Bardenet, R.
2012-01-01
ISBN:978-2-7598-1032-1; International audience; Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC) methods. We give intuition on the theoretic...
Dunn, William L
2012-01-01
Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble
Monte Carlo methods for electromagnetics
Sadiku, Matthew NO
2009-01-01
Until now, novices had to painstakingly dig through the literature to discover how to use Monte Carlo techniques for solving electromagnetic problems. Written by one of the foremost researchers in the field, Monte Carlo Methods for Electromagnetics provides a solid understanding of these methods and their applications in electromagnetic computation. Including much of his own work, the author brings together essential information from several different publications.Using a simple, clear writing style, the author begins with a historical background and review of electromagnetic theory. After addressing probability and statistics, he introduces the finite difference method as well as the fixed and floating random walk Monte Carlo methods. The text then applies the Exodus method to Laplace's and Poisson's equations and presents Monte Carlo techniques for handing Neumann problems. It also deals with whole field computation using the Markov chain, applies Monte Carlo methods to time-varying diffusion problems, and ...
Metropolis Methods for Quantum Monte Carlo Simulations
Ceperley, D. M.
2003-01-01
Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector monte carlo ({\\it i.e.} diffusion Monte Carlo with rejection), multilevel sampling in path integral Monte Carlo, the sampling of permutations, ...
Equilibrium Statistics: Monte Carlo Methods
Kröger, Martin
Monte Carlo methods use random numbers, or ‘random’ sequences, to sample from a known shape of a distribution, or to extract distribution by other means. and, in the context of this book, to (i) generate representative equilibrated samples prior being subjected to external fields, or (ii) evaluate high-dimensional integrals. Recipes for both topics, and some more general methods, are summarized in this chapter. It is important to realize, that Monte Carlo should be as artificial as possible to be efficient and elegant. Advanced Monte Carlo ‘moves’, required to optimize the speed of algorithms for a particular problem at hand, are outside the scope of this brief introduction. One particular modern example is the wavelet-accelerated MC sampling of polymer chains [406].
Applications of Monte Carlo Methods in Calculus.
Gordon, Sheldon P.; Gordon, Florence S.
1990-01-01
Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)
An introduction to Monte Carlo methods
Walter, J. -C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo sim
Improved Monte Carlo Renormalization Group Method
Gupta, R.; Wilson, K. G.; Umrigar, C.
1985-01-01
An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.
Monte Carlo methods for particle transport
Haghighat, Alireza
2015-01-01
The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...
Simulation and the Monte Carlo method
Rubinstein, Reuven Y
2016-01-01
Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...
Random Numbers and Monte Carlo Methods
Scherer, Philipp O. J.
Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.
Quantum speedup of Monte Carlo methods.
Montanaro, Ashley
2015-09-08
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.
Adiabatic optimization versus diffusion Monte Carlo methods
Jarret, Michael; Jordan, Stephen P.; Lackey, Brad
2016-10-01
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the intr
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.
2015-01-01
Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying
The Monte Carlo method the method of statistical trials
Shreider, YuA
1966-01-01
The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc.
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
An introduction to Monte Carlo methods
Walter, J.-C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo simulations are ergodicity and detailed balance. The Ising model is a lattice spin system with nearest neighbor interactions that is appropriate to illustrate different examples of Monte Carlo simulations. It displays a second order phase transition between disordered (high temperature) and ordered (low temperature) phases, leading to different strategies of simulations. The Metropolis algorithm and the Glauber dynamics are efficient at high temperature. Close to the critical temperature, where the spins display long range correlations, cluster algorithms are more efficient. We introduce the rejection free (or continuous time) algorithm and describe in details an interesting alternative representation of the Ising model using graphs instead of spins with the so-called Worm algorithm. We conclude with an important discussion of the dynamical effects such as thermalization and correlation time.
Discrete range clustering using Monte Carlo methods
Chatterji, G. B.; Sridhar, B.
1993-01-01
For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
Nuyens, Dirk
2016-01-01
This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.
Use of Monte Carlo Methods in brachytherapy; Uso del metodo de Monte Carlo en braquiterapia
Energy Technology Data Exchange (ETDEWEB)
Granero Cabanero, D.
2015-07-01
The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)
The Monte Carlo Method. Popular Lectures in Mathematics.
Sobol', I. M.
The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…
Forest canopy BRDF simulation using Monte Carlo method
Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.
2006-01-01
Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.
Rare event simulation using Monte Carlo methods
Rubino, Gerardo
2009-01-01
In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...
Recent Developments in Quantum Monte Carlo: Methods and Applications
Aspuru-Guzik, Alan; Austin, Brian; Domin, Dominik; Galek, Peter T. A.; Handy, Nicholas; Prasad, Rajendra; Salomon-Ferrer, Romelia; Umezawa, Naoto; Lester, William A.
2007-12-01
The quantum Monte Carlo method in the diffusion Monte Carlo form has become recognized for its capability of describing the electronic structure of atomic, molecular and condensed matter systems to high accuracy. This talk will briefly outline the method with emphasis on recent developments connected with trial function construction, linear scaling, and applications to selected systems.
Iterative acceleration methods for Monte Carlo and deterministic criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Urbatsch, T.J.
1995-11-01
If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.
Monte Carlo method for solving a parabolic problem
Directory of Open Access Journals (Sweden)
Tian Yi
2016-01-01
Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.
Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules
Lester, William A; Reynolds, PJ
1994-01-01
This book presents the basic theory and application of the Monte Carlo method to the electronic structure of atoms and molecules. It assumes no previous knowledge of the subject, only a knowledge of molecular quantum mechanics at the first-year graduate level. A working knowledge of traditional ab initio quantum chemistry is helpful, but not essential.Some distinguishing features of this book are: Clear exposition of the basic theory at a level to facilitate independent study. Discussion of the various versions of the theory: diffusion Monte Carlo, Green's function Monte Carlo, and release n
Quantum Monte Carlo methods algorithms for lattice models
Gubernatis, James; Werner, Philipp
2016-01-01
Featuring detailed explanations of the major algorithms used in quantum Monte Carlo simulations, this is the first textbook of its kind to provide a pedagogical overview of the field and its applications. The book provides a comprehensive introduction to the Monte Carlo method, its use, and its foundations, and examines algorithms for the simulation of quantum many-body lattice problems at finite and zero temperature. These algorithms include continuous-time loop and cluster algorithms for quantum spins, determinant methods for simulating fermions, power methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum impurity models and their use within dynamical mean-field theory, along with algorithms for analytically continuing imaginary-time quantum Monte Carlo data. The parallelization of Monte Carlo simulations is also addressed. This is an essential resource for graduate students, teachers, and researchers interested in ...
Vectorized Monte Carlo methods for reactor lattice analysis
Brown, F. B.
1984-01-01
Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
MIKOSCH, T; WANG, QA
1995-01-01
We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.
On the Markov Chain Monte Carlo (MCMC) method
Indian Academy of Sciences (India)
Rajeeva L Karandikar
2006-04-01
Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be speciﬁed indirectly. In this article, we give an introduction to this method along with some examples.
Monte Carlo methods for light propagation in biological tissues
Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine
2016-01-01
Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis–Hastings algori...
Monte Carlo methods and applications in nuclear physics
Energy Technology Data Exchange (ETDEWEB)
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.
Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo
Energy Technology Data Exchange (ETDEWEB)
Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)
2011-07-01
This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions
Directory of Open Access Journals (Sweden)
Samuel Livingstone
2014-06-01
Full Text Available Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo simulation for statistical inference and molecular dynamics is provided, with particular emphasis on methods based on Langevin diffusions. After this, geometric concepts in Markov chain Monte Carlo are introduced. A full derivation of the Langevin diffusion on a Riemannian manifold is given, together with a discussion of the appropriate Riemannian metric choice for different problems. A survey of applications is provided, and some open questions are discussed.
Perturbation Monte Carlo methods for tissue structure alterations.
Nguyen, Jennifer; Hayakawa, Carole K; Mourant, Judith R; Spanier, Jerome
2013-01-01
This paper describes an extension of the perturbation Monte Carlo method to model light transport when the phase function is arbitrarily perturbed. Current perturbation Monte Carlo methods allow perturbation of both the scattering and absorption coefficients, however, the phase function can not be varied. The more complex method we develop and test here is not limited in this way. We derive a rigorous perturbation Monte Carlo extension that can be applied to a large family of important biomedical light transport problems and demonstrate its greater computational efficiency compared with using conventional Monte Carlo simulations to produce forward transport problem solutions. The gains of the perturbation method occur because only a single baseline Monte Carlo simulation is needed to obtain forward solutions to other closely related problems whose input is described by perturbing one or more parameters from the input of the baseline problem. The new perturbation Monte Carlo methods are tested using tissue light scattering parameters relevant to epithelia where many tumors originate. The tissue model has parameters for the number density and average size of three classes of scatterers; whole nuclei, organelles such as lysosomes and mitochondria, and small particles such as ribosomes or large protein complexes. When these parameters or the wavelength is varied the scattering coefficient and the phase function vary. Perturbation calculations give accurate results over variations of ∼15-25% of the scattering parameters.
Study of the Transition Flow Regime using Monte Carlo Methods
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
Successful combination of the stochastic linearization and Monte Carlo methods
Elishakoff, I.; Colombi, P.
1993-01-01
A combination of a stochastic linearization and Monte Carlo techniques is presented for the first time in literature. A system with separable nonlinear damping and nonlinear restoring force is considered. The proposed combination of the energy-wise linearization with the Monte Carlo method yields an error under 5 percent, which corresponds to the error reduction associated with the conventional stochastic linearization by a factor of 4.6.
Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method
2002-01-01
This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.
Monte Carlo methods and models in finance and insurance
Korn, Ralf
2010-01-01
Offering a unique balance between applications and calculations, this book incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The book enables readers to find the right algorithm for a desired application and illustrates complicated methods and algorithms with simple applicat
Monte Carlo Methods for Tempo Tracking and Rhythm Quantization
Cemgil, A T; 10.1613/jair.1121
2011-01-01
We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. Exact computation of posterior features such as the MAP state is intractable in this model class, so we introduce Monte Carlo methods for integration and optimization. We compare Markov Chain Monte Carlo (MCMC) methods (such as Gibbs sampling, simulated annealing and iterative improvement) and sequential Monte Carlo methods (particle filters). Our simulation results suggest better results with sequential methods. The methods can be applied in both online and batch scenarios such as tempo tracking and transcr...
