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1

Development and validation of MCNP4C-based Monte Carlo simulator for fan- and cone-beam x-ray CT

An x-ray computed tomography (CT) simulator based on the Monte Carlo N-particle radiation transport computer code (MCNP4C) was developed for simulation of both fan- and cone-beam CT scanners. A user-friendly interface running under Matlab 6.5.1 creates the scanner geometry at different views as MCNP4C's input file. The full simulation of x-ray tube, phantom and detectors with single-slice, multi-slice and flat

Mohammad Reza Ay; Habib Zaidi

2005-01-01

2

NEPHTIS: 2D/3D validation elements using MCNP4c and TRIPOLI4 Monte-Carlo codes

High Temperature Reactors (HTRs) appear as a promising concept for the next generation of nuclear power applications. The CEA, in collaboration with AREVA-NP and EDF, is developing a core modeling tool dedicated to the prismatic block-type reactor. NEPHTIS (Neutronics Process for HTR Innovating System) is a deterministic codes system based on a standard two-steps Transport-Diffusion approach (APOLLO2/CRONOS2). Validation of such deterministic schemes usually relies on Monte-Carlo (MC) codes used as a reference. However, when dealing with large HTR cores the fission source stabilization is rather poor with MC codes. In spite of this, it is shown in this paper that MC simulations may be used as a reference for a wide range of configurations. The first part of the paper is devoted to 2D and 3D MC calculations of a HTR core with control devices. Comparisons between MCNP4c and TRIPOLI4 MC codes are performed and show very consistent results. Finally, the last part of the paper is devoted to the code to code validation of the NEPHTIS deterministic scheme. (authors)

Courau, T.; Girardi, E. [EDF R and D/SINETICS, 1av du General de Gaulle, F92141 Clamart CEDEX (France); Damian, F.; Moiron-Groizard, M. [DEN/DM2S/SERMA/LCA, CEA Saclay, F91191 Gif-sur-Yvette CEDEX (France)

2006-07-01

3

NASA Astrophysics Data System (ADS)

The use of low-energy photon emitters for brachytherapy applications, as in the treatment of the prostate or of eye tumours, has drastically increased in the last few years. New seed models for 103Pd and 125I have recently been introduced. The American Association of Physicists in Medicine recommends that measurements are made to obtain the dose rate constant, the radial dose function and the anisotropy function. These results must then be compared with Monte Carlo calculations to finally obtain the dosimetric parameters in liquid water. We have used the results obtained during the characterization of the new InterSource (furnished by IBt, Seneffe, Belgium) palladium and iodine sources to compare two Monte Carlo codes against experiment for these low energies. The measurements have been performed in three different media: two solid water plastics, WT1 and RW1, and polymethylmetacrylate. The Monte Carlo calculations were made using two different codes: MCNP4C and EGSnrc. These codes use photon cross-section data of a different origin. Differences were observed between both sets of input data below 100 keV, especially for the photoelectric effect. We obtained differences in the radial dose functions calculated with each code, which can be explained by the difference between the input data. New cross-section data were then tested for both codes. The agreement between the calculations using these new libraries is excellent. The differences are within the statistical uncertainties of the calculations. These results were compared with the experimental data. A good agreement is reached for both isotopes and in the three phantoms when the measured values are corrected for the presence of the TLDs in the phantom.

Reniers, B.; Verhaegen, F.; Vynckier, S.

2004-04-01

4

Calculation of the store house worker dose in a lost wax foundry using MCNP-4C.

Lost wax casting is an industrial process which permits the transmutation into metal of models made in wax. The wax model is covered with a silicaceous shell of the required thickness and once this shell is built the set is heated and wax melted. Liquid metal is then cast into the shell replacing the wax. When the metal is cool, the shell is broken away in order to recover the metallic piece. In this process zircon sands are used for the preparation of the silicaceous shell. These sands have varying concentrations of natural radionuclides: 238U, 232Th and 235U together with their progenics. The zircon sand is distributed in bags of 50 kg, and 30 bags are on a pallet, weighing 1,500 kg. The pallets with the bags have dimensions 80 cm x 120 cm x 80 cm, and constitute the radiation source in this case. The only pathway of exposure to workers in the store house is external radiation. In this case there is no dust because the bags are closed and covered by plastic, the store house has a good ventilation rate and so radon accumulation is not possible. The workers do not touch with their hands the bags and consequently skin contamination will not take place. In this study all situations of external irradiation to the workers have been considered; transportation of the pallets from vehicle to store house, lifting the pallets to the shelf, resting of the stock on the shelf, getting down the pallets, and carrying the pallets to production area. Using MCNP-4C exposure situations have been simulated, considering that the source has a homogeneous composition, the minimum stock in the store house is constituted by 7 pallets, and the several distances between pallets and workers when they are at work. The photons flux obtained by MCNP-4C is multiplied by the conversion factor of Flux to Kerma for air by conversion factor to Effective Dose by Kerma unit, and by the number of emitted photons. Those conversion factors are obtained of ICRP 74 table 1 and table 17 respectively. This is the way to obtain a function giving dose rate around the source. PMID:16604600

Alegría, Natalia; Legarda, Fernando; Herranz, Margarita; Idoeta, Raquel

2005-01-01

5

Monte Carlo methods Sequential Monte Carlo

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

Doucet, Arnaud

6

Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods

Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods Christian P. Robert Universit Monte Carlo Methods Textbook: Monte Carlo Statistical Methods by Christian. P. Robert and George Casella Monte Carlo Methods with R by Christian. P. Robert and George Casella [trad. franÂ¸caise 2010; japonaise

Robert, Christian P.

7

Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods

Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods Christian P. Robert Universit Monte Carlo Methods Outline Motivation and leading example Random variable generation Monte Carlo for variable dimension problems Sequential importance sampling #12;Markov Chain Monte Carlo Methods New [2004

Robert, Christian P.

8

Monte Carlo methods Rmi Bardenet

Monte Carlo methods RÃ©mi Bardenet 1 Department of Statistics, Oxford University Abstract. Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among

Boyer, Edmond

9

Advanced Monte Carlo Methods: Quasi-Monte Carlo

Advanced Monte Carlo Methods: Quasi-Monte Carlo Prof. Mike Giles mike.giles@maths.ox.ac.uk Oxford University Mathematical Institute QMC Â p. 1 #12;Quasi Monte Carlo low discrepancy sequences Koksma Â p. 2 #12;Quasi Monte Carlo Standard Monte Carlo approximates high-dimensional hypercube integral [0

Giles, Mike

10

Secondproofs Monte Carlo and Quasi-Monte Carlo Methods 2008

Secondproofs Monte Carlo and Quasi-Monte Carlo Methods 2008 #12;Secondproofs #12;Secondproofs Pierre L'Ecuyer r Art B. Owen Editors Monte Carlo and Quasi-Monte Carlo Methods 2008 #12;Secondproofs, CA 94305 USA owen@stanford.edu ISBN 978-3-642-04106-8 DOI 10.1007/978-3-642-04107-5 e-ISBN978

L'Ecuyer, Pierre

11

Monte Carlo methods Monte Carlo Principle and MCMC

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

Doucet, Arnaud

12

We shall present here the motivation and a general description of a method dealing with a class of problems in mathematical physics. The method is, essentially, a statistical approach to the study of differential equations, or more generally, of integro-differential equations that occur in various branches of the natural sciences.

S. Ulam

1949-01-01

13

THE MONTE CARLO METHOD I. INTRODUCTION

THE MONTE CARLO METHOD I. INTRODUCTION The Monte Carlo method is often referred to as a `computer physics. The purpose of this note is partly to emphasize some of the mathematical rigor behind Monte Carlo complicated for analytic techniques. With all that said, it is still useful to pursue the `Monte Carlo

California at Davis, University of

14

Monte Carlo Methods for Inference and Learning

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

Hinton, Geoffrey E.

15

The radial depth-dose distribution of a prototype 188W/188Re beta particle line source of known activity has been measured in a PMMA phantom, using a novel, ultra-thin type of LiF:Mg,Cu,P thermoluminescent detector (TLD). The measured radial dose function of this intravascular brachytherapy source agrees well with MCNP4C Monte Carlo simulations, which indicate that 188Re accounts for > or = 99% of the dose between 1 mm and 5 mm radial distance from the source axis. The TLDs were calibrated using a 90Sr/90Y beta secondary standard. Several correction factors are calculated using analytical and Monte Carlo methods. An analysis of the measurement uncertainty is made. Since it is partly determined by components of uncertainty arising from random effects, repeated measurements yield a lower uncertainty. The expanded uncertainty in the absolute dose at 2 mm radial distance equals 11%, 10%, 9% and 8% for 1, 2, 3 and 5 measurements, respectively. After a correction for source non-uniformity, the measured dose rate per unit source activity at 2 mm radial distance equals (1.53 +/- 0.16) Gy min(-1) GBq(-1) (2sigma), in agreement with the value of (1.45 +/- 0.01) Gy min(-1) GBq(-1) (2sigma) predicted by the MCNP4C simulations. PMID:12433123

Schaart, Dennis R; Bos, Adrie J J; Winkelman, August J M; Clarijs, Martijn C

2002-10-21

16

Monte Carlo Methods Geoff Gordon

Monte Carlo Methods Geoff Gordon ggordon@cs.cmu.edu February 9, 2006 #12;Numerical integration(-T(x)) As , have ExP (x) x Simulated annealing: track E(x) = xP(x)dx as #12;Used for: Bayes net inference Undirected Bayes net on x = x1, x2, . . .: P(x) = 1 Z j j(x) Typical inference problem: compute E(xi) Belief

Guestrin, Carlos

17

On Monte Carlo methods for Bayesian inference

Bayesian methods are experiencing increased use for probabilistic ecological modelling. Most Bayesian inference requires the numerical approximation of analytically intractable integrals. Two methods based on Monte Carlo simulation have appeared in the ecological\\/environmental modelling literature. Though they sound similar, the Bayesian Monte Carlo (BMC) and Markov Chain Monte Carlo (MCMC) methods are very different in their efficiency and effectiveness in

Song S. Qian; Craig A. Stow; Mark E. Borsuky

2003-01-01

18

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

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

Robert, Christian P.

19

NASA Astrophysics Data System (ADS)

The neutron transport code, Monte Carlo N-Particle (MCNP) which was wellkown as the gold standard in predicting nuclear reaction was used to model the small nuclear reactor core called "U-batteryTM", which was develop by the University of Manchester and Delft Institute of Technology. The paper introduces on the concept of modeling the small reactor core, a high temperature reactor (HTR) type with small coated TRISO fuel particle in graphite matrix using the MCNPv4C software. The criticality of the core were calculated using the software and analysed by changing key parameters such coolant type, fuel type and enrichment levels, cladding materials, and control rod type. The criticality results from the simulation were validated using the SCALE 5.1 software by [1] M Ding and J L Kloosterman, 2010. The data produced from these analyses would be used as part of the process of proposing initial core layout and a provisional list of materials for newly design reactor core. In the future, the criticality study would be continued with different core configurations and geometries.

Pauzi, A. M.

2013-06-01

20

Monte Carlo Methods in Statistics Christian Robert

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

Boyer, Edmond

21

MONTE CARLO METHOD AND SENSITIVITY ESTIMATIONS

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

Dufresne, Jean-Louis

22

What Monte Carlo methods cannot do

Although extremely flexible and obviously useful for many risk assessment problems, Monte Carlo methods have four significant limitations that risk analysts should keep in mind. (1) Like most methods based on probability theory, Monte Carlo methods are data?intensive. Consequently, they usually cannot produce results unless a considerable body of empirical information has been collected, or unless the analyst is willing

Scott Ferson

1996-01-01

23

MCM for PDEs Monte Carlo Methods for

MCM for PDEs Monte Carlo Methods for Partial Differential Equations Prof. Michael Mascagni University, Tallahassee, FL 32306 USA E-mail: mascagni@fsu.edu or mascagni@math.ethz.ch URL: http-Diffusion Equations Monte Carlo Methods for PDEs from Fluid Mechanics Probabilistic Representations for Other PDEs

Mascagni, Michael

24

Monte Carlo methods for security pricing

The Monte Carlo approach has proved to be a valuable and flexible computational tool in modern finance. This paper discusses some of the recent applications of the Monte Carlo method to security pricing problems, with emphasis on improvements in efficiency. We first review some variance reduction methods that have proved useful in finance. Then we describe the use of deterministic

Phelim Boyle; Mark Broadie; Paul Glasserman

1997-01-01

25

Current advances in Monte Carlo methods

In this review paper, we outline the principles of Monte Carlo simulation of fluid mixtures, with emphasis on methods for calculation of free energies and phase equilibria. We begin with a brief introduction to common intermolecular potential models. We discuss density-dependent potentials that can accurately represent properties over a wide range of densities. A number of Monte Carlo techniques are

Athanassios Z. Panagiotopoulos

1996-01-01

26

Multigrid Monte Carlo method. Conceptual foundations

We present details of a stochastic generalization of the multigrid method, called multigrid Monte Carlo (MGMC), that reduces critical slowing down in Monte Carlo computations of lattice field theories. For Gaussian (free) fields, critical slowing down is completely eliminated. For a phi4 model, numerical experiments show a factor of ~=10 reduction, over a standard heat-bath algorithm, in the CPU time

Jonathan Goodman; Alan D. Sokal

1989-01-01

27

Monte Carlo Methods in Geophysical Inverse Problems

Monte Carlo inversion techniques were first used by Earthscientists more than 30 years ago. Since that time they havebeen applied to a wide range of problems, from the inversion offree oscillation data for whole Earth seismic structure tostudies at the meter-scale lengths encountered in explorationseismology. This paper traces the development and application ofMonte Carlo methods for inverse problems in the

Malcolm Sambridge; Klaus Mosegaard

2002-01-01

28

Renormalization Group by Monte Carlo Methods

I discuss the basic ideas in applying the Monte Carlo methods to the renormalization-group study of static and dynamic critical phenomena within the framework of a kinetic Ising model. Simple calculations demonstrating these ideas are presented.

Shang-Keng Ma

1976-01-01

29

Advanced Monte Carlo Methods: General Principles of the Monte

Advanced Monte Carlo Methods: General Principles of the Monte Carlo Method Prof. Dr. Michael of Monte CarloProf. Dr. Michael Mascagni: Advanced Monte Carlo Methods Slide 2 of 61 Numerical Integration: The Canonical Monte Carlo Application Numerical integration is a simple problem to explain and thoroughly

Mascagni, Michael

30

Markov Chain Monte Carlo Linkage Analysis Methods

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

Robert P. Igo; Yuqun Luo; Shili Lin

31

Monte Carlo Methods for Dose Calculations

NASA Astrophysics Data System (ADS)

Monte Carlo (MC) methods are increasingly being used at ion beam therapy (IBT) centers to support various dosimetric aspects of treatment planning, from characterization of the beam delivery to forward recalculation of treatment plans. This chapter will review the basic principles of Monte Carlo methods for dose calculations in therapy with protons and heavier ions, discussing the roadmap for clinical application and ongoing investigations at different IBT centers.

Parodi, Katia

32

MONTE CARLO METHODS IN GEOPHYSICAL INVERSE Malcolm Sambridge

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

Sambridge, Malcolm

33

Monte Carlo Methods for Statistical Inference

\\u000a Monte Carlo methods are experiments. Monte Carlo experimentation is the use of simulated random numbers to estimate some functional of a probability distribution.\\u000a A problem that does not have a stochastic component can sometimes be posed as a problem with a component that can be identified\\u000a with an expectation of some function of a random variable. This is often done

James E. Gentle

34

Monte Carlo-based method to determine the strength of a neutron source

NASA Astrophysics Data System (ADS)

The utilization of a gamma-ray spectrometer with a 7.62 ×7.62 cm NaI(Tl) detector, with a spherical moderator, has been studied with the aim to measure the neutron fluence rate and to determine the neutron source strength. Moderators with a large amount of hydrogen are able to slowdown and thermalize neutrons; once thermalized, there is a probability for thermal neutrons to be captured by hydrogen, producing 2.22 MeV gamma rays. The pulse-height spectrum collected in a multichannel analyzer shows a photopeak around 2.22 MeV whose net area is proportional to total neutron fluence rate and to the neutron source strength. The characteristics of this system were determined by a Monte Carlo study using the MCNP 4C code, where a detailed model of the NaI(Tl) was utilized. Spheres of diameters 3, 5, and 10 inch were used as moderators, and the response was calculated for monoenergetic and isotopic neutrons sources.

Vega-Carrillo, H. R.; Manzanares-Acu?a, E.; Hern&Ández-D&Ávila, V. M.; Chacón-Ruíz, A.; Mercado, G. A.; Gallego, E.; Lorente, A.

35

The Monte Carlo Method and Software Reliability Theory

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

Pratt, Vaughan

36

Monte Carlo methods for fissured porous media: gridless approaches

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

Paris-Sud XI, UniversitÃ© de

37

Convergence of Sequential Monte Carlo Methods

Bayesian estimation problems where the posterior distribution evolves over time through the accumulationof data arise in many applications in statistics and related fields. Recently, a large number of algorithmsand applications based on sequential Monte Carlo methods (also known as particle filtering methods) haveappeared in the literature to solve this class of problems; see (Doucet, de Freitas & Gordon, 2001) for

Dan Crisan; Arnaud Doucet

2000-01-01

38

Sequential Monte Carlo Methods for Dynamic Systems

We provide a general framework for using Monte Carlo methods in dynamic systems and discuss its wide applications. Under this framework, several currently available techniques are studied and generalized to accommodate more complex features. All of these methods are partial combinations of three ingredients: importance sampling and resampling, rejection sampling, and Markov chain iterations. We provide guidelines on how they

Jun S. Liu; Rong Chen

1998-01-01

39

Exploring Probability and the Monte Carlo Method

NSDL National Science Digital Library

This multimedia mathematics resource examines probability. A video illustrates how math is used to evaluate the danger of avalanches in the mountains of Alberta. An interactive component allows students to compare theoretical and experimental probabilities, as well as explore the Monte Carlo method. A probability print activity is also included.

2003-01-01

40

Monte Carlo method in optical radiometry

State-of-the-art in the application of the Monte Carlo method (MCM) to the computational problems of optical radiometry is discussed. The MCM offers a universal technique for radiation transfer modelling based on the stochastic approach. Developments of the original MCM algorithms and software for calculation of effective emissivities of black bodies, absorption characteristics of cavity radiometers and photometric properties of integrating

A. V. Prokhorov

1998-01-01

41

Monte Carlo Methods in Lattice Gauge Theories

In this work, we study various Monte Carlo methods for lattice gauge theories. The mass of the 0('+) glueball for SU(2) gauge theory in 4 dimensions is calculated. This computation was done on a prototype parallel processor and the implementation of gauge theories on this system is described in detail. Using an action of the purely Wilson form (trace of

Steve William Otto

1983-01-01

42

Dosimetry of gamma chamber blood irradiator using PAGAT gel dosimeter and Monte Carlo simulations.

Currently, the use of blood irradiation for inactivating pathogenic microbes in infected blood products and preventing graft-versus-host disease (GVHD) in immune suppressed patients is greater than ever before. In these systems, dose distribution and uniformity are two important concepts that should be checked. In this study, dosimetry of the gamma chamber blood irradiator model Gammacell 3000 Elan was performed by several dosimeter methods including thermoluminescence dosimeters (TLD), PAGAT gel dosimetry, and Monte Carlo simulations using MCNP4C code. The gel dosimeter was put inside a glass phantom and the TL dosimeters were placed on its surface, and the phantom was then irradiated for 5 min and 27 sec. The dose values at each point inside the vials were obtained from the magnetic resonance imaging of the phantom. For Monte Carlo simulations, all components of the irradiator were simulated and the dose values in a fine cubical lattice were calculated using tally F6. This study shows that PAGAT gel dosimetry results are in close agreement with the results of TL dosimetry, Monte Carlo simulations, and the results given by the vendor, and the percentage difference between the different methods is less than 4% at different points inside the phantom. According to the results obtained in this study, PAGAT gel dosimetry is a reliable method for dosimetry of the blood irradiator. The major advantage of this kind of dosimetry is that it is capable of 3D dose calculation. PMID:24423829

Mohammadyari, Parvin; Zehtabian, Mehdi; Sina, Sedigheh; Tavasoli, Ali Reza; Faghihi, Reza

2014-01-01

43

A Monte Carlo method for solving unsteady adjoint equations

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

Wang, Qiqi

44

A Hybrid Monte Carlo Method for Accurate and Efficient

A Hybrid Monte Carlo Method for Accurate and Efficient Subsurface Scattering Li, Pellacini #12;Previous work Â· Accurate for all materials, but inefficient Â Monte Carlo path/light tracing Â· Accurate and Efficient for all materials Â As accurate as Monte Carlo Â More efficient than Monte Carlo

Pellacini, Fabio

45

Extended state-space Monte Carlo methods.

In this paper various extensions of the parallel-tempering algorithm are developed and their properties are analyzed. The algorithms are designed to alleviate quasiergodic sampling in systems which have rough energy landscapes by coupling individual Monte Carlo chains to form a composite chain. As with parallel tempering, the procedures are based upon extending the state space to include parameters to encourage sampling mobility. One of the drawbacks of the parallel-tempering method is the stochastic nature of the Monte Carlo dynamics in the auxiliary variables which extend the state space. In this work, the possibility of improving the sampling rate by designing deterministic methods of moving through the parameter space is investigated. The methods developed in this article, which are based upon a statistical quenching and heating procedure similar in spirit to simulated annealing, are tested on a simple two-dimensional spin system (xy model) and on a model in vacuo polypeptide system. In the coupled Monte Carlo chain algorithms, we find that the net mobility of the composite chain is determined by the competition between the characteristic time of coupling between adjacent chains and the degree of overlap of their distributions. Extensive studies of all methods are carried out to obtain optimal sampling conditions. In particular, the most efficient parallel-tempering procedure is to attempt to swap configurations after very few Monte Carlo updates of the composite chains. Furthermore, it is demonstrated that, contrary to expectations, the deterministic procedure does not improve the sampling rate over that of parallel tempering. PMID:11415039

Opps, S B; Schofield, J

2001-05-01

46

Monte Carlo methods beyond detailed balance

NASA Astrophysics Data System (ADS)

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 detailed balance. This approach is first applied to a very simple model, which shows the basic viability of the method. Then we apply it to the Ising model, where we find that the method is an improvement compared to the standard Metropolis algorithm, be it with a modest gain of a factor 2.3.

Schram, Raoul D.; Barkema, Gerard T.

2015-01-01

47

Sequential Monte Carlo Methods Nando De Freitas & Arnaud Doucet

Sequential Monte Carlo Methods Nando De Freitas & Arnaud Doucet UBC Nando De Freitas & Arnaud Doucet UBC ( ) Sequential Monte Carlo Methods 1 / 39 #12;State-Space Models fXk gk 1 hidden X -valued ( ) Sequential Monte Carlo Methods 2 / 39 #12;State-Space Models fXk gk 1 hidden X -valued Markov process with X1

Doucet, Arnaud

48

Introduction to the Diffusion Monte Carlo Method

A self-contained and tutorial presentation of the diffusion Monte Carlo method for determining the ground state energy and wave function of quantum systems is provided. First, the theoretical basis of the method is derived and then a numerical algorithm is formulated. The algorithm is applied to determine the ground state of the harmonic oscillator, the Morse oscillator, the hydrogen atom, and the electronic ground state of the H2+ ion and of the H2 molecule. A computer program on which the sample calculations are based is available upon request.

Ioan Kosztin; Byron Faber; Klaus Schulten

1997-02-20

49

The Moment Guided Monte Carlo Method

In this work we propose a new approach for the numerical simulation of kinetic equations through Monte Carlo schemes. We introduce a new technique which permits to reduce the variance of particle methods through a matching with a set of suitable macroscopic moment equations. In order to guarantee that the moment equations provide the correct solutions, they are coupled to the kinetic equation through a non equilibrium term. The basic idea, on which the method relies, consists in guiding the particle positions and velocities through moment equations so that the concurrent solution of the moment and kinetic models furnishes the same macroscopic quantities.

Pierre Degond; Giacomo Dimarco; Lorenzo Pareschi

2009-08-03

50

Quasi-Monte Carlo and Monte Carlo Methods and their Application in Finance

We give an introduction to and a survey on the use of Quasi-Monte Carlo and of Monte Carlo methods especially in option pricing and in risk man- agement. We concentrate on new techniques from the Quasi-Monte Carlo theory.

G. Larcherand; G. Leobacher

51

An introduction to Monte Carlo methods

NASA Astrophysics Data System (ADS)

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.

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

2015-01-01

52

We review two types of adaptive Monte Carlo methods for rare event simulations. These methods are based on importance sampling. The first approach selects importance sampling distributions by minimizing the variance of importance sampling estimator. The second approach selects importance sampling distributions by minimizing the cross entropy to the optimal importance sampling distribution. We also review the basic concepts of

Ming-hua Hsieh

2002-01-01

53

Simulated Annealing: A Monte Carlo Method for GPS Surveying

annealing technique,which is a Monte Carlo method, to analyze and improve the e#ciency of the deÂ signSimulated Annealing: A Monte Carlo Method for GPS Surveying Stefka Fidanova IPP -- BAS, Acad. G that uses a Monte Carlo global minimization technique for minimizing multiÂvariance functions [2

Fidanova, Stefka

54

Monte Carlo Methods: A Computational Pattern for Our Pattern Language

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

California at Berkeley, University of

55

MONTE CARLO METHODS IN GEOPHYSICAL INVERSE Malcolm Sambridge

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

Sambridge, Malcolm

56

MONTE CARLO ANALYSIS: ESTIMATING GPP WITH THE CANOPY CONDUCTANCE METHOD

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

DeLucia, Evan H.

57

Monte Carlo methods for design and analysis of radiation detectors

An overview of Monte Carlo as a practical method for designing and analyzing radiation detectors is provided. The emphasis is on detectors for radiation that is either directly or indirectly ionizing. This overview paper reviews some of the fundamental aspects of Monte Carlo, briefly addresses simulation of radiation transport by the Monte Carlo method, discusses the differences between direct and

William L. Dunn; J. Kenneth Shultis

2009-01-01

58

A Comparison of Monte-Carlo Methods for Phantom Go

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

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

59

Quantum Monte Carlo methods for nuclear physics

Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states and transition moments in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.

J. Carlson; S. Gandolfi; F. Pederiva; Steven C. Pieper; R. Schiavilla; K. E. Schmidt; R. B. Wiringa

2014-12-09

60

Methods for Monte Carlo simulations of biomacromolecules

The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies. PMID:20428473

Vitalis, Andreas; Pappu, Rohit V.

2010-01-01

61

Monte Carlo methods in an introductory electromagnetic course

Although the pedagogical value of introducing numerical methods such as finite-element methods, finite-difference methods, and moment methods in an introductory electromagnetics (EM) course has been recognized, no similar attempt has been made to introduce Monte Carlo methods. An attempt is made to fill this gap by presenting Monte Carlo procedures in simple terms that can be presented in an introductory

M. N. O. Sadiku

1990-01-01

62

Low energy photon dosimetry using Monte Carlo and convolution methods

Low energy photon dosimetry was investigated using Monte Carlo and convolution methods. Photon energy deposition kernels describing the three dimensional distribution of energy deposition about a primary photon interaction site were computed using EGS4 Monte Carlo. These photon energy deposition kernels were utilized as the convolution kernel in convolution\\/superposition dose calculations. A Monte Carlo bench mark describing the energy deposition

Joseph Michael Modrick

2000-01-01

63

Improved method for implicit Monte Carlo

The Implicit Monte Carlo (IMC) method has been used for over 30 years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Reference [2] provided an exact error analysis of IMC for 0-D problems and demonstrated that IMC can exhibit substantial errors when timesteps are large. These temporal errors are inherent in the method and are in addition to spatial discretization errors and approximations that address nonlinearities (due to variation of physical constants). In Reference [3], IMC and four other methods were analyzed in detail and compared on both theoretical grounds and the accuracy of numerical tests. As discussed in, two alternative schemes for solving the radiative transfer equations, the Carter-Forest (C-F) method and the Ahrens-Larsen (A-L) method, do not exhibit the errors found in IMC; for 0-D, both of these methods are exact for all time, while for 3-D, A-L is exact for all time and C-F is exact within a timestep. These methods can yield substantially superior results to IMC.

Brown, F. B. (Forrest B.); Martin, W. R. (William R.)

2001-01-01

64

Monte Carlo methods for TMD analyses

NASA Astrophysics Data System (ADS)

Monte Carlo simulations are an indispensable tool in experimental high-energy physics. Indeed, many discoveries rely on realistic modeling of background processes. In the field of transverse-momentum-dependent parton distribution and fragmentation functions there is a clear lack of a reliable Monte Carlo physics generator that can be used in experimental and phenomenological analyses. The need for such Monte Carlo generators, the status of some solutions and prospects are discussed.

Schnell, Gunar

2015-01-01

65

Recent Advances in Randomized Quasi-Monte Carlo Methods

We survey some of the recent developments on quasi-Monte Carlo (QMC) methods, which, in their basic form, are a deterministic counterpart to the Monte Carlo (MC) method. Our main focus is the applicability of these methods to practical problems that involve the estimation of a high-dimensional integral. We review several QMC constructions and different randomizations that have been proposed to

Pierre L’Ecuyer; Christiane Lemieux

66

4 Monte Carlo Methods in Classical Statistical Physics

4 Monte Carlo Methods in Classical Statistical Physics Wolfhard Janke Institut fÂ¨ur Theoretische update algorithms (Metropolis, heat-bath, Glauber). Then methods for the statistical analysis of the thus Carlo Methods in Classical Statistical Physics, Lect. Notes Phys. 739, 79Â140 (2008) DOI 10

Janke, Wolfhard

67

A Monte Carlo method for thermal building simulation

A simplified Monte Carlo method for finding an approximation of the building inside temperature distribution is given. Present simulation techniques are either over-simplified and use only a deterministic method, or are highly complex stochastic models. The new method consists of a Monte Carlo approach to find typical input distributions, used in conjunction with a more traditional deterministic building thermal simulation

J. Haarhoff; E. H. Mathews

2006-01-01

68

Radiative heat transfer with quasi-monte carlo methods

Monte Carlo simulation is often used to solve radiative transfer problems wherecomplex physical phenomena and geometries must be handled. Slow convergenceis a well known disadvantage of such methods. In this paper we demonstratethat a significant improvement in computation time can be achieved by usingQuasi-Monte Carlo methods to simulate Rapid Thermal Processing, which is animportant technique for the production of semiconductor

A. Kersch; W. Morokoff; A. Schuster

1994-01-01

69

Quasi-Monte Carlo Methods in Numerical Finance

This paper introduces and illustrates a new version of the Monte Carlo method that has attractive properties for the numerical valuation of derivatives. The traditional Monte Carlo method has proven to be a powerful and flexible tool for many types of derivatives calculations. Under the conventional approach pseudo-random numbers are used to evaluate the expression of interest. Unfortunately, the use

Corwin Joy; Phelim P. Boyle; Ken Seng Tan

1996-01-01

70

Monte Carlo N-Particle version 4C (MCNP4C) was used to simulate photon interactions associated with in vivo x-ray fluorescence (XRF) measurement of stable lead in bone. Experimental measurements, performed using a cylindrical anthropometric phantom (i.e., surrogate) of the human leg made from tissue substitutes for muscle and bone, revealed a significant difference between the intensity of the observed and predicted coherent backscatter peak. The observed difference was due to the failure of MCNP4C to simulate photon scatter associated with greater than six inverse angstroms of momentum transfer. The MCNP4C source code, photon directory, and photon library were modified to incorporate atomic form factors up to 7.1 inverse angstroms for the high Z elements defined in the K XRF simulation. The intensity of the predicted coherent photon backscatter peak at 88 keV using the modified code increased from 3.50 x 10(-9) to 8.59 x 10(-7) (roughly two orders of magnitude) and compares favorably with the experimental measurements. PMID:18469585

Lodwick, Camille J; Spitz, Henry B

2008-06-01

71

Time Series Simulation with Quasi Monte Carlo Methods

This paper compares quasi Monte Carlo methods, in particularso-called (t, m, s)-nets, with classical Monte Carlo approaches forsimulating econometric time-series models. Quasi Monte Carlomethods have found successful application in many fields, such asphysics, image processing, and the evaluation of financederivatives. However, they are rarely used in econometrics. Here,we apply both traditional and quasi Monte Carlo simulation methodsto time-series models that

Jenny X. Li; Peter Winker

2003-01-01

72

Monte Carlo Method for Multiple Knapsack Stefka Fidanova

Monte Carlo Method for Multiple Knapsack Problem Stefka Fidanova CLPP { BAS, Acad. G. Bonchev str. bl.25A, 1113 So#12;a, Bulgaria fidanova@parallel.bas.bg Abstract. This paper describes Monte Carlo) procedure which can be coupled with the ACO algorithm to improve the eÃ?ciency of the solving of the MKP

Fidanova, Stefka

73

Quantum Monte Carlo Method for Attractive Coulomb Potentials

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

J. S. Kole; H. De Raedt

2001-02-06

74

Extended state-space Monte Carlo methods

In this paper various extensions of the parallel-tempering algorithm are developed and their properties are analyzed. The algorithms are designed to alleviate quasiergodic sampling in systems which have rough energy landscapes by coupling individual Monte Carlo chains to form a composite chain. As with parallel tempering, the procedures are based upon extending the state space to include parameters to encourage

Sheldon B. Opps; Jeremy Schofield

2001-01-01

75

Calculating Air Resistance using the Monte Carlo Method

NSDL National Science Digital Library

Students will discover the terminal velocity to mass relationship and use this information to calculate the air resistance constant. They will evaluate the accuracy of their lab using the Monte Carlo method.

76

An assessment of the MCNP4C weight window

A new, enhanced weight window generator suite has been developed for MCNP version 4C. The new generator correctly estimates importances in either a user-specified, geometry-independent, orthogonal grid or in MCNP geometric cells. The geometry-independent option alleviates the need to subdivide the MCNP cell geometry for variance reduction purposes. In addition, the new suite corrects several pathologies in the existing MCNP weight window generator. The new generator is applied in a set of five variance reduction problems. The improved generator is compared with the weight window generator applied in MCNP4B. The benefits of the new methodology are highlighted, along with a description of its limitations. The authors also provide recommendations for utilization of the weight window generator.

Christopher N. Culbertson; John S. Hendricks

1999-12-01

77

Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms

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

Alan D. Sokal

1996-01-01

78

Perturbation Monte Carlo methods for tissue structure alterations

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

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

2013-01-01

79

A hybrid Monte Carlo and response matrix Monte Carlo method in criticality calculation

Full core calculations are very useful and important in reactor physics analysis, especially in computing the full core power distributions, optimizing the refueling strategies and analyzing the depletion of fuels. To reduce the computing time and accelerate the convergence, a method named Response Matrix Monte Carlo (RMMC) method based on analog Monte Carlo simulation was used to calculate the fixed source neutron transport problems in repeated structures. To make more accurate calculations, we put forward the RMMC method based on non-analog Monte Carlo simulation and investigate the way to use RMMC method in criticality calculations. Then a new hybrid RMMC and MC (RMMC+MC) method is put forward to solve the criticality problems with combined repeated and flexible geometries. This new RMMC+MC method, having the advantages of both MC method and RMMC method, can not only increase the efficiency of calculations, also simulate more complex geometries rather than repeated structures. Several 1-D numerical problems are constructed to test the new RMMC and RMMC+MC method. The results show that RMMC method and RMMC+MC method can efficiently reduce the computing time and variations in the calculations. Finally, the future research directions are mentioned and discussed at the end of this paper to make RMMC method and RMMC+MC method more powerful. (authors)

Li, Z.; Wang, K. [Dept. of Engineering Physics, Tsinghua Univ., Beijing, 100084 (China)

2012-07-01

80

Combinatorial nuclear level density by a Monte Carlo method

We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states, and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations.

N. Cerf

1993-09-14

81

Study of the Transition Flow Regime using Monte Carlo Methods

NASA Technical Reports Server (NTRS)

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.

Hassan, H. A.

1999-01-01

82

Successful combination of the stochastic linearization and Monte Carlo methods

NASA Technical Reports Server (NTRS)

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

Elishakoff, I.; Colombi, P.

1993-01-01

83

In this study the commissioning of a dose calculation algorithm in a currently used treatment planning system was performed and the calculation accuracy of two available methods in the treatment planning system i.e., collapsed cone convolution (CCC) and equivalent tissue air ratio (ETAR) was verified in tissue heterogeneities. For this purpose an inhomogeneous phantom (IMRT thorax phantom) was used and dose curves obtained by the TPS (treatment planning system) were compared with experimental measurements and Monte Carlo (MCNP code) simulation. Dose measurements were performed by using EDR2 radiographic films within the phantom. Dose difference (DD) between experimental results and two calculation methods was obtained. Results indicate maximum difference of 12% in the lung and 3% in the bone tissue of the phantom between two methods and the CCC algorithm shows more accurate depth dose curves in tissue heterogeneities. Simulation results show the accurate dose estimation by MCNP4C in soft tissue region of the phantom and also better results than ETAR method in bone and lung tissues. PMID:22973081

Moradi, Farhad; Mahdavi, Seyed Rabi; Mostaar, Ahmad; Motamedi, Mohsen

2012-01-01

84

The Monte Carlo method in quantum field theory

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

Colin Morningstar

2007-02-20

85

A Multivariate Time Series Method for Monte Carlo Reactor Analysis

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

Taro Ueki

2008-08-14

86

American Option Pricing on Reconfigurable Hardware Using Least-Squares Monte Carlo Method

American Option Pricing on Reconfigurable Hardware Using Least-Squares Monte Carlo Method Xiang using the simple Monte Carlo method. A number of extended Monte Carlo methods have been published, the Quasi-Monte Carlo method is adopted for stock price paths generation. Our real FPGA hardware

Arslan, Tughrul

87

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

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.

2002-01-01

88

On Monte Carlo methods for estimating ratios of normalizing constants

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

Ming-Hui Chen; Qi-Man Shao

1997-01-01

89

The Coupled Electronic-Ionic Monte Carlo Simulation Method

NASA Astrophysics Data System (ADS)

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have developed to perform QMC for the electrons coupled to another MC simulation for the ions. In this method, one estimates the Born-Oppenheimer energy E(Z) where Z represents the ionic degrees of freedom. That estimate of the energy is used in a Metropolis simulation of the ionic degrees of freedom. Important aspects of this method are how to deal with the noise, which QMC method and which trial function to use, how to deal with generalized boundary conditions on the wave function so as to reduce the finite size effects. We discuss some advantages of the CEIMC method concerning how the quantum effects of the ionic degrees of freedom can be included and how the boundary conditions can be integrated over. Using these methods, we have performed simulations of liquid H2 and metallic H on a parallel computer.

Ceperley, David; Dewing, Mark; Pierleoni, Carlo

90

Sequential Monte Carlo Methods for Statistical Analysis of Tables

We describe a sequential importance sampling (SIS) procedure for analyzing two-way zero-one or contingency tables with fixed marginal sums. An essential feature of the new method is that it samples the columns of the table progressively according to certain special distri- butions. Our method produces Monte Carlo samples that are remarkably close to the uniform distribution, enabling one to approximate

Yuguo CHEN; Susan P. HOLMES; Jun S. LIU

2003-01-01

91

Multiple-time-stepping generalized hybrid Monte Carlo methods

NASA Astrophysics Data System (ADS)

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.

Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.

