grid of nodes, spaced 40 m apart, within the summit region. The homogenous velocity and density model is justified by long wavelength of VLP data. The nonlinear inversion reveals well resolved model features and informs the interpretation through a better understanding of the possible models. This approach can also be used to evaluate possible station geometries in order to optimize networks prior to deployment.
Quantum Monte Carlo with directed loops.
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.
Monte Carlo simulation of large electron fields
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.
Dosimetry applications in GATE Monte Carlo toolkit.
Papadimitroulas, Panagiotis
2017-02-21
Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Monte Carlo implementation of polarized hadronization
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.
kmos: A lattice kinetic Monte Carlo framework
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.
Perturbation Monte Carlo methods for tissue structure alterations.
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.
A Survey on Multilevel Monte Carlo for European Options
Directory of Open Access Journals (Sweden)
Masoud Moharamnejad
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Liang, Jingang; Wang, Kan; Qiu, Yishu [Dept. of Engineering Physics, LiuQing Building, Tsinghua University, Beijing (China); Chai, Xiao Ming; Qiang, Sheng Long [Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu (China)
2016-06-15
Because of prohibitive data storage requirements in large-scale simulations, the memory problem is an obstacle for Monte Carlo (MC) codes in accomplishing pin-wise three-dimensional (3D) full-core calculations, particularly for whole-core depletion analyses. Various kinds of data are evaluated and quantificational total memory requirements are analyzed based on the Reactor Monte Carlo (RMC) code, showing that tally data, material data, and isotope densities in depletion are three major parts of memory storage. The domain decomposition method is investigated as a means of saving memory, by dividing spatial geometry into domains that are simulated separately by parallel processors. For the validity of particle tracking during transport simulations, particles need to be communicated between domains. In consideration of efficiency, an asynchronous particle communication algorithm is designed and implemented. Furthermore, we couple the domain decomposition method with MC burnup process, under a strategy of utilizing consistent domain partition in both transport and depletion modules. A numerical test of 3D full-core burnup calculations is carried out, indicating that the RMC code, with the domain decomposition method, is capable of pin-wise full-core burnup calculations with millions of depletion regions.
Equivalence of four Monte Carlo methods for photon migration in turbid media.
Sassaroli, Angelo; Martelli, Fabrizio
2012-10-01
In the field of photon migration in turbid media, different Monte Carlo methods are usually employed to solve the radiative transfer equation. We consider four different Monte Carlo methods, widely used in the field of tissue optics, that are based on four different ways to build photons' trajectories. We provide both theoretical arguments and numerical results showing the statistical equivalence of the four methods. In the numerical results we compare the temporal point spread functions calculated by the four methods for a wide range of the optical properties in the slab and semi-infinite medium geometry. The convergence of the methods is also briefly discussed.
Monte Carlo systems used for treatment planning and dose verification
Energy Technology Data Exchange (ETDEWEB)
Brualla, Lorenzo [Universitaetsklinikum Essen, NCTeam, Strahlenklinik, Essen (Germany); Rodriguez, Miguel [Centro Medico Paitilla, Balboa (Panama); Lallena, Antonio M. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain)
2017-04-15
General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations. (orig.) [German] Seit mehreren Jahrzehnten werden allgemein anwendbare Monte-Carlo-Codes zur Simulation des Strahlungstransports benutzt, um die Verteilung der absorbierten Dosis in der perkutanen Strahlentherapie mit Photonen und Elektronen zu evaluieren. Die damit erzielten Ergebnisse sind meist akkurater als solche, die mit nichtstochastischen Methoden herkoemmlicher Bestrahlungsplanungssysteme erzielt werden koennen. Wegen des damit verbundenen Arbeitsaufwands und der langen Dauer der Berechnungen wurden Monte-Carlo-Simulationen von Dosisverteilungen in der konventionellen Strahlentherapie in der Vergangenheit im Wesentlichen in der Forschung eingesetzt. Im Bemuehen, Monte-Carlo
Monte Carlo 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
Stationarity and source convergence in monte carlo criticality calculation.
Energy Technology Data Exchange (ETDEWEB)
Ueki, T. (Taro); Brown, F. B. (Forrest B.)
2002-01-01
In Monte Carlo (MC) criticality calculations, source error propagation through the stationary cycles and source convergcnce in the settling (inactive) cycles are both dominated by the dominance ratio (DR) of fission kernels, Le., the ratio of the second largest to largest eigenvalues. For symmetric two fissile component systems with DR close to unity, the extinction of fission source sites can occur in one of the components even when the initial source is symmetric and the number of histories per cycle is larger than one thousand. When such a system is made slightly asymmetric, the neutron effective multiplication factor (kern) at the inactive cycles does not reflect the convergence to stationary source distribution. To overcome this problem, relative entropy (Kullback Leibler distance) is applied to a slightly asymmetric two fissile component problem with a dominance ratio of 0.9925. Numerical results show that relative entropy is effective as a posterior diagnostic tool.
Last-passage Monte Carlo algorithm for mutual capacitance.
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.
Direct simulation Monte Carlo schemes for Coulomb interactions in plasmas
Dimarco, Giacomo; Pareschi, Lorenzo
2010-01-01
We consider the development of Monte Carlo schemes for molecules with Coulomb interactions. We generalize the classic algorithms of Bird and Nanbu-Babovsky for rarefied gas dynamics to the Coulomb case thanks to the approximation introduced by Bobylev and Nanbu (Theory of collision algorithms for gases and plasmas based on the Boltzmann equation and the Landau-Fokker-Planck equation, Physical Review E, Vol. 61, 2000). Thus, instead of considering the original Boltzmann collision operator, the schemes are constructed through the use of an approximated Boltzmann operator. With the above choice larger time steps are possible in simulations; moreover the expensive acceptance-rejection procedure for collisions is avoided and every particle collides. Error analysis and comparisons with the original Bobylev-Nanbu (BN) scheme are performed. The numerical results show agreement with the theoretical convergence rate of the approximated Boltzmann operator and the better performance of Bird-type schemes with respect to t...
A Monte Carlo Method for Calculating Initiation Probability
Energy Technology Data Exchange (ETDEWEB)
Greenman, G M; Procassini, R J; Clouse, C J
2007-03-05
A Monte Carlo method for calculating the probability of initiating a self-sustaining neutron chain reaction has been developed. In contrast to deterministic codes which solve a non-linear, adjoint form of the Boltzmann equation to calculate initiation probability, this new method solves the forward (standard) form of the equation using a modified source calculation technique. Results from this new method are compared with results obtained from several deterministic codes for a suite of historical test problems. The level of agreement between these code predictions is quite good, considering the use of different numerical techniques and nuclear data. A set of modifications to the historical test problems has also been developed which reduces the impact of neutron source ambiguities on the calculated probabilities.