Quasi-Monte Carlo methods for the Heston model
Jan Baldeaux; Dale Roberts
2012-01-01
In this paper, we discuss the application of quasi-Monte Carlo methods to the Heston model. We base our algorithms on the Broadie-Kaya algorithm, an exact simulation scheme for the Heston model. As the joint transition densities are not available in closed-form, the Linear Transformation method due to Imai and Tan, a popular and widely applicable method to improve the effectiveness of quasi-Monte Carlo methods, cannot be employed in the context of path-dependent options when the underlying pr...
Auxiliary-field quantum Monte Carlo methods in nuclei
Alhassid, Y
2016-01-01
Auxiliary-field quantum Monte Carlo methods enable the calculation of thermal and ground state properties of correlated quantum many-body systems in model spaces that are many orders of magnitude larger than those that can be treated by conventional diagonalization methods. We review recent developments and applications of these methods in nuclei using the framework of the configuration-interaction shell model.
Quantum Monte Carlo diagonalization method as a variational calculation
Energy Technology Data Exchange (ETDEWEB)
Mizusaki, Takahiro; Otsuka, Takaharu [Tokyo Univ. (Japan). Dept. of Physics; Honma, Michio
1997-05-01
A stochastic method for performing large-scale shell model calculations is presented, which utilizes the auxiliary field Monte Carlo technique and diagonalization method. This method overcomes the limitation of the conventional shell model diagonalization and can extremely widen the feasibility of shell model calculations with realistic interactions for spectroscopic study of nuclear structure. (author)
On polarization parameters of spin-1 particles and anomalous couplings in e^+e^-→ ZZ/Zγ
Rahaman, Rafiqul; Singh, Ritesh K.
2016-10-01
We study the anomalous trilinear gauge couplings of Z and γ using a complete set of polarization asymmetries for the Z boson in e^+e^-→ ZZ/Zγ processes with unpolarized initial beams. We use these polarization asymmetries, along with the cross section, to obtain a simultaneous limit on all the anomalous couplings using the Markov Chain Monte Carlo (MCMC) method. For an e^+e^- collider running at 500 GeV center-of-mass energy and 100 fb^{-1} of integrated luminosity the simultaneous limits on the anomalous couplings are 1-3× 10^{-3}.
The Monte Carlo method in quantum field theory
Morningstar, C
2007-01-01
This series of six lectures is an introduction to using the Monte Carlo method to carry out nonperturbative studies in quantum field theories. Path integrals in quantum field theory are reviewed, and their evaluation by the Monte Carlo method with Markov-chain based importance sampling is presented. Properties of Markov chains are discussed in detail and several proofs are presented, culminating in the fundamental limit theorem for irreducible Markov chains. The example of a real scalar field theory is used to illustrate the Metropolis-Hastings method and to demonstrate the effectiveness of an action-preserving (microcanonical) local updating algorithm in reducing autocorrelations. The goal of these lectures is to provide the beginner with the basic skills needed to start carrying out Monte Carlo studies in quantum field theories, as well as to present the underlying theoretical foundations of the method.
Observations on variational and projector Monte Carlo methods.
Umrigar, C J
2015-10-28
Variational Monte Carlo and various projector Monte Carlo (PMC) methods are presented in a unified manner. Similarities and differences between the methods and choices made in designing the methods are discussed. Both methods where the Monte Carlo walk is performed in a discrete space and methods where it is performed in a continuous space are considered. It is pointed out that the usual prescription for importance sampling may not be advantageous depending on the particular quantum Monte Carlo method used and the observables of interest, so alternate prescriptions are presented. The nature of the sign problem is discussed for various versions of PMC methods. A prescription for an exact PMC method in real space, i.e., a method that does not make a fixed-node or similar approximation and does not have a finite basis error, is presented. This method is likely to be practical for systems with a small number of electrons. Approximate PMC methods that are applicable to larger systems and go beyond the fixed-node approximation are also discussed.
A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods
Bijmolt, T.H.A.; Wedel, M.
1996-01-01
We compare three alternative Maximum Likelihood Multidimensional Scaling methods for pairwise dissimilarity ratings, namely MULTISCALE, MAXSCAL, and PROSCAL in a Monte Carlo study.The three MLMDS methods recover the true con gurations very well.The recovery of the true dimensionality depends on the
The Metropolis Monte Carlo Method in Statistical Physics
Landau, David P.
2003-11-01
A brief overview is given of some of the advances in statistical physics that have been made using the Metropolis Monte Carlo method. By complementing theory and experiment, these have increased our understanding of phase transitions and other phenomena in condensed matter systems. A brief description of a new method, commonly known as "Wang-Landau sampling," will also be presented.
Applications of quantum Monte Carlo methods in condensed systems
Kolorenc, Jindrich
2010-01-01
The quantum Monte Carlo methods represent a powerful and broadly applicable computational tool for finding very accurate solutions of the stationary Schroedinger equation for atoms, molecules, solids and a variety of model systems. The algorithms are intrinsically parallel and are able to take full advantage of the present-day high-performance computing systems. This review article concentrates on the fixed-node/fixed-phase diffusion Monte Carlo method with emphasis on its applications to electronic structure of solids and other extended many-particle systems.