2015-01-01

92

Monte Carlo Form-Finding Method for Tensegrity Structures

NASA Astrophysics Data System (ADS)

In this paper, we propose a Monte Carlo-based approach to solve tensegrity form-finding problems. It uses a stochastic procedure to find the deterministic equilibrium configuration of a tensegrity structure. The suggested Monte Carlo form-finding (MCFF) method is highly efficient because it does not involve complicated matrix operations and symmetry analysis and it works for arbitrary initial configurations. Both regular and non-regular tensegrity problems of large scale can be solved. Some representative examples are presented to demonstrate the efficiency and accuracy of this versatile method.

Li, Yue; Feng, Xi-Qiao; Cao, Yan-Ping

2010-05-01

93

NASA Astrophysics Data System (ADS)

Monte Carlo method was used to predict the incident radiative heat fluxes on the freeboard walls of the METU 0.3 MWt atmospheric bubbling fluidized bed combustor based on the data reported previously. The freeboard was treated as a rectangular enclosure with gray interior walls and gray, absorbing, emitting and isotropically scattering medium. A Monte Carlo solver was developed and the performance of the solver was assessed by comparing its predictions with those of method of lines solution of discrete ordinates method and experimental measurements reported previously. Parametric studies were carried out to examine the effects of particle load and anisotropic scattering on the predicted incident radiative heat fluxes. The comparisons show that Monte Carlo method reproduces the measured incident radiative heat fluxes reasonably well for the freeboard problem.

Demirkaya, Gokmen; Arinç, Faruk; Selçuk, Nevin; Ayranci, Isil

2005-06-01

94

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

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

Paris-Sud XI, UniversitÃ© de

95

1. Area: Monte Carlo Methods [up to 2 projects available] Proposer: Geoff Nicholls

1. Area: Monte Carlo Methods [up to 2 projects available] Proposer: Geoff Nicholls This is a project on Monte-Carlo methods. It can be treated as a project in Applied Probability (the approach taken developments in Monte Carlo Methods themselves, or in applications of Monte Carlo in Applied probability

Goldschmidt, Christina

96

A Quantum Monte Carlo Method at Fixed Energy

In this paper we explore new ways to study the zero temperature limit of quantum statistical mechanics using Quantum Monte Carlo simulations. We develop a Quantum Monte Carlo method in which one fixes the ground state energy as a parameter. The Hamiltonians we consider are of the form $H=H_{0}+\\lambda V$ with ground state energy E. For fixed $H_{0}$ and V, one can view E as a function of $\\lambda$ whereas we view $\\lambda$ as a function of E. We fix E and define a path integral Quantum Monte Carlo method in which a path makes no reference to the times (discrete or continuous) at which transitions occur between states. For fixed E we can determine $\\lambda(E)$ and other ground state properties of H.

Edward Farhi; Jeffrey Goldstone; David Gosset; Harvey B. Meyer

2009-12-21

97

Monte Carlo methods: a computational pattern for our pattern language

The Monte Carlo methods are an important set of algorithms in computer science. They involve estimating results by statistically sampling a parameter space with a thousands to millions of experiments. The algorithm requires a small set of parameters as input, with which it generates a large amount of computation, and outputs a concise set of aggregated results. The large amount

Jike Chong; Ekaterina Gonina; Kurt Keutzer

2010-01-01

98

Monte Carlo Method to Solve Multidimensional Bioheat Transfer Problem

The Monte Carlo method is implemented to solve the direct bioheat transfer problems, which are often encountered in the treatment planning of cancer hyperthermia. Several algorithms were developed to solve for the temperature transients inside the biological bodies with various time or space-dependent boundary conditions, blood perfusion, meta- bolic rate, and volumetric heat source for the tissues. The computer code

Zhong-Shan Deng; Jing Liu

2002-01-01

99

Markov chain Monte Carlo method and its application

Summary. The Markov chain Monte Carlo (MCMC) method, as a computer-intensive statistical tool, has enjoyed an enormous upsurge in interest over the last few years. This paper provides a simple, comprehensive and tutorial review of some of the most common areas of research in this field. We begin by discussing how MCMC algorithms can be constructed from standard building- blocks

Stephen P. Brooks

1998-01-01

100

A direct simulation Monte-Carlo method for cluster coagulation

The study presents a method for analyzing cluster coagulation which relies on a Monte Carlo analysis of individual particles as they interact and form clusters from a homogeneous, monodisperse medium. Four case studies are shown, three of which compare the results of the code to the known analytic solutions of the Smoluchowski equation, and the fourth considers the cluster size

Kurt Liffman

1992-01-01

101

Systolic Matrix Inversion Using a Monte Carlo Method

A systolic array for inverting an n × n matrix using a Monte Carlo method is proposed. The basic array computes a single row of the inverse in 3n + N + T steps ( including input and output time) and O( nNT) cells where N is the number of chains and T is the length of each chain in

Graham M. Megson; V. N. Aleksandrov; I. T. Dimov

1994-01-01

102

A Monte Carlo method for high dimensional integration

Summary A new method for the numerical integration of very high dimensional functions is introduced and implemented based on the Metropolis' Monte Carlo algorithm. The logarithm of the high dimensional integral is reduced to a 1-dimensional integration of a certain statistical function with respect to a scale parameter over the range of the unit interval. The improvement in accuracy is

Yosihiko Ogata

1989-01-01

103

Calculation of canopy bidirectional reflectance using the Monte Carlo method

For a calculation of the plant canopy bidirectional reflectance distribution function (BRDF) the Monte Carlo method is used. The plant architecture is given by a rather universal mathematical model which allows to consider such structural parameters as canopy density and height, the number of leaves per plant, distance between leaves, dimensions and orientations of leaves and stems, etc., and their

J. K. ROSS; A. L. MARSHAK

1988-01-01

104

Multicanonical multigrid Monte Carlo method and effective autocorellation time

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

W. Janke; T. Sauer

1993-12-09

105

Efficient Evaluation of System Reliability by Monte Carlo Method

This paper presents a new Monte Carlo method to estimate the reliability of a large complex system represented by a reliability block diagram or by a fault tree. Two binary functions are introduced; one dominates the system structure function and the other is dominated by the structure function. These functions can be constructed easily by using part of path sets

Hiromitsu Kumamoto; Kazuo Tanaka; Koichi Inoue

1977-01-01

106

On the Gap-Tooth direct simulation Monte Carlo method

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

Armour, Jessica D

2012-01-01

107

Structure From Motion Using Sequential Monte Carlo Methods

In this papel; the structure from motion (SfM) problem is addressed using sequential Monte Carlo methods. A new Sfn algorithm based on random sampling is derived to esti- mate the posterior distributions of camera motion and scene structure for the perspective projection camera model. Ex- perimental results show that challenging issues in solving the structure from motion problem including errors

Gang Qian; Rama Chellappa

2001-01-01

108

Markov Chain Monte Carlo Methods in Biostatistics Andrew Gelman

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

Gelman, Andrew

109

Bayesian spectral deconvolution with the exchange Monte Carlo method.

An analytical method to deconvolute spectral data into a number of simple bands is extremely important in the analysis of the chemical properties of matter. However, there are two fundamental problems with such deconvolution methods. One is how to determine the number of bands without resorting to heuristics. The other is difficulty in avoiding the parameter solution trapped into local minima due to the hierarchy and the nonlinearity of the system. In this study, we propose a novel method of spectral deconvolution based on Bayesian estimation with the exchange Monte Carlo method, which is an application of the integral approximation of stochastic complexity and the exchange Monte Carlo method. We also experimentally show its effectiveness on synthetic data and on reflectance spectral data of olivine, one of the most common minerals of terrestrial planets. PMID:22226618

Nagata, Kenji; Sugita, Seiji; Okada, Masato

2012-04-01

110

A separable shadow Hamiltonian hybrid Monte Carlo method

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

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

2009-01-01

111

Uncertainties in external dosimetry: analytical vs. Monte Carlo method.

Over the years, the International Commission on Radiological Protection (ICRP) and other organisations have formulated recommendations regarding uncertainty in occupational dosimetry. The most practical and widely accepted recommendations are the trumpet curves. To check whether routine dosemeters comply with them, a Technical Report on uncertainties issued by the International Electrotechnical Commission (IEC) can be used. In this report, the analytical method is applied to assess the uncertainty of a dosemeter fulfilling an IEC standard. On the other hand, the Monte Carlo method can be used to assess the uncertainty. In this work, a direct comparison of the analytical and the Monte Carlo methods is performed using the same input data. It turns out that the analytical method generally overestimates the uncertainty by about 10-30 %. Therefore, the results often do not comply with the recommendations of the ICRP regarding uncertainty. The results of the more realistic uncertainty evaluation using the Monte Carlo method usually comply with the recommendations of the ICRP. This is confirmed by results seen in regular tests in Germany. PMID:19942627

Behrens, R

2010-03-01

112

Quasi-Monte Carlo Methods in Robust Control Peter F. Hokayem, Chaouki T. Abdallah

Quasi-Monte Carlo Methods in Robust Control Design Peter F. Hokayem, Chaouki T. Abdallah , Peter the quasi-Monte Carlo methods of sampling to generate deterministic samples adequately dispersed, deterministic or quasi-Monte Carlo methods have proven superior to random methods in several applications

113

Extending Monte Carlo Methods to Factor Graphs with Negative and Complex Factors

Extending Monte Carlo Methods to Factor Graphs with Negative and Complex Factors Mehdi Molkaraie graph can some- times be accurately estimated by Monte Carlo methods. In this paper, such methods mass function p(x) = f(x) Zf (2) is the basis of a variety of Monte Carlo methods for esti- mating (1

Loeliger, Hans-Andrea

114

Blind Data Detection in the Presence of PLL Phase Noise by Sequential Monte Carlo Method

Blind Data Detection in the Presence of PLL Phase Noise by Sequential Monte Carlo Method Erdal Abstract-- In this paper, based on a sequential Monte Carlo method, a computationally efficient algorithm

Noels, Nele

115

Applications of Monte Carlo methods to statistical physics

An introductory review of the Monte Carlo method for the statistical mechanics of condensed matter systems is given. Basic principles (random number generation, simple sampling versus importance sampling, Markov chains and master equations, etc) are explained and some classical applications (self-avoiding walks, percolation, the Ising model) are sketched. The finite-size scaling analysis of both second- and first-order phase transitions is

K. Binder

1997-01-01

116

Structure from Motion Using Sequential Monte Carlo Methods

In this paper, the structure from motion (SfM) problem is addressed using sequential Monte Carlo methods. A new SfM algorithm based on random sampling is derived to estimate the posterior distributions of camera motion and scene structure for the perspective projection camera model. Experimental results show that challenging issues in solving the SfM problem, due to erroneous feature tracking, feature

Gang Qian; Rama Chellappa

2004-01-01

117

Mathematical foundations of the Markov chain Monte Carlo method

7.2 was jointly undertaken with Vivek Gore, andis published here for the first time.I also thank an anonymous referee for carefully reading and providinghelpful comments on a draft of this chapter.1. IntroductionThe classical Monte Carlo method is an approach to estimating quantitiesthat are hard to compute exactly. The quantity z of interest is expressed as theexpectation z = ExpZ of

Mark Jerrum

1998-01-01

118

Statistical error of reactor calculations by the Monte Carlo method

Algorithms for calculating the statistical error with allowance for intergenerational correlations are described. The algorithms are constructed on the basis of statistical analysis of the results of computations by the Monte Carlo method. As a result, simple rules for choosing the parameters of the computational techniques, such as the number of simulated generations necessary for attaining the required accuracy and the number of first skipped generations, are elaborated.

Kalugin, M. A.; Oleynik, D. S.; Sukhino-Khomenko, E. A., E-mail: sukhino-khomenko@adis.vver.kiae.ru [Russian Research Centre Kurchatov Institute (Russian Federation)

2011-12-15

119

Monte Carlo Methods and Applications for the Nuclear Shell Model

The shell-model Monte Carlo (SMMC) technique transforms the traditional nuclear shell-model problem into a path-integral over auxiliary fields. We describe below the method and its applications to four physics issues: calculations of sd-pf-shell nuclei, a discussion of electron-capture rates in pf-shell nuclei, exploration of pairing correlations in unstable nuclei, and level densities in rare earth systems.

Dean, D.J.; White, J.A.

1998-08-10

120

Monte Carlo Methods for Uncertainty Quantification Mathematical Institute, University of Oxford

(Oxford) Monte Carlo methods May 30Â31, 2013 7 / 37 #12;Stratified Sampling The key idea is to achieve Carlo methods May 30Â31, 2013 8 / 37 #12;Stratified Sampling Define Uij to be the value of ith sample (Oxford) Monte Carlo methods May 30Â31, 2013 9 / 37 #12;Stratified Sampling With stratified sampling, E

Giles, Mike

121

A path integral Monte Carlo method for Rényi entanglement entropies

We introduce a quantum Monte Carlo algorithm to measure the R\\'enyi entanglement entropies in systems of interacting bosons in the continuum. This approach is based on a path integral ground state method that can be applied to interacting itinerant bosons in any spatial dimension with direct relevance to experimental systems of quantum fluids. We demonstrate how it may be used to compute spatial mode entanglement, particle partitioned entanglement, and the entanglement of particles, providing insights into quantum correlations generated by fluctuations, indistinguishability and interactions. We present proof-of-principle calculations, and benchmark against an exactly soluble model of interacting bosons in one spatial dimension. As this algorithm retains the fundamental polynomial scaling of quantum Monte Carlo when applied to sign-problem-free models, future applications should allow for the study of entanglement entropy in large scale many-body systems of interacting bosons.

C. M. Herdman; Stephen Inglis; P. -N. Roy; R. G. Melko; A. Del Maestro

2014-04-28

122

Density of States Monte Carlo Method for Simulation of Fluids

A Monte Carlo method based on a density-of-states sampling is proposed for study of arbitrary statistical mechanical ensembles in a continuum. A random walk in the two-dimensional space of particle number and energy is used to estimate the density of states of the system; this density of states is continuously updated as the random walk visits individual states. The validity and usefulness of the method are demonstrated by applying it to the simulation of a Lennard-Jones fluid. Results for its thermodynamic properties, including the vapor-liquid phase coexistence curve, are shown to be in good agreement with high-accuracy literature data.

Qiliang Yan; Roland Faller; Juan J. de Pablo

2002-01-25

123

Monte Carlo N-particle simulation of neutron-based sterilisation of anthrax contamination

Objective To simulate the neutron-based sterilisation of anthrax contamination by Monte Carlo N-particle (MCNP) 4C code. Methods Neutrons are elementary particles that have no charge. They are 20 times more effective than electrons or ?-rays in killing anthrax spores on surfaces and inside closed containers. Neutrons emitted from a 252Cf neutron source are in the 100 keV to 2 MeV energy range. A 2.5 MeV D–D neutron generator can create neutrons at up to 1013 n s?1 with current technology. All these enable an effective and low-cost method of killing anthrax spores. Results There is no effect on neutron energy deposition on the anthrax sample when using a reflector that is thicker than its saturation thickness. Among all three reflecting materials tested in the MCNP simulation, paraffin is the best because it has the thinnest saturation thickness and is easy to machine. The MCNP radiation dose and fluence simulation calculation also showed that the MCNP-simulated neutron fluence that is needed to kill the anthrax spores agrees with previous analytical estimations very well. Conclusion The MCNP simulation indicates that a 10 min neutron irradiation from a 0.5 g 252Cf neutron source or a 1 min neutron irradiation from a 2.5 MeV D–D neutron generator may kill all anthrax spores in a sample. This is a promising result because a 2.5 MeV D–D neutron generator output >1013 n s?1 should be attainable in the near future. This indicates that we could use a D–D neutron generator to sterilise anthrax contamination within several seconds. PMID:22573293

Liu, B; Xu, J; Liu, T; Ouyang, X

2012-01-01

124

Improved criticality convergence via a modified Monte Carlo iteration method

Nuclear criticality calculations with Monte Carlo codes are normally done using a power iteration method to obtain the dominant eigenfunction and eigenvalue. In the last few years it has been shown that the power iteration method can be modified to obtain the first two eigenfunctions. This modified power iteration method directly subtracts out the second eigenfunction and thus only powers out the third and higher eigenfunctions. The result is a convergence rate to the dominant eigenfunction being |k{sub 3}|/k{sub 1} instead of |k{sub 2}|/k{sub 1}. One difficulty is that the second eigenfunction contains particles of both positive and negative weights that must sum somehow to maintain the second eigenfunction. Summing negative and positive weights can be done using point detector mechanics, but this sometimes can be quite slow. We show that an approximate cancellation scheme is sufficient to accelerate the convergence to the dominant eigenfunction. A second difficulty is that for some problems the Monte Carlo implementation of the modified power method has some stability problems. We also show that a simple method deals with this in an effective, but ad hoc manner.

Booth, Thomas E [Los Alamos National Laboratory; Gubernatis, James E [Los Alamos National Laboratory

2009-01-01

125

A simple eigenfunction convergence acceleration method for Monte Carlo

Monte Carlo transport codes typically use a power iteration method to obtain the fundamental eigenfunction. The standard convergence rate for the power iteration method is the ratio of the first two eigenvalues, that is, k{sub 2}/k{sub 1}. Modifications to the power method have accelerated the convergence by explicitly calculating the subdominant eigenfunctions as well as the fundamental. Calculating the subdominant eigenfunctions requires using particles of negative and positive weights and appropriately canceling the negative and positive weight particles. Incorporating both negative weights and a {+-} weight cancellation requires a significant change to current transport codes. This paper presents an alternative convergence acceleration method that does not require modifying the transport codes to deal with the problems associated with tracking and cancelling particles of {+-} weights. Instead, only positive weights are used in the acceleration method.

Booth, Thomas E [Los Alamos National Laboratory

2010-11-18

126

Comparison of vectorization methods used in a Monte Carlo code

This paper examines vectorization methods used in Monte Carlo codes for particle transport calculations. Event and zone selection methods developed from conventional all-zone and one-zone algorithms have been implemented in a general-purpose vectorized code, GMVP. Moreover, a vectorization procedure to treat multiple-lattice geometry has been developed using these methods. Use of lattice geometry can reduce the computation cost for a typical pressurized water reactor fuel subassembly calculation, especially when the zone selection method is used. Sample calculations for external and fission source problems are used to compare the performances of both methods with the results of conventional scalar codes. Though the speedup resulting from vectorization depends on the problem solved, a factor of 7 to 10 is obtained for practical problems on the FACOM VP-100 computer compared with the conventional scalar code, MORSE-CG.

Nakagawa, M.; Mori, T.; Sasaki, M. (Japan Atomic Energy Research Inst., Tokai Establishment Tokai-mura, Ibaraki-ken 319-11 (JP))

1991-01-01

127

ANALYSE DE SENSIBILITE : COMPARAISON ENTRE LES PLANS D'EXPERIENCES ET LA METHODE MONTE CARLO

ANALYSE DE SENSIBILITE : COMPARAISON ENTRE LES PLANS D'EXPERIENCES ET LA METHODE MONTE CARLO uncertain input and the output: Monte Carlo based method and experimental design in the field prÃ©sentÃ©es et les rÃ©sultats obtenus sont comparÃ©s Ã ceux issus de la mÃ©thode Monte Carlo. Abstract We compare

Paris-Sud XI, UniversitÃ© de

128

Limit theorems for weighted samples with applications to sequential Monte Carlo methods

In the last decade, sequential Monte Carlo methods (SMC) emerged as a key tool in computational statistics [see, e.g., Sequential Monte Carlo Methods in Practice (2001) Springer, New York, Monte Carlo Strategies in Scientific Computing (2001) Springer, New York, Complex Stochastic Systems (2001) 109–173]. These algorithms approximate a sequence of distributions by a sequence of weighted empirical measures associated to

Randal Douc; Eric Moulines

2008-01-01

129

Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference

The term “sequential Monte Carlo methods” or, equivalently, “particle filters,” refers to a general class of iterative algorithms that performs Monte Carlo approximations of a given sequence of distributions of interest (?_{t<\\/sub>). We establish in this paper a central limit theorem for the Monte Carlo estimates produced by these computational methods. This result holds under minimal assumptions on the distributions}

Nicolas Chopin

2004-01-01

130

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

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

Shimkin, Nahum

131

Monte Carlo methods designed for parallel computation Sheldon B. Opps and Jeremy Scho eld

Monte Carlo methods designed for parallel computation Sheldon B. Opps and Jeremy Scho#12;eld of these methods is that individual Monte Carlo chains, which are run on a separate nodes, are coupled together- rate calculation, for example to improve the statistics of a Monte Carlo simulation, one inherent bene

Schofield, Jeremy

132

Monte-Carlo valorisation of American options: facts and new algorithms to improve existing methods

Monte-Carlo valorisation of American options: facts and new algorithms to improve existing methods is to discuss efficient algorithms for the pricing of American options by two recently proposed Monte-Carlo type the quantization approach, are performed. Key words: American Options, Monte Carlo methods. 1. Introduction

Boyer, Edmond

133

Monte Carlo Methods for Exact & Efficient Solution of the Generalized Optimality Equations

Monte Carlo Methods for Exact & Efficient Solution of the Generalized Optimality Equations Pedro A to the complexity of planning. In this paper, we introduce Monte Carlo methods to solve the generalized optimality of Monte Carlo proposals. In particular, it is seen that the number of proposals is essentially independent

134

Monte Carlo Methods for Pricing and Hedging American Options in High Dimension

Monte Carlo Methods for Pricing and Hedging American Options in High Dimension Lucia Caramellino1.zanette@uniud.it Summary. We numerically compare some recent Monte Carlo algorithms devoted to the pricing and hedging with respect to other Monte Carlo methods in terms of computing time. Here, we propose to suitably combine

Caramellino, Lucia

135

A Quasi-Monte Carlo Method for Integration with Improved Convergence

A Quasi-Monte Carlo Method for Integration with Improved Convergence Aneta Karaivanova, Ivan Dimov anet@copern.bas.bg, ivdimov@bas.bg, sofia@copern.bas.bg Abstract. Quasi-Monte Carlo methods are based on the idea that ran- dom Monte Carlo techniques can often be improved by replacing the un- derlying source

Karaivanova, Aneta

136

Case Study: Monte Carlo Simulation Monte Carlo simulation uses random numbers and probability, chemistry, and finance. This section gives an example of using Monte Carlo simulation for estimating . To estimate using the Monte Carlo method, draw a circle with its bounding square as shown below. x y 1-1 1 -1

Liang, Y. Daniel

137

Analysis of real-time networks with monte carlo methods

NASA Astrophysics Data System (ADS)

Communication networks in embedded systems are ever more large and complex. A better understanding of the dynamics of these networks is necessary to use them at best and lower costs. Todays tools are able to compute upper bounds of end-to-end delays that a packet being sent through the network could suffer. However, in the case of asynchronous networks, those worst end-to-end delay (WEED) cases are rarely observed in practice or through simulations due to the scarce situations that lead to worst case scenarios. A novel approach based on Monte Carlo methods is suggested to study the effects of the asynchrony on the performances.

Mauclair, C.; Durrieu, G.

2013-12-01

138

A quantum transfer matrix method is proposed and examined. To obtain finite temperature properties, a small number of Monte Carlo samples for the trace summation is taken without the Monte Carlo sampling of the path integral. We introduce the method of a random orthonormal base in the Monte Carlo sampling. This makes it possible to investigate larger size systems than

Masatoshi Imada; Minoru Takahashi

1986-01-01

139

A Residual Monte Carlo Method for Spatially Discrete, Angularly Continuous Radiation Transport

Residual Monte Carlo provides exponential convergence of statistical error with respect to the number of particle histories. In the past, residual Monte Carlo has been applied to a variety of angularly discrete radiation-transport problems. Here, we apply residual Monte Carlo to spatially discrete, angularly continuous transport. By maintaining angular continuity, our method avoids the deficiencies of angular discretizations, such as

Ryan T. Wollaeger; Jeffery D. Densmore

2012-01-01

140

Monte Carlo method for determining earthquake recurrence parameters from short paleoseismic paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach

141

Monte Carlo methods for short polypeptides Jeremy Schofield a) and Mark A. Ratner

Monte Carlo methods for short polypeptides Jeremy Schofield a) and Mark A. Ratner Department! Nonphysical sampling Monte Carlo techniques that enable average structural properties of short in vacuo polypeptide chains to be calculated accurately are discussed. Updating algorithms developed for Monte Carlo

Schofield, Jeremy

142

Kernel density estimator methods for Monte Carlo radiation transport

In this dissertation, the Kernel Density Estimator (KDE), a nonparametric probability density estimator, is studied and used to represent global Monte Carlo (MC) tallies. KDE is also employed to remove the singularities from two important Monte Carlo tallies, namely point detector and surface crossing flux tallies. Finally, KDE is also applied to accelerate the Monte Carlo fission source iteration for

Kaushik Banerjee

2010-01-01

143

Heavy deformed nuclei in the shell model Monte Carlo method

We extend the shell model Monte Carlo approach to heavy deformed nuclei using a new proton-neutron formalism. The low excitation energies of such nuclei necessitate calculations at low temperatures for which a stabilization method is implemented in the canonical ensemble. We apply the method to study a well deformed rare-earth nucleus, 162Dy. The single-particle model space includes the 50-82 shell plus 1f_{7/2} orbital for protons and the 82-126 shell plus 0h_{11/2}, 1g_{9/2} orbitals for neutrons. We show that the spherical shell model reproduces well the rotational character of 162Dy within this model space. We also calculate the level density of 162Dy and find it to be in excellent agreement with the experimental level density, which we extract from several experiments.

Y. Alhassid; L. Fang; H. Nakada

2007-10-09

144

A monte carlo method for generating side chain structural ensembles.

We report a Monte Carlo side chain entropy (MC-SCE) method that uses a physical energy function inclusive of long-range electrostatics and hydrophobic potential of mean force, coupled with both backbone variations and a backbone dependent side chain rotamer library, to describe protein conformational ensembles. Using the MC-SCE method in conjunction with backbone variability, we can reliably determine the side chain rotamer populations derived from both room temperature and cryogenically cooled X-ray crystallographic structures for CypA and H-Ras and NMR J-coupling constants for CypA, Eglin-C, and the DHFR product binary complexes E:THF and E:FOL. Furthermore, we obtain near perfect discrimination between a protein's native state ensemble and ensembles of misfolded structures for 55 different proteins, thereby generating far more competitive side chain packings for all of these proteins and their misfolded states. PMID:25482539

Bhowmick, Asmit; Head-Gordon, Teresa

2015-01-01

145

Quasi-Monte Carlo methods for computing flow in random porous media

Quasi-Monte Carlo methods for computing flow in random porous media I. G. Graham, F. Y. Kuo, D://www.bath.ac.uk/math-sci/BICS #12;Quasi-Monte Carlo methods for computing flow in random porous media I. G. Graham1,4 , F. Y. Kuo2, and where classical Monte Carlo methods with random sampling are currently the method of choice

Burton, Geoffrey R.

146

solved with a Monte-Carlo technique which represents the distribution function fÂ´r v tÂµ as a set of N a Monte-Carlo method of solving this equation, with the number of bodies, N, governing the accuracy of the method (White 1982). 9.1.1 Monte carlo methods The idea behind Monte-Carlo methods is shown

Barnes, Joshua Edward

147

Diagrammatic Monte Carlo Method for Many-Polaron Problems

NASA Astrophysics Data System (ADS)

We introduce the first bold diagrammatic Monte Carlo approach to deal with polaron problems at a finite electron density nonperturbatively, i.e., by including vertex corrections to high orders. Using the Holstein model on a square lattice as a prototypical example, we demonstrate that our method is capable of providing accurate results in the thermodynamic limit in all regimes from a renormalized Fermi liquid to a single polaron, across the nonadiabatic region where Fermi and Debye energies are of the same order of magnitude. By accounting for vertex corrections, the accuracy of the theoretical description is increased by orders of magnitude relative to the lowest-order self-consistent Born approximation employed in most studies. We also find that for the electron-phonon coupling typical for real materials, the quasiparticle effective mass increases and the quasiparticle residue decreases with increasing the electron density at constant electron-phonon coupling strength.

Mishchenko, Andrey S.; Nagaosa, Naoto; Prokof'ev, Nikolay

2014-10-01

148

Diagrammatic Monte Carlo method for many-polaron problems.

We introduce the first bold diagrammatic Monte Carlo approach to deal with polaron problems at a finite electron density nonperturbatively, i.e., by including vertex corrections to high orders. Using the Holstein model on a square lattice as a prototypical example, we demonstrate that our method is capable of providing accurate results in the thermodynamic limit in all regimes from a renormalized Fermi liquid to a single polaron, across the nonadiabatic region where Fermi and Debye energies are of the same order of magnitude. By accounting for vertex corrections, the accuracy of the theoretical description is increased by orders of magnitude relative to the lowest-order self-consistent Born approximation employed in most studies. We also find that for the electron-phonon coupling typical for real materials, the quasiparticle effective mass increases and the quasiparticle residue decreases with increasing the electron density at constant electron-phonon coupling strength. PMID:25361271

Mishchenko, Andrey S; Nagaosa, Naoto; Prokof'ev, Nikolay

2014-10-17

149

Optimization of the Beam Shaping Assembly (BSA) has been performed using the MCNP4C Monte Carlo code to shape the 2.45 MeV neutrons that are produced in the D-D neutron generator. Optimal design of the BSA has been chosen by considering in-air figures of merit (FOM) which consists of 70 cm Fluental as a moderator, 30 cm Pb as a reflector, 2mm (6)Li as a thermal neutron filter and 2mm Pb as a gamma filter. The neutron beam can be evaluated by in-phantom parameters, from which therapeutic gain can be derived. Direct evaluation of both set of FOMs (in-air and in-phantom) is very time consuming. In this paper a Response Matrix (RM) method has been suggested to reduce the computing time. This method is based on considering the neutron spectrum at the beam exit and calculating contribution of various dose components in phantom to calculate the Response Matrix. Results show good agreement between direct calculation and the RM method. PMID:23954283

Kasesaz, Y; Khalafi, H; Rahmani, F

2013-12-01

150

Math 565 Monte Carlo Methods in Finance Course Description from Bulletin: In addition the student to some such simulation techniques, known as Monte Carlo methods, with focus on applications in financial risk management. Monte Carlo and Quasi Monte Carlo techniques are computational sampling methods

Heller, Barbara

151

A Constrained Path Monte Carlo Method for Fermion Ground States

We describe and discuss a recently proposed quantum Monte Carlo algorithm to compute the ground-state properties of various systems of interacting fermions. In this method, the ground state is projected from an initial wave function by a branching random walk in an over-complete basis of Slater determinants. By constraining the determinants according to a trial wave function $|\\psi_T\\rangle$, we remove the exponential decay of signal-to-noise ratio characteristic of the sign problem. The method is variational and is exact if $|\\psi_T\\rangle$ is exact. We illustrate the method by describing in detail its implementation for the two-dimensional one-band Hubbard model. We show results for lattice sizes up to $16\\times 16$ and for various electron fillings and interaction strengths. Besides highly accurate estimates of the ground-state energy, we find that the method also yields reliable estimates of other ground-state observables, such as superconducting pairing correlation functions. We conclude by discussing possible extensions of the algorithm.

Shiwei Zhang; J. Carlson; J. E. Gubernatis

1996-07-09

152

Uncertainty evaluation in robot calibration by Monte Carlo method

NASA Astrophysics Data System (ADS)

In this paper it is presented a technique to evaluate the calibration uncertainty for a robot arm calibrated by circle point analysis method. The method developed, based on probability distribution propagation calculation recommended by the Guide to the Expression of Uncertainty of Measurement, and on Monte Carlo method, makes it possible to calculate uncertainty in the identification of each robot single parameter, and thus to estimate robot positioning uncertainty in accordance to its calibration uncertainty, and not according to a set of single locations and orientations previously defined for a unique set of identified parameters. Besides, this technique allows beforehand to establish the best possible conditions for the data capture test for the identification, which turn out to have the less possible calibration uncertainty, according to the variables involved in the data capture process for the identification, by propagating their influence up to final robot accuracy. Currently, the results validity of a robot calibration procedure is expressed generally in terms of position and orientation error in a set of locations and orientations. The method presented is the first evaluation in the literature for that validity in terms of calibration uncertainty around the whole work volume.

Santolaria, J.; Ginés, M.; Vila, L.; Brau, A.; Aguilar, J. J.

2012-04-01

153

A modified Monte Carlo 'local importance function transform' method

The Local Importance Function Transform (LIFT) method uses an approximation of the contribution transport problem to bias a forward Monte-Carlo (MC) source-detector simulation [1-3]. Local (cell-based) biasing parameters are calculated from an inexpensive deterministic adjoint solution and used to modify the physics of the forward transport simulation. In this research, we have developed a new expression for the LIFT biasing parameter, which depends on a cell-average adjoint current to scalar flux (J{sup *}/{phi}{sup *}) ratio. This biasing parameter differs significantly from the original expression, which uses adjoint cell-edge scalar fluxes to construct a finite difference estimate of the flux derivative; the resulting biasing parameters exhibit spikes in magnitude at material discontinuities, causing the original LIFT method to lose efficiency in problems with high spatial heterogeneity. The new J{sup *}/{phi}{sup *} expression, while more expensive to obtain, generates biasing parameters that vary smoothly across the spatial domain. The result is an improvement in simulation efficiency. A representative test problem has been developed and analyzed to demonstrate the advantage of the updated biasing parameter expression with regards to solution figure of merit (FOM). For reference, the two variants of the LIFT method are compared to a similar variance reduction method developed by Depinay [4, 5], as well as MC with deterministic adjoint weight windows (WW). (authors)

Keady, K. P.; Larsen, E. W. [University of Michigan, Department of Nuclear Engineering and Radiological Sciences, 2355 Bonisteel Blvd., Ann Arbor, MI 48109 (United States)

2013-07-01

154

Monte Carlo methods for signal processing: a review in the statistical signal processing context

In this article, MCMC (Markov chain Monte Carlo methods) and SMC (sequential Monte Carlo methods) are introduced to sample and\\/or maximize high-dimensional probability distributions. These methods enable to perform likelihood or Bayesian inference for complex non-Gaussian signal processing problems.

A. Doucet; Xiaodong Wang

2005-01-01

155

A wave-function Monte Carlo method for simulating conditional master equations

Wave-function Monte Carlo methods are an important tool for simulating quantum systems, but the standard method cannot be used to simulate decoherence in continuously measured systems. Here we present a new Monte Carlo method for such systems. This was used to perform the simulations of a continuously measured nano-resonator in [Phys. Rev. Lett. 102, 057208 (2009)].

Kurt Jacobs

2009-06-25

156

Wave-function Monte Carlo method for simulating conditional master equations

Wave-function Monte Carlo methods are an important tool for simulating quantum systems, but the standard method cannot be used to simulate decoherence in continuously measured systems. Here I present a Monte Carlo method for such systems. This was used to perform the simulations of a continuously measured nanoresonator in [Phys. Rev. Lett. 102, 057208 (2009)].

Jacobs, Kurt [Department of Physics, University of Massachusetts at Boston, Boston, Massachusetts 02125 (United States) and Hearne Institute for Theoretical Physics, Louisiana State University, Baton Rouge, Louisiana 70803 (United States)

2010-04-15

157

We present a new, nondestructive, method for determining chemical potentials in Monte Carlo and molecular dynamics simulations. The method estimates a value for the chemical potential such that one has a balance between fictitious successful creation and destruction trials in which the Monte Carlo method is used to determine success or failure of the creation\\/destruction attempts; we thus call the

Patrick J. Fay; John R. Ray; Ralph J. Wolf

1994-01-01

158

MONTE-CARLO BASED ESTIMATION METHODS FOR RAPIDLY-VARYING SEA CLUTTER

MONTE-CARLO BASED ESTIMATION METHODS FOR RAPIDLY-VARYING SEA CLUTTER Ying Li , William Moran Monte-Carlo based methods for characteriz- ing the scattering function of rapidly-varying sea clutter. The first method uses multiple particle filtering to estimate the clutter space-time covariance marix

Nehorai, Arye

159

Sequential Monte Carlo Methods to Train Neural Network Models

We discuss a novel strategy for training neural networks using sequential Monte Carlo algorithms and propose a new hybrid gradient descent\\/sampling importance resampling algorithm (HySIR). In terms of computational time and accuracy, the hybrid SIR is a clear improvement over conventional sequential Monte Carlo techniques. The new algorithm may be viewed as a global optimization strategy that allows us to

João F. G. De Freitas; Mahesan Niranjan; Andrew H. Gee; Arnaud Doucet

2000-01-01

160

New sequential Monte Carlo methods for nonlinear dynamic systems

In this paper we present several new sequential Monte Carlo (SMC) algorithms for online estimation (filtering) of nonlinear dynamic systems. SMC has been shown to be a powerful tool for dealing with complex dynamic systems. It sequentially generates Monte Carlo samples from a proposal distribution, adjusted by a set of importance weight with respect to a target distribution, to facilitate

Dong Guo; Xiaodong Wang; Rong Chen

2005-01-01

161

NASA Astrophysics Data System (ADS)

This research utilized Monte Carlo N-Particle version 4C (MCNP4C) to simulate K X-ray fluorescent (K XRF) measurements of stable lead in bone. Simulations were performed to investigate the effects that overlying tissue thickness, bone-calcium content, and shape of the calibration standard have on detector response in XRF measurements at the human tibia. Additional simulations of a knee phantom considered uncertainty associated with rotation about the patella during XRF measurements. Simulations tallied the distribution of energy deposited in a high-purity germanium detector originating from collimated 88 keV 109Cd photons in backscatter geometry. Benchmark measurements were performed on simple and anthropometric XRF calibration phantoms of the human leg and knee developed at the University of Cincinnati with materials proven to exhibit radiological characteristics equivalent to human tissue and bone. Initial benchmark comparisons revealed that MCNP4C limits coherent scatter of photons to six inverse angstroms of momentum transfer and a Modified MCNP4C was developed to circumvent the limitation. Subsequent benchmark measurements demonstrated that Modified MCNP4C adequately models photon interactions associated with in vivo K XRF of lead in bone. Further simulations of a simple leg geometry possessing tissue thicknesses from 0 to 10 mm revealed increasing overlying tissue thickness from 5 to 10 mm reduced predicted lead concentrations an average 1.15% per 1 mm increase in tissue thickness (p < 0.0001). An anthropometric leg phantom was mathematically defined in MCNP to more accurately reflect the human form. A simulated one percent increase in calcium content (by mass) of the anthropometric leg phantom's cortical bone demonstrated to significantly reduce the K XRF normalized ratio by 4.5% (p < 0.0001). Comparison of the simple and anthropometric calibration phantoms also suggested that cylindrical calibration standards can underestimate lead content of a human leg up to 4%. The patellar bone structure in which the fluorescent photons originate was found to vary dramatically with measurement angle. The relative contribution of lead signal from the patella declined from 65% to 27% when rotated 30°. However, rotation of the source-detector about the patella from 0 to 45° demonstrated no significant effect on the net K XRF response at the knee.

Lodwick, Camille J.

162

What is a Monte Carlo Method? A method involving deliberate use of random

.4 -0.2 0 0.2 0.4 0.6 20 40 60 80 100 120 importance error 13 #12;Stratified Sampling Break [-1, 1.6 -0.4 -0.2 0 0.2 0.4 0.6 20 40 60 80 100 120 stratified error 14 #12;Stratified Importance SamplingWhat is a Monte Carlo Method? A method involving deliberate use of random numbers in a calculation

Lischinski, Dani

163

An automated variance reduction method for global Monte Carlo neutral particle transport problems

A method to automatically reduce the variance in global neutral particle Monte Carlo problems by using a weight window derived from a deterministic forward solution is presented. This method reduces a global measure of the variance of desired tallies and increases its associated figure of merit. Global deep penetration neutron transport problems present difficulties for analog Monte Carlo. When the

Marc Andrew Cooper

1999-01-01

164

Chappter 6. Diffusion of Gases in Amorphous Polymers: The Monte Carlo Void Method.