Monte-Carlo study of Dirac semimetals phase diagram
Braguta, V V; Kotov, A Yu; Nikolaev, A A
2016-01-01
In this paper the phase diagram of Dirac semimetals is studied within lattice Monte-Carlo simulation. In particular, we concentrate on the dynamical chiral symmetry breaking which results in semimetal/insulator transition. Using numerical simulation we determined the values of the critical coupling constant of the semimetal/insulator transition for different values of the anisotropy of the Fermi velocity. This measurement allowed us to draw tentative phase diagram for Dirac semimetals. It turns out that within the Dirac model with Coulomb interaction both Na$_3$Bi and Cd$_3$As$_2$ known experimentally to be Dirac semimetals would lie deeply in the insulating region of the phase diagram. It probably shows a decisive role of screening of the interelectron interaction in real materials, similar to the situation in graphene.
Monte Carlo study of Dirac semimetals phase diagram
Braguta, V. V.; Katsnelson, M. I.; Kotov, A. Yu.; Nikolaev, A. A.
2016-11-01
In this paper the phase diagram of Dirac semimetals is studied within a lattice Monte Carlo simulation. In particular, we concentrate on the dynamical chiral symmetry breaking which results in a semimetal-insulator transition. Using numerical simulation, we determine the values of the critical coupling constant of the semimetal-insulator transition for different values of the anisotropy of the Fermi velocity. This measurement allows us to draw a tentative phase diagram for Dirac semimetals. It turns out that within the Dirac model with Coulomb interaction both Na3Bi and Cd3As2 , known experimentally to be Dirac semimetals, would lie deep in the insulating region of the phase diagram. This result probably shows a decisive role of screening of the interelectron interaction in real materials, similar to the situation in graphene.
New Monte Carlo method for the self-avoiding walk
Berretti, Alberto; Sokal, Alan D.
1985-08-01
We introduce a new Monte Carlo algorithm for the self-avoiding walk (SAW), and show that it is particularly efficient in the critical region (long chains). We also introduce new and more efficient statistical techniques. We employ these methods to extract numerical estimates for the critical parameters of the SAW on the square lattice. We find μ=2.63820 ± 0.00004 ± 0.00030 γ=1.352 ± 0.006 ± 0.025 νv=0.7590 ± 0.0062 ± 0.0042 where the first error bar represents systematic error due to corrections to scaling (subjective 95% confidence limits) and the second bar represents statistical error (classical 95% confidence limits). These results are based on SAWs of average length ≈ 166, using 340 hours CPU time on a CDC Cyber 170-730. We compare our results to previous work and indicate some directions for future research.
Quantitative application of Monte Carlo simulation in Fire-PSA
Energy Technology Data Exchange (ETDEWEB)
Mangs, J.; Hostikka, S.; Korhonen, T. [Valtion Teknillinen Tutkimuskeskus, Espoo (Finland); Keski-Rahkonen, O.
2007-05-15
In a power plant a fire cell forms the basic subunit. Since the fire is initially located there, the full-scale time dependent fire simulation and estimation of target response must be performed within the fire cell. Conditional, time dependent damage probabilities in a fire cell can now be calculated for arbitrary targets (component or a subsystem) combining probabilistic (Monte Carlo) and deterministic simulation. For the latter a spectrum from simple correlations up to latest computational fluid dynamics models is available. Selection of the code is made according to the requirements form the target cell. Although calculations are numerically heavy, it is now economically possible and feasible to carry out quantitative fire-PSA for a complete plant iteratively with the main PSA. From real applications examples are shown on assessment of fire spread possibility in a relay room, and potential of fire spread on cables in a tunnel. (orig.)
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)
Monte Carlo simulations of systems with complex energy landscapes
Wüst, T.; Landau, D. P.; Gervais, C.; Xu, Y.
2009-04-01
Non-traditional Monte Carlo simulations are a powerful approach to the study of systems with complex energy landscapes. After reviewing several of these specialized algorithms we shall describe the behavior of typical systems including spin glasses, lattice proteins, and models for "real" proteins. In the Edwards-Anderson spin glass it is now possible to produce probability distributions in the canonical ensemble and thermodynamic results of high numerical quality. In the hydrophobic-polar (HP) lattice protein model Wang-Landau sampling with an improved move set (pull-moves) produces results of very high quality. These can be compared with the results of other methods of statistical physics. A more realistic membrane protein model for Glycophorin A is also examined. Wang-Landau sampling allows the study of the dimerization process including an elucidation of the nature of the process.
Optimal mesh hierarchies in Multilevel Monte Carlo methods
Von Schwerin, Erik
2016-01-08
I will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.
Introduction to quasi-Monte Carlo integration and applications
Leobacher, Gunther
2014-01-01
This textbook introduces readers to the basic concepts of quasi-Monte Carlo methods for numerical integration and to the theory behind them. The comprehensive treatment of the subject with detailed explanations comprises, for example, lattice rules, digital nets and sequences and discrepancy theory. It also presents methods currently used in research and discusses practical applications with an emphasis on finance-related problems. Each chapter closes with suggestions for further reading and with exercises which help students to arrive at a deeper understanding of the material presented. The book is based on a one-semester, two-hour undergraduate course and is well-suited for readers with a basic grasp of algebra, calculus, linear algebra and basic probability theory. It provides an accessible introduction for undergraduate students in mathematics or computer science.
Monte Carlo Radiation Hydrodynamics: Methods, Tests and Application to Supernova Type Ia Ejecta
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...
Monte-Carlo fluid approaches to detached plasmas in non-axisymmetric divertor configurations
Feng, Y.; Frerichs, H.; Kobayashi, M.; Reiter, D.
2017-03-01
Fluid transport modeling in three-dimensional boundaries of toroidal confinement devices is reviewed with the emphasis on a Monte-Carlo approach to simulate detached plasmas. The loss of axisymmetry in such configurations presents a major challenge for numerical implementation of the standard fluid model widely applied to fusion experimental devices. A large-scale effort has been made to address this problem under complementary aspects including different magnetic topologies and numerical techniques. In this paper, we give a brief review of the different strategies pioneered and the challenges involved. A more detailed description is provided for the Monte-Carlo code—EMC3-Eirene, where the physics model and the basic idea behind the applied Monte-Carlo method are presented. The focus is put on its applications to detachment studies for stellarators and tokamaks. Here, major achievements and difficulties encountered are described. Model limitations and further development plans are discussed.
Monte Carlo simulation of ICRF discharge initiation in ITER
Tripský, M.; Wauters, T.; Lyssoivan, A.; Křivská, A.; Louche, F.; Van Schoor, M.; Noterdaeme, J.-M.