Introduction to the variational and diffusion Monte Carlo methods
Toulouse, Julien; Umrigar, C J
2015-01-01
We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on the subject, we review in depth the Metropolis-Hastings algorithm used in VMC for sampling the square of an approximate wave function, discussing details important for applications to electronic systems. We also review in detail the more sophisticated DMC algorithm within the fixed-node approximation, introduced to avoid the infamous Fermionic sign problem, which allows one to sample a more accurate approximation to the ground-state wave function. Throughout this review, we discuss the statistical methods used for evaluating expectation values and statistical uncertainties. In particular, we show how to estimate nonlinear functions of expectation values and their statistical uncertainties.
Multiple-time-stepping generalized hybrid Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Bayesian Monte Carlo Method for Nuclear Data Evaluation
Energy Technology Data Exchange (ETDEWEB)
Koning, A.J., E-mail: koning@nrg.eu
2015-01-15
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using TALYS. The result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by an experiment based weight.
Monte Carlo method for magnetic impurities in metals
Hirsch, J. E.; Fye, R. M.
1986-01-01
The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.
An Overview of the Monte Carlo Methods, Codes, & Applications Group
Energy Technology Data Exchange (ETDEWEB)
Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-08-30
This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.
Optimization of sequential decisions by least squares Monte Carlo method
DEFF Research Database (Denmark)
Nishijima, Kazuyoshi; Anders, Annett
change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...
Monte Carlo methods for light propagation in biological tissues.
Vinckenbosch, Laura; Lacaux, Céline; Tindel, Samy; Thomassin, Magalie; Obara, Tiphaine
2015-11-01
Light propagation in turbid media is driven by the equation of radiative transfer. We give a formal probabilistic representation of its solution in the framework of biological tissues and we implement algorithms based on Monte Carlo methods in order to estimate the quantity of light that is received by a homogeneous tissue when emitted by an optic fiber. A variance reduction method is studied and implemented, as well as a Markov chain Monte Carlo method based on the Metropolis-Hastings algorithm. The resulting estimating methods are then compared to the so-called Wang-Prahl (or Wang) method. Finally, the formal representation allows to derive a non-linear optimization algorithm close to Levenberg-Marquardt that is used for the estimation of the scattering and absorption coefficients of the tissue from measurements.
Monte Carlo methods for multidimensional integration for European option pricing
Todorov, V.; Dimov, I. T.
2016-10-01
In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.
A separable shadow Hamiltonian hybrid Monte Carlo method.
Sweet, Christopher R; Hampton, Scott S; Skeel, Robert D; Izaguirre, Jesús A
2009-11-07
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
Monte Carlo methods for pricing ﬁnancial options
Indian Academy of Sciences (India)
N Bolia; S Juneja
2005-04-01
Pricing ﬁnancial options is amongst the most important and challenging problems in the modern ﬁnancial industry. Except in the simplest cases, the prices of options do not have a simple closed form solution and efﬁcient computational methods are needed to determine them. Monte Carlo methods have increasingly become a popular computational tool to price complex ﬁnancial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the ‘curse of dimensionality’. However, even Monte-Carlo techniques can be quite slow as the problem-size increases, motivating research in variance reduction techniques to increase the efﬁciency of the simulations. In this paper, we review some of the popular variance reduction techniques and their application to pricing options. We particularly focus on the recent Monte-Carlo techniques proposed to tackle the difﬁcult problem of pricing American options. These include: regression-based methods, random tree methods and stochastic mesh methods. Further, we show how importance sampling, a popular variance reduction technique, may be combined with these methods to enhance their effectiveness. We also brieﬂy review the evolving options market in India.
On adaptive resampling strategies for sequential Monte Carlo methods
Del Moral, Pierre; Doucet, Arnaud; Jasra, Ajay
2012-01-01
Sequential Monte Carlo (SMC) methods are a class of techniques to sample approximately from any sequence of probability distributions using a combination of importance sampling and resampling steps. This paper is concerned with the convergence analysis of a class of SMC methods where the times at which resampling occurs are computed online using criteria such as the effective sample size. This is a popular approach amongst practitioners but there are very few convergence results available for...
Monte Carlo methods in continuous time for lattice Hamiltonians
Huffman, Emilie
2016-01-01
We solve a variety of sign problems for models in lattice field theory using the Hamiltonian formulation, including Yukawa models and simple lattice gauge theories. The solutions emerge naturally in continuous time and use the dual representation for the bosonic fields. These solutions allow us to construct quantum Monte Carlo methods for these problems. The methods could provide an alternative approach to understanding non-perturbative dynamics of some lattice field theories.
Bayesian Monte Carlo method for nuclear data evaluation
Energy Technology Data Exchange (ETDEWEB)
Koning, A.J. [Nuclear Research and Consultancy Group NRG, P.O. Box 25, ZG Petten (Netherlands)
2015-12-15
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using the nuclear model code TALYS and the experimental nuclear reaction database EXFOR. The method is applied to all nuclides at the same time. First, the global predictive power of TALYS is numerically assessed, which enables to set the prior space of nuclear model solutions. Next, the method gradually zooms in on particular experimental data per nuclide, until for each specific target nuclide its existing experimental data can be used for weighted Monte Carlo sampling. To connect to the various different schools of uncertainty propagation in applied nuclear science, the result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by the EXFOR-based weight. (orig.)
Bayesian Monte Carlo method for nuclear data evaluation
Koning, A. J.