VI - 1 Chappter 6. Diffusion of Gases in Amorphous Polymers: The Monte Carlo Void Method. Mihail based on biased random walk in the free volume extracted from a polymer ("the Monte Carlo Void Method experiment.iv As a result there is little in the way of reliable predictions on how to design polymer films

Goddard III, William A.

165

MONTE CARLO METHODS FOR THE VALUATION OF MULTIPLE-EXERCISE OPTIONS

We discuss Monte Carlo methods for valuing options with multiple-exercise features in discrete time. By extending the recently developed duality ideas for American option pricing, we show how to obtain estimates on the prices of such options using Monte Carlo techniques. We prove convergence of our approach and estimate the error. The methods are applied to options in the energy

N. Meinshausen; B. M. Hambly

2004-01-01

166

Kinetic Monte Carlo method for dislocation migration in the presence of solute Chaitanya S. Deo

Kinetic Monte Carlo method for dislocation migration in the presence of solute Chaitanya S. Deo, California 94550, USA (Received 21 April 2004; published 6 January 2005) We present a kinetic Monte Carlo method for simulating dislocation motion in alloys within the framework of the kink model. The model

Cai, Wei

167

A BOUNDARY-DISPATCH MONTE CARLO (EXODUS) METHOD FOR ANALYSIS OF CONDUCTIVE HEAT TRANSFER PROBLEMS

A boundary-dispatch Monte Carlo (Exodus) method, in which the particles are dispatched from the boundaries of a conductive medium or source of heat, is developed. A fixed number of particles are dispatched from a boundary node to the nearest internal node. These particles make random walks within the medium similar to that of the conventional Monte Carlo method. Once a

Mohammad H. N. Naraghi; Shun-Chang Tsai

1993-01-01

168

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

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

2008-01-01

169

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 ...

170

Monte Carlo methods for parallel processing of diffusion equations

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

Vafadari, Cyrus

2013-01-01

171

An asymptotic-preserving Monte Carlo method for the Boltzmann equation

NASA Astrophysics Data System (ADS)

In this work, we propose an asymptotic-preserving Monte Carlo method for the Boltzmann equation that is more efficient than the currently available Monte Carlo methods in the fluid dynamic regime. This method is based on the successive penalty method [39], which is an improved BGK-penalization method originally proposed by Filbet and Jin [16]. Here we introduce the Monte Carlo implementation of the method, which, despite its lower order accuracy, is very efficient in higher dimensions or simulating some complicated chemical processes. This method allows the time step independent of the mean free time which is prohibitively small in the fluid dynamic regime. We study some basic properties of this method, and compare it with some other asymptotic-preserving Monte Carlo methods in terms of numerical performance in different regimes, from rarefied to fluid dynamic regimes, and their computational efficiency.

Ren, Wei; Liu, Hong; Jin, Shi

2014-11-01

172

NASA Astrophysics Data System (ADS)

A multiple step fixed random walk Monte Carlo method for solving heat conduction in solids with distributed internal heat sources is developed. In this method, the probability that a walker reaches a point a few steps away is calculated analytically and is stored in the computer. Instead of moving to the immediate neighboring point the walker is allowed to jump several steps further. The present multiple step random walk technique can be applied to both conventional Monte Carlo and the Exodus methods. Numerical results indicate that the present method compares well with finite difference solutions while the computation speed is much faster than that of single step Exodus and conventional Monte Carlo methods.

Naraghi, M. H. N.; Chung, B. T. F.

1982-06-01

173

. There is much unknown about the underlying reservoir model, which has many uncertain parameters. MCMC (Markov Chain Monte Carlo) is a more statistically rigorous sampling method, with a stronger theoretical base than other methods. The performance of the MCMC...

Liu, Chang

2009-05-15

174

The path-history-based fluorescence Monte Carlo method used for fluorescence tomography imaging reconstruction has attracted increasing attention. In this paper, we first validate the standard fluorescence Monte Carlo (sfMC) method by experimenting with a cylindrical phantom. Then, we describe a path-history-based decoupled fluorescence Monte Carlo (dfMC) method, analyze different perturbation fluorescence Monte Carlo (pfMC) methods, and compare the calculation accuracy and computational efficiency of the dfMC and pfMC methods using the sfMC method as a reference. The results show that the dfMC method is more accurate and efficient than the pfMC method in heterogeneous medium. PMID:25607163

Jiang, Xu; Deng, Yong; Luo, Zhaoyang; Wang, Kan; Lian, Lichao; Yang, Xiaoquan; Meglinski, Igor; Luo, Qingming

2014-12-29

175

Combining Monte Carlo and worst-case methods for trajectory prediction in air traffic control@eng.cam.ac.uk Abstract We illustrate, through a case study, a novel combination of probabilistic Monte Carlo methods-case methods, set-membership, Monte Carlo methods, particle filter, non-linear systems. #12;I. INTRODUCTION

Visintini, Andrea Lecchini

176

The stochastic Galerkin method (SGM) is an intrusive technique for propagating data uncertainty in physical models. The method reduces the random model to a system of coupled deterministic equations for the moments of stochastic spectral expansions of result quantities. We investigate solving these equations using the Monte Carlo technique. We compare the efficiency with brute-force Monte Carlo evaluation of uncertainty, the non-intrusive stochastic collocation method (SCM), and an intrusive Monte Carlo implementation of the stochastic collocation method. We also describe the stability limitations of our SGM implementation. (authors)

Franke, B. C. [Sandia National Laboratories, Albuquerque, NM 87185 (United States); Prinja, A. K. [Department of Chemical and Nuclear Engineering, University of New Mexico, Albuquerque, NM 87131 (United States)

2013-07-01

177

Evaluation of measurement uncertainty and its numerical calculation by a Monte Carlo method

NASA Astrophysics Data System (ADS)

The Guide to the Expression of Uncertainty in Measurement (GUM) is the de facto standard for the evaluation of measurement uncertainty in metrology. Recently, evaluation of measurement uncertainty has been proposed on the basis of probability density functions (PDFs) using a Monte Carlo method. The relation between this PDF approach and the standard method described in the GUM is outlined. The Monte Carlo method required for the numerical calculation of the PDF approach is described and illustrated by its application to two examples. The results obtained by the Monte Carlo method for the two examples are compared to the corresponding results when applying the GUM.

Wübbeler, Gerd; Krystek, Michael; Elster, Clemens

2008-08-01

178

Uncertainty analysis for fluorescence tomography with Monte Carlo method

NASA Astrophysics Data System (ADS)

Fluorescence tomography seeks to image an inaccessible fluorophore distribution inside an object like a small animal by injecting light at the boundary and measuring the light emitted by the fluorophore. Optical parameters (e.g. the conversion efficiency or the fluorescence life-time) of certain fluorophores depend on physiologically interesting quantities like the pH value or the oxygen concentration in the tissue, which allows functional rather than just anatomical imaging. To reconstruct the concentration and the life-time from the boundary measurements, a nonlinear inverse problem has to be solved. It is, however, difficult to estimate the uncertainty of the reconstructed parameters in case of iterative algorithms and a large number of degrees of freedom. Uncertainties in fluorescence tomography applications arise from model inaccuracies, discretization errors, data noise and a priori errors. Thus, a Markov chain Monte Carlo method (MCMC) was used to consider all these uncertainty factors exploiting Bayesian formulation of conditional probabilities. A 2-D simulation experiment was carried out for a circular object with two inclusions. Both inclusions had a 2-D Gaussian distribution of the concentration and constant life-time inside of a representative area of the inclusion. Forward calculations were done with the diffusion approximation of Boltzmann's transport equation. The reconstruction results show that the percent estimation error of the lifetime parameter is by a factor of approximately 10 lower than that of the concentration. This finding suggests that lifetime imaging may provide more accurate information than concentration imaging only. The results must be interpreted with caution, however, because the chosen simulation setup represents a special case and a more detailed analysis remains to be done in future to clarify if the findings can be generalized.

Reinbacher-Köstinger, Alice; Freiberger, Manuel; Scharfetter, Hermann

2011-07-01

179

Monte Carlo Method for Calculating the Electrostatic Energy of a Molecule

Monte Carlo Method for Calculating the Electrostatic Energy of a Molecule Michael Mascagni1 ,2, coupled by boundary conditions. A Monte Carlo estimate for the potential point values, their derivatives to a stochastic differential equation via a first-order Euler scheme (see e.g. [11]). This approach was applied [4

Mascagni, Michael

180

A Configurational Bias Monte Carlo Method for Linear and Cyclic Peptides

In this manuscript, we describe a new configurational bias Monte Carlo technique for the simulation of peptides. We focus on the biologically relevant cases of linear and cyclic peptides. Our approach leads to an efficient, Boltzmann-weighted sampling of the torsional degrees of freedom in these biological molecules, a feat not possible with previous Monte Carlo and molecular dynamics methods.

Michael W. Deem; Joel Bader

1997-09-30

181

Bayesian Training of Backpropagation Networks by the Hybrid Monte Carlo Method

. It is shown that Bayesian training of backpropagation neural networks can feasiblybe performed by the "Hybrid Monte Carlo" method. This approach allows the true predictivedistribution for a test case given a set of training cases to be approximated arbitrarily closely,in contrast to previous approaches which approximate the posterior weight distribution by aGaussian. In this work, the Hybrid Monte Carlo

Radford Neal

1993-01-01

182

PHYSICAL REVIEW E 84, 061912 (2011) Kinetic Monte Carlo method applied to nucleic acid hairpin December 2011) Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure states. Secondary structure models of nucleic acids, which record the pairings of complementary

Widom, Michael

183

Article type: Opinion Article Why the Monte Carlo Method is so important

Article type: Opinion Article Why the Monte Carlo Method is so important today Article ID Dirk P interested in carrying out random experiments on a computer. Such Monte Carlo tech- niques are now today? This article ex- plores the reasons why the MCM has evolved from a "last resort" solution

Kroese, Dirk P.

184

Though Monte Carlo localization is a popular method for mobile robot localization, it requires a method for recovery of large estimation error in itself. In this paper, a recovery method, which is named an expansion resetting method, is newly proposed. A blending of the expansion resetting method and another, which is called the sensor resetting method, is also proposed. We

Ryuichi UEDA; Tamio ARAI; K. Sakamoto; T. Kikuchi; S. Kamiya

2004-01-01

185

A Residual Monte Carlo Method for Spatially Discrete, Angularly Continuous Radiation Transport

Residual Monte Carlo provides exponential convergence of statistical error with respect to the number of particle histories. In the past, residual Monte Carlo has been applied to a variety of angularly discrete radiation-transport problems. Here, we apply residual Monte Carlo to spatially discrete, angularly continuous transport. By maintaining angular continuity, our method avoids the deficiencies of angular discretizations, such as ray effects. For planar geometry and step differencing, we use the corresponding integral transport equation to calculate an angularly independent residual from the scalar flux in each stage of residual Monte Carlo. We then demonstrate that the resulting residual Monte Carlo method does indeed converge exponentially to within machine precision of the exact step differenced solution.

Wollaeger, Ryan T. [Los Alamos National Laboratory; Densmore, Jeffery D. [Los Alamos National Laboratory

2012-06-19

186

Response kernel density estimation Monte Carlo method for electron transport

Electron transport simulation plays an important role in the dose calculation in electron cancer therapy as well as in many other fields. Traditional numerical solutions for particle transport are inadequate because of the extremely anisotropic collisions between electrons and the background medium. In principle, analog Monte Carlo (AMC) can be used, however, the large cross section for coulombic interactions makes

Jie Du

1997-01-01

187

a Path Integral Monte Carlo Method for the Quasielastic Response

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

Carlo Carraro

1990-01-01

188

Smoothness and dimension reduction in Quasi-Monte Carlo methods

Monte Carlo integration using quasirandom sequences has theoretical error bounds of size O (N?1 logdN) in dimension d, as opposed to the error of size O (N?12) for random or pseudorandom sequences. In practice, however, this improved performance for quasirandom sequences is often not observed. The degradation of performance is due to discontinuity or lack of smoothness in the integrand

B. Moskowitz; R. E. Caflisch

1996-01-01

189

Some Continuous Monte Carlo Methods for the Dirichlet Problem

Monte Carlo techniques are introduced, using stochastic models which are Markov processes. This material includes the $N$-dimensional Spherical, General Spherical, and General Dirichlet Domain processes. These processes are proved to converge with probability 1, and thus to yield direct statistical estimates of the solution to the $N$-dimensional Dirichlet problem. The results are obtained without requiring any further restrictions on the

Mervin E. Muller

1956-01-01

190

Dynamic Conditional Independence Models And Markov Chain Monte Carlo Methods

In dynamic statistical modeling situations, observations arise sequentially, causingthe model to expand by progressive incorporation of new data items and new unknownparameters. For example, in clinical monitoring, new patient-specific parameters areintroduced with each new patient. Markov chain Monte Carlo (MCMC) might be usedfor posterior inference, but would need to be redone at each expansion stage. Thus suchmethods are often too

Carlo Berzuini; Nicola G. Best; Walter R. Gilks; Cristiana Larizza

1997-01-01

191

A Monte Carlo method for the PDF equations of turbulent flow

A Monte Carlo method is presented which simulates the transport equations of joint probability density functions (pdf's) in turbulent flows. (Finite-difference solutions of the equations are impracticable, mainly because ...

Pope, S. B.

1980-01-01

192

NASA Technical Reports Server (NTRS)

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.

Firstenberg, H.

1971-01-01

193

Uncertainty Analysis in Upscaling Well Log data By Markov Chain Monte Carlo Method

, densities, and thicknesses of rocks through upscaling well log data, the Markov Chain Monte Carlo (MCMC) method is a potentially beneficial tool that uses randomly generated parameters with a Bayesian framework producing the posterior information...

Hwang, Kyubum

2010-01-16

194

Investigation into the properties and application of the Diffusion Monte Carlo method

This paper shall be a discussion of the properties of the Diffusion Monte Carlo (DMC) method and its applications. The discussion shall cover the basic theory behind the algorithm and the class of problems it is designed ...

Orieka, Ogheneovie (Ogheneovie O.)

2014-01-01

195

Multivariate Population Balances via Moment and Monte Carlo Simulation Methods: An Important Sol with a population balance equation governing evolution of the "dispersed" (suspended) particle population. Early, hopefully, motivate a broader attack on important multivariate population balance problems, including those

196

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

Li, Yaohang

197

Efficient, automated Monte Carlo methods for radiation transport

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

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

2008-11-20

198

Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method. PMID:24892069

Siswantoro, Joko; Idrus, Bahari

2014-01-01

199

Comparison of Monte Carlo methods for fluorescence molecular tomography—computational efficiency

Purpose: The Monte Carlo method is an accurate model for time-resolved quantitative fluorescence tomography. However, this method suffers from low computational efficiency due to the large number of photons required for reliable statistics. This paper presents a comparison study on the computational efficiency of three Monte Carlo-based methods for time-domain fluorescence molecular tomography. Methods: The methods investigated to generate time-gated Jacobians were the perturbation Monte Carlo (pMC) method, the adjoint Monte Carlo (aMC) method and the mid-way Monte Carlo (mMC) method. The effects of the different parameters that affect the computation time and statistics reliability were evaluated. Also, the methods were applied to a set of experimental data for tomographic application. Results:In silico results establish that, the investigated parameters affect the computational time for the three methods differently (linearly, quadratically, or not significantly). Moreover, the noise level of the Jacobian varies when these parameters change. The experimental results in preclinical settings demonstrates the feasibility of using both aMC and pMC methods for time-resolved whole body studies in small animals within a few hours. Conclusions: Among the three Monte Carlo methods, the mMC method is a computationally prohibitive technique that is not well suited for time-domain fluorescence tomography applications. The pMC method is advantageous over the aMC method when the early gates are employed and large number of detectors is present. Alternatively, the aMC method is the method of choice when a small number of source-detector pairs are used. PMID:21992393

Chen, Jin; Intes, Xavier

2011-01-01

200

Direct Monte Carlo simulation methods for nonreacting and reacting systems at fixed total internal; published 18 July 2002 A Monte Carlo computer simulation method is presented for directly performing. In this paper, we describe a methodology for performing Monte Carlo simulations at fixed U or at fixed H

Lisal, Martin

201

Density-of-states Monte Carlo method for simulation of fluids Qiliang Yan, Roland Faller, and Juan, Wisconsin 53706 Received 6 November 2001; accepted 30 January 2002 A Monte Carlo method based on a density Monte Carlo methodologies have been developed in the last decade to circumvent the sampling problem

Faller, Roland

202

Chapter 11 Quantum Monte Carlo methods If, in some cataclysm, all scientific knowledge were of Thermodynamics. 11.1 Introduction The aim of this chapter is to present examples of applications of Monte CarloA, are the coordinates and 1, .., A, 265 #12;Quantum Monte Carlo methods are sets of relevant quantum numbers

Elster, Charlotte

203

Kinetic Monte Carlo method for rule-based modeling of biochemical networks Jin Yang,1,* Michael I June 2008; published 10 September 2008 We present a kinetic Monte Carlo method for simulating chemical of simulation is O log2 M per reaction event for efficient ki- netic Monte Carlo KMC implementations 12

Faeder, Jim

204

This review presents in a comprehensive and tutorial form the basic principles of the Monte Carlo method, as applied to the solution of transport problems in semiconductors. Sufficient details of a typical Monte Carlo simulation have been given to allow the interested reader to create his own Monte Carlo program, and the method has been briefly compared with alternative theoretical

Carlo Jacoboni; Lino Reggiani

1983-01-01

205

APR1400 LBLOCA uncertainty quantification by Monte Carlo method and comparison with Wilks' formula

An analysis of the uncertainty quantification for the PWR LBLOCA by the Monte Carlo calculation has been performed and compared with the tolerance level determined by Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LBLOCA accident were determined by the PIRT results from the BEMUSE project. The Monte-Carlo method shows that the 95. percentile PCT value can be obtained reliably with a 95% confidence level using the Wilks' formula. The extra margin by the Wilks' formula over the true 95. percentile PCT by the Monte-Carlo method was rather large. Even using the 3 rd order formula, the calculated value using the Wilks' formula is nearly 100 K over the true value. It is shown that, with the ever increasing computational capability, the Monte-Carlo method is accessible for the nuclear power plant safety analysis within a realistic time frame. (authors)

Hwang, M.; Bae, S.; Chung, B. D. [Korea Atomic Energy Research Inst., 150 Dukjin-dong, Yuseong-gu, Daejeon (Korea, Republic of)

2012-07-01

206

NASA Astrophysics Data System (ADS)

We present a multiple-set overlapping-domain decomposed strategy for parallelizing the Monte Carlo Synthetic Acceleration method. Monte Carlo Synthetic Acceleration methods use the Neumann-Ulam class of Monte Carlo solvers for linear systems to accelerate a fixed-point iteration sequence. Effective parallel algorithms for these methods require the parallelization of the underlying Neumann-Ulam solvers. To do this in a domain decomposed environment, we borrow strategies traditionally implemented in Monte Carlo particle transport to parallelize the problem. The parallel Neumann-Ulam and multiple-set overlapping-domain decomposition algorithms are presented along with parallel scaling data for the resulting implementation using the Titan Cray XK7 machine at Oak Ridge National Laboratory.

Slattery, Stuart R.; Evans, Thomas M.; Wilson, Paul P. H.

2014-06-01

207

Recent Bayesian methods for the analysis of infectious disease outbreak data using stochastic epidemic models are reviewed. These methods rely on Markov chain Monte Carlo methods. Both temporal and non-temporal data are considered. The methods are illustrated with a number of examples featuring different models and datasets.

Philip D. O’Neill

2002-01-01

208

Advanced computational methods for nodal diffusion, Monte Carlo, and S[sub N] problems

This document describes progress on five efforts for improving effectiveness of computational methods for particle diffusion and transport problems in nuclear engineering: (1) Multigrid methods for obtaining rapidly converging solutions of nodal diffusion problems. A alternative line relaxation scheme is being implemented into a nodal diffusion code. Simplified P2 has been implemented into this code. (2) Local Exponential Transform method for variance reduction in Monte Carlo neutron transport calculations. This work yielded predictions for both 1-D and 2-D x-y geometry better than conventional Monte Carlo with splitting and Russian Roulette. (3) Asymptotic Diffusion Synthetic Acceleration methods for obtaining accurate, rapidly converging solutions of multidimensional SN problems. New transport differencing schemes have been obtained that allow solution by the conjugate gradient method, and the convergence of this approach is rapid. (4) Quasidiffusion (QD) methods for obtaining accurate, rapidly converging solutions of multidimensional SN Problems on irregular spatial grids. A symmetrized QD method has been developed in a form that results in a system of two self-adjoint equations that are readily discretized and efficiently solved. (5) Response history method for speeding up the Monte Carlo calculation of electron transport problems. This method was implemented into the MCNP Monte Carlo code. In addition, we have developed and implemented a parallel time-dependent Monte Carlo code on two massively parallel processors.

Martin, W.R.

1993-01-01

209

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

Keinan, Alon

210

Markov Chain Monte Carlo Method without Detailed Balance

We present a specific algorithm that generally satisfies the balance condition without imposing the detailed balance in the Markov chain Monte Carlo. In our algorithm, the average rejection rate is minimized, and even reduced to zero in many relevant cases. The absence of the detailed balance also introduces a net stochastic flow in a configuration space, which further boosts up the convergence. We demonstrate that the autocorrelation time of the Potts model becomes more than 6 times shorter than that by the conventional Metropolis algorithm. Based on the same concept, a bounce-free worm algorithm for generic quantum spin models is formulated as well.

Hidemaro Suwa; Synge Todo

2010-07-14

211

Monte Carlo methods via the use of the central-limit theorem

NASA Astrophysics Data System (ADS)

In the present letter we give a new method to handle the sign problem. In fact we apply the central-limit theorem on the phase, which appears in the expression of the Monte Carlo after certain manipulations. Then we can use standard methods to calculate the two expressions that appear. In fact we manage to reduce real-time integration to a case similar to imaginary-time integration. The present method can be combined with other methods such as the stationary-phase Monte Carlo methods are. We apply the present theory to the path integral representation of the time displacement amplitude.

Thrapsaniotis, E. G.

2003-08-01

212

A New Monte Carlo Method for Time-Dependent Neutrino Radiation Transport

Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck & Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.

Ernazar Abdikamalov; Adam Burrows; Christian D. Ott; Frank Löffler; Evan O'Connor; Joshua C. Dolence; Erik Schnetter

2012-03-13

213

A NEW MONTE CARLO METHOD FOR TIME-DEPENDENT NEUTRINO RADIATION TRANSPORT

Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck and Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.

Abdikamalov, Ernazar; Ott, Christian D.; O'Connor, Evan [TAPIR, California Institute of Technology, MC 350-17, 1200 E California Blvd., Pasadena, CA 91125 (United States); Burrows, Adam; Dolence, Joshua C. [Department of Astrophysical Sciences, Princeton University, Peyton Hall, Ivy Lane, Princeton, NJ 08544 (United States); Loeffler, Frank; Schnetter, Erik, E-mail: abdik@tapir.caltech.edu [Center for Computation and Technology, Louisiana State University, 216 Johnston Hall, Baton Rouge, LA 70803 (United States)

2012-08-20

214

NASA Astrophysics Data System (ADS)

We present lattice Monte Carlo calculations of fermion-dimer scattering in the limit of zero-range interactions using the adiabatic projection method. The adiabatic projection method uses a set of initial cluster states and Euclidean time projection to give a systematically improvable description of the low-lying scattering cluster states in a finite volume. We use Lüscher's finite-volume relations to determine the s -wave, p -wave, and d -wave phase shifts. For comparison, we also compute exact lattice results using Lanczos iteration and continuum results using the Skorniakov-Ter-Martirosian equation. For our Monte Carlo calculations we use a new lattice algorithm called impurity lattice Monte Carlo. This algorithm can be viewed as a hybrid technique which incorporates elements of both worldline and auxiliary-field Monte Carlo simulations.

Elhatisari, Serdar; Lee, Dean

2014-12-01

215

A cavity-biased (T, V, mu) Monte Carlo method for the computer simulation of fluids

A modified sampling technique is proposed for use in Monte Carlo calculations in the grand canonical ensemble. The new method, called the cavity-biased (T, V, mu) Monte Carlo procedure, attempts insertions of new particles into existing cavities in the system instead of at randomly selected points. Calculations on supercritical Lennard-Jones fluid showed an 8-fold increase in the efficiency of the

Mihaly Mezei

1980-01-01

216

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

We perform a stability analysis of a Monte Carlo method for simulating the Compton scattering of photons by free electron in high energy density applications and develop time-step limits that avoid unstable and oscillatory solutions. Implementing this Monte Carlo technique in multi physics problems typically requires evaluating the material temperature at its beginning-of-time-step value, which can lead to this undesirable behavior. With a set of numerical examples, we demonstrate the efficacy of our time-step limits.

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

2009-01-01

217

A Monte Carlo synthetic-acceleration method for solving the thermal radiation diffusion equation

We present a novel synthetic-acceleration-based Monte Carlo method for solving the equilibrium thermal radiation diffusion equation in three spatial 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 our Monte Carlo method is an effective solver for sparse matrix systems. For solutions converged to the same tolerance, it performs competitively with deterministic methods including preconditioned conjugate gradient and GMRES. We also discuss various aspects of preconditioning the method and its general applicability to broader classes of problems.

Evans, Thomas M., E-mail: evanstm@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Mosher, Scott W., E-mail: moshersw@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Slattery, Stuart R., E-mail: sslattery@wisc.edu [University of Wisconsin–Madison, 1500 Engineering Dr., Madison, WI 53716 (United States); Hamilton, Steven P., E-mail: hamiltonsp@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN 37831 (United States)

2014-02-01

218

A Monte Carlo Synthetic-Acceleration Method for Solving the Thermal Radiation Diffusion Equation

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.

Evans, Thomas M [ORNL] [ORNL; Mosher, Scott W [ORNL] [ORNL; Slattery, Stuart [University of Wisconsin, Madison] [University of Wisconsin, Madison

2014-01-01

219

A New Method for the Calculation of Diffusion Coefficients with Monte Carlo

NASA Astrophysics Data System (ADS)

This paper presents a new Monte Carlo-based method for the calculation of diffusion coefficients. One distinctive feature of this method is that it does not resort to the computation of transport cross sections directly, although their functional form is retained. Instead, a special type of tally derived from a deterministic estimate of Fick's Law is used for tallying the total cross section, which is then combined with a set of other standard Monte Carlo tallies. Some properties of this method are presented by means of numerical examples for a multi-group 1-D implementation. Calculated diffusion coefficients are in general good agreement with values obtained by other methods.

Dorval, Eric

2014-06-01

220

Extended state-space Monte Carlo methods Sheldon B. Opps and Jeremy Schofield

. The methods developed in this article, which are based upon a statistical quenching and heating procedure distribution. In particular, MC methods have been fre- quently utilized in the field of statistical physicsExtended state-space Monte Carlo methods Sheldon B. Opps and Jeremy Schofield Chemical Physics

Schofield, Jeremy

221

Green Function Monte Carlo Method for Excited States of Quantum System

A novel scheme to solve the quantum eigenvalue problem through the imaginary-time Green function Monte Carlo method is presented. This method is applicable to the excited states as well as to the ground state of a generic system. We demonstrate the validity of the method with the numerical examples on three simple systems including a discretized sine-Gordon model.

Taksu Cheon

1996-01-06

222

The S/sub N//Monte Carlo response matrix hybrid method

A hybrid method has been developed to iteratively couple S/sub N/ and Monte Carlo regions of the same problem. This technique avoids many of the restrictions and limitations of previous attempts to do the coupling and results in a general and relatively efficient method. We demonstrate the method with some simple examples.

Filippone, W.L.; Alcouffe, R.E.

1987-01-01

223

Monte Carlo Methods to Model Radiation Interactions and Induced Damage

NASA Astrophysics Data System (ADS)

This review is devoted to the analysis of some Monte Carlo (MC) simulation programmes which have been developed to describe radiation interaction with biologically relevant materials. Current versions of the MC codes Geant4 (GEometry ANd Tracking 4), PENELOPE (PENetration and Energy Loss of Positrons and Electrons), EPOTRAN (Electron and POsitron TRANsport), and LEPTS (Low-Energy Particle Track Simulation) are described. Mean features of each model, as the type of radiation to consider, the energy range covered by primary and secondary particles, the type of interactions included in the simulation and the considered target geometries are discussed. Special emphasis lies on recent developments that, together with (still emerging) new databases that include adequate data for biologically relevant materials, bring us continuously closer to a realistic, physically meaningful description of radiation damage in biological tissues.

Muñoz, Antonio; Fuss, Martina C.; Cortés-Giraldo, M. A.; Incerti, Sébastien; Ivanchenko, Vladimir; Ivanchenko, Anton; Quesada, J. M.; Salvat, Francesc; Champion, Christophe; Gómez-Tejedor, Gustavo García

224

On Monte Carlo and molecular dynamics methods inspired by Tsallis statistics: Methodology Generalized Monte Carlo and molecular dynamics algorithms which provide enhanced sampling of the phase space is made with standard Metropolis Monte Carlo and the J-walking algorithm of Franz, Freeman and Doll

Straub, John E.

225

Multivariate Monte Carlo Methods for the Reflection Grating Spectrometers on XMM-Newton

We propose a novel multivariate Monte Carlo method as an efficient and flexible approach to analyzing extended X-ray sources with the Reflection Grating Spectrometer (RGS) on XMM Newton. A multi-dimensional interpolation method is used to efficiently calculate the response function for the RGS in conjunction with an arbitrary spatially-varying spectral model. Several methods of event comparison that effectively compare the multivariate RGS data are discussed. The use of a multi-dimensional instrument Monte Carlo also creates many opportunities for the use of complex astrophysical Monte Carlo calculations in diffuse X-ray spectroscopy. The methods presented here could be generalized to other X-ray instruments as well.

Peterson, J.

2004-11-10

226

Multivariate Monte Carlo Methods for the Reflection Grating Spectrometers on XMM-Newton

We propose a novel multivariate Monte Carlo method as an efficient and flexible approach to analyzing extended X-ray sources with the Reflection Grating Spectrometer (RGS) on XMM Newton. A multi-dimensional interpolation method is used to efficiently calculate the response function for the RGS in conjunction with an arbitrary spatially-varying spectral model. Several methods of event comparison that effectively compare the multivariate RGS data are discussed. The use of a multi-dimensional instrument Monte Carlo also creates many opportunities for the use of complex astrophysical Monte Carlo calculations in diffuse X-ray spectroscopy. The methods presented here could be generalized to other X-ray instruments as well.

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

2004-10-26

227

Clock Quantum Monte Carlo: an imaginary-time method for real-time quantum dynamics

In quantum information theory, there is an explicit mapping between general unitary dynamics and Hermitian ground state eigenvalue problems known as the Feynman-Kitaev Clock. A prominent family of methods for the study of quantum ground states are quantum Monte Carlo methods, and recently the full configuration interaction quantum Monte Carlo (FCIQMC) method has demonstrated great promise for practical systems. We combine the Feynman-Kitaev Clock with FCIQMC to formulate a new technique for the study of quantum dynamics problems. Numerical examples using quantum circuits are provided as well as a technique to further mitigate the sign problem through time-dependent basis rotations. Moreover, this method allows one to combine the parallelism of Monte Carlo techniques with the locality of time to yield an effective parallel-in-time simulation technique.

Jarrod R. McClean; Alán Aspuru-Guzik

2014-10-07

228

Clock quantum Monte Carlo technique: An imaginary-time method for real-time quantum dynamics

NASA Astrophysics Data System (ADS)

In quantum information theory, there is an explicit mapping between general unitary dynamics and Hermitian ground-state eigenvalue problems known as the Feynman-Kitaev clock Hamiltonian. A prominent family of methods for the study of quantum ground states is quantum Monte Carlo methods, and recently the full configuration interaction quantum Monte Carlo (FCIQMC) method has demonstrated great promise for practical systems. We combine the Feynman-Kitaev clock Hamiltonian with FCIQMC to formulate a technique for the study of quantum dynamics problems. Numerical examples using quantum circuits are provided as well as a technique to further mitigate the sign problem through time-dependent basis rotations. Moreover, this method allows one to combine the parallelism of Monte Carlo techniques with the locality of time to yield an effective parallel-in-time simulation technique.

McClean, Jarrod R.; Aspuru-Guzik, Alán

2015-01-01

229

Tackling the Fermionic Sign Problem in the Auxiliary-Field Monte Carlo Method

We explore a novel and straightforward solution to the sign problem that has plagued the Auxiliary-field Monte Carlo (AFMC) method applied to many-body systems for more than a decade. We present a solution to the sign problem that has plagued the Auxiliary-field Monte Carlo (AFMC) method for more than a decade and report a breakthrough where excellent agreement between AFMC and exact CI calculations for fully realistic nuclear applications is achieved. This result offers the capability, unmatched by other methods, to achieve exact solutions for large-scale quantum many-body systems.

G. Stoitcheva; W. E. Ormand; D. Neuhauser; D. J. Dean

2007-08-22

230

Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the SHIFT Monte Carlo code within the Scale code package. The methods were used for several simple test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods.

Perfetti, Christopher M [ORNL] [ORNL; Martin, William R [University of Michigan] [University of Michigan; Rearden, Bradley T [ORNL] [ORNL; Williams, Mark L [ORNL] [ORNL

2012-01-01

231

NASA Astrophysics Data System (ADS)

The scaling Monte Carlo method and Gaussian model are applied to simulate the transportation of light beam with arbitrary waist radius. Much of the time, Monte Carlo simulation is performed for pencil or cone beam where the initial status of the photon is identical. In practical application, incident light is always focused on the sample to form approximate Gauss distribution on the surface. With alteration of focus position in the sample, the initial status of the photon will not be identical any more. Using the hyperboloid method, the initial reflect angle and coordinates are generated statistically according to the size of Gaussian waist and focus depth. Scaling calculation is performed with baseline data from standard Monte Carlo simulation. The scaling method incorporated with the Gaussian model was tested, and proved effective over a range of scattering coefficients from 20% to 180% relative to the value used in baseline simulation. In most cases, percentage error was less than 10%. The increasing of focus depth will result in larger error of scaled radial reflectance in the region close to the optical axis. In addition to evaluating accuracy of scaling the Monte Carlo method, this study has given implications for inverse Monte Carlo with arbitrary parameters of optical system.

Lin, Lin; Zhang, Mei

2015-02-01

232

Markov chain Monte Carlo method for tracking myocardial borders

NASA Astrophysics Data System (ADS)

Cardiac magnetic resonance studies have led to a greater understanding of the pathophysiology of ischemic heart disease. Manual segmentation of myocardial borders, a major task in the data analysis of these studies, is a tedious and time consuming process subject to observer bias. Automated segmentation reduces the time needed to process studies and removes observer bias. We propose an automated segmentation algorithm that uses an active contour to capture the endo- and epicardial borders of the left ventricle in a mouse heart. The contour is initialized by computing the ellipse corresponding to the maximal gradient inverse of variation (GICOV) value. The GICOV is the mean divided by the normalized standard deviation of the image intensity gradient in the outward normal direction along the contour. The GICOV is maximal when the contour lies along strong, relatively constant gradients. The contour is then evolved until it maximizes the GICOV value subject to shape constraints. The problem is formulated in a Bayesian framework and is implemented using a Markov Chain Monte Carlo technique.

Janiczek, Robert; Ray, N.; Acton, Scott T.; Roy, R. J.; French, Brent A.; Epstein, F. H.

2005-03-01

233

We describe the detailed balance method of determining the chemical potential using molecular dynamics or Monte Carlo simulations. The method estimates a value for the chemical potential such that one has a balance between fictitious successful creation and destruction trials. The Monte Carlo method is used to determine success or failure of the creation\\/destruction attempts; we thus call the method

Patrick James Fay

1993-01-01

234

Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues

We introduce a novel and efficient method to provide solutions to inverse photon migration problems in hetero- geneous turbid media. The method extracts derivative information from a single Monte Carlo simulation to permit the rapid determination of rates of change in the detected photon signal with respect to perturbations in background tissue optical properties. We then feed this derivative information

Carole K. Hayakawa; Jerome Spanier; Frédéric Bevilacqua; Andrew K. Dunn; Joon S. You; Bruce J. Tromberg; Vasan Venugopalan

2001-01-01

235

On the use of low discrepancy sequences in Monte Carlo methods

Quasi-random (or low discrepancy) sequences are sequences for which the convergence to the uniform distribution on occurs rapidly. Such sequences are used in quasi-Monte Carlo methods for which the convergence speed, with respect to the first terms of the sequence, is in , where is the mathematical dimension of the problem considered. The disadvan- tage of these methods is that

Bruno Tuffin

1996-01-01

236

In providing a method for solving non-linear optimization problems Monte Carlo techniques avoid the need for linearization but, in practice, are often prohibitive because of the large number of models that must be considered. A new class of methods known as Genetic Algorithms have recently been devised in the field of Artificial Intelligence. We outline the basic concept of genetic

Kerry Gallagher; Malcolm Sambridge; Guy Drijkoningen

1991-01-01

237

A Monte Carlo Study of Eight Confidence Interval Methods for Coefficient Alpha

ERIC Educational Resources Information Center

The purpose of this research is to examine eight of the different methods for computing confidence intervals around alpha that have been proposed to determine which of these, if any, is the most accurate and precise. Monte Carlo methods were used to simulate samples under known and controlled population conditions. In general, the differences in…

Romano, Jeanine L.; Kromrey, Jeffrey D.; Hibbard, Susan T.

2010-01-01

238

Sampling uncertainty evaluation for data acquisition board based on Monte Carlo method

NASA Astrophysics Data System (ADS)

Evaluating the data acquisition board sampling uncertainty is a difficult problem in the field of signal sampling. This paper analyzes the sources of dada acquisition board sampling uncertainty in the first, then introduces a simulation theory of dada acquisition board sampling uncertainty evaluation based on Monte Carlo method and puts forward a relation model of sampling uncertainty results, sampling numbers and simulation times. In the case of different sample numbers and different signal scopes, the author establishes a random sampling uncertainty evaluation program of a PCI-6024E data acquisition board to execute the simulation. The results of the proposed Monte Carlo simulation method are in a good agreement with the GUM ones, and the validities of Monte Carlo method are represented.

Ge, Leyi; Wang, Zhongyu

2008-10-01

239

NASA Astrophysics Data System (ADS)

This paper presents the calculation of ultrasonic beam parameters focal distance, focal length, and focal widths on X-axis and Y-axis for non-destructive testing probes. The measurement uncertainties were estimated using Monte Carlo Method, and compared to those obtained using Guide to the expression of uncertainty in measurement (GUM) approach. The results show that the mean values and the combined uncertainties are identical, but the probabilistically symmetric 95 % coverage intervals determined on the basis of the GUM uncertainty framework were more conservative than the ones achieved using Monte Carlo Method. Moreover, the calculation of the numerical tolerance between the coverage intervals obtained from Monte Carlo Method and GUM shows they are statistically different. Hence, a more conservative uncertainty approach will be achieved using GUM uncertainty framework.

Alvarenga, A. V.; Silva, C. E. R.; Costa-Felix, R. P. B.

2012-05-01

240

Methods of Monte Carlo electron transport in particle-in-cell codes

An algorithm has been implemented in CCUBE and ISIS to treat electron transport in materials using a Monte Carlo method in addition to the electron dynamics determined by the self-consistent electromagnetic, relativistic, particle-in-cell simulation codes that have been used extensively to model generation of electron beams and intense microwave production. Incorporation of a Monte Carlo method to model the transport of electrons in materials (conductors and dielectrics) in a particle-in-cell code represents a giant step toward realistic simulation of the physics of charged-particle beams. The basic Monte Carlo method used in the implementation includes both scattering of electrons by background atoms and energy degradation.