2015-12-01
Discharges produced and sustained by ion cyclotron range of frequency (ICRF) waves in absence of plasma current will be used on ITER for (ion cyclotron-) wall conditioning (ICWC). The here presented simulations aim at ensuring that the ITER ICRH&CD system can be safely employed for ICWC and at finding optimal parameters to initiate the plasma. The 1D Monte Carlo code RFdinity1D3V was developed to simulate ICRF discharge initiation. The code traces the electron motion along one toroidal magnetic field line, accelerated by the RF field in front of the ICRF antenna. Electron collisions in the calculations are handled by a Monte Carlo procedure taking into account their energies and the related electron collision cross sections for collisions with H2, H2+ and H+. The code also includes Coulomb collisions between electrons and ions (e - e, e - H2+ , e - H+). We study the electron multiplication rate as a function of the RF discharge parameters (i) antenna input power (0.1-5MW), and (ii) the neutral pressure (H2) for two antenna phasing (monopole [0000]-phasing and small dipole [0π0π]-phasing). Furthermore, we investigate the electron multiplication rate dependency on the distance from the antenna straps. This radial dependency results from the decreasing electric amplitude and field smoothening with increasing distance from the antenna straps. The numerical plasma breakdown definition used in the code corresponds to the moment when a critical electron density nec for the low hybrid resonance (ω = ωLHR) is reached. This numerical definition was previously found in qualitative agreement with experimental breakdown times obtained from the literature and from experiments on the ASDEX Upgrade and TEXTOR.
Reducing quasi-ergodicity in a double well potential by Tsallis Monte Carlo simulation
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...
Finding organic vapors - a Monte Carlo approach
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.
Coherent Scattering Imaging Monte Carlo Simulation
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
Monte Carlo MP2 on Many Graphical Processing Units.
Doran, Alexander E; Hirata, So
2016-10-11
In the Monte Carlo second-order many-body perturbation (MC-MP2) method, the long sum-of-product matrix expression of the MP2 energy, whose literal evaluation may be poorly scalable, is recast into a single high-dimensional integral of functions of electron pair coordinates, which is evaluated by the scalable method of Monte Carlo integration. The sampling efficiency is further accelerated by the redundant-walker algorithm, which allows a maximal reuse of electron pairs. Here, a multitude of graphical processing units (GPUs) offers a uniquely ideal platform to expose multilevel parallelism: fine-grain data-parallelism for the redundant-walker algorithm in which millions of threads compute and share orbital amplitudes on each GPU; coarse-grain instruction-parallelism for near-independent Monte Carlo integrations on many GPUs with few and infrequent interprocessor communications. While the efficiency boost by the redundant-walker algorithm on central processing units (CPUs) grows linearly with the number of electron pairs and tends to saturate when the latter exceeds the number of orbitals, on a GPU it grows quadratically before it increases linearly and then eventually saturates at a much larger number of pairs. This is because the orbital constructions are nearly perfectly parallelized on a GPU and thus completed in a near-constant time regardless of the number of pairs. In consequence, an MC-MP2/cc-pVDZ calculation of a benzene dimer is 2700 times faster on 256 GPUs (using 2048 electron pairs) than on two CPUs, each with 8 cores (which can use only up to 256 pairs effectively). We also numerically determine that the cost to achieve a given relative statistical uncertainty in an MC-MP2 energy increases as O(n(3)) or better with system size n, which may be compared with the O(n(5)) scaling of the conventional implementation of deterministic MP2. We thus establish the scalability of MC-MP2 with both system and computer sizes.
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.)
An Unbiased Hessian Representation for Monte Carlo PDFs
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...
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)
Monte Carlo studies of model Langmuir monolayers.
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
Implementation and analysis of an adaptive multilevel Monte Carlo algorithm
Hoel, Hakon
2014-01-01
We present an adaptive multilevel Monte Carlo (MLMC) method for weak approximations of solutions to Itô stochastic dierential equations (SDE). The work [11] proposed and analyzed an MLMC method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a single level Euler-Maruyama Monte Carlo method from O(TOL-3) to O(TOL-2 log(TOL-1)2) for a mean square error of O(TOL2). Later, the work [17] presented an MLMC method using a hierarchy of adaptively re ned, non-uniform time discretizations, and, as such, it may be considered a generalization of the uniform time discretizationMLMC method. This work improves the adaptiveMLMC algorithms presented in [17] and it also provides mathematical analysis of the improved algorithms. In particular, we show that under some assumptions our adaptive MLMC algorithms are asymptotically accurate and essentially have the correct complexity but with improved control of the complexity constant factor in the asymptotic analysis. Numerical tests include one case with singular drift and one with stopped diusion, where the complexity of a uniform single level method is O(TOL-4). For both these cases the results con rm the theory, exhibiting savings in the computational cost for achieving the accuracy O(TOL) from O(TOL-3) for the adaptive single level algorithm to essentially O(TOL-2 log(TOL-1)2) for the adaptive MLMC algorithm. © 2014 by Walter de Gruyter Berlin/Boston 2014.
Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks
Moraes, Alvaro
2015-01-07
Stochastic reaction networks (SRNs) is a class of continuous-time Markov chains intended to describe, from the kinetic point of view, the time-evolution of chemical systems in which molecules of different chemical species undergo a finite set of reaction channels. This talk is based on articles [4, 5, 6], where we are interested in the following problem: given a SRN, X, defined though its set of reaction channels, and its initial state, x0, estimate E (g(X(T))); that is, the expected value of a scalar observable, g, of the process, X, at a fixed time, T. This problem lead us to define a series of Monte Carlo estimators, M, such that, with high probability can produce values close to the quantity of interest, E (g(X(T))). More specifically, given a user-selected tolerance, TOL, and a small confidence level, η, find an estimator, M, based on approximate sampled paths of X, such that, P (|E (g(X(T))) − M| ≤ TOL) ≥ 1 − η; even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.
Monte Carlo study of the isotropic-nematic transition in a fluid of thin hard disk
Frenkel, D.; Eppenga, R.
1982-01-01
The first numerical determination of the thermodynamic isotropic-nematic transition in a simple three-dimensional model fluid, viz., a system of infinitely thin hard platelets, is reported. Thermodynamic properties were studied with use of the constant-pressure Monte Carlo method; Widom's particle-i
Huh, J; Angerman, H.J; ten Brinke, G.
1996-01-01
Symmetric diblock copolymer blends A(f)B(1-f)/A(1-f)B(f) (0 less than or equal to f less than or equal to 0.5) are theoretically discussed in terms of a multiorder parameter approach and numerically investigated by Monte Carlo simulations. Theoretically, our main result is that below f congruent to
ELRADGEN: Monte Carlo generator for radiative events in elastic electron-proton scattering
Afanasiev, A V; Ilyichev, A N; Niczyporuk, B B
2003-01-01
We discuss the theoretical approach and practical algorithms for simulation of radiative events in elastic ep-scattering. A new Monte Carlo generator for real photon emission events in the process of elastic electron-proton scattering is presented. We perform a few consistency checks and present numerical results.