2015-12-01
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using the nuclear model code TALYS and the experimental nuclear reaction database EXFOR. The method is applied to all nuclides at the same time. First, the global predictive power of TALYS is numerically assessed, which enables to set the prior space of nuclear model solutions. Next, the method gradually zooms in on particular experimental data per nuclide, until for each specific target nuclide its existing experimental data can be used for weighted Monte Carlo sampling. To connect to the various different schools of uncertainty propagation in applied nuclear science, the result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by the EXFOR-based weight.
Development of ray tracing visualization program by Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Higuchi, Kenji; Otani, Takayuki [Japan Atomic Energy Research Inst., Tokyo (Japan); Hasegawa, Yukihiro
1997-09-01
Ray tracing algorithm is a powerful method to synthesize three dimensional computer graphics. In conventional ray tracing algorithms, a view point is used as a starting point of ray tracing, from which the rays are tracked up to the light sources through center points of pixels on the view screen to calculate the intensities of the pixels. This manner, however, makes it difficult to define the configuration of light source as well as to strictly simulate the reflections of the rays. To resolve these problems, we have developed a new ray tracing means which traces rays from a light source, not from a view point, with use of Monte Carlo method which is widely applied in nuclear fields. Moreover, we adopt the variance reduction techniques to the program with use of the specialized machine (Monte-4) for particle transport Monte Carlo so that the computational time could be successfully reduced. (author)
Monte Carlo Methods for Bridging the Timescale Gap
Wilding, Nigel; Landau, David P.
We identify the origin, and elucidate the character of the extended time-scales that plague computer simulation studies of first and second order phase transitions. A brief survey is provided of a number of new and existing techniques that attempt to circumvent these problems. Attention is then focused on two novel methods with which we have particular experience: “Wang-Landau sampling” and Phase Switch Monte Carlo. Detailed case studies are made of the application of the Wang-Landau approach to calculate the density of states of the 2D Ising model and the Edwards-Anderson spin glass. The principles and operation of Phase Switch Monte Carlo are described and its utility in tackling ‘difficult’ first order phase transitions is illustrated via a case study of hard-sphere freezing. We conclude with a brief overview of promising new methods for the improvement of deterministic, spin dynamics simulations.
Cluster Monte Carlo methods for the FePt Hamiltonian
Lyberatos, A.; Parker, G. J.
2016-02-01
Cluster Monte Carlo methods for the classical spin Hamiltonian of FePt with long range exchange interactions are presented. We use a combination of the Swendsen-Wang (or Wolff) and Metropolis algorithms that satisfies the detailed balance condition and ergodicity. The algorithms are tested by calculating the temperature dependence of the magnetization, susceptibility and heat capacity of L10-FePt nanoparticles in a range including the critical region. The cluster models yield numerical results in good agreement within statistical error with the standard single-spin flipping Monte Carlo method. The variation of the spin autocorrelation time with grain size is used to deduce the dynamic exponent of the algorithms. Our cluster models do not provide a more accurate estimate of the magnetic properties at equilibrium.
Dynamical Monte Carlo method for stochastic epidemic models
Aiello, O E
2002-01-01
A new approach to Dynamical Monte Carlo Methods is introduced to simulate markovian processes. We apply this approach to formulate and study an epidemic Generalized SIRS model. The results are in excellent agreement with the forth order Runge-Kutta method in a region of deterministic solution. Introducing local stochastic interactions, the Runge-Kutta method is not applicable, and we solve and check it self-consistently with a stochastic version of the Euler Method. The results are also analyzed under the herd-immunity concept.
On adaptive resampling strategies for sequential Monte Carlo methods
Del Moral, Pierre; Jasra, Ajay; 10.3150/10-BEJ335
2012-01-01
Sequential Monte Carlo (SMC) methods are a class of techniques to sample approximately from any sequence of probability distributions using a combination of importance sampling and resampling steps. This paper is concerned with the convergence analysis of a class of SMC methods where the times at which resampling occurs are computed online using criteria such as the effective sample size. This is a popular approach amongst practitioners but there are very few convergence results available for these methods. By combining semigroup techniques with an original coupling argument, we obtain functional central limit theorems and uniform exponential concentration estimates for these algorithms.
Novel Extrapolation Method in the Monte Carlo Shell Model
Shimizu, Noritaka; Mizusaki, Takahiro; Otsuka, Takaharu; Abe, Takashi; Honma, Michio
2010-01-01
We propose an extrapolation method utilizing energy variance in the Monte Carlo shell model in order to estimate the energy eigenvalue and observables accurately. We derive a formula for the energy variance with deformed Slater determinants, which enables us to calculate the energy variance efficiently. The feasibility of the method is demonstrated for the full $pf$-shell calculation of $^{56}$Ni, and the applicability of the method to a system beyond current limit of exact diagonalization is shown for the $pf$+$g_{9/2}$-shell calculation of $^{64}$Ge.
A new hybrid method--combined heat flux method with Monte-Carlo method to analyze thermal radiation
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A new hybrid method, Monte-Carlo-Heat-Flux (MCHF) method, was presented to analyze the radiative heat transfer of participating medium in a three-dimensional rectangular enclosure using combined the Monte-Carlo method with the heat flux method. Its accuracy and reliability was proved by comparing the computational results with exact results from classical "Zone Method".