Kwan, T.J.T.; Snell, C.M.

1985-01-01

241

Monte Carlo Method for Real-Time Path Integration

We describe a stochastic quadrature method that is designed for the evaluation of generalized, complex averages. Motivated by recent advances in spare sampling techniques, this method is based on a combination of parallel tempering and stationary phase filtering methods. Numerical application of the resulting ``stationary tempering'' approach is presented.

Dubravko Sabo; J. D. Doll; David L. Freeman

2003-01-01

242

Monte Carlo Method for Real-Time Path Integration

We describe a stochastic quadrature method that is designed for the evaluation of generalized, complex averages. Motivated by recent advances in spare sampling techniques, this method is based on a combination of parallel tempering and stationary phase filtering methods. Numerical application of the resulting “stationary tempering” approach is presented.

Dubravko Sabo; J. D. Doll; David L. Freeman

2003-01-01

243

Monte Carlo Method for Real-Time Path Integration

NASA Astrophysics Data System (ADS)

We describe a stochastic quadrature method that is designed for the evaluation of generalized, complex averages. Motivated by recent advances in spare sampling techniques, this method is based on a combination of parallel tempering and stationary phase filtering methods. Numerical application of the resulting "stationary tempering" approach is presented.

Sabo, Dubravko; Doll, J. D.; Freeman, David L.

2003-11-01

244

On sequential Monte Carlo sampling methods for Bayesian filtering

In this article, we present an overview of methods for sequential simulation from posterior distribu- tions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is devel- oped that unifies many of the methods which have been proposed over the last few decades in

ARNAUD DOUCET; SIMON GODSILL; CHRISTOPHE ANDRIEU

2000-01-01

245

We present a new algorithm for calculating the Renyi entanglement entropy of interacting fermions using the continuous-time quantum Monte Carlo method. The algorithm only samples the interaction correction of the entanglement entropy, which by design ensures the efficient calculation of weakly interacting systems. Combined with Monte Carlo reweighting, the algorithm also performs well for systems with strong interactions. We demonstrate the potential of this method by studying the quantum entanglement signatures of the charge-density-wave transition of interacting fermions on a square lattice. PMID:25259962

Wang, Lei; Troyer, Matthias

2014-09-12

246

We present a new algorithm for calculating the Renyi entanglement entropy of interacting fermions using the continuous-time quantum Monte Carlo method. The algorithm only samples interaction correction of the entanglement entropy, which by design ensures efficient calculation of weakly interacting systems. Combined with Monte Carlo reweighting, the algorithm also performs well for systems with strong interactions. We demonstrate the potential of this method by studying the quantum entanglement signatures of the charge-density-wave transition of interacting fermions on a square lattice.

Lei Wang; Matthias Troyer

2014-07-02

247

Improved methods of handling massive tallies in reactor Monte Carlo Code RMC

Monte Carlo simulations containing a large number of tallies generally suffer severe performance penalties due to a significant amount of run time spent in searching for and scoring individual tally bins. This paper describes the improved methods of handling large numbers of tallies, which have been implemented in the RMC Monte Carlo code. The calculation results demonstrate that the proposed methods can considerably improve the tally performance when massive tallies are treated. In the calculated case with 6 million of tally regions, only 10% of run time is increased in each active cycle against each inactive cycle. (authors)

She, D.; Wang, K.; Sun, J.; Qiu, Y. [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China)

2013-07-01

248

Advantages of Analytical Transformations in Monte Carlo Methods for Radiation Transport

Monte Carlo methods for radiation transport typically attempt to solve an integral by directly sampling analog or weighted particles, which are treated as physical entities. Improvements to the methods involve better sampling, probability games or physical intuition about the problem. We show that significant improvements can be achieved by recasting the equations with an analytical transform to solve for new, non-physical entities or fields. This paper looks at one such transform, the difference formulation for thermal photon transport, showing a significant advantage for Monte Carlo solution of the equations for time dependent transport. Other related areas are discussed that may also realize significant benefits from similar analytical transformations.

McKinley, M S; Brooks III, E D; Daffin, F

2004-12-13

249

Uncertainties evaluations in the ray-tracing algorithm based on Monte Carlo method

NASA Astrophysics Data System (ADS)

Although Ray tracing method is an effective aided design method in optical system, the uncertainty caused by this method is not very clearly. The relationship between the number of rays and uncertainty has been explored in this paper, while using the Monte Carlo algorithm in Ray tracing method. It shows that if the simulation relative deviation should be limited to 0.1%, at least 1000000 rays must be used.

Feng, Guojin; Li, Ping; He, Yingwei; Wang, Yu; Wu, Houping

2014-08-01

250

A Hamiltonian Monte Carlo method for Bayesian Inference of Supermassive Black Hole Binaries

We investigate the use of a Hamiltonian Monte Carlo to map out the posterior density function for supermassive black hole binaries. While previous Markov Chain Monte Carlo (MCMC) methods, such as Metropolis-Hastings MCMC, have been successfully employed for a number of different gravitational wave sources, these methods are essentially random walk algorithms. The Hamiltonian Monte Carlo treats the inverse likelihood surface as a "gravitational potential" and by introducing canonical positions and momenta, dynamically evolves the Markov chain by solving Hamilton's equations of motion. We present an implementation of the Hamiltonian Markov Chain that is faster, and more efficient by a factor of approximately the dimension of the parameter space, than the standard MCMC.

Edward K. Porter; Jérôme Carré

2013-11-29

251

Revised methods for few-group cross sections generation in the Serpent Monte Carlo code

This paper presents new calculation methods, recently implemented in the Serpent Monte Carlo code, and related to the production of homogenized few-group constants for deterministic 3D core analysis. The new methods fall under three topics: 1) Improved treatment of neutron-multiplying scattering reactions, 2) Group constant generation in reflectors and other non-fissile regions and 3) Homogenization in leakage-corrected criticality spectrum. The methodology is demonstrated by a numerical example, comparing a deterministic nodal diffusion calculation using Serpent-generated cross sections to a reference full-core Monte Carlo simulation. It is concluded that the new methodology improves the results of the deterministic calculation, and paves the way for Monte Carlo based group constant generation. (authors)

Fridman, E. [Reactor Safety Div., Helmholz-Zentrum Dresden-Rossendorf, POB 51 01 19, Dresden, 01314 (Germany); Leppaenen, J. [VTT Technical Research Centre of Finland, POB 1000, FI-02044 VTT (Finland)

2012-07-01

252

A Monte Carlo method for an objective Bayesian procedure

This paper describes a method for an objective selection of the optimal prior distribution, or for adjusting its hyper-parameter, among the competing priors for a variety of Bayesian models. In order to implement this method, the integration of very high dimensional functions is required to get the normalizing constants of the posterior and even of the prior distribution. The logarithm

Yosihiko Ogata

1990-01-01

253

A multi-group Monte Carlo core analysis method and its application in SCWR design

Complex geometry and spectrum have been the characteristics of many newly developed nuclear energy systems, so the suitability and precision of the traditional deterministic codes are doubtable while being applied to simulate these systems. On the contrary, the Monte Carlo method has the inherent advantages of dealing with complex geometry and spectrum. The main disadvantage of Monte Carlo method is that it takes long time to get reliable results, so the efficiency is too low for the ordinary core designs. A new Monte Carlo core analysis scheme is developed, aimed to increase the calculation efficiency. It is finished in two steps: Firstly, the assembly level simulation is performed by continuous energy Monte Carlo method, which is suitable for any geometry and spectrum configuration, and the assembly multi-group constants are tallied at the same time; Secondly, the core level calculation is performed by multi-group Monte Carlo method, using the assembly group constants generated in the first step. Compared with the heterogeneous Monte Carlo calculations of the whole core, this two-step scheme is more efficient, and the precision is acceptable for the preliminary analysis of novel nuclear systems. Using this core analysis scheme, a SCWR core was designed based on a new SCWR assembly design. The core output is about 1,100 MWe, and a cycle length of about 550 EFPDs can be achieved with 3-batch refueling pattern. The average and maximum discharge burn-up are about 53.5 and 60.9 MWD/kgU respectively. (authors)

Zhang, P.; Wang, K.; Yu, G. [Dept. of Engineering Physics, Tsinghua Univ., Beijing, 100084 (China)

2012-07-01

254

A rare event sampling method for diffusion Monte Carlo using smart darting

NASA Astrophysics Data System (ADS)

We identify a set of multidimensional potential energy surfaces sufficiently complex to cause both the classical parallel tempering and the guided or unguided diffusion Monte Carlo methods to converge too inefficiently for practical applications. The mathematical model is constructed as a linear combination of decoupled Double Wells [(DDW)n]. We show that the set (DDW)n provides a serious test for new methods aimed at addressing rare event sampling in stochastic simulations. Unlike the typical numerical tests used in these cases, the thermodynamics and the quantum dynamics for (DDW)n can be solved deterministically. We use the potential energy set (DDW)n to explore and identify methods that can enhance the diffusion Monte Carlo algorithm. We demonstrate that the smart darting method succeeds at reducing quasiergodicity for n ? 100 using just 1 × 106 moves in classical simulations (DDW)n. Finally, we prove that smart darting, when incorporated into the regular or the guided diffusion Monte Carlo algorithm, drastically improves its convergence. The new method promises to significantly extend the range of systems computationally tractable by the diffusion Monte Carlo algorithm.

Roberts, K.; Sebsebie, R.; Curotto, E.

2012-02-01

255

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

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

2008-10-31

256

Sequential Monte Carlo Methods With Applications To Communication Channels

to achieve this by incorporating noisy observations as they become available with prior knowledge of the system model. Bayesian methods provide a general framework for dynamic state estimation problems. The central idea behind this recursive Bayesian...

Boddikurapati, Sirish

2010-07-14

257

Stabilizing Canonical-Ensemble Calculations in the Auxiliary-Field Monte Carlo Method

Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.

C. N. Gilbreth; Y. Alhassid

2014-02-14

258

We present a new, nondestructive, method for determining chemical potentials in Monte Carlo and molecular dynamics simulations. The method estimates a value for the chemical potential such that one has a balance between fictitious successful creation and destruction trials in which the Monte Carlo method is used to determine success or failure of the creation/destruction attempts; we thus call the method a detailed balance method. The method allows one to obtain estimates of the chemical potential for a given species in any closed ensemble simulation; the closed ensemble is paired with a natural'' open ensemble for the purpose of obtaining creation and destruction probabilities. We present results for the Lennard-Jones system and also for an embedded atom model of liquid palladium, and compare to previous results in the literature for these two systems. We are able to obtain an accurate estimate of the chemical potential for the Lennard-Jones system at higher densities than reported in the literature.

Fay, P.J.; Ray, J.R. (Department of Physics and Astronomy, Kinard Laboratory of Physics, Clemson University, Clemson, South Carolina 29634-1911 (United States)); Wolf, R.J. (Savannah River Technology Center, Westinghouse Savannah River Company, Aiken, South Carolina 29808 (United States))

1994-02-01

259

Advanced Markov Chain Monte Carlo Methods for Iterative (Turbo) Multiuser Detection

Recently, Markov Chain Monte Carlo (MCMC) sampling methods have evolved as new promising solutions to both multiuser and multiple-input multiple-output (MIMO) detection problems. Approaches based on Gibbs sampling as a special type of MCMC methods are well suited due to their good trade-off between performance and complexity. However, it is known that detection methods based on Gibbs sampling show a

Markus A. Dangl; Zhenning Shi; Mark C. Reed

260

A quasi-Monte Carlo method for computing double and other multiple integrals

The heuristic importance of the Monte Carlo method lies in the fact that it shows the possibility of computing numerically integrals in many dimensions by taking averages of integrand values at a number of points in such a way that, for a given degree of accuracy, this number does not depend substantially on the number of dimensions of the domain

S. K. Zaremba

1970-01-01

261

Quasi-Monte Carlo methods for elliptic PDEs with random coefficients and applications

We devise and implement quasi-Monte Carlo methods for computing the expectations of nonlinear functionals of solutions of a class of elliptic partial differential equations with random coefficients. Our motivation comes from fluid flow in random porous media, where relevant functionals include the fluid pressure\\/velocity at any point in space or the breakthrough time of a pollution plume being transported by

I. G. Graham; F. Y. Kuo; D. Nuyens; R. Scheichl; I. H. Sloan

2011-01-01

262

The Euler-Maruyama scheme is known to diverge strongly and numerically weakly when applied to nonlinear stochastic differential equations (SDEs) with superlinearly growing and globally one-sided Lipschitz continuous drift coefficients. Classical Monte Carlo simulations do, however, not suffer from this divergence behavior of Euler's method because this divergence behavior happens on rare events. Indeed, for such nonlinear SDEs the classical Monte

Martin Hutzenthaler; Arnulf Jentzen; Peter E. Kloeden

2011-01-01

263

In the present study, the robust thermal design of a power device package was accomplished using thermal conduction calculation, design of experiment, response surface method and Monte Carlo simulation. Initially, the effects of the design parameters on the solder strain were examined in terms of the thermal expansion difference as a result of unsteady thermal conduction simulation. From the factorial

Yasuyuki Yokono; Katsumi Hisano; Kenji Hirohata

2008-01-01

264

An Efficient Monte Carlo Method for Optimal Control Problems with Uncertainty

A general framework is proposed for what we call the sensitivity derivative Monte Carlo (SDMC) solution of optimal control problems with a stochastic parameter. This method employs the residual in the first-order Taylor series expansion of the cost functional in terms of the stochastic parameter rather than the cost functional itself. A rigorous estimate is derived for the variance of

Yanzhao Cao; M. Y. Hussaini; T. A. Zang

2003-01-01

265

Study of CANDU Thorium-based Fuel Cycles by Deterministic and Monte Carlo Methods

Study of CANDU Thorium-based Fuel Cycles by Deterministic and Monte Carlo Methods A. Nuttin1 , P, there is a renewal of interest in self-sustainable thorium fuel cycles applied to various concepts such as Molten here, with a shorter term view, to re-evaluate the economic competitiveness of once-through thorium

Paris-Sud XI, UniversitÃ© de

266

A convergence proof for Bird's direct simulation Monte Carlo method for the Boltzmann equation

Bird's direct simulation Monte Carlo method for the Boltzmann equation is considered. The limit (as the number of particles tends to infinity) of the random empirical measures associated with the Bird algorithm is shown to be a deterministic measure-valued function satisfying an equation close (in a certain sense) to the Boltzmann equation. A Markov jump process is introduced, which is

Wolfgang Wagner

1992-01-01

267

Multiple target tracking using Sequential Monte Carlo Methods and statistical data association

This paper presents two approaches for the problem of multiple target tracking (MTT) and specifically people tracking. Both filters are based on sequential Monte Carlo methods (SMCM) and joint probability data association (JPDA). The filters have been implemented and tested on real data from a laser measurement system. Experiments show that both approaches are able to track multiple moving persons.

Oliver Frank; J uan Nieto; Jose Guivant; Steve Scheding

2003-01-01

268

A Monte Carlo Method for the PDF Equations of Turbulent Reactive Flow

—A Monte Carlo method is presented which simulates the transport equations of joint probability density functions (pdf's) in turbulent flows. (Finite-difference solutions of the equations are impracticable, mainly because of the large dimensionality of the pdf's). Attention is focused on an equation for the joint pdf of chemical and thermodynamic properties in turbulent reactive flows. It is shown that the

S. B. POPE

1981-01-01

269

A Comparison of Four Monte Carlo Methods for Estimating the Probability of s-t Connectedness

This paper describes and compares the performance of four alternative Monte Carlo sampling plans for estimating the probability that two nodes, s and t, are connected in an undirected network whose arcs fail randomly and independently. Models of this type are commonly used when computing the reliability of a system of randomly failing components. The first method, dagger sampling, relies

George S. Fishman

1986-01-01

270

Analyses of infectious disease data from household outbreaks by Markov chain Monte Carlo methods

This paper exploresthe use of Markov chain Monte Carlo (MCMC) methods for the analysis ofinfectious disease data, with the hope that they will permit analyses to be madeunder more realistic assumptions. Two important kinds of data sets are considered,containing temporal and non-temporal information respectively, from outbreaks ofmeasles and influenza. Stochastic epidemic models are used to describe the processesthat generate the

Philip D. ONeill; David J. Balding; Niels G. Becker; Mervi Eerola; Denis Mollison

2000-01-01

271

Simulations for gas flows in microgeometries using the direct simulation Monte Carlo method

Micro gas flows are often encountered in MEMS devices and classical CFD could not accurately predict the flow and thermal behavior due to the high Knudsen number. Therefore, the gas flow in microgeometries was investigated using the direct simulation Monte Carlo (DSMC) method. New treatments for boundary conditions are verified by simulations of micro-Poiseuille flow, compared with the previous boundary

Moran Wang; Zhixin Li

2004-01-01

272

Quasi-Monte Carlo Methods in Computer Graphics: The Global Illumination Problem

The main part of the global illumination problem of computer graphics is given by a Fredholm integral equation of the second kind, describing the light distribution in a closed environment. Calculating photorealistic images from that equation requires its kernel to be very complex and discontinuous. Due to this complexity Monte Carlo methods are an interesting tool for estimating a solution.

Alexander Keller

1995-01-01

273

Scalar and Parallel Optimized Implementation of the Direct Simulation Monte Carlo Method

This paper describes a new concept for the implementation of the direct simulation Monte Carlo (DSMC) method. It uses a localized data structure based on a computational cell to achieve high performance, especially on workstation processors, which can also be used in parallel. Since the data structure makes it possible to freely assign any cell to any processor, a domain

Stefan Dietrich; Iain D. Boyd

1996-01-01

274

Markov Chain Monte Carlo Methods and the Label Switching Problem in Bayesian Mixture Modeling

In the past ten years there has been a dramatic increase of interest in the Bayesian analysis of finite mixture models. This is primarily because of the emergence of Markov chain Monte Carlo (MCMC) methods. While MCMC provides a convenient way to draw inference from complicated statistical models, there are many, perhaps underappreciated, problems associated with the MCMC analysis of

A. Jasra; C. C. Holmes; D. A. Stephens

2005-01-01

275

In 1988, Felsenstein described a framework for assessing the likelihood of a genetic data set in which all of the possible genealogical histories of the data are considered, each in proportion to their probability. Although not analytically solvable, several approaches, including Markov chain Monte Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which

Jody Hey; Rasmus Nielsen

2007-01-01

276

Bayesian Phylogenetic Inference Using DNA Sequences: A Markov Chain Monte Carlo Method

An improved Bayesian method is presented for estimating phylogenetic trees using DNA sequence data. The birth- death process with species sampling is used to specify the prior distribution of phylogenies and ancestral speciation times, and the posterior probabilities of phylogenies are used to estimate the maximum posterior probability (MAP) tree. Monte Carlo integration is used to integrate over the ancestral

Ziheng Yang; Bruce Rannala

277

Comparison of Monte-Carlo and Einstein methods in the light-gas interactions

To study the propagation of light in nebulae, many astrophysicists use a Monte-Carlo computation which does not take interferences into account. Replacing the wrong method by Einstein coefficients theory gives, on an example, a theoretical spectrum much closer to the observed one.

Jacques Moret-Bailly

2010-01-18

278

Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water

ERIC Educational Resources Information Center

Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…

Gergely, John Robert

2009-01-01

279

Mechanical behavior of strands in CIC conductor analyzed by Monte Carlo method

The computer simulation of mechanical behavior of strands in a cable-in-conduit (CIC) conductor analyzed by Monte Carlo method has been carried out for analyzing the stability of the CIC conductor. In the CIC conductor, the mechanical behavior of strands during energizing has not been evaluated sufficiently and hence the quantitative evaluation of the frictional heating, the contact stress between strands

Tomoki Sasaki; Shigehiro Nishijima

1999-01-01

280

for shallow wa- ter tracking that is based on a widely used motion model and the shallow water sound fieldSEQUENTIAL MONTE CARLO METHODS FOR SHALLOW WATER TRACKING USING MULTIPLE SENSORS WITH ADAPTIVE framework for tracking problems in shallow water environments where the conventional plane-wave assumptions

Nehorai, Arye

281

ERIC Educational Resources Information Center

The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…

Kim, Jee-Seon; Bolt, Daniel M.

2007-01-01

282

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel computational devices that can be housed in conventional desktop and laptop computers and can be thought of as prototypes of the next generation of many-core processors. For certain classes of population-based Monte Carlo algorithms they offer massively parallel simulation, with the added advantage over conventional distributed multi-core processors that they are cheap, easily accessible, easy to maintain, easy to code, dedicated local devices with low power consumption. On a canonical set of stochastic simulation examples including population-based Markov chain Monte Carlo methods and Sequential Monte Carlo methods, we nd speedups from 35 to 500 fold over conventional single-threaded computer code. Our findings suggest that GPUs have the potential to facilitate the growth of statistical modelling into complex data rich domains through the availability of cheap and accessible many-core computation. We believe the speedup we observe should motivate wider use of parallelizable simulation methods and greater methodological attention to their design. PMID:22003276

Lee, Anthony; Yau, Christopher; Giles, Michael B; Doucet, Arnaud; Holmes, Christopher C

2010-12-01

283

Generalized Moment Method for Gap Estimation and Quantum Monte Carlo Level Spectroscopy

We formulate a convergent sequence for the gap estimation in the worldline quantum Monte Carlo method. The ambiguity left in the conventional gap calculation for quantum systems is eliminated. The level spectroscopy from quantum Monte Carlo data is developed as an application of the unbiased gap estimation. From the spectrum analysis, we precisely determine the Kosterlitz-Thouless type quantum phase transition point in the spin-Peierls model as $\\lambda_{\\rm c} = 0.2245 \\pm 0.0017$ for phonon frequency $\\omega=1/4$. We demonstrate that the criticality at the transition point is described by the $k=1$ $SU(2)$ Wess-Zumino-Witten model.

Hidemaro Suwa; Synge Todo

2014-01-31

284

Electrical conductivity of high-pressure liquid hydrogen by quantum Monte Carlo methods.

We compute the electrical conductivity for liquid hydrogen at high pressure using Monte Carlo techniques. The method uses coupled electron-ion Monte Carlo simulations to generate configurations of liquid hydrogen. For each configuration, correlated sampling of electrons is performed in order to calculate a set of lowest many-body eigenstates and current-current correlation functions of the system, which are summed over in the many-body Kubo formula to give ac electrical conductivity. The extrapolated dc conductivity at 3000 K for several densities shows a liquid semiconductor to liquid-metal transition at high pressure. Our results are in good agreement with shock-wave data. PMID:20366267

Lin, Fei; Morales, Miguel A; Delaney, Kris T; Pierleoni, Carlo; Martin, Richard M; Ceperley, D M

2009-12-18

285

Power Analysis for Complex Mediational Designs Using Monte Carlo Methods

ERIC Educational Resources Information Center

Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex…

Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

2010-01-01

286

MCMs: Early History and The Basics Monte Carlo Methods

detonation 2. The People: Enrico Fermi, Stan Ulam, John von Neumann, Nick Metropolis, Edward Teller, ... 3 people to work on the fission problem: The Physicists 1. Enrico Fermi: experimental Nuclear Physics out to be "fudged" In the 1930's, Fermi used sampling methods to estimate quantities involved

Mascagni, Michael

287

On performance measures for infinite swapping Monte Carlo methods

NASA Astrophysics Data System (ADS)

We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications, we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters.

Doll, J. D.; Dupuis, Paul

2015-01-01

288

Applications of Malliavin calculus to Monte Carlo methods in finance

. This paper presents an original probabilistic method for the numerical computations of Greeks (i.e. price sensitivities)\\u000a in finance. Our approach is based on the {\\\\it integration-by-parts} formula, which lies at the core of the theory of variational\\u000a stochastic calculus, as developed in the Malliavin calculus. The Greeks formulae, both with respect to initial conditions\\u000a and for smooth perturbations of

Eric Fournié; Jean-Michel Lasry; Jérôme Lebuchoux; Pierre-Louis Lions; Nizar Touzi

1999-01-01

289

On performance measures for infinite swapping Monte Carlo methods.

We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications, we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters. PMID:25591342

Doll, J D; Dupuis, Paul

2015-01-14

290

A Monte Carlo implementation of the predictor-corrector Quasi-Static method

The Quasi-Static method (QS) is a useful tool for solving reactor transients since it allows for larger time steps when updating neutron distributions. Because of the beneficial attributes of Monte Carlo (MC) methods (exact geometries and continuous energy treatment), it is desirable to develop a MC implementation for the QS method. In this work, the latest version of the QS method known as the Predictor-Corrector Quasi-Static method is implemented. Experiments utilizing two energy-groups provide results that show good agreement with analytical and reference solutions. The method as presented can easily be implemented in any continuous energy, arbitrary geometry, MC code. (authors)

Hackemack, M. W.; Ragusa, J. C. [Department of Nuclear Engineering, Texas A and M University, 337 Zachry Engineering Building, College Station, TX 77843 (United States); Griesheimer, D. P.; Pounders, J. M. [Bettis Atomic Laboratory, Bechtel Marine Propulsion Corporation, P.O. Box 79, West Mifflin, PA 15122 (United States)

2013-07-01

291

NASA Astrophysics Data System (ADS)

This study evaluated the Monte Carlo method for determining the dose calculation in fluoroscopy by using a realistic human phantom. The dose was calculated by using Monte Carlo N-particle extended (MCNPX) in simulations and was measured by using Korean Typical Man-2 (KTMAN-2) phantom in the experiments. MCNPX is a widely-used simulation tool based on the Monte-Carlo method and uses random sampling. KTMAN-2 is a virtual phantom written in MCNPX language and is based on the typical Korean man. This study was divided into two parts: simulations and experiments. In the former, the spectrum generation program (SRS-78) was used to obtain the output energy spectrum for fluoroscopy; then, each dose to the target organ was calculated using KTMAN-2 with MCNPX. In the latter part, the output of the fluoroscope was calibrated first and TLDs (Thermoluminescent dosimeter) were inserted in the ART (Alderson Radiation Therapy) phantom at the same places as in the simulation. Thus, the phantom was exposed to radiation, and the simulated and the experimental doses were compared. In order to change the simulation unit to the dose unit, we set the normalization factor (NF) for unit conversion. Comparing the simulated with the experimental results, we found most of the values to be similar, which proved the effectiveness of the Monte Carlo method in fluoroscopic dose evaluation. The equipment used in this study included a TLD, a TLD reader, an ART phantom, an ionization chamber and a fluoroscope.

Kim, Minho; Lee, Hyounggun; Kim, Hyosim; Park, Hongmin; Lee, Wonho; Park, Sungho

2014-03-01

292

A Hamiltonian Monte-Carlo method for Bayesian inference of supermassive black hole binaries

NASA Astrophysics Data System (ADS)

We investigate the use of a Hamiltonian Monte-Carlo to map out the posterior density function for supermassive black hole binaries. While previous Markov Chain Monte-Carlo (MCMC) methods, such as Metropolis-Hastings MCMC, have been successfully employed for a number of different gravitational wave sources, these methods are essentially random walk algorithms. The Hamiltonian Monte-Carlo treats the inverse likelihood surface as a ‘gravitational potential’ and by introducing canonical positions and momenta, dynamically evolves the Markov chain by solving Hamilton's equations of motion. This method is not as widely used as other MCMC algorithms due to the necessity of calculating gradients of the log-likelihood, which for most applications results in a bottleneck that makes the algorithm computationally prohibitive. We circumvent this problem by using accepted initial phase-space trajectory points to analytically fit for each of the individual gradients. Eliminating the waveform generation needed for the numerical derivatives reduces the total number of required templates for a {{10}^{6}} iteration chain from \\sim {{10}^{9}} to \\sim {{10}^{6}}. The result is in an implementation of the Hamiltonian Monte-Carlo that is faster, and more efficient by a factor of approximately the dimension of the parameter space, than a Hessian MCMC.

Porter, Edward K.; Carré, Jérôme

2014-07-01

293

Comparison of Monte Carlo and discrete ordinates methods in a three-dimensional well-logging problem

In this paper, the authors compare the Monte Carlo and the two discrete ordinates methods (nodal and conventional) in the benchmark well-logging problem. Although the problem is prototypical of well-logging systems, it severely tests the capabilities of transport methods. The Monte Carlo calculations were performed with the Los Alamos code, MCNP. The discrete ordinates calculations were performed using the Schlumberger

A. Badruzzaman; J. Chiaramonte

1985-01-01

294

Monte-Carlo methods make Dempster-Shafer formalism feasible

NASA Technical Reports Server (NTRS)

One of the main obstacles to the applications of Dempster-Shafer formalism is its computational complexity. If we combine m different pieces of knowledge, then in general case we have to perform up to 2(sup m) computational steps, which for large m is infeasible. For several important cases algorithms with smaller running time were proposed. We prove, however, that if we want to compute the belief bel(Q) in any given query Q, then exponential time is inevitable. It is still inevitable, if we want to compute bel(Q) with given precision epsilon. This restriction corresponds to the natural idea that since initial masses are known only approximately, there is no sense in trying to compute bel(Q) precisely. A further idea is that there is always some doubt in the whole knowledge, so there is always a probability p(sub o) that the expert's knowledge is wrong. In view of that it is sufficient to have an algorithm that gives a correct answer a probability greater than 1-p(sub o). If we use the original Dempster's combination rule, this possibility diminishes the running time, but still leaves the problem infeasible in the general case. We show that for the alternative combination rules proposed by Smets and Yager feasible methods exist. We also show how these methods can be parallelized, and what parallelization model fits this problem best.

Kreinovich, Vladik YA.; Bernat, Andrew; Borrett, Walter; Mariscal, Yvonne; Villa, Elsa

1991-01-01

295

An efficient two-stage Markov chain Monte Carlo method for dynamic data integration

NASA Astrophysics Data System (ADS)

In this paper, we use a two-stage Markov chain Monte Carlo (MCMC) method for subsurface characterization that employs coarse-scale models. The purpose of the proposed method is to increase the acceptance rate of MCMC by using inexpensive coarse-scale runs based on single-phase upscaling. Numerical results demonstrate that our approach leads to a severalfold increase in the acceptance rate and provides a practical approach to uncertainty quantification during subsurface characterization.

Efendiev, Y.; Datta-Gupta, A.; Ginting, V.; Ma, X.; Mallick, B.

2005-12-01

296

Multivariate Monte Carlo Methods for the Reflection Grating Spectrometers on XMM-Newton

We propose a novel multivariate Monte Carlo method as an efficient and\\u000aflexible approach to analyzing extended X-ray sources with the Reflection\\u000aGrating Spectrometer (RGS) on XMM Newton. A multi-dimensional interpolation\\u000amethod is used to efficiently calculate the response function for the RGS in\\u000aconjunction with an arbitrary spatially-varying spectral model. Several methods\\u000aof event comparison that effectively compare the

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

2004-01-01

297

Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the Shift Monte Carlo code within the SCALE code package. The methods were used for two small-scale test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods. (authors)

Perfetti, C.; Martin, W. [Univ. of Michigan, Dept. of Nuclear Engineering and Radiological Sciences, 2355 Bonisteel Boulevard, Ann Arbor, MI 48109-2104 (United States); Rearden, B.; Williams, M. [Oak Ridge National Laboratory, Reactor and Nuclear Systems Div., Bldg. 5700, P.O. Box 2008, Oak Ridge, TN 37831-6170 (United States)

2012-07-01

298

NASA Astrophysics Data System (ADS)

Image formation in fluorescence diffuse optical tomography is critically dependent on construction of the Jacobian matrix. For clinical and preclinical applications, because of the highly heterogeneous characteristics of the medium, Monte Carlo methods are frequently adopted to construct the Jacobian. Conventional adjoint Monte Carlo method typically compute the Jacobian by multiplying the photon density fields radiated from the source at the excitation wavelength and from the detector at the emission wavelength. Nonetheless, this approach assumes that the source and the detector in Green's function are reciprocal, which is invalid in general. This assumption is particularly questionable in small animal imaging, where the mean free path length of photons is typically only one order of magnitude smaller than the representative dimension of the medium. We propose a new method that does not rely on the reciprocity of the source and the detector by tracing photon propagation entirely from the source to the detector. This method relies on the perturbation Monte Carlo theory to account for the differences in optical properties of the medium at the excitation and the emission wavelengths. Compared to the adjoint methods, the proposed method is more valid in reflecting the physical process of photon transport in diffusive media and is more efficient in constructing the Jacobian matrix for densely sampled configurations.

Zhang, Xiaofeng

2012-03-01

299

A New Monte Carlo Method and Its Implications for Generalized Cluster Algorithms

We describe a novel switching algorithm based on a ``reverse'' Monte Carlo method, in which the potential is stochastically modified before the system configuration is moved. This new algorithm facilitates a generalized formulation of cluster-type Monte Carlo methods, and the generalization makes it possible to derive cluster algorithms for systems with both discrete and continuous degrees of freedom. The roughening transition in the sine-Gordon model has been studied with this method, and high-accuracy simulations for system sizes up to $1024^2$ were carried out to examine the logarithmic divergence of the surface roughness above the transition temperature, revealing clear evidence for universal scaling of the Kosterlitz-Thouless type.

C. H. Mak; Arun K. Sharma

2007-04-12

300

On a Monte Carlo method for measurement uncertainty evaluation and its implementation

NASA Astrophysics Data System (ADS)

The ‘Guide to the Expression of Uncertainty in Measurement’ (GUM) provides a framework and procedure for evaluating and expressing measurement uncertainty. The procedure has two main limitations. Firstly, the way a coverage interval is constructed to contain values of the measurand with a stipulated coverage probability is approximate. Secondly, insufficient guidance is given for the multivariate case in which there is more than one measurand. In order to address these limitations, two specific guidance documents (or ‘Supplements to the GUM’) on, respectively, a Monte Carlo method for uncertainty evaluation (Supplement 1) and extensions to any number of measurands (Supplement 2) have been published. A further document on developing and using measurement models in the context of uncertainty evaluation (Supplement 3) is also planned, but not considered in this paper. An overview is given of these guidance documents. In particular, a Monte Carlo method, which is the focus of Supplements 1 and 2, is described as a numerical approach to implement the ‘propagation of distributions’ formulated using the ‘change of variables formula’. Although applying a Monte Carlo method is conceptually straightforward, some of the practical aspects of using the method are considered, such as the choice of the number of trials and ensuring an implementation is memory-efficient. General comments about the implications of using the method in measurement and calibration services, such as the need to achieve transferability of measurement results, are made.

Harris, P. M.; Cox, M. G.

2014-08-01

301

A comparison of the Monte Carlo and the flux gradient method for atmospheric diffusion

In order to model the dispersal of atmospheric pollutants in the planetary boundary layer, various methods of parameterizing turbulent diffusion have been employed. The purpose of this paper is to use a three-dimensional particle-in-cell transport and diffusion model to compare the Markov chain (Monte Carlo) method of statistical particle diffusion with the deterministic flux gradient (K-theory) method. The two methods are heavily used in the study of atmospheric diffusion under complex conditions, with the Monte Carlo method gaining in popularity partly because of its more direct application of turbulence parameters. The basis of comparison is a data set from night-time drainage flow tracer experiments performed by the US Department of Energy Atmospheric Studies in Complex Terrain (ASCOT) program at the Geysers geothermal region in northern California. The Atmospheric Diffusion Particle-In-Cell (ADPIC) model used is the main model in the Lawrence Livermore National Laboratory emergency response program: Atmospheric Release Advisory Capability (ARAC). As a particle model, it can simulate diffusion in both the flux gradient and Monte Carlo modes. 9 refs., 6 figs.

Lange, R.

1990-05-01

302

Monte Carlo method of radiative transfer applied to a turbulent flame modeling with LES

NASA Astrophysics Data System (ADS)

Radiative transfer plays an important role in the numerical simulation of turbulent combustion. However, for the reason that combustion and radiation are characterized by different time scales and different spatial and chemical treatments, the radiation effect is often neglected or roughly modelled. The coupling of a large eddy simulation combustion solver and a radiation solver through a dedicated language, CORBA, is investigated. Two formulations of Monte Carlo method (Forward Method and Emission Reciprocity Method) employed to resolve RTE have been compared in a one-dimensional flame test case using three-dimensional calculation grids with absorbing and emitting media in order to validate the Monte Carlo radiative solver and to choose the most efficient model for coupling. Then the results obtained using two different RTE solvers (Reciprocity Monte Carlo method and Discrete Ordinate Method) applied on a three-dimensional flame holder set-up with a correlated-k distribution model describing the real gas medium spectral radiative properties are compared not only in terms of the physical behavior of the flame, but also in computational performance (storage requirement, CPU time and parallelization efficiency). To cite this article: J. Zhang et al., C. R. Mecanique 337 (2009).

Zhang, Jin; Gicquel, Olivier; Veynante, Denis; Taine, Jean

2009-06-01

303

Application de la methode des sous-groupes au calcul Monte-Carlo multigroupe

NASA Astrophysics Data System (ADS)

This thesis is dedicated to the development of a Monte Carlo neutron transport solver based on the subgroup (or multiband) method. In this formalism, cross sections for resonant isotopes are represented in the form of probability tables on the whole energy spectrum. This study is intended in order to test and validate this approach in lattice physics and criticality-safety applications. The probability table method seems promising since it introduces an alternative computational way between the legacy continuous-energy representation and the multigroup method. In the first case, the amount of data invoked in continuous-energy Monte Carlo calculations can be very important and tend to slow down the overall computational time. In addition, this model preserves the quality of the physical laws present in the ENDF format. Due to its cheap computational cost, the multigroup Monte Carlo way is usually at the basis of production codes in criticality-safety studies. However, the use of a multigroup representation of the cross sections implies a preliminary calculation to take into account self-shielding effects for resonant isotopes. This is generally performed by deterministic lattice codes relying on the collision probability method. Using cross-section probability tables on the whole energy range permits to directly take into account self-shielding effects and can be employed in both lattice physics and criticality-safety calculations. Several aspects have been thoroughly studied: (1) The consistent computation of probability tables with a energy grid comprising only 295 or 361 groups. The CALENDF moment approach conducted to probability tables suitable for a Monte Carlo code. (2) The combination of the probability table sampling for the energy variable with the delta-tracking rejection technique for the space variable, and its impact on the overall efficiency of the proposed Monte Carlo algorithm. (3) The derivation of a model for taking into account anisotropic effects of the scattering reaction consistent with the subgroup method. In this study, we generalize the Discrete Angle Technique, already proposed for homogeneous, multigroup cross sections, to isotopic cross sections on the form of probability tables. In this technique, the angular density is discretized into probability tables. Similarly to the cross-section case, a moment approach is used to compute the probability tables for the scattering cosine. (4) The introduction of a leakage model based on the B1 fundamental mode approximation. Unlike deterministic lattice packages, most Monte Carlo-based lattice physics codes do not include leakage models. However the generation of homogenized and condensed group constants (cross sections, diffusion coefficients) require the critical flux. This project has involved the development of a program into the DRAGON framework, written in Fortran 2003 and wrapped with a driver in C, the GANLIB 5. Choosing Fortran 2003 has permitted the use of some modern features, such as the definition of objects and methods, data encapsulation and polymorphism. The validation of the proposed code has been performed by comparison with other numerical methods: (1) The continuous-energy Monte Carlo method of the SERPENT code. (2) The Collision Probability (CP) method and the discrete ordinates (SN) method of the DRAGON lattice code. (3) The multigroup Monte Carlo code MORET, coupled with the DRAGON code. Benchmarks used in this work are representative of some industrial configurations encountered in reactor and criticality-safety calculations: (1)Pressurized Water Reactors (PWR) cells and assemblies. (2) Canada-Deuterium Uranium Reactors (CANDU-6) clusters. (3) Critical experiments from the ICSBEP handbook (International Criticality Safety Benchmark Evaluation Program).