Comparison of the Monte Carlo adjoint-weighted and differential operator perturbation methods
Energy Technology Data Exchange (ETDEWEB)
Kiedrowski, Brian C [Los Alamos National Laboratory; Brown, Forrest B [Los Alamos National Laboratory
2010-01-01
Two perturbation theory methodologies are implemented for k-eigenvalue calculations in the continuous-energy Monte Carlo code, MCNP6. A comparison of the accuracy of these techniques, the differential operator and adjoint-weighted methods, is performed numerically and analytically. Typically, the adjoint-weighted method shows better performance over a larger range; however, there are exceptions.
Monte Carlo simulation - a powerful tool to support experimental activities in structure reliability
Energy Technology Data Exchange (ETDEWEB)
Yuritzinn, T. [CEA Saclay, Dept. de Mecanique et de Technologie (DRN/DMT/SEMT/LISN), 91 - Gif-sur-Yvette (France); Chapuliot, S. [CEA Saclay, Dept. Modelisation de Systemes et Structures (DM2S/SEMT), 91 - Gif sur Yvette (France); Eid, M. [CEA Saclay, Dept. de Mecanique et de Technologie (DRN/DMT/SERMA/LCA), 91 - Gif-sur-Yvette (France); Masson, R.; Dahl, A.; Moinereau, D. [Electricite de France (EDF), 75 - Paris (France)
2003-07-01
Monte-Carlo Simulation (MCS) can have different uses in supporting structure reliability investigations and assessments. In this paper we focus our interest on the use of MCS as a numerical tool to support the fitting of the experimental data related to toughness experiments. (authors)
Hybrid Monte Carlo algorithm for lattice QCD with two flavors of dynamical Ginsparg-Wilson quarks
Liu Chua
1999-01-01
We study aspects concerning numerical simulations of lattice QCD with two flavors of dynamical Ginsparg-Wilson quarks with degenerate masses. A hybrid Monte Carlo algorithm is described and a formula for the fermionic force is derived for two specific implementations. The implementation with the optimal rational approximation method is favored in both CPU time and memory consumption.
Hybrid Monte Carlo algorithm for lattice QCD with two flavors of dynamical Ginsparg-Wilson quarks
Liu, Chuan
1998-01-01
We study aspects concerning numerical simulations of Lattice QCD with two flavors of dynamical Ginsparg-Wilson quarks with degenerate masses. A Hybrid Monte Carlo algorithm is described and the formula for the fermionic force is derived for two specific implementations. The implementation with optimal rational approximation method is favored both in CPU time and memory consumption.
Monte Carlo simulation of SU(2) Yang-Mills theory with light gluinos
Campos, I; Kirchner, R; Luckmann, S; Montvay, István; Münster, G; Spanderen, K; Westphalen, J
1999-01-01
In a numerical Monte Carlo simulation of SU(2) Yang-Mills theory with light dynamical gluinos the low energy features of the dynamics as confinement and bound state mass spectrum are investigated. The motivation is supersymmetry at vanishing gluino mass. The performance of the applied two-step multi-bosonic dynamical fermion algorithm is discussed.
Monte Carlo simulation of SU(2) Yang-Mills theory with light gluinos
Energy Technology Data Exchange (ETDEWEB)
Campos, I.; Kirchner, R.; Montvay, I. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Feo, A.; Luckmann, S.; Muenster, G.; Spanderen, K. [Muenster Univ. (Germany). Inst. fuer Theoretische Physik 1
1999-12-01
In a numerical Monte Carlo simulation of SU(2) Yang-Mills theory with light dynamical gluinos the low energy features of the dynamics as confinement and bound state mass spectrum are investigated. The motivation is supersymmetry at vanishing gluino mass. The performance of the applied two-step multi-bosonic dynamical fermion algorithm is discussed. (orig.)
A variance-reduced electrothermal Monte Carlo method for semiconductor device simulation
Energy Technology Data Exchange (ETDEWEB)
Muscato, Orazio; Di Stefano, Vincenza [Univ. degli Studi di Catania (Italy). Dipt. di Matematica e Informatica; Wagner, Wolfgang [Weierstrass-Institut fuer Angewandte Analysis und Stochastik (WIAS) Leibniz-Institut im Forschungsverbund Berlin e.V., Berlin (Germany)
2012-11-01
This paper is concerned with electron transport and heat generation in semiconductor devices. An improved version of the electrothermal Monte Carlo method is presented. This modification has better approximation properties due to reduced statistical fluctuations. The corresponding transport equations are provided and results of numerical experiments are presented.
Penalized Splines for Smooth Representation of High-dimensional Monte Carlo Datasets
Whitehorn, Nathan; Lafebre, Sven
2013-01-01
Detector response to a high-energy physics process is often estimated by Monte Carlo simulation. For purposes of data analysis, the results of this simulation are typically stored in large multi-dimensional histograms, which can quickly become both too large to easily store and manipulate and numerically problematic due to unfilled bins or interpolation artifacts. We describe here an application of the penalized spline technique to efficiently compute B-spline representations of such tables and discuss aspects of the resulting B-spline fits that simplify many common tasks in handling tabulated Monte Carlo data in high-energy physics analysis, in particular their use in maximum-likelihood fitting.
New simpler method of matching NLO corrections with parton shower Monte Carlo
Jadach, S; Sapeta, S; Siodmok, A; Skrzypek, M
2016-01-01
Next steps in development of the KrkNLO method of implementing NLO QCD corrections to hard processes in parton shower Monte Carlo programs are presented. This new method is a simpler alternative to other well-known approaches, such as MC@NLO and POWHEG. The KrkNLO method owns its simplicity to the use of parton distribution functions (PDFs) in a new, so-called Monte Carlo (MC), factorization scheme which was recently fully defined for the first time. Preliminary numerical results for the Higgs-boson production process are also presented.
A Monte Carlo Synthetic-Acceleration Method for Solving the Thermal Radiation Diffusion Equation
Energy Technology Data Exchange (ETDEWEB)
Evans, Thomas M [ORNL; Mosher, Scott W [ORNL; Slattery, Stuart [University of Wisconsin, Madison
2014-01-01
We present a novel synthetic-acceleration based Monte Carlo method for solving the equilibrium thermal radiation diusion equation in three dimensions. The algorithm performance is compared against traditional solution techniques using a Marshak benchmark problem and a more complex multiple material problem. Our results show that not only can our Monte Carlo method be an eective solver for sparse matrix systems, but also that it performs competitively with deterministic methods including preconditioned Conjugate Gradient while producing numerically identical results. We also discuss various aspects of preconditioning the method and its general applicability to broader classes of problems.
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.
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.