On polarization parameters of spin-1 particles and anomalous couplings in e{sup +}e{sup -} → ZZ/Zγ
Energy Technology Data Exchange (ETDEWEB)
Rahaman, Rafiqul; Singh, Ritesh K. [Indian Institute of Science Education and Research Kolkata, Department of Physical Sciences, Mohanpur (India)
2016-10-15
We study the anomalous trilinear gauge couplings of Z and γ using a complete set of polarization asymmetries for the Z boson in e{sup +}e{sup -} → ZZ/Zγ processes with unpolarized initial beams. We use these polarization asymmetries, along with the cross section, to obtain a simultaneous limit on all the anomalous couplings using the Markov Chain Monte Carlo (MCMC) method. For an e{sup +}e{sup -} collider running at 500 GeV center-of-mass energy and 100 fb{sup -1} of integrated luminosity the simultaneous limits on the anomalous couplings are 1-3 x 10{sup -3}. (orig.)
Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications
Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne
2014-01-01
The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.
Eigenvalue analysis using a full-core Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Okafor, K.C.; Zino, J.F. (Westinghouse Savannah River Co., Aiken, SC (United States))
1992-01-01
The reactor physics codes used at the Savannah River Site (SRS) to predict reactor behavior have been continually benchmarked against experimental and operational data. A particular benchmark variable is the observed initial critical control rod position. Historically, there has been some difficulty predicting this position because of the difficulties inherent in using computer codes to model experimental or operational data. The Monte Carlo method is applied in this paper to study the initial critical control rod positions for the SRS K Reactor. A three-dimensional, full-core MCNP model of the reactor was developed for this analysis.
Application of Monte Carlo methods in tomotherapy and radiation biophysics
Hsiao, Ya-Yun
Helical tomotherapy is an attractive treatment for cancer therapy because highly conformal dose distributions can be achieved while the on-board megavoltage CT provides simultaneous images for accurate patient positioning. The convolution/superposition (C/S) dose calculation methods typically used for Tomotherapy treatment planning may overestimate skin (superficial) doses by 3-13%. Although more accurate than C/S methods, Monte Carlo (MC) simulations are too slow for routine clinical treatment planning. However, the computational requirements of MC can be reduced by developing a source model for the parts of the accelerator that do not change from patient to patient. This source model then becomes the starting point for additional simulations of the penetration of radiation through patient. In the first section of this dissertation, a source model for a helical tomotherapy is constructed by condensing information from MC simulations into series of analytical formulas. The MC calculated percentage depth dose and beam profiles computed using the source model agree within 2% of measurements for a wide range of field sizes, which suggests that the proposed source model provides an adequate representation of the tomotherapy head for dose calculations. Monte Carlo methods are a versatile technique for simulating many physical, chemical and biological processes. In the second major of this thesis, a new methodology is developed to simulate of the induction of DNA damage by low-energy photons. First, the PENELOPE Monte Carlo radiation transport code is used to estimate the spectrum of initial electrons produced by photons. The initial spectrum of electrons are then combined with DNA damage yields for monoenergetic electrons from the fast Monte Carlo damage simulation (MCDS) developed earlier by Semenenko and Stewart (Purdue University). Single- and double-strand break yields predicted by the proposed methodology are in good agreement (1%) with the results of published
A Monte Carlo Method for Calculating Initiation Probability
Energy Technology Data Exchange (ETDEWEB)
Greenman, G M; Procassini, R J; Clouse, C J
2007-03-05
A Monte Carlo method for calculating the probability of initiating a self-sustaining neutron chain reaction has been developed. In contrast to deterministic codes which solve a non-linear, adjoint form of the Boltzmann equation to calculate initiation probability, this new method solves the forward (standard) form of the equation using a modified source calculation technique. Results from this new method are compared with results obtained from several deterministic codes for a suite of historical test problems. The level of agreement between these code predictions is quite good, considering the use of different numerical techniques and nuclear data. A set of modifications to the historical test problems has also been developed which reduces the impact of neutron source ambiguities on the calculated probabilities.
The macro response Monte Carlo method for electron transport
Energy Technology Data Exchange (ETDEWEB)
Svatos, M M
1998-09-01
The main goal of this thesis was to prove the feasibility of basing electron depth dose calculations in a phantom on first-principles single scatter physics, in an amount of time that is equal to or better than current electron Monte Carlo methods. The Macro Response Monte Carlo (MRMC) method achieves run times that are on the order of conventional electron transport methods such as condensed history, with the potential to be much faster. This is possible because MRMC is a Local-to-Global method, meaning the problem is broken down into two separate transport calculations. The first stage is a local, in this case, single scatter calculation, which generates probability distribution functions (PDFs) to describe the electron's energy, position and trajectory after leaving the local geometry, a small sphere or "kugel" A number of local kugel calculations were run for calcium and carbon, creating a library of kugel data sets over a range of incident energies (0.25 MeV - 8 MeV) and sizes (0.025 cm to 0.1 cm in radius). The second transport stage is a global calculation, where steps that conform to the size of the kugels in the library are taken through the global geometry. For each step, the appropriate PDFs from the MRMC library are sampled to determine the electron's new energy, position and trajectory. The electron is immediately advanced to the end of the step and then chooses another kugel to sample, which continues until transport is completed. The MRMC global stepping code was benchmarked as a series of subroutines inside of the Peregrine Monte Carlo code. It was compared to Peregrine's class II condensed history electron transport package, EGS4, and MCNP for depth dose in simple phantoms having density inhomogeneities. Since the kugels completed in the library were of relatively small size, the zoning of the phantoms was scaled down from a clinical size, so that the energy deposition algorithms for spreading dose across 5-10 zones per kugel could
Radiative heat transfer by the Monte Carlo method
Hartnett †, James P; Cho, Young I; Greene, George A; Taniguchi, Hiroshi; Yang, Wen-Jei; Kudo, Kazuhiko
1995-01-01
This book presents the basic principles and applications of radiative heat transfer used in energy, space, and geo-environmental engineering, and can serve as a reference book for engineers and scientists in researchand development. A PC disk containing software for numerical analyses by the Monte Carlo method is included to provide hands-on practice in analyzing actual radiative heat transfer problems.Advances in Heat Transfer is designed to fill the information gap between regularly scheduled journals and university level textbooks by providing in-depth review articles over a broader scope than journals or texts usually allow.Key Features* Offers solution methods for integro-differential formulation to help avoid difficulties* Includes a computer disk for numerical analyses by PC* Discusses energy absorption by gas and scattering effects by particles* Treats non-gray radiative gases* Provides example problems for direct applications in energy, space, and geo-environmental engineering
Modelling a gamma irradiation process using the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Soares, Gabriela A.; Pereira, Marcio T., E-mail: gas@cdtn.br, E-mail: mtp@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2011-07-01
In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)
Multi-pass Monte Carlo simulation method in nuclear transmutations.