Martin, Nicolas

304

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

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

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

2008-01-01

305

Isospin-projected nuclear level densities by the shell model Monte Carlo method

We have developed an efficient isospin projection method in the shell model Monte Carlo approach for isospin-conserving Hamiltonians. For isoscalar observables this projection method has the advantage of being exact sample by sample. The isospin projection method allows us to take into account the proper isospin dependence of the nuclear interaction, thus avoiding a sign problem that such an interaction introduces in unprojected calculations. We apply our method in the calculation of the isospin dependence of level densities in the complete $pf+g_{9/2}$ shell. We find that isospin-dependent corrections to the total level density are particularly important for $N \\sim Z$ nuclei.

H. Nakada; Y. Alhassid

2008-09-24

306

NASA Astrophysics Data System (ADS)

The way of measuring diameter by use of measuring bow height and chord length is commonly adopted for the large diameter work piece. In the process of computing the diameter of large work piece, measurement uncertainty is an important parameter and is always employed to evaluate the reliability of the measurement results. Therefore, it is essential to present reliable methods to evaluate the measurement uncertainty, especially in precise measurement. Because of the limitations of low convergence and unstable results of the Monte-Carlo (MC) method, the quasi-Monte-Carlo (QMC) method is used to estimate the measurement uncertainty. The QMC method is an improvement of the ordinary MC method which employs highly uniform quasi random numbers to replace MC's pseudo random numbers. In the process of evaluation, first, more homogeneous random numbers (quasi random numbers) are generated based on Halton's sequence. Then these random numbers are transformed into the desired distribution random numbers. The desired distribution random numbers are used to simulate the measurement errors. By computing the simulation results, measurement uncertainty can be obtained. An experiment of cylinder diameter measurement and its uncertainty evaluation are given. In the experiment, the guide to the expression of uncertainty in measurement method, MC method, and QMC method are validated. The result shows that the QMC method has a higher convergence rate and more stable evaluation results than that of the MC method. Therefore, the QMC method can be applied effectively to evaluate the measurement uncertainty.

Jing, Hui; Li, Cong; Kuang, Bing; Huang, Meifa; Zhong, Yanru

2012-09-01

307

Comparison of Monte Carlo methods for criticality benchmarks: Pointwise compared to multigroup

Transport codes use multigroup cross sections where neutrons are divided into broad energy groups, and the monoenergetic equation is solved for each group with a group-averaged cross section. Monte Carlo codes differ in that they allow the use of the most basic pointwise cross-section data directly in a calculation. Most of the first Monte Carlo codes were not able to utilize this feature, however, because of the memory limitations of early computers and the lack of pointwise cross-section data. Consequently, codes written in 1970s, such as KENO-IV and MORSE-C, were adapted to use multigroup cross-section sets similar to those used in the S{sub n} transport codes. With advances in computer memory capacities and the availability of pointwise cross-section sets, new Monte Carlo codes employing pointwise cross-section libraries, such as the Los Alamos National Laboratory code MCNP and the Lawrence Livermore National Laboratory (LLNL) code COG were developed for criticality, as well as radiation transport calculations. To compare pointwise and multigroup Monte Carlo methods for criticality benchmark calculations, this paper presents and evaluated the results from the KENO-IV, MORSE-C, MCNP, and COG codes. The critical experiments selected for benchmarking include LLNL fast metal systems and low-enriched uranium moderated and reflected systems.

Choi, J.S.; Alesso, P.H.; Pearson, J.S. (Lawrence Livermore National Lab., CA (USA))

1989-01-01

308

Monte Carlo method for photon heating using temperature-dependent optical properties.

The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues. A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties. The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes. PMID:25488656

Slade, Adam Broadbent; Aguilar, Guillermo

2015-02-01

309

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

Takahiro Mizusaki; Noritaka Shimizu

2012-01-27

310

Folding a 20 amino acid ?? peptide with the diffusion process-controlled Monte Carlo method

NASA Astrophysics Data System (ADS)

In this study we report on the application of the diffusion process-controlled Monte Carlo method to a 20 amino acid ?? peptide (Ac-E-T-Q-A-A-L-L-A-A-Q-K-A-Y-H-P-M-T-M-T-G-Am). The polypeptide chain is represented by a set of 126 particles, the side chains are modeled by spheres, and the backbone dihedral angles ? and ? of each of the amino acid residue are essentially restricted to a set of ten high probability regions, although the whole ?-? space may be visited in the course of the simulation. The method differs from other off-lattice Monte Carlo methods, in that the escape time from one accepted conformation to the next is estimated and limited at each iteration. The conformations are evaluated on the basis of pairwise nonbonded side chain energies derived from statistical distributions of contacts in real proteins and a simple main chain hydrogen bonding potential. As a result of four simulations starting from random extended conformations and one starting from a structure consistent with NMR data, the lowest-energy conformation (i.e., the ?? fold) is detected in ˜103 Monte Carlo steps, although the estimated probability of getting the ?? motif is ˜10-12. The predicted conformations deviate by 3.0 Å rms from a model structure compatible with the experimental results. In this work further evidence is provided that this method is useful in determining the lowest-energy region of medium-size polypeptide chains.

Derreumaux, Philippe

1997-08-01

311

Monte Carlo Method for Predicting a Physically Based Drop Size Distribution Evolution of a Spray

NASA Astrophysics Data System (ADS)

We report in this paper a method for predicting the evolution of a physically based drop size distribution of a spray, by coupling the Maximum Entropy Formalism and the Monte Carlo scheme. Using the discrete or continuous population balance equation, a Mass Flow Algorithm is formulated taking into account interactions between droplets via coalescence. After deriving a kernel for coalescence, we solve the time dependent drop size distribution equation using a Monte Carlo method. We apply the method to the spray of a new print-head known as a Spray On Demand (SOD) device; the process exploits ultrasonic spray generation via a Faraday instability where the fluid/structure interaction causing the instability is described by a modified Hamilton's principle. This has led to a physically-based approach for predicting the initial drop size distribution within the framework of the Maximum Entropy Formalism (MEF): a three-parameter generalized Gamma distribution is chosen by using conservation of mass and energy. The calculation of the drop size distribution evolution by Monte Carlo method shows the effect of spray droplets coalescence both on the number-based or volume-based drop size distributions.

Tembely, Moussa; Lécot, Christian; Soucemarianadin, Arthur

2010-03-01

312

Efficient Continuous-time Quantum Monte Carlo Method for the Ground State of Correlated Fermions

We present the ground state extension of the efficient quantum Monte Carlo algorithm for lattice fermions of arXiv:1411.0683. Based on continuous-time expansion of imaginary-time projection operator, the algorithm is free of systematic error and scales \\emph{linearly} with projection time and interaction strength. Compared to the conventional quantum Monte Carlo methods for lattice fermions, this approach has greater flexibility and is easier to combine with powerful machinery such as histogram reweighting and extended ensemble simulation techniques. We discuss the implementation of the continuous-time projection in detail using the spinless $t-V$ model as an example and compare the numerical results with exact diagonalization, density-matrix-renormalization-group and infinite projected entangled-pair states calculations. Finally we use the method to study the fermionic quantum critical point of spinless fermions on a honeycomb lattice and confirm previous results concerning its critical exponents.

Lei Wang; Mauro Iazzi; Philippe Corboz; Matthias Troyer

2015-01-05

313

Efficient Continuous-time Quantum Monte Carlo Method for the Ground State of Correlated Fermions

We present the ground state extension of the efficient quantum Monte Carlo algorithm for lattice fermions of arXiv:1411.0683. Based on continuous-time expansion of imaginary-time projection operator, the algorithm is free of systematic error and scales \\emph{linearly} with projection time and interaction strength. Compared to the conventional quantum Monte Carlo methods for lattice fermions, this approach has greater flexibility and is easier to combine with powerful machinery such as histogram reweighting and extended ensemble simulation techniques. We discuss the implementation of the continuous-time projection in detail using the spinless $t-V$ model as an example and compare the numerical results with exact diagonalization, density-matrix-renormalization-group and infinite projected entangled-pair states calculations. Finally we use the method to study the fermionic quantum critical point of spinless fermions on a honeycomb lattice and confirm previous results concerning its critical exponents.

Wang, Lei; Corboz, Philippe; Troyer, Matthias

2015-01-01

314

We introduce a particle-number reprojection method in the shell model Monte Carlo that enables the calculation of observables for a series of nuclei using a Monte Carlo sampling for a single nucleus. The method is used to calculate nuclear level densities in the complete $(pf+g_{9/2})$-shell using a good-sign Hamiltonian. Level densities of odd-A and odd-odd nuclei are reliably extracted despite an additional sign problem. Both the mass and the $T_z$ dependence of the experimental level densities are well described without any adjustable parameters. The single-particle level density parameter is found to vary smoothly with mass. The odd-even staggering observed in the calculated backshift parameter follows the experimental data more closely than do empirical formulae.

Y. Alhassid; S. Liu; H. Nakada

1999-10-14

315

Mesh-based Monte Carlo method in time-domain widefield fluorescence molecular tomography

Abstract. We evaluated the potential of mesh-based Monte Carlo (MC) method for widefield time-gated fluorescence molecular tomography, aiming to improve accuracy in both shape discretization and photon transport modeling in preclinical settings. An optimized software platform was developed utilizing multithreading and distributed parallel computing to achieve efficient calculation. We validated the proposed algorithm and software by both simulations and in vivo studies. The results establish that the optimized mesh-based Monte Carlo (mMC) method is a computationally efficient solution for optical tomography studies in terms of both calculation time and memory utilization. The open source code, as part of a new release of mMC, is publicly available at http://mcx.sourceforge.net/mmc/. PMID:23224008

Chen, Jin; Fang, Qianqian; Intes, Xavier

2012-01-01

316

Using the Monte Carlo method for modelling river flow, displacement and random scatter of sampling parameters and frequency curve ordinates have been established. A fundamental basis for the normalization of river flow has been developed. Mise en modèle statistique du débit des rivières par la méthode de Monte Carlo et évaluation des paramètres de la distribution et des quantiles Résumé.

A. V. Rozhdestvensky; V. M. Zvereva

317

Calculation of the Effective Emissivities of Specular-Diffuse Cavities by the Monte Carlo Method

An algorithm of the Monte Carlo method is described which allows evaluation of the effective emissivities of isothermal and nonisothermal specular-diffuse black-body cavities for use in radiometry, photometry and optical pyrometry. The calculation provides estimates of normal spectral effective emissivity for black-body cavities, formed by cone surfaces and a cylinder. It does this for an isothermal cavity and for a

V. I. Sapritsky; A. V. Prokhorov

1992-01-01

318

Null-collision technique in the direct-simulation Monte Carlo method

The null-collision concept is introduced into the direct-simulation Monte Carlo method in the rarefied gas dynamics. The null-collision technique overcomes the principle fault in the time-counter technique and the difficulties in the collision-frequency technique. The computation time required for the null-collision technique is comparable to that for the time-counter technique. Therefore, it is concluded that the null-collision technique is superior

Katsuhisa Koura

1986-01-01

319

Applications of Malliavin calculus to Monte-Carlo methods in finance. II

. This paper is the sequel of Part I [1], where we showed how to use the so-called Malliavin calculus in order to devise efficient\\u000a Monte-Carlo (numerical) methods for Finance. First, we return to the formulas developed in [1] concerning the “greeks” used\\u000a in European options, and we answer to the question of optimal weight functional in the sense of

Eric Fournié; Jean-Michel Lasry; Jérôme Lebuchoux; Pierre-Louis Lions

2001-01-01

320

We discuss the Auxiliary Field Quantum Monte Carlo (AFQMC) method applied to dilute neutron matter at finite temperatures. We formulate the discrete Hubbard-Stratonovich transformation for the interaction with finite effective range which is free from the sign problem. The AFQMC results are compared with those obtained from exact diagonalization for a toy model. Preliminary calculations of energy and chemical potential as a function of temperature are presented.

G. Wlazlowski; P. Magierski

2008-12-04

321

NASA Astrophysics Data System (ADS)

In this study, problems of statistical simulation of acoustic radiation propagation in the lower atmosphere along the vertical and horizontal paths by the Monte Carlo method and construction of the acoustic model of the atmosphere are considered. The influence of the geometry of problem being solved, radiation frequency, angle of source divergence, and outer scale of turbulence on the transmitted radiation intensity is discussed with allowance for the contribution of multiply scattered radiation.

Shamanaeva, L. G.; Belov, V. V.; Burkatovskaya, Yu. B.; Krasnenko, N. P.

2012-11-01

322

Monte Carlo Methods for Estimating Interfacial Free Energies and Line Tensions

Excess contributions to the free energy due to interfaces occur for many problems encountered in the statistical physics of\\u000a condensed matter when coexistence between different phases is possible (e.g. wetting phenomena, nucleation, crystal growth,\\u000a etc.). This article reviews two methods to estimate both interfacial free energies and line tensions by Monte Carlo simulations\\u000a of simple models, (e.g. the Ising model,

Kurt Binder; Benjamin Block; Subir K. Das; Peter Virnau; David Winter

2011-01-01

323

Analysis of small bipropellant engine internal flows by the direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

This paper presents the first application of the direct simulation Monte Carlo method to the calculation of the internal nozzle flow of a small operational bipropellant thruster. Because of the smallness of the engine, molecular simulation is necessary to capture thermal as well as velocity slip nonequilibrium effects. The present implementation of the Monte Carlo method includes several improvements on the usual computational techniques used. A finite-difference Navier-Stokes solution was also obtained for use both as the input and a comparison to the direct simulation. The results are presented as contours of Mach numbers, densities, pressures, and temperatures. The trends of the contours obtained from the continuum calculation and those from the direct simulation are similar, but the magnitudes of the flowfield properties differ by as much as a factor of two. The effects of the nozzle area ratio were also investigated using the Monte Carlo method. These effects are confined to the region near the nozzle exit where rarefaction effects become important.

Doo, Y. C.; Nelson, D. A.

1987-06-01

324

Monte Carlo Methods in Materials Science Based on FLUKA and ROOT

NASA Technical Reports Server (NTRS)

A comprehensive understanding of mitigation measures for space radiation protection necessarily involves the relevant fields of nuclear physics and particle transport modeling. One method of modeling the interaction of radiation traversing matter is Monte Carlo analysis, a subject that has been evolving since the very advent of nuclear reactors and particle accelerators in experimental physics. Countermeasures for radiation protection from neutrons near nuclear reactors, for example, were an early application and Monte Carlo methods were quickly adapted to this general field of investigation. The project discussed here is concerned with taking the latest tools and technology in Monte Carlo analysis and adapting them to space applications such as radiation shielding design for spacecraft, as well as investigating how next-generation Monte Carlos can complement the existing analytical methods currently used by NASA. We have chosen to employ the Monte Carlo program known as FLUKA (A legacy acronym based on the German for FLUctuating KAscade) used to simulate all of the particle transport, and the CERN developed graphical-interface object-oriented analysis software called ROOT. One aspect of space radiation analysis for which the Monte Carlo s are particularly suited is the study of secondary radiation produced as albedoes in the vicinity of the structural geometry involved. This broad goal of simulating space radiation transport through the relevant materials employing the FLUKA code necessarily requires the addition of the capability to simulate all heavy-ion interactions from 10 MeV/A up to the highest conceivable energies. For all energies above 3 GeV/A the Dual Parton Model (DPM) is currently used, although the possible improvement of the DPMJET event generator for energies 3-30 GeV/A is being considered. One of the major tasks still facing us is the provision for heavy ion interactions below 3 GeV/A. The ROOT interface is being developed in conjunction with the CERN ALICE (A Large Ion Collisions Experiment) software team through an adaptation of their existing AliROOT (ALICE Using ROOT) architecture. In order to check our progress against actual data, we have chosen to simulate the ATIC14 (Advanced Thin Ionization Calorimeter) cosmic-ray astrophysics balloon payload as well as neutron fluences in the Mir spacecraft. This paper contains a summary of status of this project, and a roadmap to its successful completion.

Pinsky, Lawrence; Wilson, Thomas; Empl, Anton; Andersen, Victor

2003-01-01

325

Level Densities of Heavy Nuclei by the Shell Model Monte Carlo Method

The microscopic calculation of nuclear level densities in the presence of correlations is a difficult many-body problem. The shell model Monte Carlo method provides a powerful technique to carry out such calculations using the framework of the configuration-interaction shell model in spaces that are many orders of magnitude larger than spaces that can be treated by conventional methods. We present recent applications of the method to the calculation of level densities and their collective enhancement factors in heavy nuclei. The calculated level densities are in close agreement with experimental data.

Y. Alhassid; C. Özen; H. Nakada

2013-05-24

326

A modification of the Monte Carlo method for simulation of radiative transfer in molecular clouds

We propose a method of simulation that is based on the averaging of formal solutions of the transfer equation by taking the integral by the Monte Carlo method. This method is used to compute two models, which correspond to the limiting cases of hot gas and cold background radiation and of hot background radiation and cold gas, for E-methanol emission from a compact homogeneous spherical region. We analyse model level populations by using rotational diagrams in the limiting cases mentioned above. Model optical depths of the lines with frequencies below 300 GHz up to J=11 inclusive are given.

Maxim A. Voronkov

2000-08-30

327

Exact solutions of the QCD evolution equations using Monte Carlo method

We present the exact and precise (~0.1%) numerical solution of the QCD evolution equations for the parton distributions in a wide range of $Q$ and $x$ using Monte Carlo (MC) method, which relies on the so-called Markovian algorithm. We point out certain advantages of such a method with respect to the existing non-MC methods. We also formulate a challenge of constructing non-Markovian MC algorithm for the evolution equations for the initial state QCD radiation with tagging the type and $x$ of the exiting parton. This seems to be within the reach of the presently available computer CPUs and the sophistication of the MC techniques.

S. Jadach; M. Skrzypek

2003-12-26

328

NASA Astrophysics Data System (ADS)

The effective delayed neutron fraction ? plays an important role in kinetics and static analysis of the reactor physics experiments. It is used as reactivity unit referred to as "dollar". Usually, it is obtained by computer simulation due to the difficulty in measuring it experimentally. In 1965, Keepin proposed a method, widely used in the literature, for the calculation of the effective delayed neutron fraction ?. This method requires calculation of the adjoint neutron flux as a weighting function of the phase space inner products and is easy to implement by deterministic codes. With Monte Carlo codes, the solution of the adjoint neutron transport equation is much more difficult because of the continuous-energy treatment of nuclear data. Consequently, alternative methods, which do not require the explicit calculation of the adjoint neutron flux, have been proposed. In 1997, Bretscher introduced the k-ratio method for calculating the effective delayed neutron fraction; this method is based on calculating the multiplication factor of a nuclear reactor core with and without the contribution of delayed neutrons. The multiplication factor set by the delayed neutrons (the delayed multiplication factor) is obtained as the difference between the total and the prompt multiplication factors. Using Monte Carlo calculation Bretscher evaluated the ? as the ratio between the delayed and total multiplication factors (therefore the method is often referred to as the k-ratio method). In the present work, the k-ratio method is applied by Monte Carlo (MCNPX) and deterministic (PARTISN) codes. In the latter case, the ENDF/B nuclear data library of the fuel isotopes (235U and 238U) has been processed by the NJOY code with and without the delayed neutron data to prepare multi-group WIMSD neutron libraries for the lattice physics code DRAGON, which was used to generate the PARTISN macroscopic cross sections. In recent years Meulekamp and van der Marck in 2006 and Nauchi and Kameyama in 2005 proposed new methods for the effective delayed neutron fraction calculation with only one Monte Carlo computer simulation, compared with the k-ratio method which require two criticality calculations. In this paper, the Meulekamp/Marck and Nauchi/Kameyama methods are applied for the first time by the MCNPX computer code and the results obtained by all different methods are compared.

Zhong, Zhaopeng; Talamo, Alberto; Gohar, Yousry

2013-07-01

329

Lattice-switching Monte Carlo method for crystals of flexible molecules

NASA Astrophysics Data System (ADS)

We discuss implementation of the lattice-switching Monte Carlo method (LSMC) as a binary sampling between two synchronized Markov chains exploring separated minima in the potential energy landscape. When expressed in this fashion, the generalization to more complex crystals is straightforward. We extend the LSMC method to a flexible model of linear alkanes, incorporating bond length and angle constraints. Within this model, we accurately locate a transition between two polymorphs of n -butane with increasing density, and suggest this as a benchmark problem for other free-energy methods.

Bridgwater, Sally; Quigley, David

2014-12-01

330

Quasi-Monte Carlo methods for lattice systems: A first look

NASA Astrophysics Data System (ADS)

We investigate the applicability of quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N, where N is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this behavior for certain problems to 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. Catalogue identifier: AERJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERJ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence version 3 No. of lines in distributed program, including test data, etc.: 67759 No. of bytes in distributed program, including test data, etc.: 2165365 Distribution format: tar.gz Programming language: C and C++. Computer: PC. Operating system: Tested on GNU/Linux, should be portable to other operating systems with minimal efforts. Has the code been vectorized or parallelized?: No RAM: The memory usage directly scales with the number of samples and dimensions: Bytes used = “number of samples” × “number of dimensions” × 8 Bytes (double precision). Classification: 4.13, 11.5, 23. External routines: FFTW 3 library (http://www.fftw.org) Nature of problem: Certain physical models formulated as a quantum field theory through the Feynman path integral, such as quantum chromodynamics, require a non-perturbative treatment of the path integral. The only known approach that achieves this is the lattice regularization. In this formulation the path integral is discretized to a finite, but very high dimensional integral. So far only Monte Carlo, and especially Markov chain-Monte Carlo methods like the Metropolis or the hybrid Monte Carlo algorithm have been used to calculate approximate solutions of the path integral. These algorithms often lead to the undesired effect of autocorrelation in the samples of observables and suffer in any case from the slow asymptotic error behavior proportional to N, if N is the number of samples. Solution method: This program applies the quasi-Monte Carlo approach and the reweighting technique (respectively the weighted uniform sampling method) to generate uncorrelated samples of observables of the anharmonic oscillator with an improved asymptotic error behavior. Unusual features: The application of the quasi-Monte Carlo approach is quite revolutionary in the field of lattice field theories. Running time: The running time depends directly on the number of samples N and dimensions d. On modern computers a run with up to N=216=65536 (including 9 replica runs) and d=100 should not take much longer than one minute.

Jansen, K.; Leovey, H.; Ammon, A.; Griewank, A.; Müller-Preussker, M.

2014-03-01

331

Visual improvement for bad handwriting based on Monte-Carlo method

NASA Astrophysics Data System (ADS)

A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2014-03-01

332

Effects of CT based Voxel Phantoms on Dose Distribution Calculated with Monte Carlo Method

NASA Astrophysics Data System (ADS)

A few CT-based voxel phantoms were produced to investigate the sensitivity of Monte Carlo simulations of x-ray beam and electron beam to the proportions of elements and the mass densities of the materials used to express the patient's anatomical structure. The human body can be well outlined by air, lung, adipose, muscle, soft bone and hard bone to calculate the dose distribution with Monte Carlo method. The effects of the calibration curves established by using various CT scanners are not clinically significant based on our investigation. The deviation from the values of cumulative dose volume histogram derived from CT-based voxel phantoms is less than 1% for the given target.

Chen, Chaobin; Huang, Qunying; Wu, Yican

2005-04-01

333

Temperature-extrapolation method for Implicit Monte Carlo - Radiation hydrodynamics calculations

We present a method for implementing temperature extrapolation in Implicit Monte Carlo solutions to radiation hydrodynamics problems. The method is based on a BDF-2 type integration to estimate a change in material temperature over a time step. We present results for radiation only problems in an infinite medium and for a 2-D Cartesian hohlraum problem. Additionally, radiation hydrodynamics simulations are presented for an RZ hohlraum problem and a related 3D problem. Our results indicate that improvements in noise and general behavior are possible. We present considerations for future investigations and implementations. (authors)

McClarren, R. G. [Department of Nuclear Engineering, Texas A and M University, 3133 TAMU, College Station, TX 77802 (United States); Urbatsch, T. J. [XTD-5: Air Force Systems, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 77845 (United States)

2013-07-01

334

A high order method for orbital conjunctions analysis: Monte Carlo collision probability computation

NASA Astrophysics Data System (ADS)

Three methods for the computation of the probability of collision between two space objects are presented. These methods are based on the high order Taylor expansion of the time of closest approach (TCA) and distance of closest approach (DCA) of the two orbiting objects with respect to their initial conditions. The identification of close approaches is first addressed using the nominal objects states. When a close approach is identified, the dependence of the TCA and DCA on the uncertainties in the initial states is efficiently computed with differential algebra (DA) techniques. In the first method the collision probability is estimated via fast DA-based Monte Carlo simulation, in which, for each pair of virtual objects, the DCA is obtained via the fast evaluation of its Taylor expansion. The second and the third methods are the DA version of Line Sampling and Subset Simulation algorithms, respectively. These are introduced to further improve the efficiency and accuracy of Monte Carlo collision probability computation, in particular for cases of very low collision probabilities. The performances of the methods are assessed on orbital conjunctions occurring in different orbital regimes and dynamical models. The probabilities obtained and the associated computational times are compared against standard (i.e. not DA-based) version of the algorithms and analytical methods. The dependence of the collision probability on the initial orbital state covariance is investigated as well.

Morselli, Alessandro; Armellin, Roberto; Di Lizia, Pierluigi; Bernelli Zazzera, Franco

2015-01-01

335

A boundary-dispatch Monte Carlo (Exodus) method for analysis of conductive heat transfer problems

A boundary-dispatch Monte Carlo (Exodus) method, in which the particles are dispatched from the boundaries of a conductive medium or source of heat, is developed. A fixed number of particles are dispatched from a boundary node to the nearest internal node. These particles make random walks within the medium similar to that of the conventional Monte Carlo method. Once a particle visits an internal node, a number equal to the temperature of the boundary node from which particles are dispatched is added to a counter. Performing this procedure for all boundary nodes, the temperature of a node can be determined by dividing the flag, or the counter of this node by the total number of particle visits to this node. Two versions of the boundary-dispatch method (BDM) are presented, multispecies and bispecies BDM. The results of bispecies BDM based on the Exodus dispatching method compare well with the Gauss-Seidel method in both accuracy and computational time. Its computational time is much less than the shrinking-boundary Exodus method.

Naraghi, M.H.N. [Manhattan Coll., Riverdale, NY (United States); Shunchang Tsai [Harvard Univ., Cambridge, MA (United States)

1993-12-01

336

A method based on Monte Carlo simulation for the determination of the G(E) function.

The G(E) function method is a spectrometric method for the exposure dose estimation; this paper describes a method based on Monte Carlo method to determine the G(E) function of a 4? × 4? × 16? NaI(Tl) detector. Simulated spectrums of various monoenergetic gamma rays in the region of 40 -3200 keV and the corresponding deposited energy in an air ball in the energy region of full-energy peak were obtained using Monte Carlo N-particle Transport Code. Absorbed dose rate in air was obtained according to the deposited energy and divided by counts of corresponding full-energy peak to get the G(E) function value at energy E in spectra. Curve-fitting software 1st0pt was used to determine coefficients of the G(E) function. Experimental results show that the calculated dose rates using the G(E) function determined by the authors' method are accordant well with those values obtained by ionisation chamber, with a maximum deviation of 6.31 %. PMID:24795395

Chen, Wei; Feng, Tiancheng; Liu, Jun; Su, Chuanying; Tian, Yanjie

2015-02-01

337

Sequential Monte Carlo estimation on point processes has been successfully applied to predict the movement from neural activity. However, there exist some issues along with this method such as the simplified tuning model and the high computational complexity, which may degenerate the decoding performance of motor brain machine interfaces. In this paper, we adopt a general tuning model which takes recent ensemble activity into account. The goodness-of-fit analysis demonstrates that the proposed model can predict the neuronal response more accurately than the one only depending on kinematics. A new sequential Monte Carlo algorithm based on the proposed model is constructed. The algorithm can significantly reduce the root mean square error of decoding results, which decreases 23.6% in position estimation. In addition, we accelerate the decoding speed by implementing the proposed algorithm in a massive parallel manner on GPU. The results demonstrate that the spike trains can be decoded as point process in real time even with 8000 particles or 300 neurons, which is over 10 times faster than the serial implementation. The main contribution of our work is to enable the sequential Monte Carlo algorithm with point process observation to output the movement estimation much faster and more accurately. PMID:24949462

Wang, Fang; Liao, Yuxi; Zheng, Xiaoxiang

2014-01-01

338

A new time quantifiable Monte Carlo method in simulating magnetization reversal process

We propose a new time quantifiable Monte Carlo (MC) method to simulate the thermally induced magnetization reversal for an isolated single domain particle system. The MC method involves the determination of density of states, and the use of Master equation for time evolution. We derive an analytical factor to convert MC steps into real time intervals. Unlike a previous time quantified MC method, our method is readily scalable to arbitrarily long time scales, and can be repeated for different temperatures with minimal computational effort. Based on the conversion factor, we are able to make a direct comparison between the results obtained from MC and Langevin dynamics methods, and find excellent agreement between them. An analytical formula for the magnetization reversal time is also derived, which agrees very well with both numerical Langevin and time-quantified MC results, over a large temperature range and for parallel and oblique easy axis orientations.

X. Z. Cheng; M. B. A. Jalil; H. K. Lee; Y. Okabe

2005-04-14

339

Paleoearthquake observations often lack enough events at a given site to directly define a probability density function (PDF) for earthquake recurrence. Sites with fewer than 10-15 intervals do not provide enough information to reliably determine the shape of the PDF using standard maximum-likelihood techniques (e.g., Ellsworth et al., 1999). In this paper I present a method that attempts to fit wide ranges of distribution parameters to short paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most likely recurrence PDF parameters, and a ranked distribution of parameters is returned that can be used to assess uncertainties in hazard calculations. In tests on short synthetic earthquake series, the method gives results that cluster around the mean of the input distribution, whereas maximum likelihood methods return the sample means (e.g., NIST/SEMATECH, 2006). For short series (fewer than 10 intervals), sample means tend to reflect the median of an asymmetric recurrence distribution, possibly leading to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach may be useful for assessing recurrence from limited paleoearthquake records. Further, the degree of functional dependence among parameters like mean recurrence interval and coefficient of variation can be established. The method is described for use with time-independent and time-dependent PDFs, and results from 19 paleoseismic sequences on strike-slip faults throughout the state of California are given.

Parsons, T.

2008-01-01

340

Paleoearthquake observations often lack enough events at a given site to directly define a probability density function (PDF) for earthquake recurrence. Sites with fewer than 10-15 intervals do not provide enough information to reliably determine the shape of the PDF using standard maximum-likelihood techniques [e.g., Ellsworth et al., 1999]. In this paper I present a method that attempts to fit wide ranges of distribution parameters to short paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most likely recurrence PDF parameters, and a ranked distribution of parameters is returned that can be used to assess uncertainties in hazard calculations. In tests on short synthetic earthquake series, the method gives results that cluster around the mean of the input distribution, whereas maximum likelihood methods return the sample means [e.g., NIST/SEMATECH, 2006]. For short series (fewer than 10 intervals), sample means tend to reflect the median of an asymmetric recurrence distribution, possibly leading to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach may be useful for assessing recurrence from limited paleoearthquake records. Further, the degree of functional dependence among parameters like mean recurrence interval and coefficient of variation can be established. The method is described for use with time-independent and time-dependent PDF?s, and results from 19 paleoseismic sequences on strike-slip faults throughout the state of California are given.

Parsons, Tom

2008-01-01

341

We present a numerical method and computer code to calculate the radiative transfer and excitation of molecular lines. Formulating the Monte Carlo method from the viewpoint of cells rather than photons allows us to separate local and external contributions to the radiation field. This separation is critical to accurate and fast performance at high optical depths (tau>100). The random nature of the Monte Carlo method serves to verify the independence of the solution to the angular, spatial, and frequency sampling of the radiation field. These features allow use of our method in a wide variety of astrophysical problems without specific adaptations: in any axially symmetric source model and for all atoms or molecules for which collisional rate coefficients are available. Continuum emission and absorption by dust is explicitly taken into account but scattering is neglected. We illustrate these features in calculations of (i) the HCO+ J=1-0 and 3-2 emission from a flattened protostellar envelope with infall and rotation, (ii) the CO, HCO+, CN and HCN emission from a protoplanetary disk and (iii) HCN emission from a high-mass young stellar object, where infrared pumping is important. The program can be used for optical depths up to 1000-10,000, depending on source model. We expect this program to be an important tool in analysing data from present and future infrared and (sub) millimetre telescopes.

Michiel R. Hogerheijde; Floris F. S. van der Tak

2000-08-10

342

Fast Monte Carlo Electron-Photon Transport Method and Application in Accurate Radiotherapy

NASA Astrophysics Data System (ADS)

Monte Carlo (MC) method is the most accurate computational method for dose calculation, but its wide application on clinical accurate radiotherapy is hindered due to its poor speed of converging and long computation time. In the MC dose calculation research, the main task is to speed up computation while high precision is maintained. The purpose of this paper is to enhance the calculation speed of MC method for electron-photon transport with high precision and ultimately to reduce the accurate radiotherapy dose calculation time based on normal computer to the level of several hours, which meets the requirement of clinical dose verification. Based on the existing Super Monte Carlo Simulation Program (SuperMC), developed by FDS Team, a fast MC method for electron-photon coupled transport was presented with focus on two aspects: firstly, through simplifying and optimizing the physical model of the electron-photon transport, the calculation speed was increased with slightly reduction of calculation accuracy; secondly, using a variety of MC calculation acceleration methods, for example, taking use of obtained information in previous calculations to avoid repeat simulation of particles with identical history; applying proper variance reduction techniques to accelerate MC method convergence rate, etc. The fast MC method was tested by a lot of simple physical models and clinical cases included nasopharyngeal carcinoma, peripheral lung tumor, cervical carcinoma, etc. The result shows that the fast MC method for electron-photon transport was fast enough to meet the requirement of clinical accurate radiotherapy dose verification. Later, the method will be applied to the Accurate/Advanced Radiation Therapy System ARTS as a MC dose verification module.

Hao, Lijuan; Sun, Guangyao; Zheng, Huaqing; Song, Jing; Chen, Zhenping; Li, Gui

2014-06-01

343

In Monte Carlo iterated-fission-source calculations relative uncertainties on local tallies tend to be larger in lower-power regions and smaller in higher-power regions. Reducing the largest uncertainties to an acceptable level simply by running a larger number of neutron histories is often prohibitively expensive. The uniform fission site method has been developed to yield a more spatially-uniform distribution of relative uncertainties. This is accomplished by biasing the density of fission neutron source sites while not biasing the solution. The method is integrated into the source iteration process, and does not require any auxiliary forward or adjoint calculations. For a given amount of computational effort, the use of the method results in a reduction of the largest uncertainties relative to the standard algorithm. Two variants of the method have been implemented and tested. Both have been shown to be effective. (authors)

Hunter, J. L. [Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., 24-107, Cambridge, MA 02139 (United States); Sutton, T. M. [Knolls Atomic Power Laboratory, Bechtel Marine Propulsion Corporation, P. O. Box 1072, Schenectady, NY 12301-1072 (United States)

2013-07-01

344

The shell model Monte Carlo (SMMC) method enables calculations in model spaces that are many orders of magnitude larger than those that can be treated by conventional methods, and is particularly suitable for the calculation of level densities in the presence of correlations. We review recent advances and applications of SMMC for the microscopic calculation of level densities. Recent developments include (i) a method to calculate accurately the ground-state energy of an odd-mass nucleus, circumventing a sign problem that originates in the projection on an odd number of particles, and (ii) a method to calculate directly level densities, which, unlike state densities, do not include the spin degeneracy of the levels. We calculated the level densities of a family of nickel isotopes $^{59-64}$Ni and of a heavy deformed rare-earth nucleus $^{162}$Dy and found them to be in close agreement with various experimental data sets.

Y. Alhassid; M. Bonett-Matiz; S. Liu; A. Mukherjee; H. Nakada

2014-01-01

345

NASA Astrophysics Data System (ADS)

The shell model Monte Carlo (SMMC) method enables calculations in model spaces that are many orders of magnitude larger than those that can be treated by conventional methods, and is particularly suitable for the calculation of level densities in the presence of correlations. We review recent advances and applications of SMMC for the microscopic calculation of level densities. Recent developments include (i) a method to calculate accurately the ground-state energy of an odd-mass nucleus, circumventing a sign problem that originates in the projection on an odd number of particles, and (ii) a method to calculate directly level densities, which, unlike state densities, do not include the spin degeneracy of the levels. We calculated the level densities of a family of nickel isotopes 59-64Ni and of a heavy deformed rare-earth nucleus 162Dy and found them to be in close agreement with various experimental data sets.

Alhassid, Y.; Bonett-Matiz, M.; Liu, S.; Mukherjee, A.; Nakada, H.

2014-04-01

346

A steady-state convergence detection method for Monte Carlo simulation

NASA Astrophysics Data System (ADS)

In the direct simulation Monte Carlo (DSMC), exclusion of microscopic data sampled in the unsteady phase can accelerate the convergence and lead to more accurate results in the steady state problem. In this study, a new method for detection of the steady state onset, called Probabilistic Automatic Reset Sampling (PARS), is introduced. The new method can detect the steady state automatically and reset sample after satisfying the reset criteria based on statistics. The method is simple and does not need any user-specified inputs. The simulation results show that the proposed strategy can work well even in condition with constant number of particles inside the domain which was the main drawback of the previous methods.

Karchani, Abolfazl; Ejtehadi, Omid; Myong, Rho Shin

2014-12-01

347

CCMR: Method Development of Dynamic Mass Diffusion Monte Carlo using Lennard-Jones Clusters

NSDL National Science Digital Library

The Lennard-Jones clusters, clusters of inert particles have a long history of being studied. Many algorithms have been proposed and used with a varying level of success from "basin hopping" [1] to “greedy search” [2]. Despite these achievements, the Lennard-Jones potential continues to be a widely studied model. Not only is it a good test case for new particle structure algorithms, but it is still an interesting model that we can yet learn from. In this project we proposed to study these cluster using a method never before attempted: dynamic mass diffusion Monte Carlo.

Craig, Helen A.

2007-08-29

348

Refinement of overlapping local/global iteration method based on Monte Carlo/p-CMFD calculations

In this paper, the overlapping local/global (OLG) iteration method based on Monte Carlo/p-CMFD calculations is refined in two aspects. One is the consistent use of estimators to generate homogenized scattering cross sections. Another is that the incident or exiting angular interval is divided into multi-angular bins to modulate albedo boundary conditions for local problems. Numerical tests show that, compared to the one angle bin case in a previous study, the four angle bin case shows significantly improved results. (authors)

Jo, Y.; Yun, S.; Cho, N. Z. [Korea Advanced Institute of Science and Technology - KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701 (Korea, Republic of)

2013-07-01

349

A Monte Carlo method for chemical potential determination in single and multiple occupancy crystals

We describe a Monte Carlo scheme which, in a single simulation, yields a measurement of the chemical potential of a crystalline solid. Within the isobaric ensemble, this immediately provides an estimate of the system free energy, with statistical uncertainties that are determined precisely and transparently. An extension to multiple occupancy ("cluster") solids permits the direct determination of the cluster chemical potential and hence the equilibrium conditions. We apply the method to a model exhibiting cluster crystalline phases, where we find evidence for an infinite cascade of critical points terminating coexistence between crystals of differing site occupancies.