Z_3 Polyakov Loop Models and Inverse Monte-Carlo Methods
Wozar, Christian; Uhlmann, Sebastian; Wipf, Andreas; Heinzl, Thomas
2007-01-01
We study effective Polyakov loop models for SU(3) Yang-Mills theory at finite temperature. A comprehensive mean field analysis of the phase diagram is carried out and compared to the results obtained from Monte-Carlo simulations. We find a rich phase structure including ferromagnetic and antiferromagnetic phases. Due to the presence of a tricritical point the mean field approximation agrees very well with the numerical data. Critical exponents associated with second-order transitions coincide with those of the Z_3 Potts model. Finally, we employ inverse Monte-Carlo methods to determine the effective couplings in order to match the effective models to Yang-Mills theory.
Calibration and Monte Carlo modelling of neutron long counters
Tagziria, H
2000-01-01
The Monte Carlo technique has become a very powerful tool in radiation transport as full advantage is taken of enhanced cross-section data, more powerful computers and statistical techniques, together with better characterisation of neutron and photon source spectra. At the National Physical Laboratory, calculations using the Monte Carlo radiation transport code MCNP-4B have been combined with accurate measurements to characterise two long counters routinely used to standardise monoenergetic neutron fields. New and more accurate response function curves have been produced for both long counters. A novel approach using Monte Carlo methods has been developed, validated and used to model the response function of the counters and determine more accurately their effective centres, which have always been difficult to establish experimentally. Calculations and measurements agree well, especially for the De Pangher long counter for which details of the design and constructional material are well known. The sensitivit...
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.
Properties of Reactive Oxygen Species by Quantum Monte Carlo
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 ...
LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events
Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V
2008-01-01
In this paper we report on LCG Monte Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC collaborations by experts. In many cases, the modern Monte Carlo simulation of physical processes requires expert knowledge in Monte Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project.
The Monte Carlo method in quantum field theory
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.
Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations
Hoogenboom, J. Eduard; Dufek, Jan
2014-06-01
This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.
Monte Carlo 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.
Efficiency of Monte Carlo sampling in chaotic systems.
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.
Sequential Monte Carlo on large binary sampling spaces
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...
Monte Carlo simulation of laser attenuation characteristics in fog
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.
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.
Meaningful timescales from Monte Carlo simulations of molecular systems
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.
Monte Carlo Methods for Tempo Tracking and Rhythm Quantization
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...
Introduction to the variational and diffusion Monte Carlo methods
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.
Monte Carlo Simulation in Statistical Physics An Introduction
Binder, Kurt
2010-01-01
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...
Applicability of Quasi-Monte Carlo for lattice systems
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.
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...
The Specific Bias in Dynamic Monte Carlo Simulations of Nuclear Reactor
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.
Annealing evolutionary stochastic approximation Monte Carlo for global optimization
Liang, Faming
2010-04-08
In this paper, we propose a new algorithm, the so-called annealing evolutionary stochastic approximation Monte Carlo (AESAMC) algorithm as a general optimization technique, and study its convergence. AESAMC possesses a self-adjusting mechanism, whose target distribution can be adapted at each iteration according to the current samples. Thus, AESAMC falls into the class of adaptive Monte Carlo methods. This mechanism also makes AESAMC less trapped by local energy minima than nonadaptive MCMC algorithms. Under mild conditions, we show that AESAMC can converge weakly toward a neighboring set of global minima in the space of energy. AESAMC is tested on multiple optimization problems. The numerical results indicate that AESAMC can potentially outperform simulated annealing, the genetic algorithm, annealing stochastic approximation Monte Carlo, and some other metaheuristics in function optimization. © 2010 Springer Science+Business Media, LLC.
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.
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.
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)
Parton distribution functions in Monte Carlo factorisation scheme
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.
Kinetic Monte Carlo method applied to nucleic acid hairpin folding.
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.
Quasi-Monte Carlo methods for the Heston model
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...
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.
An overview of Monte Carlo treatment planning for radiotherapy.
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.
Applications of quantum Monte Carlo methods in condensed systems
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.
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.
Monte Carlo methods and models in finance and insurance
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
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.
PEPSI — a Monte Carlo generator for polarized leptoproduction
Mankiewicz, L.; Schäfer, A.; Veltri, M.
1992-09-01
We describe PEPSI (Polarized Electron Proton Scattering Interactions), a Monte Carlo program for polarized deep inelastic leptoproduction mediated by electromagnetic interaction, and explain how to use it. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering. The hard virtual gamma-parton scattering is generated according to the polarization-dependent QCD cross-section of the first order in α S. PEPSI requires the standard polarization-independent JETSET routines to simulate the fragmentation into final hadrons.
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.
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.
Novel Quantum Monte Carlo Approaches for Quantum Liquids
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
Monte Carlo simulation of electrons in dense gases
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.
Green's function monte carlo and the many-fermion problem
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.
Cosmological Markov Chain Monte Carlo simulation with Cmbeasy
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.
Monte Carlo model for electron degradation in xenon gas
Mukundan, Vrinda
2016-01-01
We have developed a Monte Carlo model for studying the local degradation of electrons in the energy range 9-10000 eV in xenon gas. Analytically fitted form of electron impact cross sections for elastic and various inelastic processes are fed as input data to the model. Two dimensional numerical yield spectrum, which gives information on the number of energy loss events occurring in a particular energy interval, is obtained as output of the model. Numerical yield spectrum is fitted analytically, thus obtaining analytical yield spectrum. The analytical yield spectrum can be used to calculate electron fluxes, which can be further employed for the calculation of volume production rates. Using yield spectrum, mean energy per ion pair and efficiencies of inelastic processes are calculated. The value for mean energy per ion pair for Xe is 22 eV at 10 keV. Ionization dominates for incident energies greater than 50 eV and is found to have an efficiency of 65% at 10 keV. The efficiency for the excitation process is 30%...
Forward Monte Carlo Computations of Polarized Microwave Radiation
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.
Lattice Monte Carlo simulation of Galilei variant anomalous diffusion
Energy Technology Data Exchange (ETDEWEB)
Guo, Gang, E-mail: hndzgg@aliyun.com [School of Information System and Management, National University of Defense Technology, Changsha, 410073 (China); Institute of Computer Science, University of Rostock, Albert Einstein Str. 22, Rostock, 18059 (Germany); Bittig, Arne, E-mail: arne.bittig@uni-rostock.de [Institute of Computer Science, University of Rostock, Albert Einstein Str. 22, Rostock, 18059 (Germany); Uhrmacher, Adelinde, E-mail: lin@informatik.uni-rostock.de [Institute of Computer Science, University of Rostock, Albert Einstein Str. 22, Rostock, 18059 (Germany)
2015-05-01
The observation of an increasing number of anomalous diffusion phenomena motivates the study to reveal the actual reason for such stochastic processes. When it is difficult to get analytical solutions or necessary to track the trajectory of particles, lattice Monte Carlo (LMC) simulation has been shown to be particularly useful. To develop such an LMC simulation algorithm for the Galilei variant anomalous diffusion, we derive explicit solutions for the conditional and unconditional first passage time (FPT) distributions with double absorbing barriers. According to the theory of random walks on lattices and the FPT distributions, we propose an LMC simulation algorithm and prove that such LMC simulation can reproduce both the mean and the mean square displacement exactly in the long-time limit. However, the error introduced in the second moment of the displacement diverges according to a power law as the simulation time progresses. We give an explicit criterion for choosing a small enough lattice step to limit the error within the specified tolerance. We further validate the LMC simulation algorithm and confirm the theoretical error analysis through numerical simulations. The numerical results agree with our theoretical predictions very well.