Mateescu, Liviu; Kadambi, N Prasad; Ravindra, Nuggehalli M
2016-12-01
Monte Carlo methods, in their direct brute simulation incarnation, bring realistic results if the involved probabilities, be they geometrical or otherwise, remain constant for the duration of the simulation. However, there are physical setups where the evolution of the simulation represents a modification of the simulated system itself. Chief among such evolving simulated systems are the activation/transmutation setups. That is, the simulation starts with a given set of probabilities, which are determined by the geometry of the system, the components and by the microscopic interaction cross-sections. However, the relative weight of the components of the system changes along with the steps of the simulation. A natural measure would be adjusting probabilities after every step of the simulation. On the other hand, the physical system has typically a number of components of the order of Avogadro's number, usually 10(25) or 10(26) members. A simulation step changes the characteristics for just a few of these members; a probability will therefore shift by a quantity of 1/10(25). Such a change cannot be accounted for within a simulation, because then the simulation should have then a number of at least 10(28) steps in order to have some significance. This is not feasible, of course. For our computing devices, a simulation of one million steps is comfortable, but a further order of magnitude becomes too big a stretch for the computing resources. We propose here a method of dealing with the changing probabilities, leading to the increasing of the precision. This method is intended as a fast approximating approach, and also as a simple introduction (for the benefit of students) in the very branched subject of Monte Carlo simulations vis-à-vis nuclear reactors.
New Monte Carlo method for the self-avoiding walk
Berretti, Alberto; Sokal, Alan D.
1985-08-01
We introduce a new Monte Carlo algorithm for the self-avoiding walk (SAW), and show that it is particularly efficient in the critical region (long chains). We also introduce new and more efficient statistical techniques. We employ these methods to extract numerical estimates for the critical parameters of the SAW on the square lattice. We find μ=2.63820 ± 0.00004 ± 0.00030 γ=1.352 ± 0.006 ± 0.025 νv=0.7590 ± 0.0062 ± 0.0042 where the first error bar represents systematic error due to corrections to scaling (subjective 95% confidence limits) and the second bar represents statistical error (classical 95% confidence limits). These results are based on SAWs of average length ≈ 166, using 340 hours CPU time on a CDC Cyber 170-730. We compare our results to previous work and indicate some directions for future research.
Particle acceleration at shocks - A Monte Carlo method
Kirk, J. G.; Schneider, P.
1987-01-01
A Monte Carlo method is presented for the problem of acceleration of test particles at relativistic shocks. The particles are assumed to diffuse in pitch angle as a result of scattering off magnetic irregularities frozen into the fluid. Several tests are performed using the analytic results available for both relativistic and nonrelativistic shock speeds. The acceleration at relativistic shocks under the influence of radiation losses is investigated, including the effects of a momentum dependence in the diffusion coefficient. The results demonstrate the usefulness of the technique in those situations in which the diffusion approximation cannot be employed, such as when relativistic bulk motion is considered, when particles are permitted to escape at the boundaries, and when the effects of the finite length of the particle mean free path are important.
Interacting multiagent systems kinetic equations and Monte Carlo methods
Pareschi, Lorenzo
2014-01-01
The description of emerging collective phenomena and self-organization in systems composed of large numbers of individuals has gained increasing interest from various research communities in biology, ecology, robotics and control theory, as well as sociology and economics. Applied mathematics is concerned with the construction, analysis and interpretation of mathematical models that can shed light on significant problems of the natural sciences as well as our daily lives. To this set of problems belongs the description of the collective behaviours of complex systems composed by a large enough number of individuals. Examples of such systems are interacting agents in a financial market, potential voters during political elections, or groups of animals with a tendency to flock or herd. Among other possible approaches, this book provides a step-by-step introduction to the mathematical modelling based on a mesoscopic description and the construction of efficient simulation algorithms by Monte Carlo methods. The ar...