Nigel B. Wilding; Peter Sollich

2012-09-14

350

Application of the direct simulation Monte Carlo method to the full shuttle geometry

NASA Technical Reports Server (NTRS)

A new set of programs has been developed for the application of the direct simulation Monte Carlo (or DSMC) method to rarefied gas flows with complex three-dimensional boundaries. The programs are efficient in terms of the computational load and also in terms of the effort required to set up particular cases. This efficiency is illustrated through computations of the flow about the Shuttle Orbiter. The general flow features are illustrated for altitudes from 170 to 100 km. Also, the computed lift-drag ratio during re-entry is compared with flight measurements.

Bird, G. A.

1990-01-01

351

Configuration-interaction Monte Carlo method and its application to the trapped unitary Fermi gas

We develop a quantum Monte Carlo method to estimate the ground-state energy of a fermionic many-particle system in the configuration-interaction shell model approach. The fermionic sign problem is circumvented by using a guiding wave function in Fock space. The method provides an upper bound on the ground-state energy whose tightness depends on the choice of the guiding wave function. We argue that the antisymmetric geminal product class of wave functions is a good choice for guiding wave functions. We demonstrate our method for the trapped two-species fermionic cold atom system in the unitary regime of infinite scattering length using the particle-number projected Hartree-Fock-Bogoliubov wave function as the guiding wave function. We estimate the ground-state energy and energy-staggering pairing gap as a function of the number of particles. Our results compare favorably with exact numerical diagonalization results and with previous coordinate-space Monte Carlo calculations.

Abhishek Mukherjee; Y. Alhassid

2013-04-05

352

A new Monte Carlo method for dynamical evolution of non-spherical stellar systems

We have developed a novel Monte Carlo method for simulating the dynamical evolution of stellar systems in arbitrary geometry. The orbits of stars are followed in a smooth potential represented by a basis-set expansion and perturbed after each timestep using local velocity diffusion coefficients from the standard two-body relaxation theory. The potential and diffusion coefficients are updated after an interval of time that is a small fraction of the relaxation time, but may be longer than the dynamical time. Thus our approach is a bridge between the Spitzer's formulation of the Monte Carlo method and the temporally smoothed self-consistent field method. The primary advantages are the ability to follow the secular evolution of shape of the stellar system, and the possibility of scaling the amount of two-body relaxation to the necessary value, unrelated to the actual number of particles in the simulation. Possible future applications of this approach in galaxy dynamics include the problem of consumption of stars...

Vasiliev, Eugene

2014-01-01

353

Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method

NASA Astrophysics Data System (ADS)

Diffusion Monte Carlo is a highly accurate Quantum Monte Carlo method for electronic structure calculations of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency on parallel machines. This step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receiving at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm: a simple renumbering of the MPI ranks based on proximity and a space filling curve significantly improves the MPI Allgather performance. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL show up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that require load balancing.

Sudheer, C. D.; Krishnan, S.; Srinivasan, A.; Kent, P. R. C.

2013-02-01

354

Efficient implementation of a Monte Carlo method for uncertainty evaluation in dynamic measurements

NASA Astrophysics Data System (ADS)

Measurement of quantities having time-dependent values such as force, acceleration or pressure is a topic of growing importance in metrology. The application of the Guide to the Expression of Uncertainty in Measurement (GUM) and its Supplements to the evaluation of uncertainty for such quantities is challenging. We address the efficient implementation of the Monte Carlo method described in GUM Supplements 1 and 2 for this task. The starting point is a time-domain observation equation. The steps of deriving a corresponding measurement model, the assignment of probability distributions to the input quantities in the model, and the propagation of the distributions through the model are all considered. A direct implementation of a Monte Carlo method can be intractable on many computers since the storage requirement of the method can be large compared with the available computer memory. Two memory-efficient alternatives to the direct implementation are proposed. One approach is based on applying updating formulae for calculating means, variances and point-wise histograms. The second approach is based on evaluating the measurement model sequentially in time. A simulated example is used to compare the performance of the direct and alternative procedures.

Eichstädt, S.; Link, A.; Harris, P.; Elster, C.

2012-06-01

355

A new Monte Carlo method for dynamical evolution of non-spherical stellar systems

NASA Astrophysics Data System (ADS)

We have developed a novel Monte Carlo method for simulating the dynamical evolution of stellar systems in arbitrary geometry. The orbits of stars are followed in a smooth potential represented by a basis-set expansion and perturbed after each timestep using local velocity diffusion coefficients from the standard two-body relaxation theory. The potential and diffusion coefficients are updated after an interval of time that is a small fraction of the relaxation time, but may be longer than the dynamical time. Thus, our approach is a bridge between the Spitzer's formulation of the Monte Carlo method and the temporally smoothed self-consistent field method. The primary advantages are the ability to follow the secular evolution of shape of the stellar system, and the possibility of scaling the amount of two-body relaxation to the necessary value, unrelated to the actual number of particles in the simulation. Possible future applications of this approach in galaxy dynamics include the problem of consumption of stars by a massive black hole in a non-spherical galactic nucleus, evolution of binary supermassive black holes, and the influence of chaos on the shape of galaxies, while for globular clusters it may be used for studying the influence of rotation.

Vasiliev, Eugene

2015-01-01

356

The applicability of certain Monte Carlo methods to the analysis of interacting polymers

The authors consider polymers, modeled as self-avoiding walks with interactions on a hexagonal lattice, and examine the applicability of certain Monte Carlo methods for estimating their mean properties at equilibrium. Specifically, the authors use the pivoting algorithm of Madras and Sokal and Metroplis rejection to locate the phase transition, which is known to occur at {beta}{sub crit} {approx} 0.99, and to recalculate the known value of the critical exponent {nu} {approx} 0.58 of the system for {beta} = {beta}{sub crit}. Although the pivoting-Metropolis algorithm works well for short walks (N < 300), for larger N the Metropolis criterion combined with the self-avoidance constraint lead to an unacceptably small acceptance fraction. In addition, the algorithm becomes effectively non-ergodic, getting trapped in valleys whose centers are local energy minima in phase space, leading to convergence towards different values of {nu}. The authors use a variety of tools, e.g. entropy estimation and histograms, to improve the results for large N, but they are only of limited effectiveness. Their estimate of {beta}{sub crit} using smaller values of N is 1.01 {+-} 0.01, and the estimate for {nu} at this value of {beta} is 0.59 {+-} 0.005. They conclude that even a seemingly simple system and a Monte Carlo algorithm which satisfies, in principle, ergodicity and detailed balance conditions, can in practice fail to sample phase space accurately and thus not allow accurate estimations of thermal averages. This should serve as a warning to people who use Monte Carlo methods in complicated polymer folding calculations. The structure of the phase space combined with the algorithm itself can lead to surprising behavior, and simply increasing the number of samples in the calculation does not necessarily lead to more accurate results.

Krapp, D.M. Jr. [Univ. of California, Berkeley, CA (United States)

1998-05-01

357

Auxiliary-field quantum Monte Carlo method for strongly paired fermions

We solve the zero-temperature unitary Fermi gas problem by incorporating a BCS importance function into the auxiliary-field quantum Monte Carlo method. We demonstrate that this method does not suffer from a sign problem and that it increases the efficiency of standard techniques by many orders of magnitude for strongly paired fermions. We calculate the ground-state energies exactly for unpolarized systems with up to 66 particles on lattices of up to 27{sup 3} sites, obtaining an accurate result for the universal parameter {xi}. We also obtain results for interactions with different effective ranges and find that the energy is consistent with a universal linear dependence on the product of the Fermi momentum and the effective range. This method will have many applications in superfluid cold atom systems and in both electronic and nuclear structures where pairing is important.

Carlson, J.; Gandolfi, Stefano [Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Schmidt, Kevin E. [Department of Physics, Arizona State University, Tempe, Arizona 85287 (United States); Zhang, Shiwei [Department of Physics, College of William and Mary, Williamsburg, Virginia 23187 (United States)

2011-12-15

358

Comparison of Monte Carlo and discrete ordinates methods in a three-dimensional well-logging problem

In this paper, the authors compare the Monte Carlo and the two discrete ordinates methods (nodal and conventional) in the benchmark well-logging problem. Although the problem is prototypical of well-logging systems, it severely tests the capabilities of transport methods. The Monte Carlo calculations were performed with the Los Alamos code, MCNP. The discrete ordinates calculations were performed using the Schlumberger three-dimensional nodal transport code, LENA3D (Linear Expansion Nodal Anisotropic 3D). The three-dimensional discrete nodal transport method developed and coded in LENA3D appears to be significantly faster than the Monte Carlo method in MCNP for this problem. The linear surface flux nodal method yields the accuracy of a Monte Carlo calculation with more than an order of magnitude less computing time for this problem. The method thus offers the potential for performing large-scale three-dimensional transport calculations to complement Monte Carlo methods in well-logging and other radiation transport problems.

Badruzzaman, A.; Chiaramonte, J.

1985-11-01

359

Investigation of a New Monte Carlo Method for the Transitional Gas Flow

The Direct Simulation Monte Carlo method (DSMC) is well developed for rarefied gas flow in transition flow regime when 0.01

Luo, X.; Day, Chr. [Karlsruhe Institute of Technology(KIT), Institute for Technical Physics, 76021, Karlsruhe (Germany)

2011-05-20

360

NASA Astrophysics Data System (ADS)

Simple Monte Carlo simulations can assist both the cultural astronomy researcher while the Research Design is developed and the eventual evaluators of research products. Following the method we describe allows assessment of the probability for there to be false positives associated with a site. Even seemingly evocative alignments may be meaningless, depending on the site characteristics and the number of degrees of freedom the researcher allows. In many cases, an observer may have to limit comments to "it is nice and it might be culturally meaningful, rather than saying "it is impressive so it must mean something". We describe a basic language with an associated set of attributes to be cataloged. These can be used to set up simple Monte Carlo simulations for a site. Without collaborating cultural evidence, or trends with similar attributes (for example a number of sites showing the same anticipatory date), the Monte Carlo simulation can be used as a filter to establish the likeliness that the observed alignment phenomena is the result of random factors. Such analysis may temper any eagerness to prematurely attribute cultural meaning to an observation. For the most complete description of an archaeological site, we urge researchers to capture the site attributes in a manner which permits statistical analysis. We also encourage cultural astronomers to record that which does not work, and that which may seem to align, but has no discernable meaning. Properly reporting situational information as tenets of the research design will reduce the subjective nature of archaeoastronomical interpretation. Examples from field work will be discussed.

Hull, Anthony B.; Ambruster, C.; Jewell, E.

2012-01-01

361

variational Monte Carlo KEVIN E. RILEY* and JAMES B. ANDERSONy Department of Chemistry, 152 Davey Laboratory for trial wavefunctions used in quantum Monte Carlo calculations of molecular structure. These numerical). This energy difference corresponds to about 1% of the correlation energy. Variational Monte Carlo (VMC) has

Anderson, James B.

362

Kinetics of electron-positron pair plasmas using an adaptive Monte Carlo method

A new algorithm for implementing the adaptive Monte Carlo method is given. It is used to solve the relativistic Boltzmann equations that describe the time evolution of a nonequilibrium electron-positron pair plasma containing high-energy photons and pairs. The collision kernels for the photons as well as pairs are constructed for Compton scattering, pair annihilation and creation, bremsstrahlung, and Bhabha & Moller scattering. For a homogeneous and isotropic plasma, analytical equilibrium solutions are obtained in terms of the initial conditions. For two non-equilibrium models, the time evolution of the photon and pair spectra is determined using the new method. The asymptotic numerical solutions are found to be in a good agreement with the analytical equilibrium states. Astrophysical applications of this scheme are discussed.

Ravi P. Pilla; Jacob Shaham

1997-02-21

363

DSMC calculations for the double ellipse. [direct simulation Monte Carlo method

NASA Technical Reports Server (NTRS)

The direct simulation Monte Carlo (DSMC) method involves the simultaneous computation of the trajectories of thousands of simulated molecules in simulated physical space. Rarefied flow about the double ellipse for test case 6.4.1 has been calculated with the DSMC method of Bird. The gas is assumed to be nonreacting nitrogen flowing at a 30 degree incidence with respect to the body axis, and for the surface boundary conditions, the wall is assumed to be diffuse with full thermal accommodation and at a constant wall temperature of 620 K. A parametric study is presented that considers the effect of variations of computational domain, gas model, cell size, and freestream density on surface quantities.

Moss, James N.; Price, Joseph M.; Celenligil, M. Cevdet

1990-01-01

364

Analysis of vibrational-translational energy transfer using the direct simulation Monte Carlo method

NASA Technical Reports Server (NTRS)

A new model is proposed for energy transfer between the vibrational and translational modes for use in the direct simulation Monte Carlo method (DSMC). The model modifies the Landau-Teller theory for a harmonic oscillator and the rate transition is related to an experimental correlation for the vibrational relaxation time. Assessment of the model is made with respect to three different computations: relaxation in a heat bath, a one-dimensional shock wave, and hypersonic flow over a two-dimensional wedge. These studies verify that the model achieves detailed balance, and excellent agreement with experimental data is obtained in the shock wave calculation. The wedge flow computation reveals that the usual phenomenological method for simulating vibrational nonequilibrium in the DSMC technique predicts much higher vibrational temperatures in the wake region.

Boyd, Iain D.

1991-01-01

365

Breast thermography is one of the scanning techniques used for breast cancer detection. Looking at breast thermal image it is difficult to interpret parameters or tumor such as depth, size and location which are useful for diagnosis and treatment of breast cancer. In our previous work (ITBIC) we proposed a framework for estimation of tumor size using clever algorithms and the radiative heat transfer model. In this paper, we expand it to incorporate the more realistic Pennes bio-heat transfer model and Markov Chain Monte Carlo (MCMC) method, and analyze it's performance in terms of computational speed, accuracy, robustness against noisy inputs, ability to make use of prior information and ability to estimate multiple parameters simultaneously. We discuss the influence of various parameters used in its implementation. We apply this method on clinical data and extract reliable results for the first time using breast thermography. PMID:20198744

Umadevi, V; Suresh, S; Raghavan, S V

2009-01-01

366

Monte Carlo methods for optimizing the piecewise constant Mumford-Shah segmentation model

NASA Astrophysics Data System (ADS)

Natural images are depicted in a computer as pixels on a square grid and neighboring pixels are generally highly correlated. This representation can be mapped naturally to a statistical physics framework on a square lattice. In this paper, we developed an effective use of statistical mechanics to solve the image segmentation problem, which is an outstanding problem in image processing. Our Monte Carlo method using several advanced techniques, including block-spin transformation, Eden clustering and simulated annealing, seeks the solution of the celebrated Mumford-Shah image segmentation model. In particular, the advantage of our method is prominent for the case of multiphase segmentation. Our results verify that statistical physics can be a very efficient approach for image processing.

Watanabe, Hiroshi; Sashida, Satoshi; Okabe, Yutaka; Lee, Hwee Kuan

2011-02-01

367

The Linked Neighbour List (LNL) method for fast off-lattice Monte Carlo simulations of fluids

NASA Astrophysics Data System (ADS)

We present a new algorithm, called linked neighbour list (LNL), useful to substantially speed up off-lattice Monte Carlo simulations of fluids by avoiding the computation of the molecular energy before every attempted move. We introduce a few variants of the LNL method targeted to minimise memory footprint or augment memory coherence and cache utilisation. Additionally, we present a few algorithms which drastically accelerate neighbour finding. We test our methods on the simulation of a dense off-lattice Gay-Berne fluid subjected to periodic boundary conditions observing a speedup factor of about 2.5 with respect to a well-coded implementation based on a conventional link-cell. We provide several implementation details of the different key data structures and algorithms used in this work.

Mazzeo, M. D.; Ricci, M.; Zannoni, C.

2010-03-01

368

Monte Carlo methods for localization of cones given multielectrode retinal ganglion cell recordings

It has recently become possible to identify cone photoreceptors in primate retina from multi-electrode recordings of ganglion cell spiking driven by visual stimuli of sufficiently high spatial resolution. In this paper we present a statistical approach to the problem of identifying the number, locations, and color types of the cones observed in this type of experiment. We develop an adaptive Markov Chain Monte Carlo (MCMC) method that explores the space of cone configurations, using a Linear-Nonlinear-Poisson (LNP) encoding model of ganglion cell spiking output, while analytically integrating out the functional weights between cones and ganglion cells. This method provides information about our posterior certainty about the inferred cone properties, and additionally leads to improvements in both the speed and quality of the inferred cone maps, compared to earlier “greedy” computational approaches. PMID:23194406

Sadeghi, K.; Gauthier, J.L.; Field, G.D.; Greschner, M.; Agne, M.; Chichilnisky, E.J.; Paninski, L.

2013-01-01

369

Monte Carlo Monte Carlo at Work by Gary D. Doolen and John Hendricks E very second nearly 10,000,000,000 "random" numbers are being generated on computers around the world for Monte Carlo solutions to problems hundreds of full-time careers invested in the fine art of generating Monte Carlo solutions--a livelihood

370

Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography

NASA Astrophysics Data System (ADS)

This paper discusses the electrical impedance tomography (EIT) problem: electric currents are injected into a body with unknown electromagnetic properties through a set of contact electrodes. The corresponding voltages that are needed to maintain these currents are measured. The objective is to estimate the unknown resistivity, or more generally the impedivity distribution of the body based on this information. The most commonly used method to tackle this problem in practice is to use gradient-based local linearizations. We give a proof for the differentiability of the electrode boundary data with respect to the resistivity distribution and the contact impedances. Due to the ill-posedness of the problem, regularization has to be employed. In this paper, we consider the EIT problem in the framework of Bayesian statistics, where the inverse problem is recast into a form of statistical inference. The problem is to estimate the posterior distribution of the unknown parameters conditioned on measurement data. From the posterior density, various estimates for the resistivity distribution can be calculated as well as a posteriori uncertainties. The search of the maximum a posteriori estimate is typically an optimization problem, while the conditional expectation is computed by integrating the variable with respect to the posterior probability distribution. In practice, especially when the dimension of the parameter space is large, this integration must be done by Monte Carlo methods such as the Markov chain Monte Carlo (MCMC) integration. These methods can also be used for calculation of a posteriori uncertainties for the estimators. In this paper, we concentrate on MCMC integration methods. In particular, we demonstrate by numerical examples the statistical approach when the prior densities are non-differentiable, such as the prior penalizing the total variation or the L1 norm of the resistivity.

Kaipio, Jari P.; Kolehmainen, Ville; Somersalo, Erkki; Vauhkonen, Marko

2000-10-01

371

Hybrid Monte Carlo/Deterministic Methods for Accelerating Active Interrogation Modeling

The potential for smuggling special nuclear material (SNM) into the United States is a major concern to homeland security, so federal agencies are investigating a variety of preventive measures, including detection and interdiction of SNM during transport. One approach for SNM detection, called active interrogation, uses a radiation source, such as a beam of neutrons or photons, to scan cargo containers and detect the products of induced fissions. In realistic cargo transport scenarios, the process of inducing and detecting fissions in SNM is difficult due to the presence of various and potentially thick materials between the radiation source and the SNM, and the practical limitations on radiation source strength and detection capabilities. Therefore, computer simulations are being used, along with experimental measurements, in efforts to design effective active interrogation detection systems. The computer simulations mostly consist of simulating radiation transport from the source to the detector region(s). Although the Monte Carlo method is predominantly used for these simulations, difficulties persist related to calculating statistically meaningful detector responses in practical computing times, thereby limiting their usefulness for design and evaluation of practical active interrogation systems. In previous work, the benefits of hybrid methods that use the results of approximate deterministic transport calculations to accelerate high-fidelity Monte Carlo simulations have been demonstrated for source-detector type problems. In this work, the hybrid methods are applied and evaluated for three example active interrogation problems. Additionally, a new approach is presented that uses multiple goal-based importance functions depending on a particle s relevance to the ultimate goal of the simulation. Results from the examples demonstrate that the application of hybrid methods to active interrogation problems dramatically increases their calculational efficiency.

Peplow, Douglas E. [ORNL; Miller, Thomas Martin [ORNL; Patton, Bruce W [ORNL; Wagner, John C [ORNL

2013-01-01

372

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

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

Hsi-Sheng Goan

2004-06-15

373

The GUINEVERE experiment (Generation of Uninterrupted Intense Neutrons at the lead Venus Reactor) is an experimental program in support of the ADS technology presently carried out at SCK-CEN in Mol (Belgium). In the experiment a modified lay-out of the original thermal VENUS critical facility is coupled to an accelerator, built by the French body CNRS in Grenoble, working in both continuous and pulsed mode and delivering 14 MeV neutrons by bombardment of deuterons on a tritium-target. The modified lay-out of the facility consists of a fast subcritical core made of 30% U-235 enriched metallic Uranium in a lead matrix. Several off-line and on-line reactivity measurement techniques will be investigated during the experimental campaign. This report is focused on the simulation by deterministic (ERANOS French code) and Monte Carlo (MCNPX US code) calculations of three reactivity measurement techniques, Slope ({alpha}-fitting), Area-ratio and Source-jerk, applied to a GUINEVERE subcritical configuration (namely SC1). The inferred reactivity, in dollar units, by the Area-ratio method shows an overall agreement between the two deterministic and Monte Carlo computational approaches, whereas the MCNPX Source-jerk results are affected by large uncertainties and allow only partial conclusions about the comparison. Finally, no particular spatial dependence of the results is observed in the case of the GUINEVERE SC1 subcritical configuration. (authors)

Bianchini, G.; Burgio, N.; Carta, M. [ENEA C.R. CASACCIA, via Anguillarese, 301, 00123 S. Maria di Galeria Roma (Italy); Peluso, V. [ENEA C.R. BOLOGNA, Via Martiri di Monte Sole, 4, 40129 Bologna (Italy); Fabrizio, V.; Ricci, L. [Univ. of Rome La Sapienza, C/o ENEA C.R. CASACCIA, via Anguillarese, 301, 00123 S. Maria di Galeria Roma (Italy)

2012-07-01

374

Graduiertenschule Hybrid Monte Carlo

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

Heermann, Dieter W.

375

A voxel warping method for 4D dose accumulation was implemented in the VMC++ Monte Carlo code. Dose calculations using this\\u000a method were compared with an energy remapping method in simple deforming phantoms with exact transformations to show that\\u000a the methods are equivalent. We also demonstrate that in patient geometries, the voxel warping and energy remapping method\\u000a can be used to

E. Heath; I. Kawrakow; F. Tessier; J. V. Siebers

376

Nonequilibrium hypersonic flows simulations with asymptotic-preserving Monte Carlo methods

NASA Astrophysics Data System (ADS)

In the rarefied gas dynamics, the DSMC method is one of the most popular numerical tools. It performs satisfactorily in simulating hypersonic flows surrounding re-entry vehicles and micro-/nano- flows. However, the computational cost is expensive, especially when Kn ? 0. Even for flows in the near-continuum regime, pure DSMC simulations require a number of computational efforts for most cases. Albeit several DSMC/NS hybrid methods are proposed to deal with this, those methods still suffer from the boundary treatment, which may cause nonphysical solutions. Filbet and Jin [1] proposed a framework of new numerical methods of Boltzmann equation, called asymptotic preserving schemes, whose computational costs are affordable as Kn ? 0. Recently, Ren et al. [2] realized the AP schemes with Monte Carlo methods (AP-DSMC), which have better performance than counterpart methods. In this paper, AP-DSMC is applied in simulating nonequilibrium hypersonic flows. Several numerical results are computed and analyzed to study the efficiency and capability of capturing complicated flow characteristics.

Ren, Wei; Liu, Hong; Jin, Shi

2014-12-01

377

A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter. The unbounded error growth found in the extended Kalman filter, which is caused by an overly simplified closure in

Geir Evensen

1994-01-01

378

In this paper, we deepen the R&D program named DTO-DC (Digital Object Test and Dosimetric Console), which goal is to develop an efficient, accurate and full method to achieve dosimetric quality control (QC) of radiotherapy treatment planning system (TPS). This method is mainly based on Digital Test Objects (DTOs) and on Monte Carlo (MC) simulation using the PENELOPE code [1].

Yassine Benhdech; Stéphane Beaumont; Jean-Pierre Guédon; Tarraf Torfeh

2010-01-01

379

We introduce a new statistical computing method, called data cloning, to calculate maximum likelihood estimates and their standard errors for complex ecological models. Although the method uses the Bayesian framework and exploits the computational simplicity of the Markov chain Monte Carlo (MCMC) algorithms, it provides valid frequentist inferences such as the maximum likelihood estimates and their standard errors. The inferences

Subhash R. Lele; Brian Dennis; Frithjof Lutscher

2007-01-01

380

A First-Passage Kinetic Monte Carlo method for reaction–drift–diffusion processes

Stochastic reaction–diffusion models are now a popular tool for studying physical systems in which both the explicit diffusion of molecules and noise in the chemical reaction process play important roles. The Smoluchowski diffusion-limited reaction model (SDLR) is one of several that have been used to study biological systems. Exact realizations of the underlying stochastic processes described by the SDLR model can be generated by the recently proposed First-Passage Kinetic Monte Carlo (FPKMC) method. This exactness relies on sampling analytical solutions to one and two-body diffusion equations in simplified protective domains. In this work we extend the FPKMC to allow for drift arising from fixed, background potentials. As the corresponding Fokker–Planck equations that describe the motion of each molecule can no longer be solved analytically, we develop a hybrid method that discretizes the protective domains. The discretization is chosen so that the drift–diffusion of each molecule within its protective domain is approximated by a continuous-time random walk on a lattice. New lattices are defined dynamically as the protective domains are updated, hence we will refer to our method as Dynamic Lattice FPKMC or DL-FPKMC. We focus primarily on the one-dimensional case in this manuscript, and demonstrate the numerical convergence and accuracy of our method in this case for both smooth and discontinuous potentials. We also present applications of our method, which illustrate the impact of drift on reaction kinetics.

Mauro, Ava J., E-mail: avamauro@bu.edu [Department of Mathematics and Statistics, Boston University, 111 Cummington Mall, Boston, MA 02215 (United States); Sigurdsson, Jon Karl; Shrake, Justin [Department of Mathematics, University of California, Santa Barbara (United States)] [Department of Mathematics, University of California, Santa Barbara (United States); Atzberger, Paul J., E-mail: atzberg@math.ucsb.edu [6712 South Hall, Department of Mathematics, University of California, Santa Barbara, CA 93106 (United States); Isaacson, Samuel A., E-mail: isaacson@math.bu.edu [Department of Mathematics and Statistics, Boston University, 111 Cummington Mall, Boston, MA 02215 (United States)

2014-02-15

381

A First-Passage Kinetic Monte Carlo method for reaction-drift-diffusion processes

NASA Astrophysics Data System (ADS)

Stochastic reaction-diffusion models are now a popular tool for studying physical systems in which both the explicit diffusion of molecules and noise in the chemical reaction process play important roles. The Smoluchowski diffusion-limited reaction model (SDLR) is one of several that have been used to study biological systems. Exact realizations of the underlying stochastic processes described by the SDLR model can be generated by the recently proposed First-Passage Kinetic Monte Carlo (FPKMC) method. This exactness relies on sampling analytical solutions to one and two-body diffusion equations in simplified protective domains. In this work we extend the FPKMC to allow for drift arising from fixed, background potentials. As the corresponding Fokker-Planck equations that describe the motion of each molecule can no longer be solved analytically, we develop a hybrid method that discretizes the protective domains. The discretization is chosen so that the drift-diffusion of each molecule within its protective domain is approximated by a continuous-time random walk on a lattice. New lattices are defined dynamically as the protective domains are updated, hence we will refer to our method as Dynamic Lattice FPKMC or DL-FPKMC. We focus primarily on the one-dimensional case in this manuscript, and demonstrate the numerical convergence and accuracy of our method in this case for both smooth and discontinuous potentials. We also present applications of our method, which illustrate the impact of drift on reaction kinetics.

Mauro, Ava J.; Sigurdsson, Jon Karl; Shrake, Justin; Atzberger, Paul J.; Isaacson, Samuel A.

2014-02-01

382

Microscopic Nuclear Level Densities from Fe to Ge by the Shell Model Monte Carlo Method

We calculate microscopically total and parity-projected level densities for $\\beta$-stable even-even nuclei between Fe and Ge, using the shell model Monte Carlo methods in the complete $(pf+0g_{9/2})$-shell. A single-particle level density parameter $a$ and backshift parameter $\\Delta$ are extracted by fitting the calculated densities to a backshifted Bethe formula, and their systematics are studied across the region. Shell effects are observed in $\\Delta$ for nuclei with Z=28 or N=28 and in the behavior of $A/a$ as a function of the number of neutrons. We find a significant parity-dependence of the level densities for nuclei with $A \\alt 60$, which diminishes as $A$ increases.

H. Nakada; Y. Alhassid

1998-09-22

383

The Auxiliary Field Diffusion Monte Carlo Method for Nuclear Physics and Nuclear Astrophysics

In this thesis, I discuss the use of the Auxiliary Field Diffusion Monte Carlo method to compute the ground state of nuclear Hamiltonians, and I show several applications to interesting problems both in nuclear physics and in nuclear astrophysics. In particular, the AFDMC algorithm is applied to the study of several nuclear systems, finite, and infinite matter. Results about the ground state of nuclei ($^4$He, $^8$He, $^{16}$O and $^{40}$Ca), neutron drops (with 8 and 20 neutrons) and neutron rich-nuclei (isotopes of oxygen and calcium) are discussed, and the equation of state of nuclear and neutron matter are calculated and compared with other many-body calculations. The $^1S_0$ superfluid phase of neutron matter in the low-density regime was also studied.

Stefano Gandolfi

2007-12-09

384

A spectral analysis of the domain decomposed Monte Carlo method for linear systems

The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)

Slattery, S. R.; Wilson, P. P. H. [Engineering Physics Department, University of Wisconsin - Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Evans, T. M. [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 (United States)

2013-07-01

385

Study of temperature drop in microchannel using direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

The Direct Simulation Monte Carlo (DSMC) method has long been used to study subsonic rarefied gas flows in microchannels. A considerable temperature drop across the length is observed in the previous studies. Such simulations are performed for small aspect ratios (length / height) of the order of 10. However, most experimental studies are performed at aspect ratios of 100 or more, where such temperature drops are not observed. The objective of this paper is to study the effect of the aspect ratio as well as the pressure ratio (P_inlet/P_exit) on the temperature drop across microchannels for inlet Kn ranging from 0.05 to 3. It is aimed to find out the aspect ratio and the pressure ratio to have isothermal flow situation. Apart from DSMC simulations, a simple analysis is carried out to calculate the outlet temperature by solving the conservation of mass, momentum and energy. The parameter values required for isothermal conditions are identified.

Gavasane, Abhimanyu; Agrawal, Amit; Pradeep, A. M.; Bhandarkar, Upendra

2014-12-01

386

A Monte Carlo Method for Modeling Thermal Damping: Beyond the Brownian-Motion Master Equation

The "standard" Brownian motion master equation, used to describe thermal damping, is not completely positive, and does not admit a Monte Carlo method, important in numerical simulations. To eliminate both these problems one must add a term that generates additional position diffusion. He we show that one can obtain a completely positive simple quantum Brownian motion, efficiently solvable, without any extra diffusion. This is achieved by using a stochastic Schroedinger equation (SSE), closely analogous to Langevin's equation, that has no equivalent Markovian master equation. Considering a specific example, we show that this SSE is sensitive to nonlinearities in situations in which the master equation is not, and may therefore be a better model of damping for nonlinear systems.

Kurt Jacobs

2009-01-06

387

A Monte Carlo Method for Projecting Uncertainty in 2D Lagrangian Trajectories

NASA Astrophysics Data System (ADS)

In this study, a novel method is proposed for modeling the propagation of uncertainty due to subgrid-scale processes through a Lagrangian trajectory advected by ocean surface velocities. The primary motivation and application is differentiating between active and passive trajectories for sea turtles as observed through satellite telemetry. A spatiotemporal launch box is centered on the time and place of actual launch and populated with launch points. Synthetic drifters are launched at each of these locations, adding, at each time step along the trajectory, Monte Carlo perturbations in velocity scaled to the natural variability of the velocity field. The resulting trajectory cloud provides a dynamically evolving density field of synthetic drifter locations that represent the projection of subgrid-scale uncertainty out in time. Subsequently, by relaunching synthetic drifters at points along the trajectory, plots are generated in a daisy chain configuration of the “most likely passive pathways” for the drifter.

Robel, A.; Lozier, S.; Gary, S. F.

2009-12-01

388

NASA Technical Reports Server (NTRS)

The results are reported of two unrelated studies. The first was an investigation of the formulation of the equations for non-uniform unsteady flows, by perturbation of an irrotational flow to obtain the linear Green's equation. The resulting integral equation was found to contain a kernel which could be expressed as the solution of the adjoint flow equation, a linear equation for small perturbations, but with non-constant coefficients determined by the steady flow conditions. It is believed that the non-uniform flow effects may prove important in transonic flutter, and that in such cases, the use of doublet type solutions of the wave equation would then prove to be erroneous. The second task covered an initial investigation into the use of the Monte Carlo method for solution of acoustical field problems. Computed results are given for a rectangular room problem, and for a problem involving a circular duct with a source located at the closed end.

Haviland, J. K.

1974-01-01

389

A Monte Carlo method for variance estimation for estimators based on induced smoothing.

An important issue in statistical inference for semiparametric models is how to provide reliable and consistent variance estimation. Brown and Wang (2005. Standard errors and covariance matrices for smoothed rank estimators. Biometrika 92: , 732-746) proposed a variance estimation procedure based on an induced smoothing for non-smooth estimating functions. Herein a Monte Carlo version is developed that does not require any explicit form for the estimating function itself, as long as numerical evaluation can be carried out. A general convergence theory is established, showing that any one-step iteration leads to a consistent variance estimator and continuation of the iterations converges at an exponential rate. The method is demonstrated through the Buckley-James estimator and the weighted log-rank estimators for censored linear regression, and rank estimation for multiple event times data. PMID:24812418

Jin, Zhezhen; Shao, Yongzhao; Ying, Zhiliang

2015-01-01

390

NASA Astrophysics Data System (ADS)

A study of the dielectric and magnetic properties of multiferroic materials using the Monte Carlo (MC) method is presented. Two different systems are considered: the first, ferroelectric-antiferromagnetic (FE-AFM) recently studied by X. S. Gaoand J. M. Liu and the second antiferroelectric-ferromagnetic (AFE-FM). Based on the DIFFOUR-Ising hybrid microscopic model developed by Janssen, a Hamiltonian that takes into account the magnetoelectric coupling in both ferroic phases is proposed. The obtained results show that the existence of such coupling modifies the ferroelectric and magnetic ordering in both phases. Additionally, it is shown that the presence of a magnetic or an electric field influences the electric polarization and the magnetization, respectively, making evident the magnetoelectric effect.

Sosa, A.; Almodovar, N. S.; Portelles, J.; Heiras, J.; Siqueiros, J. M.

2012-03-01

391

The FLUKA code for application of Monte Carlo methods to promote high precision ion beam therapy

Monte Carlo (MC) methods are increasingly being utilized to support several aspects of commissioning and clinical operation of ion beam therapy facilities. In this contribution two emerging areas of MC applications are outlined. The value of MC modeling to promote accurate treatment planning is addressed via examples of application of the FLUKA code to proton and carbon ion therapy at the Heidelberg Ion Beam Therapy Center in Heidelberg, Germany, and at the Proton Therapy Center of Massachusetts General Hospital (MGH) Boston, USA. These include generation of basic data for input into the treatment planning system (TPS) and validation of the TPS analytical pencil-beam dose computations. Moreover, we review the implementation of PET/CT (Positron-Emission-Tomography / Computed- Tomography) imaging for in-vivo verification of proton therapy at MGH. Here, MC is used to calculate irradiation-induced positron-emitter production in tissue for comparison with the +-activity measurement in order to infer indirect infor...

Parodi, K; Cerutti, F; Ferrari, A; Mairani, A; Paganetti, H; Sommerer, F

2010-01-01

392

A Monte-Carlo method for ex-core neutron response

A Monte Carlo neutron transport kernel capability primarily for ex-core neutron response is described. The capability consists of the generation of a set of response kernels, which represent the neutron transport from the core to a specific ex-core volume. This is accomplished by tagging individual neutron histories from their initial source sites and tracking them throughout the problem geometry, tallying those that interact in the geometric regions of interest. These transport kernels can subsequently be combined with any number of core power distributions to determine detector response for a variety of reactor Thus, the transport kernels are analogous to an integrated adjoint response. Examples of pressure vessel response and ex-core neutron detector response are provided to illustrate the method.

Gamino, R.G.; Ward, J.T.; Hughes, J.C. [Lockheed Martin Corp., Schenectady, NY (United States)

1997-10-01

393

The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations

NASA Astrophysics Data System (ADS)

The aim of ab-initio approaches is the simulation of many-body quantum systems from the first principles of quantum mechanics. These methods are traditionally based on the many-body Schrödinger equation which represents an incredible mathematical challenge. In this paper, we introduce the many-body Wigner Monte Carlo method in the context of distinguishable particles and in the absence of spin-dependent effects. Despite these restrictions, the method has several advantages. First of all, the Wigner formalism is intuitive, as it is based on the concept of a quasi-distribution function. Secondly, the Monte Carlo numerical approach allows scalability on parallel machines that is practically unachievable by means of other techniques based on finite difference or finite element methods. Finally, this method allows time-dependent ab-initio simulations of strongly correlated quantum systems. In order to validate our many-body Wigner Monte Carlo method, as a case study we simulate a relatively simple system consisting of two particles in several different situations. We first start from two non-interacting free Gaussian wave packets. We, then, proceed with the inclusion of an external potential barrier, and we conclude by simulating two entangled (i.e. correlated) particles. The results show how, in the case of negligible spin-dependent effects, the many-body Wigner Monte Carlo method provides an efficient and reliable tool to study the time-dependent evolution of quantum systems composed of distinguishable particles.

Sellier, J. M.; Dimov, I.

2014-09-01

394

This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC sequence of SCALE and the ADVANTG/MCNP framework. Application of the method to representative, real-world problems, including calculation of dose rate and energy dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.

Wagner, John C [ORNL] [ORNL; Peplow, Douglas E. [ORNL] [ORNL; Mosher, Scott W [ORNL] [ORNL

2014-01-01

395

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

396

Vacation matrix method for fission source convergence in Monte Carlo criticality calculations

NASA Astrophysics Data System (ADS)

Fission source convergence in Monte Carlo criticality calculations can be difficult for some types of problems, particularly those with weak neutron communication between different regions of the problem. Several attempts to solve this problem have met with limited success. The Fission Matrix method has been the method of choice for the acceleration of convergence of the fission source distribution to the fundamental eigenmode, or steady-state distribution. A new approach is introduced to circumvent the statistical noise of the estimated fission matrix and to make the physical model amenable to improvement by engineering means. The new Vacation Matrix method achieves the correct fission source distribution by identifying the key variables that contribute to the noise of the solution. It determines which of these variables are independent of one another and can be altered without changing the real system but, instead, by changing only the spatial binning used to define the solution matrix geometry---these variables are the leakage probability and the vacated source probability. The said variables, and their associated noise, are strategically removed from the system model, leading directly to the vacation matrix model. The Vacation Matrix method is a new way of looking at an old problem.

Finch, Joshua P.

397

An energy transfer method for 4D Monte Carlo dose calculation

This article presents a new method for four-dimensional Monte Carlo dose calculations which properly addresses dose mapping for deforming anatomy. The method, called the energy transfer method (ETM), separates the particle transport and particle scoring geometries: Particle transport takes place in the typical rectilinear coordinate system of the source image, while energy deposition scoring takes place in a desired reference image via use of deformable image registration. Dose is the energy deposited per unit mass in the reference image. ETM has been implemented into DOSXYZnrc and compared with a conventional dose interpolation method (DIM) on deformable phantoms. For voxels whose contents merge in the deforming phantom, the doses calculated by ETM are exactly the same as an analytical solution, contrasting to the DIM which has an average 1.1% dose discrepancy in the beam direction with a maximum error of 24.9% found in the penumbra of a 6 MV beam. The DIM error observed persists even if voxel subdivision is used. The ETM is computationally efficient and will be useful for 4D dose addition and benchmarking alternative 4D dose addition algorithms. PMID:18841862

Siebers, Jeffrey V.; Zhong, Hualiang

2008-01-01

398

Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods

NASA Technical Reports Server (NTRS)

Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.