A generic algorithm for Monte Carlo simulation of proton transport
Energy Technology Data Exchange (ETDEWEB)
Salvat, Francesc, E-mail: francesc.salvat@ub.edu
2013-12-01
A mixed (class II) algorithm for Monte Carlo simulation of the transport of protons, and other heavy charged particles, in matter is presented. The emphasis is on the electromagnetic interactions (elastic and inelastic collisions) which are simulated using strategies similar to those employed in the electron–photon code PENELOPE. Elastic collisions are described in terms of numerical differential cross sections (DCSs) in the center-of-mass frame, calculated from the eikonal approximation with the Dirac–Hartree–Fock–Slater atomic potential. The polar scattering angle is sampled by employing an adaptive numerical algorithm which allows control of interpolation errors. The energy transferred to the recoiling target atoms (nuclear stopping) is consistently described by transformation to the laboratory frame. Inelastic collisions are simulated from DCSs based on the plane–wave Born approximation (PWBA), making use of the Sternheimer–Liljequist model of the generalized oscillator strength, with parameters adjusted to reproduce (1) the electronic stopping power read from the input file, and (2) the total cross sections for impact ionization of inner subshells. The latter were calculated from the PWBA including screening and Coulomb corrections. This approach provides quite a realistic description of the energy-loss distribution in single collisions, and of the emission of X-rays induced by proton impact. The simulation algorithm can be readily modified to include nuclear reactions, when the corresponding cross sections and emission probabilities are available, and bremsstrahlung emission.
A generic algorithm for Monte Carlo simulation of proton transport
Salvat, Francesc
2013-12-01
A mixed (class II) algorithm for Monte Carlo simulation of the transport of protons, and other heavy charged particles, in matter is presented. The emphasis is on the electromagnetic interactions (elastic and inelastic collisions) which are simulated using strategies similar to those employed in the electron-photon code PENELOPE. Elastic collisions are described in terms of numerical differential cross sections (DCSs) in the center-of-mass frame, calculated from the eikonal approximation with the Dirac-Hartree-Fock-Slater atomic potential. The polar scattering angle is sampled by employing an adaptive numerical algorithm which allows control of interpolation errors. The energy transferred to the recoiling target atoms (nuclear stopping) is consistently described by transformation to the laboratory frame. Inelastic collisions are simulated from DCSs based on the plane-wave Born approximation (PWBA), making use of the Sternheimer-Liljequist model of the generalized oscillator strength, with parameters adjusted to reproduce (1) the electronic stopping power read from the input file, and (2) the total cross sections for impact ionization of inner subshells. The latter were calculated from the PWBA including screening and Coulomb corrections. This approach provides quite a realistic description of the energy-loss distribution in single collisions, and of the emission of X-rays induced by proton impact. The simulation algorithm can be readily modified to include nuclear reactions, when the corresponding cross sections and emission probabilities are available, and bremsstrahlung emission.
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.)
On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations
Bayer, Christian
2014-01-01
We consider the setting of estimating the mean of a random variable by a sequential stopping rule Monte Carlo (MC) method. The performance of a typical second moment based sequential stopping rule MC method is shown to be unreliable in such settings both by numerical examples and through analysis. By analysis and approximations, we construct a higher moment based stopping rule which is shown in numerical examples to perform more reliably and only slightly less efficiently than the second moment based stopping rule.
Effective quantum Monte Carlo algorithm for modeling strongly correlated systems
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
Time management for Monte-Carlo tree search in Go
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
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.
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.
Determining MTF of digital detector system with Monte Carlo simulation
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.
Data libraries as a collaborative tool across Monte Carlo codes
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.
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)
Monte Carlo simulation of quantum statistical lattice models
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
Distributed and Adaptive Darting Monte Carlo through Regenerations
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
A novel Monte Carlo approach to hybrid local volatility models
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.
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.
Monte Carlo Simulation of Partially Confined Flexible Polymers
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
Tackling the premature convergence problem in Monte-Carlo localization
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
Nonequilibrium Candidate Monte Carlo Simulations with Configurational Freezing Schemes.
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.
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.
Multi-microcomputer system for Monte-Carlo calculations
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.
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)
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...
Monte Carlo estimation of the conditional Rasch model
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
Monte Carlo estimation of the conditional Rasch model
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
Nanoporous gold formation by dealloying : A Metropolis Monte Carlo study
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
Quantum Monte Carlo simulation of topological phase transitions
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.
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.
A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods
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
Direct determination of liquid phase coexistence by Monte Carlo simulations
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.
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
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...
Testing Dependent Correlations with Nonoverlapping Variables: A Monte Carlo Simulation
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…
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.
Auxiliary-field quantum Monte Carlo methods in nuclei
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.
Play It Again: Teaching Statistics with Monte Carlo Simulation
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…
Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm
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.
Monte Carlo method for magnetic impurities in metals
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.
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.
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.
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.
Observations on variational and projector Monte Carlo methods.
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.
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.
Quantum Monte Carlo simulation of topological phase transitions
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.
Exploring Mass Perception with Markov Chain Monte Carlo
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…
CMS Monte Carlo production operations in a distributed computing environment
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.
A Variational Monte Carlo Approach to Atomic Structure
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.
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.
The Metropolis Monte Carlo Method in Statistical Physics
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.
Exploring Mass Perception with Markov Chain Monte Carlo
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…
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.
Monte Carlo Simulation of Partially Confined Flexible Polymers
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
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.
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.
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)
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)
Direct aperture optimization for IMRT using Monte Carlo generated beamlets.
Bergman, Alanah M; Bush, Karl; Milette, Marie-Pierre; Popescu, I Antoniu; Otto, Karl; Duzenli, Cheryl
2006-10-01
This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods.
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
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.
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls)
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...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls).xml
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...
Monte Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (Emc2.xls).
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...
Mont Carlo Simulation Program from the World Petroleum Assessment 2000, DDS-60 (emcee.xls)
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...
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.
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.)
Directory of Open Access Journals (Sweden)
Marco eHofmann
2014-12-01
Full Text Available Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over two years. The results showed good agreement of modelled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in soil water holding capacity. The improved model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes.
Hofmann, Marco; Lux, Robert; Schultz, Hans R
2014-01-01
Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively, green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over 2 years. The results showed good agreement of modeled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity (SWC) and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in SWC. The improved model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes.
Hopping electron model with geometrical frustration: kinetic Monte Carlo simulations
Terao, Takamichi
2016-09-01
The hopping electron model on the Kagome lattice was investigated by kinetic Monte Carlo simulations, and the non-equilibrium nature of the system was studied. We have numerically confirmed that aging phenomena are present in the autocorrelation function C ({t,tW )} of the electron system on the Kagome lattice, which is a geometrically frustrated lattice without any disorder. The waiting-time distributions p(τ ) of hopping electrons of the system on Kagome lattice has been also studied. It is confirmed that the profile of p (τ ) obtained at lower temperatures obeys the power-law behavior, which is a characteristic feature of continuous time random walk of electrons. These features were also compared with the characteristics of the Coulomb glass model, used as a model of disordered thin films and doped semiconductors. This work represents an advance in the understanding of the dynamics of geometrically frustrated systems and will serve as a basis for further studies of these physical systems.
Multi-Index Monte Carlo (MIMC) When sparsity meets sampling
Tempone, Raul
2015-01-07
This talk focuses into our newest method: Multi Index Monte Carlo (MIMC). The MIMC method uses a stochastic combination technique to solve the given approximation problem, generalizing the notion of standard MLMC levels into a set of multi indices that should be properly chosen to exploit the available regularity. Indeed, instead of using first-order differences as in standard MLMC, MIMC uses high-order differences to reduce the variance of the hierarchical differences dramatically. This in turn gives a new improved complexity result that increases the domain of the problem parameters for which the method achieves the optimal convergence rate, O(TOL-2). Using optimal index sets that we determined, MIMC achieves a better rate for the computational complexity does not depend on the dimensionality of the underlying problem, up to logarithmic factors. We present numerical results related to a three dimensional PDE with random coefficients to substantiate some of the derived computational complexity rates. Finally, using the Lindeberg-Feller theorem, we also show the asymptotic normality of the statistical error in the MIMC estimator and justify in this way our error estimate that allows prescribing both the required accuracy and confidence in the final result
Thermally activated repolarization of antiferromagnetic particles: Monte Carlo dynamics
Soloviev, S. V.; Popkov, A. F.; Knizhnik, A. A.; Iskandarova, I. M.
2017-02-01
Based on the equation of motion of an antiferromagnetic moment, taking into account a random field of thermal fluctuations, we propose a Monte Carlo (MC) scheme for the numerical simulation of the evolutionary dynamics of an antiferromagnetic particle, corresponding to the Langevin dynamics in the Kramers theory for the two-well potential. Conditions for the selection of the sphere of fluctuations of random deviations of the antiferromagnetic vector at an MC time step are found. A good agreement with the theory of Kramers thermal relaxation is demonstrated for varying temperatures and heights of energy barrier over a wide range of integration time steps in an overdamped regime. Based on the developed scheme, we performed illustrative calculations of the temperature drift of the exchange bias under the fast annealing of a ferromagnet-antiferromagnet structure, taking into account the random variation of anisotropy directions in antiferromagnetic grains and their sizes. The proposed approach offers promise for modeling magnetic sensors and spintronic memory devices containing heterostructures with antiferromagnetic layers.
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.
Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications
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.
The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature
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.
Fast orthogonal transforms for multi-level quasi-Monte Carlo integration
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.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
Ben Issaid, Chaouki
2015-05-12
Experimental design can be vital when experiments are resource-exhaustive and time-consuming. In this work, we carry out experimental design in the Bayesian framework. To measure the amount of information that 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 about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, MLMC 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 MLMC method imposes fewer assumptions, such as the asymptotic concentration of posterior measures, required for instance by the Laplace approximation (LA). We test the MLMC method using two numerical examples. The first example is the design of sensor deployment for a Darcy flow problem governed by a one-dimensional Poisson equation. We place the sensors in the locations where the pressure is measured, and we model the conductivity field as a piecewise constant random vector with two parameters. The second one is chemical Enhanced Oil Recovery (EOR) core flooding experiment assuming homogeneous permeability. We measure the cumulative oil recovery, from a horizontal core flooded by water, surfactant and polymer, for different injection rates. The model parameters consist of the endpoint relative permeabilities, the residual saturations and the relative permeability exponents for the three phases: water, oil and
Multi-index Monte Carlo: when sparsity meets sampling
Haji Ali, Abdul Lateef
2015-06-27
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, we use in MIMC high-order mixed differences instead of using first-order differences as in MLMC to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis and which increase the domain of the problem parameters for which we achieve the optimal convergence, O(TOL−2). Moreover, in MIMC, the rate of increase of required memory with respect to TOL is independent of the number of directions up to a logarithmic term which allows far more accurate solutions to be calculated for higher dimensions than what is possible when using MLMC. We motivate the setting of MIMC by first focusing on a simple full tensor index set. We then propose a systematic construction of optimal sets of indices for MIMC based on properly defined profits that in turn depend on the average cost per sample and the corresponding weak error and variance. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be the total degree type. In some cases, using optimal index sets, MIMC achieves a better rate for the computational complexity than the corresponding rate when using full tensor index sets. We also show the asymptotic normality of the statistical error in the resulting MIMC estimator and justify in this way our error estimate, which allows both the required accuracy and the confidence level in our computational
Monte Carlo Simulation for LINAC Standoff Interrogation of Nuclear Material
Energy Technology Data Exchange (ETDEWEB)
Clarke, Shaun D [ORNL; Flaska, Marek [ORNL; Miller, Thomas Martin [ORNL; Protopopescu, Vladimir A [ORNL; Pozzi, Sara A [ORNL
2007-06-01
The development of new techniques for the interrogation of shielded nuclear materials relies on the use of Monte Carlo codes to accurately simulate the entire system, including the interrogation source, the fissile target and the detection environment. The objective of this modeling effort is to develop analysis tools and methods-based on a relevant scenario-which may be applied to the design of future systems for active interrogation at a standoff. For the specific scenario considered here, the analysis will focus on providing the information needed to determine the type and optimum position of the detectors. This report describes the results of simulations for a detection system employing gamma rays to interrogate fissile and nonfissile targets. The simulations were performed using specialized versions of the codes MCNPX and MCNP-PoliMi. Both prompt neutron and gamma ray and delayed neutron fluxes have been mapped in three dimensions. The time dependence of the prompt neutrons in the system has also been characterized For this particular scenario, the flux maps generated with the Monte Carlo model indicate that the detectors should be placed approximately 50 cm behind the exit of the accelerator, 40 cm away from the vehicle, and 150 cm above the ground. This position minimizes the number of neutrons coming from the accelerator structure and also receives the maximum flux of prompt neutrons coming from the source. The lead shielding around the accelerator minimizes the gamma-ray background from the accelerator in this area. The number of delayed neutrons emitted from the target is approximately seven orders of magnitude less than the prompt neutrons emitted from the system. Therefore, in order to possibly detect the delayed neutrons, the detectors should be active only after all prompt neutrons have scattered out of the system. Preliminary results have shown this time to be greater than 5 ?s after the accelerator pulse. This type of system is illustrative of a