Chung, Chang-Hong; Kim, Sku C.; Stubbs, Robert M.; Dewitt, Kenneth J.

1994-01-01

399

The study of particle coagulation and sintering processes is important in a variety of research studies ranging from cell fusion and dust motion to aerosol formation applications. These processes are traditionally simulated using either Monte-Carlo methods or integro-differential equations for particle number density functions. In this paper, we present a computational technique for cases where we believe that accurate closed evolution equations for a finite number of moments of the density function exist in principle, but are not explicitly available. The so-called equation-free computational framework is then employed to numerically obtain the solution of these unavailable closed moment equations by exploiting (through intelligent design of computational experiments) the corresponding fine-scale (here, Monte-Carlo) simulation. We illustrate the use of this method by accelerating the computation of evolving moments of uni- and bivariate particle coagulation and sintering through short simulation bursts of a constant-number Monte-Carlo scheme.

Zou Yu, E-mail: yzou@Princeton.ED [Department of Chemical Engineering, Princeton University, Princeton, NJ 08544 (United States); Kavousanakis, Michail E., E-mail: mkavousa@Princeton.ED [Department of Chemical Engineering, Princeton University, Princeton, NJ 08544 (United States); Kevrekidis, Ioannis G., E-mail: yannis@Princeton.ED [Department of Chemical Engineering, Princeton University, Princeton, NJ 08544 (United States); Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544 (United States); Fox, Rodney O., E-mail: rofox@iastate.ed [Department of Chemical and Biological Engineering, Iowa State University, Ames, IA 50011 (United States)

2010-07-20

400

NASA Astrophysics Data System (ADS)

Source anisotropy is a very important factor in the brachytherapy quality assurance of high-dose rate (HDR) afterloading stepping sources. If anisotropy is not taken into account then doses received by a brachytherapy patient in certain directions can be in error by a clinically significant amount. Experimental measurements of anisotropy are very labour intensive. We have shown that within acceptable limits of accuracy, Monte Carlo integration (MCI) of a modified Sievert integral (3D generalization) can provide the necessary data within a much shorter time scale than can experiments. Hence MCI can be used for routine quality assurance schedules whenever a new design of HDR or PDR is used for brachytherapy afterloading. Our MCI calculation results are compared with published experimental data and Monte Carlo simulation data for microSelectron and VariSource sources. We have shown not only that MCI offers advantages over alternative numerical integration methods, but also that treating filtration coefficients as radial distance-dependent functions improves Sievert integral accuracy at low energies. This paper also provides anisotropy data for three new sources, one for the microSelectron-HDR and two for the microSelectron-PDR, for which data are currently not available. The information we have obtained in this study can be incorporated into clinical practice.

Baltas, Dimos; Giannouli, Stavroula; Garbi, Anastasia; Diakonos, Fotios; Geramani, Konstantina; Ioannidis, Georgios T.; Tsalpatouros, Alexios; Uzunoglu, Nikolaos; Kolotas, Christos; Zamboglou, Nikolaos

1998-06-01

401

NASA Technical Reports Server (NTRS)

A new solution procedure has been developed to analyze the flowfield properties in the vicinity of the Inertial Upper Stage/Spacecraft during the 1st stage (SRMI) burn. Continuum methods are used to compute the nozzle flow and the exhaust plume flowfield as far as the boundary where the breakdown of translational equilibrium leaves these methods invalid. The Direct Simulation Monte Carlo (DSMC) method is applied everywhere beyond this breakdown boundary. The flowfield distributions of density, velocity, temperature, relative abundance, surface flux density, and pressure are discussed for each species for 2 sets of boundary conditions: vacuum and freestream. The interaction of the exhaust plume and the freestream with the spacecraft and the 2-stream direct interaction are discussed. The results show that the low density, high velocity, counter flowing free-stream substantially modifies the flowfield properties and the flux density incident on the spacecraft. A freestream bow shock is observed in the data, located forward of the high density region of the exhaust plume into which the freestream gas does not penetrate. The total flux density incident on the spacecraft, integrated over the SRM1 burn interval is estimated to be of the order of 10 to the 22nd per sq m (about 1000 atomic layers).

Hueser, J. E.; Brock, F. J.; Melfi, L. T., Jr.; Bird, G. A.

1984-01-01

402

Statistical Properties of Nuclei by the Shell Model Monte Carlo Method

We use quantum Monte Carlo methods in the framework of the interacting nuclear shell model to calculate the statistical properties of nuclei at finite temperature and/or excitation energies. With this approach we can carry out realistic calculations in much larger configuration spaces than are possible by conventional methods. A major application of the methods has been the microscopic calculation of nuclear partition functions and level densities, taking into account both correlations and shell effects. Our results for nuclei in the mass region A ~ 50 - 70 are in remarkably good agreement with experimental level densities without any adjustable parameters and are an improvement over empirical formulas. We have recently extended the shell model theory of level statistics to higher temperatures, including continuum effects. We have also constructed simple statistical models to explain the dependence of the microscopically calculated level densities on good quantum numbers such as parity. Thermal signatures of pairing correlations are identified through odd-even effects in the heat capacity.

Y. Alhassid

2006-04-26

403

Bridging the gap between quantum Monte Carlo and F12-methods

NASA Astrophysics Data System (ADS)

Tensor product approximation of pair-correlation functions opens a new route from quantum Monte Carlo (QMC) to explicitly correlated F12 methods. Thereby one benefits from stochastic optimization techniques used in QMC to get optimal pair-correlation functions which typically recover more than 85% of the total correlation energy. Our approach incorporates, in particular, core and core-valence correlation which are poorly described by homogeneous and isotropic ansatz functions usually applied in F12 calculations. We demonstrate the performance of the tensor product approximation by applications to atoms and small molecules. It turns out that the canonical tensor format is especially suitable for the efficient computation of two- and three-electron integrals required by explicitly correlated methods. The algorithm uses a decomposition of three-electron integrals, originally introduced by Boys and Handy and further elaborated by Ten-no in his 3d numerical quadrature scheme, which enables efficient computations in the tensor format. Furthermore, our method includes the adaptive wavelet approximation of tensor components where convergence rates are given in the framework of best N-term approximation theory.

Chinnamsetty, Sambasiva Rao; Luo, Hongjun; Hackbusch, Wolfgang; Flad, Heinz-Jürgen; Uschmajew, André

2012-06-01

404

MONTE CARLO EXTENSION OF QUASIMONTE CARLO Art B. Owen

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

Owen, Art

405

A general Monte Carlo method for mapping multiple quantitative trait loci

In this paper we address the mapping of multiple quantitative trait loci (QTLs) in line crosses for which the genetic data are highly incomplete. Such complicated situations occur, for instance, when dominant markers are used or when unequally informative markers are used in experiments with outbred populations. We describe a general and flexible Monte Carlo expectation-maximization (Monte Carlo EM) algorithm

Ritsert C. Jansen

1996-01-01

406

In previous work, exponential convergence of Monte Carlo solutions using the reduced source method with Legendre expansion has been achieved only in one-dimensional rod and slab geometries. In this paper, the method is applied to three-dimensional (right parallelepiped) problems, with resulting evidence suggesting success. As implemented in this paper, the method approximates an angular integral of the flux with a discrete-ordinates numerical quadrature. It is possible that this approximation introduces an inconsistency that must be addressed.

Favorite, J.A.

1999-09-01

407

A sensitivity analysis has been performed for a 14MeV neutron benchmark on an iron assembly, typical for a fusion neutronic integral experiment. Probabilistic and deterministic computational methods have been used in the sensitivity calculations with the main objective to check and validate the novel Monte Carlo technique for calculating point detector sensitivities. Good agreement has been achieved between the Monte

U Fischer; I Kodeli; C Konno; R. L Perel

2004-01-01

408

The prediction of material microstructure is of great interest to the material designers since the property and performance of materials depend strongly on their microstructures. In this research the Monte Carlo method and grain growth phenomenon have been used to predict the limiting grain size in the presence of second phase particles. The results showed a good agreement with the

S. M. Hafez Haghighat; A. Karimi Taheri

2008-01-01

409

The study of particle coagulation and sintering processes is important in a variety of research studies ranging from cell fusion and dust motion to aerosol formation applications. These processes are traditionally simulated using either Monte-Carlo methods or integro-differential equations for particle number density functions. In this paper, we present a computational technique for cases where we believe that accurate closed

Yu Zou; Michail E. Kavousanakis; Ioannis G. Kevrekidis; Rodney O. Fox

2010-01-01

410

A honeycomb probe was designed to measure the optical properties of biological tissues using single Monte Carlo method. The ongoing project is intended to be a multi-wavelength, real time, and in-vivo technique to detect breast cancer. Preliminary...

Bendele, Travis Henry

2013-02-22

411

The algorithms of estimation of the time series correlation functions in nuclear reactor calculations using the Monte Carlo method are described. Correlation functions are used for the estimation of biases, for calculations of variance taking into account the correlations between neutron generations, and for choosing skipped generations.

Kalugin, M. A.; Oleynik, D. S.; Sukhino-Khomenko, E. A., E-mail: sukhino-khomenko@adis.vver.kiae.ru [National Research Centre Kurchatov Institute (Russian Federation)

2012-12-15

412

In this paper, the optical concentration ratio for the parabolic trough solar concentrators (PTSCs), which is a key boundary condition in the heat transfer performance analysis, would be simulated and computed by Monte Carlo Ray-Trace (MCRT) method in different conditions. In the computation process, non-parallelism of solar rays, geometric concentrating ratio and rim angle would be considered. Based on the

Bin Yang; Jun Zhao; Tao Xu; Qiang Zhu

2010-01-01

413

A Method for Coating Fibers in Oxide Composites Jared H. Weaver, James Yang, Carlos G. Levi of the most significant developments in fiber coatings for oxide composites has been the discovery of LaPO4 oxide fibers after matrix infiltration and sintering is devised and demonstrated. It uses

Zok, Frank

414

The purpose of this work was to extend the verification of Monte Carlo based methods for estimating radiation dose in computed tomography (CT) exams beyond a single CT scanner to a multidetector CT (MDCT) scanner, and from cylindrical CTDI phantom measurements to both cylindrical and physical anthropomorphic phantoms. Both cylindrical and physical anthropomorphic phantoms were scanned on an MDCT under

J. J. DeMarco; C. H. Cagnon; D. D. Cody; D. M. Stevens; C. H. McCollough; J. O'Daniel; M. F. McNitt-Gray

2005-01-01

415

Total and parity-projected level densities of iron-region nuclei are calculated microscopically by using Monte Carlo methods for the nuclear shell model in the complete $(pf+0g_{9/2})$-shell. The calculated total level density is found to be in good agreement with the experimental level density. The Monte Carlo calculations offer a significant improvement over the thermal Hartree-Fock approximation. Contrary to the Fermi gas model, it is found that the level density has a significant parity-dependence in the neutron resonance region. The systematics of the level density parameters (including shell effects) in the iron region is presented.

H. Nakada; Y. Alhassid

1998-01-21

416

We discuss the recently proposed multicanonical multigrid Monte Carlo method and apply it to the scalar $\\phi^4$-model on a square lattice. To investigate the performance of the new algorithm at the field-driven first-order phase transitions between the two ordered phases we carefully analyze the autocorrelations of the Monte Carlo process. Compared with standard multicanonical simulations a real-time improvement of about one order of magnitude is established. The interface tension between the two ordered phases is extracted from high-statistics histograms of the magnetization applying histogram reweighting techniques.

Wolfhard Janke; Tilman Sauer

1994-12-17

417

A reverse Monte Carlo (RMC) method is developed to obtain the energy loss function (ELF) and optical constants from a measured reflection electron energy-loss spectroscopy (REELS) spectrum by an iterative Monte Carlo (MC) simulation procedure. The method combines the simulated annealing method, i.e., a Markov chain Monte Carlo (MCMC) sampling of oscillator parameters, surface and bulk excitation weighting factors, and band gap energy, with a conventional MC simulation of electron interaction with solids, which acts as a single step of MCMC sampling in this RMC method. To examine the reliability of this method, we have verified that the output data of the dielectric function are essentially independent of the initial values of the trial parameters, which is a basic property of a MCMC method. The optical constants derived for SiO{sub 2} in the energy loss range of 8-90 eV are in good agreement with other available data, and relevant bulk ELFs are checked by oscillator strength-sum and perfect-screening-sum rules. Our results show that the dielectric function can be obtained by the RMC method even with a wide range of initial trial parameters. The RMC method is thus a general and effective method for determining the optical properties of solids from REELS measurements.

Da, B.; Sun, Y.; Ding, Z. J. [Hefei National Laboratory for Physical Sciences at Microscale and Department of Physics, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People's Republic of China (China)] [Hefei National Laboratory for Physical Sciences at Microscale and Department of Physics, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People's Republic of China (China); Mao, S. F. [School of Nuclear Science and Technology, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People's Republic of China (China)] [School of Nuclear Science and Technology, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People's Republic of China (China); Zhang, Z. M. [Centre of Physical Experiments, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People's Republic of China (China)] [Centre of Physical Experiments, University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People's Republic of China (China); Jin, H.; Yoshikawa, H.; Tanuma, S. [Advanced Surface Chemical Analysis Group, National Institute for Materials Science, 1-2-1 Sengen Tsukuba, Ibaraki 305-0047 (Japan)] [Advanced Surface Chemical Analysis Group, National Institute for Materials Science, 1-2-1 Sengen Tsukuba, Ibaraki 305-0047 (Japan)

2013-06-07

418

NASA Astrophysics Data System (ADS)

Monte Carlo calculations are increasingly used to assess stray radiation dose to healthy organs of proton therapy patients and estimate the risk of secondary cancer. Among the secondary particles, neutrons are of primary concern due to their high relative biological effectiveness. The validation of Monte Carlo simulations for out-of-field neutron doses remains however a major challenge to the community. Therefore this work focused on developing a global experimental approach to test the reliability of the MCNPX models of two proton therapy installations operating at 75 and 178 MeV for ocular and intracranial tumor treatments, respectively. The method consists of comparing Monte Carlo calculations against experimental measurements of: (a) neutron spectrometry inside the treatment room, (b) neutron ambient dose equivalent at several points within the treatment room, (c) secondary organ-specific neutron doses inside the Rando-Alderson anthropomorphic phantom. Results have proven that Monte Carlo models correctly reproduce secondary neutrons within the two proton therapy treatment rooms. Sensitive differences between experimental measurements and simulations were nonetheless observed especially with the highest beam energy. The study demonstrated the need for improved measurement tools, especially at the high neutron energy range, and more accurate physical models and cross sections within the Monte Carlo code to correctly assess secondary neutron doses in proton therapy applications.

Farah, J.; Martinetti, F.; Sayah, R.; Lacoste, V.; Donadille, L.; Trompier, F.; Nauraye, C.; De Marzi, L.; Vabre, I.; Delacroix, S.; Hérault, J.; Clairand, I.

2014-06-01

419

Monte Carlo calculations are increasingly used to assess stray radiation dose to healthy organs of proton therapy patients and estimate the risk of secondary cancer. Among the secondary particles, neutrons are of primary concern due to their high relative biological effectiveness. The validation of Monte Carlo simulations for out-of-field neutron doses remains however a major challenge to the community. Therefore this work focused on developing a global experimental approach to test the reliability of the MCNPX models of two proton therapy installations operating at 75 and 178 MeV for ocular and intracranial tumor treatments, respectively. The method consists of comparing Monte Carlo calculations against experimental measurements of: (a) neutron spectrometry inside the treatment room, (b) neutron ambient dose equivalent at several points within the treatment room, (c) secondary organ-specific neutron doses inside the Rando-Alderson anthropomorphic phantom. Results have proven that Monte Carlo models correctly reproduce secondary neutrons within the two proton therapy treatment rooms. Sensitive differences between experimental measurements and simulations were nonetheless observed especially with the highest beam energy. The study demonstrated the need for improved measurement tools, especially at the high neutron energy range, and more accurate physical models and cross sections within the Monte Carlo code to correctly assess secondary neutron doses in proton therapy applications. PMID:24800943

Farah, J; Martinetti, F; Sayah, R; Lacoste, V; Donadille, L; Trompier, F; Nauraye, C; De Marzi, L; Vabre, I; Delacroix, S; Hérault, J; Clairand, I

2014-06-01

420

Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods

The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highly detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.

Godfrey, Andrew T [ORNL; Gehin, Jess C [ORNL; Bekar, Kursat B [ORNL; Celik, Cihangir [ORNL

2014-01-01

421

A new Monte Carlo method for getting the density of states of atomic cluster systems

NASA Astrophysics Data System (ADS)

A novel Monte Carlo flat histogram algorithm is proposed to get the classical density of states in terms of the potential energy, g(Ep), for systems with continuous variables such as atomic clusters. It aims at avoiding the long iterative process of the Wang-Landau method and controlling carefully the convergence, but keeping the ability to overcome energy barriers. Our algorithm is based on a preliminary mapping in a series of points (called a ?-mapping), obtained by a two-parameter local probing of g(Ep), and it converges in only two subsequent reweighting iterations on large intervals. The method is illustrated on the model system of a 432 atom cluster bound by a Rydberg type potential. Convergence properties are first examined in detail, particularly in the phase transition zone. We get g(Ep) varying by a factor 103700 over the energy range [0.01 < Ep < 6000 eV], covered by only eight overlapping intervals. Canonical quantities are derived, such as the internal energy U(T) and the heat capacity CV(T). This reveals the solid to liquid phase transition, lying in our conditions at the triple point. This phase transition is further studied by computing a Lindemann-Berry index, the atomic cluster density n(r), and the pressure, demonstrating the progressive surface melting at this triple point. Some limited results are also given for 1224 and 4044 atom clusters.

Soudan, J.-M.; Basire, M.; Mestdagh, J.-M.; Angelié, C.

2011-10-01

422

Uncertainty quantification through the Monte Carlo method in a cloud computing setting

NASA Astrophysics Data System (ADS)

The Monte Carlo (MC) method is the most common technique used for uncertainty quantification, due to its simplicity and good statistical results. However, its computational cost is extremely high, and, in many cases, prohibitive. Fortunately, the MC algorithm is easily parallelizable, which allows its use in simulations where the computation of a single realization is very costly. This work presents a methodology for the parallelization of the MC method, in the context of cloud computing. This strategy is based on the MapReduce paradigm, and allows an efficient distribution of tasks in the cloud. This methodology is illustrated on a problem of structural dynamics that is subject to uncertainties. The results show that the technique is capable of producing good results concerning statistical moments of low order. It is shown that even a simple problem may require many realizations for convergence of histograms, which makes the cloud computing strategy very attractive (due to its high scalability capacity and low-cost). Additionally, the results regarding the time of processing and storage space usage allow one to qualify this new methodology as a solution for simulations that require a number of MC realizations beyond the standard.

Cunha, Americo; Nasser, Rafael; Sampaio, Rubens; Lopes, Hélio; Breitman, Karin

2014-05-01

423

Variational Monte Carlo Methods for Strongly Correlated Quantum Systems on Multileg Ladders

NASA Astrophysics Data System (ADS)

Quantum mechanical systems of strongly interacting particles in two dimensions comprise a realm of condensed matter physics for which there remain many unanswered theoretical questions. In particular, the most formidable challenges may lie in cases where the ground states show no signs of ordering, break no symmetries, and support many gapless excitations. Such systems are known to exhibit exotic, disordered ground states that are notoriously difficult to study analytically using traditional perturbation techniques or numerically using the most recent methods (e.g., tensor network states) due to the large amount of spatial entanglement. Slave particle descriptions provide a glimmer of hope in the attempt to capture the fundamental, low-energy physics of these highly non-trivial phases of matter. To this end, this dissertation describes the construction and implementation of trial wave functions for use with variational Monte Carlo techniques that can easily model slave particle states. While these methods are extremely computationally tractable in two dimensions, we have applied them here to quasi-one-dimensional systems so that the results of other numerical techniques, such as the density matrix renormalization group, can be directly compared to those determined by the trial wave functions and so that exclusively one-dimensional analytic approaches, namely bosonization, can be employed. While the focus here is on the use of variational Monte Carlo, the sum of these different numerical and analytical tools has yielded a remarkable amount of insight into several exotic quantum ground states. In particular, the results of research on the d-wave Bose liquid phase, an uncondensed state of strongly correlated hard-core bosons living on the square lattice whose wave function exhibits a d-wave sign structure, and the spin Bose-metal phase, a spin-1/2, SU(2) invariant spin liquid of strongly correlated spins living on the triangular lattice, will be presented. Both phases support gapless excitations along surfaces in momentum space in two spatial dimensions and at incommensurate wave vectors in quasi-one dimension, where we have studied them on three- and four-leg ladders. An extension of this work to the study of d-wave correlated itinerant electrons will be discussed.

Block, Matthew S.

424

Quantifying uncertainties in pollutant mapping studies using the Monte Carlo method

NASA Astrophysics Data System (ADS)

Routine air monitoring provides accurate measurements of annual average concentrations of air pollutants, but the low density of monitoring sites limits its capability in capturing intra-urban variation. Pollutant mapping studies measure air pollutants at a large number of sites during short periods. However, their short duration can cause substantial uncertainty in reproducing annual mean concentrations. In order to quantify this uncertainty for existing sampling strategies and investigate methods to improve future studies, we conducted Monte Carlo experiments with nationwide monitoring data from the EPA Air Quality System. Typical fixed sampling designs have much larger uncertainties than previously assumed, and produce accurate estimates of annual average pollution concentrations approximately 80% of the time. Mobile sampling has difficulties in estimating long-term exposures for individual sites, but performs better for site groups. The accuracy and the precision of a given design decrease when data variation increases, indicating challenges in sites intermittently impact by local sources such as traffic. Correcting measurements with reference sites does not completely remove the uncertainty associated with short duration sampling. Using reference sites with the addition method can better account for temporal variations than the multiplication method. We propose feasible methods for future mapping studies to reduce uncertainties in estimating annual mean concentrations. Future fixed sampling studies should conduct two separate 1-week long sampling periods in all 4 seasons. Mobile sampling studies should estimate annual mean concentrations for exposure groups with five or more sites. Fixed and mobile sampling designs have comparable probabilities in ordering two sites, so they may have similar capabilities in predicting pollutant spatial variations. Simulated sampling designs have large uncertainties in reproducing seasonal and diurnal variations at individual sites, but are capable to predict these variations for exposure groups.

Tan, Yi; Robinson, Allen L.; Presto, Albert A.

2014-12-01

425

Summarizing the output of a Monte Carlo method for uncertainty evaluation

NASA Astrophysics Data System (ADS)

The ‘Guide to the Expression of Uncertainty in Measurement’ (GUM) requires that the way a measurement uncertainty is expressed should be transferable. It should be possible to use directly the uncertainty evaluated for one measurement as a component in evaluating the uncertainty for another measurement that depends on the first. Although the method for uncertainty evaluation described in the GUM meets this requirement of transferability, it is less clear how this requirement is to be achieved when GUM Supplement 1 is applied. That Supplement uses a Monte Carlo method to provide a sample composed of many values drawn randomly from the probability distribution for the measurand. Such a sample does not constitute a convenient way of communicating knowledge about the measurand. In this paper consideration is given to obtaining a more compact summary of such a sample that preserves information about the measurand contained in the sample and can be used in a subsequent uncertainty evaluation. In particular, a coverage interval for the measurand that corresponds to a given coverage probability is often required. If the measurand is characterized by a probability distribution that is not close to being Gaussian, sufficient information has to be conveyed to enable such a coverage interval to be computed reliably. A quantile function in the form of an extended lambda distribution can provide adequate approximations in a number of cases. This distribution is defined by a fixed number of adjustable parameters determined, for example, by matching the moments of the distribution to those calculated in terms of the sample of values. In this paper, alternative flexible models for the quantile function and methods for determining a quantile function from a sample of values are proposed for meeting the above needs.

Harris, P. M.; Matthews, C. E.; Cox, M. G.; Forbes, A. B.

2014-06-01

426

A new method for state of health (SOH) and remaining useful life (RUL) estimations for lithium-ion batteries using Dempster–Shafer theory (DST) and the Bayesian Monte Carlo (BMC) method is proposed. In this work, an empirical model based on the physical degradation behavior of lithium-ion batteries is developed. Model parameters are initialized by combining sets of training data based on DST.

Wei He; Nicholas Williard; Michael Osterman; Michael Pecht

2011-01-01

427

Feasibility of a Monte Carlo-deterministic hybrid method for fast reactor analysis

A Monte Carlo and deterministic hybrid method is investigated for the analysis of fast reactors in this paper. Effective multi-group cross sections data are generated using a collision estimator in the MCNP5. A high order Legendre scattering cross section data generation module was added into the MCNP5 code. Both cross section data generated from MCNP5 and TRANSX/TWODANT using the homogeneous core model were compared, and were applied to DIF3D code for fast reactor core analysis of a 300 MWe SFR TRU burner core. For this analysis, 9 groups macroscopic-wise data was used. In this paper, a hybrid calculation MCNP5/DIF3D was used to analyze the core model. The cross section data was generated using MCNP5. The k{sub eff} and core power distribution were calculated using the 54 triangle FDM code DIF3D. A whole core calculation of the heterogeneous core model using the MCNP5 was selected as a reference. In terms of the k{sub eff}, 9-group MCNP5/DIF3D has a discrepancy of -154 pcm from the reference solution, 9-group TRANSX/TWODANT/DIF3D analysis gives -1070 pcm discrepancy. (authors)

Heo, W.; Kim, W.; Kim, Y. [Korea Advanced Institute of Science and Technology - KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701 (Korea, Republic of); Yun, S. [Korea Atomic Energy Research Institute - KAERI, 989-111 Daedeok-daero, Yuseong-gu, Daejeon, 305-353 (Korea, Republic of)

2013-07-01

428

Simulation of aggregating particles in complex flows by the lattice kinetic Monte Carlo method

NASA Astrophysics Data System (ADS)

We develop and validate an efficient lattice kinetic Monte Carlo (LKMC) method for simulating particle aggregation in laminar flows with spatially varying shear rate, such as parabolic flow or flows with standing vortices. A contact time model was developed to describe the particle-particle collision efficiency as a function of the local shear rate, G, and approach angle, ?. This model effectively accounts for the hydrodynamic interactions between approaching particles, which is not explicitly considered in the LKMC framework. For imperfect collisions, the derived collision efficiency [\\varepsilon = 1 - int_0^{{? {? /2} {sin ? exp ( { - 2\\cot ? {{? _{agg} }/ { ? _{agg} } G} )} d?] was found to depend only on ?agg/G, where ?agg is the specified aggregation rate. For aggregating platelets in tube flow, ? _{agg} = 0.683 s-1 predicts the experimentally measured ? across a physiological range (G = 40-1000 s-1) and is consistent with ?2b?3-fibrinogen bond dynamics. Aggregation in parabolic flow resulted in the largest aggregates forming near the wall where shear rate and residence time were maximal, however intermediate regions between the wall and the center exhibited the highest aggregation rate due to depletion of reactants nearest the wall. Then, motivated by stenotic or valvular flows, we employed the LKMC simulation developed here for baffled geometries that exhibit regions of squeezing flow and standing recirculation zones. In these calculations, the largest aggregates were formed within the vortices (maximal residence time), while squeezing flow regions corresponded to zones of highest aggregation rate.

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

2011-01-01

429

Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics

Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation.

Hall, Howard L [ORNL

2012-01-01

430

Monte carlo method-based QSAR modeling of penicillins binding to human serum proteins.

The binding of penicillins to human serum proteins was modeled with optimal descriptors based on the Simplified Molecular Input-Line Entry System (SMILES). The concentrations of protein-bound drug for 87 penicillins expressed as percentage of the total plasma concentration were used as experimental data. The Monte Carlo method was used as a computational tool to build up the quantitative structure-activity relationship (QSAR) model for penicillins binding to plasma proteins. One random data split into training, test and validation set was examined. The calculated QSAR model had the following statistical parameters: r(2) ?=?0.8760, q(2) ?=?0.8665, s?=?8.94 for the training set and r(2) ?=?0.9812, q(2) ?=?0.9753, s?=?7.31 for the test set. For the validation set, the statistical parameters were r(2) ?=?0.727 and s?=?12.52, but after removing the three worst outliers, the statistical parameters improved to r(2) ?=?0.921 and s?=?7.18. SMILES-based molecular fragments (structural indicators) responsible for the increase and decrease of penicillins binding to plasma proteins were identified. The possibility of using these results for the computer-aided design of new penicillins with desired binding properties is presented. PMID:25408278

Veselinovi?, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikoli?, Goran M; Veselinovi?, Aleksandar M

2015-01-01

431

Monte Carlo studies of 3d N=6 SCFT via localization method

We perform Monte Carlo study of the 3d N=6 superconformal U(N)*U(N) Chern-Simons gauge theory (ABJM theory), which is conjectured to be dual to M-theory or type IIA superstring theory on certain AdS backgrounds. Our approach is based on a localization method, which reduces the problem to the simulation of a simple matrix model. This enables us to circumvent the difficulties in the original theory such as the sign problem and the SUSY breaking on a lattice. The new approach opens up the possibility of probing the quantum aspects of M-theory and testing the AdS_4/CFT_3 duality at the quantum level. Here we calculate the free energy, and confirm the N^{3/2} scaling in the M-theory limit predicted from the gravity side. We also find that our results nicely interpolate the analytical formulae proposed previously in the M-theory and type IIA regimes.

Masazumi Honda; Masanori Hanada; Yoshinori Honma; Jun Nishimura; Shotaro Shiba; Yutaka Yoshida

2012-11-29

432

NASA Astrophysics Data System (ADS)

Using the homogeneous electron gas (HEG) as a model, we investigate the sources of error in the "initiator" adaptation to full configuration interaction quantum Monte Carlo (i-FCIQMC), with a view to accelerating convergence. In particular, we find that the fixed-shift phase, where the walker number is allowed to grow slowly, can be used to effectively assess stochastic and initiator error. Using this approach we provide simple explanations for the internal parameters of an i-FCIQMC simulation. We exploit the consistent basis sets and adjustable correlation strength of the HEG to analyze properties of the algorithm, and present finite basis benchmark energies for N = 14 over a range of densities 0.5 ? rs ? 5.0 a.u. A single-point extrapolation scheme is introduced to produce complete basis energies for 14, 38, and 54 electrons. It is empirically found that, in the weakly correlated regime, the computational cost scales linearly with the plane wave basis set size, which is justifiable on physical grounds. We expect the fixed-shift strategy to reduce the computational cost of many i-FCIQMC calculations of weakly correlated systems. In addition, we provide benchmarks for the electron gas, to be used by other quantum chemical methods in exploring periodic solid state systems.

Shepherd, James J.; Booth, George H.; Alavi, Ali

2012-06-01

433

QSAR models for HEPT derivates as NNRTI inhibitors based on Monte Carlo method.

A series of 107 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio) thymine (HEPT) with anti-HIV-1 activity as a non-nucleoside reverse transcriptase inhibitor (NNRTI) has been studied. Monte Carlo method has been used as a tool to build up the quantitative structure-activity relationships (QSAR) for anti-HIV-1 activity. The QSAR models were calculated with the representation of the molecular structure by simplified molecular input-line entry system and by the molecular graph. Three various splits into training and test set were examined. Statistical quality of all build models is very good. Best calculated model had following statistical parameters: for training set r(2) = 0.8818, q(2) = 0.8774 and r(2) = 0.9360, q(2) = 0.9243 for test set. Structural indicators (alerts) for increase and decrease of the IC50 are defined. Using defined structural alerts computer aided design of new potential anti-HIV-1 HEPT derivates is presented. PMID:24657566

Toropova, Alla P; Toropov, Andrey A; Veselinovi?, Jovana B; Miljkovi?, Filip N; Veselinovi?, Aleksandar M

2014-04-22

434

NASA Astrophysics Data System (ADS)

Monte Carlo simulation methods were used to investigate the absorbed dose distribution around several preliminary source configurations and the 3M Company models 6701, 6702, and 6711 I-125 seeds in water. Simulations for the preliminary sources, all of which were structurally simpler than the seeds, were conducted to demonstrate correct behavior of the computer software. The relative dose distributions of the three seed models were found to be anisotropic, and distinct. Observed differences in the relative dose distributions of the three models are attributable to differences in seed design and photon emission spectrum. Variations in end weld thicknesses and radioactivity distributions within the seeds were found to have substantial influence on the relative dose distributions. Dosimetry estimates along the longitudinal axis of the seeds are particularly uncertain due to such variations. Finally, perturbations of the single seed dose distribution created by neighboring seeds within the implant were determined. Such perturbations are strongly dependent on the seed model used and on the separation between seeds. Simple superposition of single seed dose distributions in multiple seed implants causes overestimation of dose within seed planes. Errors may be quite large for single plane implants with small seed separations. The results of this study provide a means to reduce errors in iodine seed implant dosimetry through the use of seed design-specific two-dimensional dosimetry data, and through improved understanding of the causes of uncertainties in iodine seed relative dose distributions.

Burns, Gregory Scott

435

Applications of Monte Carlo methods for the analysis of MHTGR case of the PROTEUS benchmark

Monte Carlo methods, as implemented in the MCNP code, have been used to analyze the neutronics characteristics of benchmarks related to Modular High Temperature Gas-Cooled Reactors. The benchmarks are idealized versions of the Japanes (VHTRC) and Swiss (PROTEUS) facilities and an actual configurations of the PROTEUS Configuration I experiment. The purpose of the unit cell benchmarks is to compare multiplication constants, critical bucklings, migration lengths, reaction rates and spectral indices. The purpose of the full reactors benchmarks is to compare multiplication constants, reaction rates, spectral indices, neutron balances, reaction rates profiles, temperature coefficients of reactivity and effective delayed neutron fractions. All of these parameters can be calculated by MCNP, which can provide a very detailed model of the geometry of the configurations, from fuel particles to entire fuel assemblies, using at the same time a continuous energy model. These characteristics make MCNP a very useful tool to analyze these MHTGR benchmarks. We have used the MCNP latest version, 4.x, eld = 01/12/93 with an ENDF/B-V cross section library. This library does not yet contain temperature dependent resonance materials, so all calculations correspond to room temperature, T = 300{degree}K. Two separate reports were made -- one for the VHTRC, the other for the PROTEUS benchmark.

Difilippo, F.C.

1994-04-01

436

Applications of Monte Carlo methods for the analysis of MHTGR case of the VHTRC benchmark

Monte Carlo methods, as implemented in the MCNP code, have been used to analyze the neutronics characteristics of benchmarks related to Modular High Temperature Gas-Cooled Reactors. The benchmarks are idealized versions of the Japanese (VHTRC) and Swiss (PROTEUS) facilities and an actual configuration of the PROTEUS Configuration 1 experiment. The purpose of the unit cell benchmarks is to compare multiplication constants, critical bucklings, migration lengths, reaction rates and spectral indices. The purpose of the full reactors benchmarks is to compare multiplication constants, reaction rates, spectral indices, neutron balances, reaction rates profiles, temperature coefficients of reactivity and effective delayed neutron fractions. All of these parameters can be calculated by MCNP, which can provide a very detailed model of the geometry of the configurations, from fuel particles to entire fuel assemblies, using at the same time a continuous energy model. These characteristics make MCNP a very useful tool to analyze these MHTGR benchmarks. The author has used the MCNP latest version, 4.x, eld = 01/12/93 with an ENDF/B-V cross section library. This library does not yet contain temperature dependent resonance materials, so all calculations correspond to room temperature, T = 300{degrees}K. Two separate reports were made -- one for the VHTRC, the other for the PROTEUS benchmark.

Difilippo, F.C.

1994-03-01

437

Markov chain Monte Carlo methods for assigning larvae to natal sites using natural geochemical tags.

Geochemical signatures deposited in otoliths are a potentially powerful means of identifying the origin and dispersal history of fish. However, current analytical methods for assigning natal origins of fish in mixed-stock analyses require knowledge of the number of potential sources and their characteristic geochemical signatures. Such baseline data are difficult or impossible to obtain for many species. A new approach to this problem can be found in iterative Markov Chain Monte Carlo (MCMC) algorithms that simultaneously estimate population parameters and assign individuals to groups. MCMC procedures only require an estimate of the number of source populations, and post hoc model selection based on the deviance information criterion can be used to infer the correct number of chemically distinct sources. We describe the basics of the MCMC approach and outline the specific decisions required when implementing the technique with otolith geochemical data. We also illustrate the use of the MCMC approach on simulated data and empirical geochemical signatures in otoliths from young-of-the-year and adult weakfish, Cynoscion regalis, from the U.S. Atlantic coast. While we describe how investigators can use MCMC to complement existing analytical tools for use with otolith geochemical data, the MCMC approach is suitable for any mixed-stock problem with a continuous, multivariate data. PMID:19263887

White, J Wilson; Standish, Julie D; Thorrold, Simon R; Warner, Robert R

2008-12-01

438

Monte Carlo evaluation of accuracy and noise properties of two scatter correction methods

Two independent scatter correction techniques, transmission dependent convolution subtraction (TDCS) and triple-energy window (TEW) method, were evaluated in terms of quantitative accuracy and noise properties using Monte Carlo simulation (EGS4). Emission projections (primary, scatter and scatter plus primary) were simulated for {sup 99m}Tc and {sup 201}Tl for numerical chest phantoms. Data were reconstructed with ordered-subset ML-EM algorithm including attenuation correction using the transmission data. In the chest phantom simulation, TDCS provided better S/N than TEW, and better accuracy, i.e., 1.0% vs -7.2% in myocardium, and -3.7% vs -30.1% in the ventricular chamber for {sup 99m}Tc with TDCS and TEW, respectively. For {sup 201}Tl, TDCS provided good visual and quantitative agreement with simulated true primary image without noticeably increasing the noise after scatter correction. Overall TDCS proved to be more accurate and less noisy than TEW, facilitating quantitative assessment of physiological functions with SPECT.

Narita, Y. [Research Institute for Brain and Blood Vessels, Akita City (Japan); [Tohoku Univ., Sendai (Japan); Eberl, S. [Royal Prince Alfred Hospital, Sydney (Australia); Nakamura, T. [Tohoku Univ., Sendai (Japan)] [and others

1996-12-31

439

IR imaging simulation and analysis for aeroengine exhaust system based on reverse Monte Carlo method

NASA Astrophysics Data System (ADS)

The IR radiation characteristics of aeroengine are the important basis for IR stealth design and anti-stealth detection of aircraft. With the development of IR imaging sensor technology, the importance of aircraft IR stealth increases. An effort is presented to explore target IR radiation imaging simulation based on Reverse Monte Carlo Method (RMCM), which combined with the commercial CFD software. Flow and IR radiation characteristics of an aeroengine exhaust system are investigated, which developing a full size geometry model based on the actual parameters, using a flow-IR integration structured mesh, obtaining the engine performance parameters as the inlet boundary conditions of mixer section, and constructing a numerical simulation model of engine exhaust system of IR radiation characteristics based on RMCM. With the above models, IR radiation characteristics of aeroengine exhaust system is given, and focuses on the typical detecting band of IR spectral radiance imaging at azimuth 20°. The result shows that: (1) in small azimuth angle, the IR radiation is mainly from the center cone of all hot parts; near the azimuth 15°, mixer has the biggest radiation contribution, while center cone, turbine and flame stabilizer equivalent; (2) the main radiation components and space distribution in different spectrum is different, CO2 at 4.18, 4.33 and 4.45 micron absorption and emission obviously, H2O at 3.0 and 5.0 micron absorption and emission obviously.