Poster — Thur Eve — 14: Improving Tissue Segmentation for Monte Carlo Dose Calculation using DECT
Energy Technology Data Exchange (ETDEWEB)
Di Salvio, A.; Bedwani, S.; Carrier, J-F. [Centre hospitalier de l' Université de Montréal (Canada); Bouchard, H. [National Physics Laboratory, Teddington (United Kingdom)
2014-08-15
Purpose: To improve Monte Carlo dose calculation accuracy through a new tissue segmentation technique with dual energy CT (DECT). Methods: Electron density (ED) and effective atomic number (EAN) can be extracted directly from DECT data with a stoichiometric calibration method. Images are acquired with Monte Carlo CT projections using the user code egs-cbct and reconstructed using an FDK backprojection algorithm. Calibration is performed using projections of a numerical RMI phantom. A weighted parameter algorithm then uses both EAN and ED to assign materials to voxels from DECT simulated images. This new method is compared to a standard tissue characterization from single energy CT (SECT) data using a segmented calibrated Hounsfield unit (HU) to ED curve. Both methods are compared to the reference numerical head phantom. Monte Carlo simulations on uniform phantoms of different tissues using dosxyz-nrc show discrepancies in depth-dose distributions. Results: Both SECT and DECT segmentation methods show similar performance assigning soft tissues. Performance is however improved with DECT in regions with higher density, such as bones, where it assigns materials correctly 8% more often than segmentation with SECT, considering the same set of tissues and simulated clinical CT images, i.e. including noise and reconstruction artifacts. Furthermore, Monte Carlo results indicate that kV photon beam depth-dose distributions can double between two tissues of density higher than muscle. Conclusions: A direct acquisition of ED and the added information of EAN with DECT data improves tissue segmentation and increases the accuracy of Monte Carlo dose calculation in kV photon beams.
Collision of Physics and Software in the Monte Carlo Application Toolkit (MCATK)
Energy Technology Data Exchange (ETDEWEB)
Sweezy, Jeremy Ed [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-01-21
The topic is presented in a series of slides organized as follows: MCATK overview, development strategy, available algorithms, problem modeling (sources, geometry, data, tallies), parallelism, miscellaneous tools/features, example MCATK application, recent areas of research, and summary and future work. MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library with continuous energy neutron and photon transport. Designed to build specialized applications and to provide new functionality in existing general-purpose Monte Carlo codes like MCNP, it reads ACE formatted nuclear data generated by NJOY. The motivation behind MCATK was to reduce costs. MCATK physics involves continuous energy neutron & gamma transport with multi-temperature treatment, static eigenvalue (k_{eff} and α) algorithms, time-dependent algorithm, and fission chain algorithms. MCATK geometry includes mesh geometries and solid body geometries. MCATK provides verified, unit-test Monte Carlo components, flexibility in Monte Carlo application development, and numerous tools such as geometry and cross section plotters.
Quantum-trajectory Monte Carlo method for study of electron-crystal interaction in STEM.
Ruan, Z; Zeng, R G; Ming, Y; Zhang, M; Da, B; Mao, S F; Ding, Z J
2015-07-21
In this paper, a novel quantum-trajectory Monte Carlo simulation method is developed to study electron beam interaction with a crystalline solid for application to electron microscopy and spectroscopy. The method combines the Bohmian quantum trajectory method, which treats electron elastic scattering and diffraction in a crystal, with a Monte Carlo sampling of electron inelastic scattering events along quantum trajectory paths. We study in this work the electron scattering and secondary electron generation process in crystals for a focused incident electron beam, leading to understanding of the imaging mechanism behind the atomic resolution secondary electron image that has been recently achieved in experiment with a scanning transmission electron microscope. According to this method, the Bohmian quantum trajectories have been calculated at first through a wave function obtained via a numerical solution of the time-dependent Schrödinger equation with a multislice method. The impact parameter-dependent inner-shell excitation cross section then enables the Monte Carlo sampling of ionization events produced by incident electron trajectories travelling along atom columns for excitation of high energy knock-on secondary electrons. Following cascade production, transportation and emission processes of true secondary electrons of very low energies are traced by a conventional Monte Carlo simulation method to present image signals. Comparison of the simulated image for a Si(110) crystal with the experimental image indicates that the dominant mechanism of atomic resolution of secondary electron image is the inner-shell ionization events generated by a high-energy electron beam.
Monte Carlo simulation for kinetic chemotaxis model: An application to the traveling population wave
Yasuda, Shugo
2017-02-01
A Monte Carlo simulation of chemotactic bacteria is developed on the basis of the kinetic model and is applied to a one-dimensional traveling population wave in a microchannel. In this simulation, the Monte Carlo method, which calculates the run-and-tumble motions of bacteria, is coupled with a finite volume method to calculate the macroscopic transport of the chemical cues in the environment. The simulation method can successfully reproduce the traveling population wave of bacteria that was observed experimentally and reveal the microscopic dynamics of bacterium coupled with the macroscopic transports of the chemical cues and bacteria population density. The results obtained by the Monte Carlo method are also compared with the asymptotic solution derived from the kinetic chemotaxis equation in the continuum limit, where the Knudsen number, which is defined by the ratio of the mean free path of bacterium to the characteristic length of the system, vanishes. The validity of the Monte Carlo method in the asymptotic behaviors for small Knudsen numbers is numerically verified.
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
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)
JEWEL - a Monte Carlo Model for Jet Quenching
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...
Applying polynomial filtering to mass preconditioned Hybrid Monte Carlo
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.
Monte Carlo uncertainty analyses for integral beryllium experiments
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.
Kinetic Monte Carlo Studies of Hydrogen Abstraction from Graphite
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...
Minimising biases in full configuration interaction quantum Monte Carlo
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.
Sign problem and Monte Carlo calculations beyond Lefschetz thimbles
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.
Minimising biases in full configuration interaction quantum Monte Carlo.
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.
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...
Monte Carlo Study of Real Time Dynamics on the Lattice
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.
Fixed-Node Diffusion Monte Carlo of Lithium Systems
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.
Monte Carlo Methods in ICF (LIRPP Vol. 13)
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.
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.
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.
Adaptive Monte Carlo on multivariate binary sampling spaces
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...
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.
Quantum Monte Carlo calculations with chiral effective field theory interactions.
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.
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.
Monte Carlo methods for light propagation in biological tissues.
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.
Monte Carlo simulation of quantum Zeno effect in the brain
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 ...
Monte Carlo Simulations of Neutron Oil well Logging Tools
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