Chen, Shiguo; Chen, Lihai; Mo, Dongla; Shi, Jingcheng

2014-11-01

440

Absorbed Dose Calculations Using Mesh-based Human Phantoms And Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Health risks attributable to the exposure to ionizing radiation are considered to be a function of the absorbed or equivalent dose to radiosensitive organs and tissues. However, as human tissue cannot express itself in terms of equivalent dose, exposure models have to be used to determine the distribution of equivalent dose throughout the human body. An exposure model, be it physical or computational, consists of a representation of the human body, called phantom, plus a method for transporting ionizing radiation through the phantom and measuring or calculating the equivalent dose to organ and tissues of interest. The FASH2 (Female Adult meSH) and the MASH2 (Male Adult meSH) computational phantoms have been developed at the University of Pernambuco in Recife/Brazil based on polygon mesh surfaces using open source software tools and anatomical atlases. Representing standing adults, FASH2 and MASH2 have organ and tissue masses, body height and body mass adjusted to the anatomical data published by the International Commission on Radiological Protection for the reference male and female adult. For the purposes of absorbed dose calculations the phantoms have been coupled to the EGSnrc Monte Carlo code, which can transport photons, electrons and positrons through arbitrary media. This paper reviews the development of the FASH2 and the MASH2 phantoms and presents dosimetric applications for X-ray diagnosis and for prostate brachytherapy.

Kramer, Richard

2011-08-01

441

Calculation of complete fusion cross sections of heavy ion reactions using the Monte Carlo method

The nucleus-nucleus potential for the fusion reactions {sup 40}Ca+{sup 48}Ca, {sup 16}O+{sup 208}Pb, and {sup 48}Ca+{sup 48}Ca has been calculated using the Monte Carlo method. The results obtained indicate that the technique employed for the calculation of the nucleus-nucleus potential is an efficient one. The effects of the spin and the isospin terms have also been studied using the same technique. The analysis of the results obtained for the {sup 48}Ca+{sup 48}Ca reaction reveal that the isospin-dependent term in the nucleon-nucleon potential causes the nuclear potential to drop by an amount of 0.5 MeV. The analytical calculations of the fusion cross section, particularly those at energies less than the fusion barrier, are in good agreement with the experimental data. In these calculations the effective nucleon-nucleon potential chosen is of the M3Y-Paris potential form and no adjustable parameter has been used.

Ghodsi, O. N.; Mahmoodi, M.; Ariai, J. [Sciences Faculty, Department of Physics, University of Mazandaran, Post Office Box 47415-416, Babolsar (Iran, Islamic Republic of); Physics Group, University of Payam Noor, Mashad 433 (Iran, Islamic Republic of)

2007-03-15

442

HRMC_1.1: Hybrid Reverse Monte Carlo method with silicon and carbon potentials

NASA Astrophysics Data System (ADS)

The Hybrid Reverse Monte Carlo (HRMC) code models the atomic structure of materials via the use of a combination of constraints including experimental diffraction data and an empirical energy potential. This energy constraint is in the form of either the Environment Dependent Interatomic Potential (EDIP) for carbon and silicon and the original and modified Stillinger-Weber potentials applicable to silicon. In this version, an update is made to correct an error in the EDIP carbon energy calculation routine. New version program summaryProgram title: HRMC version 1.1 Catalogue identifier: AEAO_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAO_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 36 991 No. of bytes in distributed program, including test data, etc.: 907 800 Distribution format: tar.gz Programming language: FORTRAN 77 Computer: Any computer capable of running executables produced by the g77 Fortran compiler. Operating system: Unix, Windows RAM: Depends on the type of empirical potential use, number of atoms and which constraints are employed. Classification: 7.7 Catalogue identifier of previous version: AEAO_v1_0 Journal reference of previous version: Comput. Phys. Comm. 178 (2008) 777 Does the new version supersede the previous version?: Yes Nature of problem: Atomic modelling using empirical potentials and experimental data. Solution method: Monte Carlo Reasons for new version: An error in a term associated with the calculation of energies using the EDIP carbon potential which results in incorrect energies. Summary of revisions: Fix to correct brackets in the two body part of the EDIP carbon potential routine. Additional comments: The code is not standard FORTRAN 77 but includes some additional features and therefore generates errors when compiled using the Nag95 compiler. It does compile successfully with the GNU g77 compiler ( http://www.gnu.org/software/fortran/fortran.html). Running time: Depends on the type of empirical potential use, number of atoms and which constraints are employed. The test included in the distribution took 37 minutes on a DEC Alpha PC.

Opletal, G.; Petersen, T. C.; O'Malley, B.; Snook, I. K.; McCulloch, D. G.; Yarovsky, I.

2011-02-01

443

Parallel Markov Chain Monte Carlo Methods for Large Scale Statistical Inverse Problems

but also the uncertainty of these estimations. Markov chain Monte Carlo (MCMC) is a useful technique to sample the posterior distribution and information can be extracted from the sampled ensemble. However, MCMC is very expensive to compute, especially...

Wang, Kainan

2014-04-18

444

Several problems are studied with both the discrete transfer and Monte Carlo methods for predicting radiative heat transfer in three-dimensional, nonhomogeneous, participating media. Previous studies have verified the discrete transfer method only in two-dimensional, isotropically scattering media. This paper therefore demonstrates its applicability to scattering problems in three-dimensional geometries, with comparisons against solutions by a pathlength-based Monte Carlo method. In this respect, formulations for both methods are presented with suitable modifications and extensions to their traditional approach. Both algorithms are found to provide numerical solutions in good agreement with published benchmark results which used the YIX, Monte Carlo and finite element methods to determine the radiative transport in a unit cube. New solutions in an arbitrary L-shaped geometry with a body-fitted mesh are presented. The average deviation between the two methods is less than 1.2% for both the boundary surface flux and the divergence of radiative flux or gas emissive power within the enclosed media.

Henson, J.C.; Malalasekera, W.M.G.; Dent, J.C. [Loughborough Univ. (United Kingdom). Dept. of Mechanical Engineering

1996-11-01

445

The equations of nonlinear, time-dependent radiative transfer are known to yield the equilibrium diffusion equation as the leading-order solution of an asymptotic analysis when the mean-free path and mean-free time of a photon become small. We apply this same analysis to the Fleck-Cummings, Carter-Forest, and N'kaoua Monte Carlo approximations for grey (frequency-independent) radiative transfer. Although Monte Carlo simulation usually does

Jeffery D. Densmore; Edward W. Larsen

2004-01-01

446

The equations of nonlinear, time-dependent radiative transfer are known to yield the equilibrium diffusion equation as the leading-order solution of an asymptotic analysis when the mean-free path and mean-free time of a photon become small. We apply this same analysis to the Fleck–Cummings, Carter–Forest, and N'kaoua Monte Carlo approximations for grey (frequency-independent) radiative transfer. Although Monte Carlo simulation usually does

Jeffery D. Densmore; Edward W. Larsen

2004-01-01

447

Quasielastic response with a real-time path-integral Monte Carlo method

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

C. Carraro; S. E. Koonin

1990-01-01

448

The choice of appropriate interaction models is among the major disadvantages of conventional methods such as molecular dynamics and Monte Carlo simulations. On the other hand, the so-called reverse Monte Carlo (RMC) method, based on experimental data, can be applied without any interatomic and/or intermolecular interactions. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term into the acceptance criteria. This method is referred to as the hybrid reverse Monte Carlo (HRMC) method. The idea of this paper is to test the validity of a combined potential model of coulomb and Lennard-Jones in a fluoride glass system BaMnMF_{7} (M=Fe,V) using HRMC method. The results show a good agreement between experimental and calculated characteristics, as well as a meaningful improvement in partial pair distribution functions. We suggest that this model should be used in calculating the structural properties and in describing the average correlations between components of fluoride glass or a similar system. We also suggest that HRMC could be useful as a tool for testing the interaction potential models, as well as for conventional applications.

S. M. Mesli; M. Habchi; M. Kotbi; H. Xu

2013-03-25

449

The Unified Monte Carlo method (UMC) has been suggested to avoid certain limitations and approximations inherent to the well-known Generalized Least Squares (GLS) method of nuclear data evaluation. This contribution reports on an investigation of the performance of the UMC method in comparison with the GLS method. This is accomplished by applying both methods to simple examples with few input values that were selected to explore various features of the evaluation process that impact upon the quality of an evaluation. Among the issues explored are: i) convergence of UMC results with the number of Monte Carlo histories and the ranges of sampled values; ii) a comparison of Monte Carlo sampling using the Metropolis scheme and a brute force approach; iii) the effects of large data discrepancies; iv) the effects of large data uncertainties; v) the effects of strong or weak model or experimental data correlations; and vi) the impact of ratio data and integral data. Comparisons are also made of the evaluated results for these examples when the input values are first transformed to comparable logarithmic values prior to performing the evaluation. Some general conclusions that are applicable to more realistic evaluation exercises are offered.

Capote, Roberto [Nuclear Data Section, International Atomic Energy Agency, P.O. Box 100, Wagramer Strasse 5, A-1400 Vienna (Austria)], E-mail: Roberto.CapoteNoy@iaea.org; Smith, Donald L. [Argonne National Laboratory, 1710 Avenida del Mundo, Coronado, California 92118-3073 (United States)

2008-12-15

450

Forward treatment planning for modulated electron radiotherapy (MERT) employing Monte Carlo methods

Purpose: This paper describes the development of a forward planning process for modulated electron radiotherapy (MERT). The approach is based on a previously developed electron beam model used to calculate dose distributions of electron beams shaped by a photon multi leaf collimator (pMLC). Methods: As the electron beam model has already been implemented into the Swiss Monte Carlo Plan environment, the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) can be included in the planning process for MERT. In a first step, CT data are imported into Eclipse and a pMLC shaped electron beam is set up. This initial electron beam is then divided into segments, with the electron energy in each segment chosen according to the distal depth of the planning target volume (PTV) in beam direction. In order to improve the homogeneity of the dose distribution in the PTV, a feathering process (Gaussian edge feathering) is launched, which results in a number of feathered segments. For each of these segments a dose calculation is performed employing the in-house developed electron beam model along with the macro Monte Carlo dose calculation algorithm. Finally, an automated weight optimization of all segments is carried out and the total dose distribution is read back into Eclipse for display and evaluation. One academic and two clinical situations are investigated for possible benefits of MERT treatment compared to standard treatments performed in our clinics and treatment with a bolus electron conformal (BolusECT) method. Results: The MERT treatment plan of the academic case was superior to the standard single segment electron treatment plan in terms of organs at risk (OAR) sparing. Further, a comparison between an unfeathered and a feathered MERT plan showed better PTV coverage and homogeneity for the feathered plan, with V{sub 95%} increased from 90% to 96% and V{sub 107%} decreased from 8% to nearly 0%. For a clinical breast boost irradiation, the MERT plan led to a similar homogeneity in the PTV compared to the standard treatment plan while the mean body dose was lower for the MERT plan. Regarding the second clinical case, a whole breast treatment, MERT resulted in a reduction of the lung volume receiving more than 45% of the prescribed dose when compared to the standard plan. On the other hand, the MERT plan leads to a larger low-dose lung volume and a degraded dose homogeneity in the PTV. For the clinical cases evaluated in this work, treatment plans using the BolusECT technique resulted in a more homogenous PTV and CTV coverage but higher doses to the OARs than the MERT plans. Conclusions: MERT treatments were successfully planned for phantom and clinical cases, applying a newly developed intuitive and efficient forward planning strategy that employs a MC based electron beam model for pMLC shaped electron beams. It is shown that MERT can lead to a dose reduction in OARs compared to other methods. The process of feathering MERT segments results in an improvement of the dose homogeneity in the PTV.

Henzen, D., E-mail: henzen@ams.unibe.ch; Manser, P.; Frei, D.; Volken, W.; Born, E. J.; Lössl, K.; Aebersold, D. M.; Fix, M. K. [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010 Berne (Switzerland)] [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010 Berne (Switzerland); Neuenschwander, H. [Clinic for Radiation-Oncology, Lindenhofspital Bern, CH-3012 Berne (Switzerland)] [Clinic for Radiation-Oncology, Lindenhofspital Bern, CH-3012 Berne (Switzerland); Stampanoni, M. F. M. [Institute for Biomedical Engineering, ETH Zürich and Paul Scherrer Institut, CH-5234 Villigen (Switzerland)] [Institute for Biomedical Engineering, ETH Zürich and Paul Scherrer Institut, CH-5234 Villigen (Switzerland)

2014-03-15

451

Modeling radiation from the atmosphere of Io with Monte Carlo methods

NASA Astrophysics Data System (ADS)

Conflicting observations regarding the dominance of either sublimation or volcanism as the source of the atmosphere on Io and disparate reports on the extent of its spatial distribution and the absolute column abundance invite the development of detailed computational models capable of improving our understanding of Io's unique atmospheric structure and origin. To validate a global numerical model of Io's atmosphere against astronomical observations requires a 3-D spherical-shell radiative transfer (RT) code to simulate disk-resolved images and disk-integrated spectra from the ultraviolet to the infrared spectral region. In addition, comparison of simulated and astronomical observations provides important information to improve existing atmospheric models. In order to achieve this goal, a new 3-D spherical-shell forward/backward photon Monte Carlo code capable of simulating radiation from absorbing/emitting and scattering atmospheres with an underlying emitting and reflecting surface was developed. A new implementation of calculating atmospheric brightness in scattered sunlight is presented utilizing the notion of an "effective emission source" function. This allows for the accumulation of the scattered contribution along the entire path of a ray and the calculation of the atmospheric radiation when both scattered sunlight and thermal emission contribute to the observed radiation---which was not possible in previous models. A "polychromatic" algorithm was developed for application with the backward Monte Carlo method and was implemented in the code. It allows one to calculate radiative intensity at several wavelengths simultaneously, even when the scattering properties of the atmosphere are a function of wavelength. The application of the "polychromatic" method improves the computational efficiency because it reduces the number of photon bundles traced during the simulation. A 3-D gas dynamics model of Io's atmosphere, including both sublimation and volcanic sources of SO2 gas, is analyzed by simulating spectra and images from the model corresponding to three important observations: (1) simulations of the mid-IR disk-averaged observations of Io's sunlit hemisphere at 19 mum, obtained with TEXES during 2001-2004; (2) simulations of disk-resolved images at Lyman-a (1216 A or 0.1216 mum) obtained with the Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph (STIS) during 1997-2001; and (3) disk-integrated simulations of emission line profiles in the millimeter wavelength range (1.2-1.4 mm) obtained with the IRAM-30 m telescope in Oct.-Nov. 1999. We found that our atmospheric model generally reproduces the longitudinal variation in the strength of absorption band from the mid-IR data; however, the best match is obtained when the simulation results are shifted ˜ 30° toward lower longitudes. The simulations of Lyman-alpha images do not show the mid-to-high latitude bright patches seen in the observations, suggesting that the model atmosphere predicts column number densities that are too high at those latitudes. The simulations of emission line profiles in the millimeter spectral region support the hypothesis that the atmospheric dynamics favorably explain the observed line widths, which are too wide to be formed by Doppler broadening alone. The computational modeling and simulation tools needed to study light scattering from volcanic plumes, which play a significant role in structuring the atmosphere on Io, is developed. The radiative transfer code is applied to the simulation of the brightness in scattered sunlight from a Prometheus-type plume on Io, as observed in limb-viewing geometry by the Galileo Solid State Imager (SSI). The computations are performed utilizing the "polychromatic" method, thus calculating the plume brightness for the entire filter bandpass in a single simulation. Such simulations account for multiple scattering and reflection of sunlight from the surface, not included in previous studies, and may serve as a powerful tool for simulating the plume obs

Gratiy, Sergey

452

NASA Astrophysics Data System (ADS)

The impingement of gas plumes from small thrusters on spacecraft surfaces is modeled using the direct simulation Monte Carlo (DSMC) technique. Strategies for improving the efficiency and resolution of DSMC simulations are presented. These methods include variable scaling of simulation parameters and computational grid design. Computational cost of a simulation can be reduced by as much as two orders of magnitude using these methods. A parallel, three-dimensional implementation of the DSMC method is described. A flexible, cell-based grid methodology is employed which allows the use of structured, unstructured or hybrid grids. This provides the ability to handle complex geometric configurations. An efficient particle tracing scheme is used for particle movement which eliminates the need for an explicit sorting step. Strong numerical performance and high parallel efficiencies are obtained. Several impingement problems are investigated in order to test the accuracy and performance of the DSMC method and implementation for plume flows. The first problem is a nitrogen plume from a resistojet nozzle impinging on an axisymmetric body. The plume flow is started with exit plane data from a simulation of the diverging section of the nozzle. Good agreement is found with experimental data for surface pressure over a range of body locations. A free jet of nitrogen impacting on an inclined flat plate is examined as a three-dimensional test case. The three-dimensional code is validated through comparison with an axisymmetric simulation of the case where the plume axis is normal to the plate. Good agreement is found with experimental measurements of surface pressure, shear stress and heat transfer for several plate orientations. Free molecular analysis is found to over predict surface properties while providing good qualitative agreement. The plume of a hydrazine thruster mounted on a model satellite configuration is investigated to demonstrate the ability to compute complex configurations. Surface properties and integrated impingement effects are calculated on a solar array panel. The plume is shown to transfer a significant fraction of the thruster's momentum and energy to the array. Free molecular analysis is less accurate as a result of multi species and boundary layer effects.

Kannenberg, Keith Christopher

453

Monto Carlo extension of quasi-Monte Carlo

This paper surveys recent research on using Monte Carlo techniques to improve quasi-Monte Carlo techniques. Randomized quasi-Monte Carlo methods provide a basis for error estimation. They have, in the special case of scrambled nets, also been observed to improve accuracy. Finally through Latin supercube sampling it is possible to use Monte Carlo methods to extend quasi-Monte Carlo methods to higher

Art B. Owen

1998-01-01

454

In this paper, the work that has been done to implement variance reduction techniques in a three dimensional, multi group Monte Carlo code - Tortilla, that works within the frame work of the commercial deterministic code - Attila, is presented. This project is aimed to develop an integrated Hybrid code that seamlessly takes advantage of the deterministic and Monte Carlo methods for deep shielding radiation detection problems. Tortilla takes advantage of Attila's features for generating the geometric mesh, cross section library and source definitions. Tortilla can also read importance functions (like adjoint scalar flux) generated from deterministic calculations performed in Attila and use them to employ variance reduction schemes in the Monte Carlo simulation. The variance reduction techniques that are implemented in Tortilla are based on the CADIS (Consistent Adjoint Driven Importance Sampling) method and the LIFT (Local Importance Function Transform) method. These methods make use of the results from an adjoint deterministic calculation to bias the particle transport using techniques like source biasing, survival biasing, transport biasing and weight windows. The results obtained so far and the challenges faced in implementing the variance reduction techniques are reported here. (authors)

Somasundaram, E.; Palmer, T. S. [Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, 116 Radiation Center, Corvallis, OR 97332-5902 (United States)

2013-07-01

455

Modeling and simulation of radiation from hypersonic flows with Monte Carlo methods

NASA Astrophysics Data System (ADS)

During extreme-Mach number reentry into Earth's atmosphere, spacecraft experience hypersonic non-equilibrium flow conditions that dissociate molecules and ionize atoms. Such situations occur behind a shock wave leading to high temperatures, which have an adverse effect on the thermal protection system and radar communications. Since the electronic energy levels of gaseous species are strongly excited for high Mach number conditions, the radiative contribution to the total heat load can be significant. In addition, radiative heat source within the shock layer may affect the internal energy distribution of dissociated and weakly ionized gas species and the number density of ablative species released from the surface of vehicles. Due to the radiation total heat load to the heat shield surface of the vehicle may be altered beyond mission tolerances. Therefore, in the design process of spacecrafts the effect of radiation must be considered and radiation analyses coupled with flow solvers have to be implemented to improve the reliability during the vehicle design stage. To perform the first stage for radiation analyses coupled with gas-dynamics, efficient databasing schemes for emission and absorption coefficients were developed to model radiation from hypersonic, non-equilibrium flows. For bound-bound transitions, spectral information including the line-center wavelength and assembled parameters for efficient calculations of emission and absorption coefficients are stored for typical air plasma species. Since the flow is non-equilibrium, a rate equation approach including both collisional and radiatively induced transitions was used to calculate the electronic state populations, assuming quasi-steady-state (QSS). The Voigt line shape function was assumed for modeling the line broadening effect. The accuracy and efficiency of the databasing scheme was examined by comparing results of the databasing scheme with those of NEQAIR for the Stardust flowfield. An accuracy of approximately 1 % was achieved with an efficiency about three times faster than the NEQAIR code. To perform accurate and efficient analyses of chemically reacting flowfield - radiation interactions, the direct simulation Monte Carlo (DSMC) and the photon Monte Carlo (PMC) radiative transport methods are used to simulate flowfield - radiation coupling from transitional to peak heating freestream conditions. The non-catalytic and fully catalytic surface conditions were modeled and good agreement of the stagnation-point convective heating between DSMC and continuum fluid dynamics (CFD) calculation under the assumption of fully catalytic surface was achieved. Stagnation-point radiative heating, however, was found to be very different. To simulate three-dimensional radiative transport, the finite-volume based PMC (FV-PMC) method was employed. DSMC - FV-PMC simulations with the goal of understanding the effect of radiation on the flow structure for different degrees of hypersonic non-equilibrium are presented. It is found that except for the highest altitudes, the coupling of radiation influences the flowfield, leading to a decrease in both heavy particle translational and internal temperatures and a decrease in the convective heat flux to the vehicle body. The DSMC - FV-PMC coupled simulations are compared with the previous coupled simulations and correlations obtained using continuum flow modeling and one-dimensional radiative transport. The modeling of radiative transport is further complicated by radiative transitions occurring during the excitation process of the same radiating gas species. This interaction affects the distribution of electronic state populations and, in turn, the radiative transport. The radiative transition rate in the excitation/de-excitation processes and the radiative transport equation (RTE) must be coupled simultaneously to account for non-local effects. The QSS model is presented to predict the electronic state populations of radiating gas species taking into account non-local radiation. The definition of the escape factor which is depende

Sohn, Ilyoup

456

NASA Astrophysics Data System (ADS)

We study a simulation of spectral reflectance in human skin tissue using ray-tracing software and the Monte Carlo method on the basis of a graphics processing unit (GPU). An analysis of light propagation using ray-tracing software has several advantages in that it can readily reproduce the complex structure of skin tissue, such as grooves of the skin surface or the boundaries of skin tissue layers, and perform optical simulation with optical elements close to those in a real experiment using only the ray-tracing software. Meanwhile, it has a serious disadvantage in that the simulation time is extremely long because the algorithm is CPU-based. To overcome this disadvantage, we propose a simulation method using the ray-tracing software and a GPU-based Monte Carlo simulation (MCS). The results of the simulation are shown and discussed.

Funamizu, Hideki; Maeda, Takaaki; Sasaki, Shoko; Nishidate, Izumi; Aizu, Yoshihisa

2014-05-01

457

Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method

NASA Astrophysics Data System (ADS)

The thermodynamics of iron clusters of various sizes, from 76 to 2452 atoms, typical of the catalyst particles used for carbon nanotubes growth, has been explored by a flat histogram Monte Carlo (MC) algorithm (called the ?-mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, gp(Ep) in the configurational space, in terms of the potential energy of the system, with good and well controlled convergence properties, particularly in the melting phase transition zone which is of interest in this work. To describe the system, an iron potential has been implemented, called "corrected EAM" (cEAM), which approximates the MEAM potential of Lee et al. [Phys. Rev. B 64, 184102 (2001)] with an accuracy better than 3 meV/at, and a five times larger computational speed. The main simplification concerns the angular dependence of the potential, with a small impact on accuracy, while the screening coefficients Sij are exactly computed with a fast algorithm. With this potential, ergodic explorations of the clusters can be performed efficiently in a reasonable computing time, at least in the upper half of the solid zone and above. Problems of ergodicity exist in the lower half of the solid zone but routes to overcome them are discussed. The solid-liquid (melting) phase transition temperature Tm is plotted in terms of the cluster atom number Nat. The standard N_{at}^{-1/3} linear dependence (Pawlow law) is observed for Nat >300, allowing an extrapolation up to the bulk metal at 1940 ±50 K. For Nat <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I.

Basire, M.; Soudan, J.-M.; Angelié, C.

2014-09-01

458

Recovering the inflationary potential: An analysis using flow methods and Markov chain Monte Carlo

NASA Astrophysics Data System (ADS)

Since its inception in 1980 by Guth [1], inflation has emerged as the dominant paradigm for describing the physics of the early universe. While inflation has matured theoretically over two decades, it has only recently begun to be rigorously tested observationally. Measurements of the cosmic microwave background (CMB) and large-scale structure surveys (LSS) have begun to unravel the mysteries of the inflationary epoch with exquisite and unprecedented accuracy. This thesis is a contribution to the effort of reconstructing the physics of inflation. This information is largely encoded in the potential energy function of the inflaton, the field that drives the inflationary expansion. With little theoretical guidance as to the probable form of this potential, reconstruction is a predominantly data-driven endeavor. This thesis presents an investigation of the constrainability of the inflaton potential given current CMB and LSS data. We develop a methodology based on the inflationary flow formalism that provides an assessment of our current ability to resolve the form of the inflaton potential in the face of experimental and statistical error. We find that there is uncertainty regarding the initial dynamics of the inflaton field, related to the poor constraints that can be drawn on the primordial power spectrum on large scales. We also investigate the future prospects of potential reconstruction, as might be expected when data from ESA's Planck Surveyor becomes available. We develop an approach that utilizes Markov chain Monte Carlo to analyze the statistical properties of the inflaton potential. Besides providing constraints on the parameters of the potential, this method makes it possible to perform model selection on the inflationary model space. While future data will likely determine the general features of the inflaton, there will likely be many different models that remain good fits to the data. Bayesian model selection will then be needed to draw comparisons between these different models in a statistically rigorous fashion.

Powell, Brian A.

459

Nuclear Instruments and Methods in Physics Research A 527 (2004) 201Â205 A full Monte Carlo 30 mm3 each. The EGSnrc Monte Carlo code has been used to simulate several characteristics from our previous experience with a small animal imaging scanner [1,2]. The YAP-PEM is based on Yttrium

Lanconelli, Nico

460

NASA Astrophysics Data System (ADS)

Although the importance of hydrogeological heterogeneity on contaminant transport is well recognized, the influence of the heterogeneity on remediation efficacy is not yet well established. In this study, we investigated the utility of high-resolution tomographic seismic data for estimating hydrogeological zonation using Markov chain Monte Carlo (MCMC) methods. The method was tested on data collected at the DOE NABIR Field Research Center (FRC) at Oak Ridge National Laboratory in Tennessee, where the subsurface consists of steeply dipping and fractured saprolite, and where ongoing studies are investigating the potential of biostimulation for uranium remediation. Our previously developed hydrogeophysical estimation approaches have been applied to several datasets collected within saturated porous environments. Those studies focused on estimating hydraulic conductivity using geophysical tomographic data, by first deriving relationships between co-located geophysical attributes and hydraulic conductivity measurements, and then using them in Bayesian models to estimate hydraulic conductivity. However, we found that developing relationships between seismic velocity and hydraulic conductivity with confidence at this fractured site proved difficult, possibly due to the difference in sampling volumes of the borehole flowmeter data and the geophysical data, which is exacerbated by the presence of fractures. For example, the wellbore flowmeter data collected at the site may sense the local fractures intersecting the wellbores, whereas the seismic data may sense fracture zones in a directionally dependent and effective manner over the distance between the two boreholes. Instead of estimating the absolute values of hydraulic conductivity as we did in other projects, we chose to estimate the hydrogeological zonation, defined as the probability of observing high permeability fracture zones, by integrating crosswell seismic and borehole flowmeter data using a Bayesian model. Within the Bayesian framework, both seismic velocity and zonation indicator at each pixel were considered as random variables, and crosswell seismic travel time and borehole flowmeter measurements were considered as data with measurement errors. Our goal was to estimate all the unknown quantities simultaneously by conditioning to the available data. We used MCMC methods to solve the Bayesian model by drawing many samples from the posterior distribution functions. Using those samples, we obtained the probability of observing high permeability fracture zones at each pixel along the tomographic cross sections. Our estimation results suggest that, over the study area, a localized high permeability fracture zone has laterally varying thickness and geological dip.

Chen, J.; Hubbard, S.; Fienen, M.; Mehlhorn, T.; Watson, D.

2003-12-01

461

Geometrically-compatible 3-D Monte Carlo and discrete-ordinates methods

This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The purpose of this project was two-fold. The first purpose was to develop a deterministic discrete-ordinates neutral-particle transport scheme for unstructured tetrahedral spatial meshes, and implement it in a computer code. The second purpose was to modify the MCNP Monte Carlo radiation transport code to use adjoint solutions from the tetrahedral-mesh discrete-ordinates code to reduce the statistical variance of Monte Carlo solutions via a weight-window approach. The first task has resulted in a deterministic transport code that is much more efficient for modeling complex 3-D geometries than any previously existing deterministic code. The second task has resulted in a powerful new capability for dramatically reducing the cost of difficult 3-D Monte Carlo calculations.

Morel, J.E.; Wareing, T.A.; McGhee, J.M.; Evans, T.M.

1998-12-31

462

Path integral Monte Carlo (PIMC) is a quantum-level simulation method based on a stochastic sampling of the many-body thermal density matrix. Utilizing the imaginary-time formulation of Feynman's sum-over-histories, it includes thermal fluctuations and particle correlations in a natural way. Over the past two decades, PIMC has been applied to the study of the electron gas, hydrogen under extreme pressure, and

Kenneth Paul Esler

2006-01-01

463

NASA Astrophysics Data System (ADS)

Calculations of thermodynamic properties of Helium plasma by using the Reaction Ensemble Monte Carlo method (REMC) are presented. Non ideal effects at high pressure are observed. Calculations, performed by using Exp-6 or multi-potential curves in the case of neutral-charge interactions, show that in the thermodynamic conditions considered no significative differences are observed. Results have been obtained by using a Graphics Processing Unit (GPU)-CUDA C version of REMC.

D'Angola, A.; Tuttafesta, M.; Guadagno, M.; Santangelo, P.; Laricchiuta, A.; Colonna, G.; Capitelli, M.

2012-11-01

464

The TSUNAMI computational sequences currently in the SCALE 5 code system provide an automated approach to performing sensitivity and uncertainty analysis for eigenvalue responses, using either one-dimensional discrete ordinates or three-dimensional Monte Carlo methods. This capability has recently been expanded to address eigenvalue-difference responses such as reactivity changes. This paper describes the methodology and presents results obtained for an example advanced CANDU reactor design. (authors)

Williams, M. L.; Gehin, J. C.; Clarno, K. T. [Oak Ridge National Laboratory, Bldg. 5700, P.O. Box 2008, Oak Ridge, TN 37831-6170 (United States)

2006-07-01

465

NASA Astrophysics Data System (ADS)

Two of the primary challenges associated with the neutronic analysis of the Very High Temperature Reactor (VHTR) are accounting for resonance self-shielding in the particle fuel (contributing to the double heterogeneity) and accounting for temperature feedback due to Doppler broadening. The double heterogeneity challenge is addressed by defining a "double heterogeneity factor" (DHF) that allows conventional light water reactor (LWR) lattice physics codes to analyze VHTR configurations. The challenge of treating Doppler broadening is addressed by a new "on-the-fly" methodology that is applied during the random walk process with negligible impact on computational efficiency. Although this methodology was motivated by the need to treat temperature feedback in a VHTR, it is applicable to any reactor design. The on-the-fly Doppler methodology is based on a combination of Taylor and asymptotic series expansions. The type of series representation was determined by investigating the temperature dependence of U238 resonance cross sections in three regions: near the resonance peaks, mid-resonance, and the resonance wings. The coefficients for these series expansions were determined by regressions over the energy and temperature range of interest. The comparison of the broadened cross sections using this methodology with the NJOY cross sections was excellent. A Monte Carlo code was implemented to apply the combined regression model and used to estimate the additional computing cost which was found to be less than 1%. The DHF accounts for the effect of the particle heterogeneity on resonance absorption in particle fuel. The first level heterogeneity posed by the VHTR fuel particles is a unique characteristic that cannot be accounted for by conventional LWR lattice physics codes. On the other hand, Monte Carlo codes can take into account the detailed geometry of the VHTR including resolution of individual fuel particles without performing any type of resonance approximation. The DHF, basically a self shielding factor, was found to be weakly dependent on space and fuel depletion. The DHF only depends strongly on the packing fraction in a fuel compact. Therefore, it is proposed that DHFs be tabulated as a function of packing fraction to analyze the heterogeneous fuel in VHTR configuration with LWR lattice physics codes.

Yesilyurt, Gokhan

466

Quasielastic response with a real-time path-integral Monte Carlo method

NASA Astrophysics Data System (ADS)

We formulate the quasielastic response of a nonrelativistic many-body system at zero temperature in terms of ground-state density-matrix elements and real-time path integrals that embody the final-state interactions. While the former provide the weight for a conventional Monte Carlo calculation, the latter require a more sophisticated treatment. We argue that the stationary-phase Monte Carlo technique recently developed by Doll et al. can be used to study the approach to ``Y scaling.'' We perform calculations for a particle in a potential well in one and three dimensions and compare them with the exact results available for these models.

Carraro, C.; Koonin, S. E.

1990-04-01

467

Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues

The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL.

Harris, G.; Van Horn, R.

1996-06-01

468

NASA Astrophysics Data System (ADS)

Ab initio folding of the avian pancreatic polypeptide using a diffusion-process-controlled Monte Carlo method is presented. This method differs from other Monte Carlo methods in that two successive conformations must be kinetically connected in a small period of time. The 36-residue polypeptide is represented using a hybrid level of structure description: the backbone is treated at an all-atom level, while the side chains are modeled as spheres. The conformations are evaluated on the basis of pairwise contact energies between the side chains, a main chain hydrogen bonding potential, and local bonded potentials. Starting from various extended conformations, the chain reaches the basin of lowest energy in ˜1000-3500 Monte Carlo steps and the predicted conformations deviate by ˜3.0 Å rms from the x-ray structure. The eight trajectories suggest a three-step mechanism: (1) early formation of the ? helix in the region 14-33, (2) cooperative formation of long-range interactions, and (3) stabilization of the polyprolinelike conformation in the region 1-8 in the final steps of folding.

Derreumaux, Philippe

1998-07-01

469

A simple method of efficiency calibration for gamma spectrometry was performed. This method, which focused on measuring the radioactivity of (137)Cs in food samples, was based on Monte Carlo simulations available in the free-of-charge toolkit GEANT4. Experimentally, the efficiency values of a high-purity germanium detector were calculated for three reference materials representing three different food items. These efficiency values were compared with their counterparts produced by a computer code that simulated experimental conditions. Interestingly, the output of the simulation code was in acceptable agreement with the experimental findings, thus validating the proposed method. PMID:24214912

Alrefae, T

2014-12-01

470

Monte Carlo (MC) methods, based on random updates and the trial-and-error principle, are well suited to retrieve form-free particle size distributions from small-angle scattering patterns of non-interacting low-concentration scatterers such as particles in solution or precipitates in metals. Improvements are presented to existing MC methods, such as a non-ambiguous convergence criterion, nonlinear scaling of contributions to match their observability in a scattering measurement, and a method for estimating the minimum visibility threshold and uncertainties on the resulting size distributions. PMID:23596341

Pauw, Brian R.; Pedersen, Jan Skov; Tardif, Samuel; Takata, Masaki; Iversen, Bo B.

2013-01-01

471

A set of multi-group eigenvalue (Keff) benchmark problems in three-dimensional homogenised reactor core configurations have been solved using the deterministic finite element transport theory code EVENT and the Monte Carlo code MCNP4C. The principal aim of this work is to qualify numerical methods and algorithms implemented in EVENT. The benchmark problems were compiled and published by the Nuclear Data Agency

A. K. Ziver; M. S. Shahdatullah; M. D. Eaton; C. R. E. de Oliveira; A. P. Umpleby; C. C. Pain; A. J. H. Goddard

2005-01-01

472

Magnetic interpretation by the Monte Carlo method with application to the intrusion of the Crimea

NASA Astrophysics Data System (ADS)

The study involves the application of geophysical methods for geological mapping. Magnetic and radiometric measurements were used to delineate the intrusive bodies in Bakhchysarai region of the Crimea. Proton magnetometers used to measure the total magnetic field in the area and variation station. Scintillation radiometer used to determine the radiation dose. Due to susceptimeter measured the magnetic susceptibility of rocks. It deal with the fact that in this area of research the rock mass appears on the surface. Anomalous values of the magnetic intensity were obtained as the difference between the observed measurements and values on variation station. Through geophysical data were given maps of the anomalous magnetic field, radiation dose, and magnetic susceptibility. Geology of area consisted from magmatic rocks and overlying sedimentary rocks. The main task of research was to study the geometry and the magnetization vector of igneous rocks. Intrusive body composed of diabase and had an average magnetic susceptibility, weak dose rate and negative magnetic field. Sedimentary rocks were represented by clays. They had a low value of the magnetic susceptibility and the average dose rate. Map of magnetic susceptibility gave information about the values and distribution of magnetized bodies close to the surface. These data were used to control and elaboration the data of the magnetic properties for magnetic modelling. Magnetic anomaly map shows the distribution of magnetization in depth. Interpretation profile was located perpendicular to the strike of the intrusive body. Modelling was performed for profile of the magnetic field. Used the approach for filling by rectangular blocks of geological media. The fitting implemented for value magnetization and its vector for ever block. Fitting was carried out using the Monte Carlo method in layers from the bottom to top. After passing through all the blocks were fixed magnetic parameters of the block with the best approximation between the theoretical and observed fields i.e. object function. It was first iteration. The next iteration begins with this block. If after next access through blocks was not reduce the objective function is carried out with the passage of the last block as in the first iteration. This technique worked well for separate synthetic models. As result was obtained the geometric boundaries of geological objects. Igneous rocks are nearly vertical magnetization with respect to the current field. Perhaps, this is because the Jurassic diabase at its formation frozen in time when the magnetic poles have opposite signs in comparison to the modern magnetic field. Due to the magnetic modelling obtained geological section that consistent with geological concept.

Gryshchuk, Pavlo

2014-05-01

473

The Markov chain Monte Carlo method: an approach to approximate counting and integration

In the area of statistical physics, Monte Carlo algorithms based on Markov chain simulation have been in use for many years. The validity of these algorithms depends cru- cially on the rate of convergence to equilibrium of the Markov chain being simulated. Unfortunately, the classical theory of stochastic processes hardly touches on the sort of non-asymptotic analysis required in this

Mark Jerrum; Alistair Sinclair

1996-01-01

474

A MONTE CARLO METHOD FOR COMPUTING THE TRANSMISSION OF FAST NEUTRONS THROUGH A LEAD SHIELD (thesis)

A digital computer program, employing Monte Carlo techniques, was ; designed to compute the transmission of fast neutrons through a spherical lead ; shield. The source is contained in a void at the center of the shield, and ; surface fluxes are computed. Both elastic and inelastic scattering of the ; neutrons are considered by the program. Flow charts were

Humphries

1958-01-01

475

The electrostatic persistence length calculated from Monte Carlo, variational and perturbation a screened Coulomb potential for the electrostatic interactions. For the flexible model the electrostatic . As long as the salt content is low and 1 is longer than the end-to-end distance, the electrostatic

Peterson, Carsten

476

for predicting molecule-specific ionization, excitation, and scattering cross sections in the very low energy regime that can be applied in