On polarization parameters of spin-$1$ particles and anomalous couplings in $e^+e^-\\to ZZ/Z\\gamma$
Rahaman, Rafiqul
2016-01-01
We propose a complete set of asymmetries to construct the polarization density matrix for a massive spin-$1$ particle at colliders. We study their sensitivity to the anomalous trilinear gauge couplings of neutral gauge bosons in $e^+e^-\\to ZZ/Z\\gamma$ processes with unpolarized initial beams. We use these polarization asymmetries, along with the cross-section, to obtain a simultaneous limit on all the anomalous coupling using Markov Chain Monte Carlo (MCMC) method. For an $e^+e^-$ collider running at $500$ GeV center-of-mass energy and $100$ fb$^{-1}$ of integrated luminosity the simultaneous limits on the anomalous couplings are $1\\sim3\\times 10^{-3}$.
Search for $ZW/ZZ \\to \\ell^+ \\ell^-$ + Jets Production in $p\\bar{p}$ Collisions at CDF
Energy Technology Data Exchange (ETDEWEB)
Ketchum, Wesley Robert [Univ. of Chicago, IL (United States)
2012-12-01
The Standard Model of particle physics describes weak interactions mediated by massive gauge bosons that interact with each other in well-defined ways. Observations of the production and decay of WW, WZ, and ZZ boson pairs are an opportunity to check that these self-interactions agree with the Standard Model predictions. Furthermore, final states that include quarks are very similar to the most prominent final state of Higgs bosons produced in association with a W or Z boson. Diboson production where WW is a significant component has been observed at the Tevatron collider in semi-hadronic decay modes. We present a search for ZW and ZZ production in a final state containing two charged leptons and two jets using 8.9 fb^{-1} of data recorded with the CDF detector at the Tevatron. We select events by identifying those that contain two charged leptons, two hadronic jets, and low transverse missing energy (E_{T} ). We increase our acceptance by using a wide suite of high-p_{T} lepton triggers and by relaxing many lepton identification requirements. We develop a new method for calculating corrections to jet energies based on whether the originating parton was a quark or gluon to improve the agreement between data and the Monte Carlo simulations used to model our diboson signal and dominant backgrounds. We also make use of neural-network-based discriminants that are trained to pick out jets originating from b quarks and light-flavor quarks, thereby increasing our sensitivity to Z → b$\\bar{b}$ and W=Z → q$\\bar{p'}$0 decays, respectively. The number of signal events is extracted through a simultaneous fit to the dijet mass spectrum in three channels: a heavy-flavor tagged channel, a light-flavor tagged channel, and an untagged channel. We measure σ_{ZW/ZZ}= 2.5^{+2.0}_{ -1.0} pb, which is consistent with the SM cross section of 5.1 pb. We establish an upper limit on the cross section of σ_{ZW/ZZ} < 6.1 pb
Seriation in paleontological data using markov chain Monte Carlo methods.
Directory of Open Access Journals (Sweden)
Kai Puolamäki
2006-02-01
Full Text Available Given a collection of fossil sites with data about the taxa that occur in each site, the task in biochronology is to find good estimates for the ages or ordering of sites. We describe a full probabilistic model for fossil data. The parameters of the model are natural: the ordering of the sites, the origination and extinction times for each taxon, and the probabilities of different types of errors. We show that the posterior distributions of these parameters can be estimated reliably by using Markov chain Monte Carlo techniques. The posterior distributions of the model parameters can be used to answer many different questions about the data, including seriation (finding the best ordering of the sites and outlier detection. We demonstrate the usefulness of the model and estimation method on synthetic data and on real data on large late Cenozoic mammals. As an example, for the sites with large number of occurrences of common genera, our methods give orderings, whose correlation with geochronologic ages is 0.95.
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 ...
Monte-Carlo Method for Coalbed Methane Resource Assessment in Key Coal Mining Areas of China
Institute of Scientific and Technical Information of China (English)
Yang Yongguo; Chen Yuhua; Qin Yong; Cheng Qiuming
2008-01-01
Monte-Carlo method is used for estimating coalbed methane (CBM) resources in key coal mining areas of China. Monte-Carlo method is shown to be superior to the traditional volumetric method with constant parameters in the calculation of CBM resources. The focus of the article is to introduce the main algorithm and the realization of functions estimated by Monte-Carlo method, including selection of parameters, determination of distribution function, generation of pseudo-random numbers, and evaluation of the parameters corresponding to pseudo-random numbers. A specified software on the basis of Monte-Carlo method is developed using Visual C++ for the assessment of the CBM resources. A case study shows that calculation results using Monte-Carlo method have smaller error range in comparison with those using volumetric method.
Exact special twist method for quantum Monte Carlo simulations
Dagrada, Mario; Karakuzu, Seher; Vildosola, Verónica Laura; Casula, Michele; Sorella, Sandro
2016-12-01
We present a systematic investigation of the special twist method introduced by Rajagopal et al. [Phys. Rev. B 51, 10591 (1995), 10.1103/PhysRevB.51.10591] for reducing finite-size effects in correlated calculations of periodic extended systems with Coulomb interactions and Fermi statistics. We propose a procedure for finding special twist values which, at variance with previous applications of this method, reproduce the energy of the mean-field infinite-size limit solution within an adjustable (arbitrarily small) numerical error. This choice of the special twist is shown to be the most accurate single-twist solution for curing one-body finite-size effects in correlated calculations. For these reasons we dubbed our procedure "exact special twist" (EST). EST only needs a fully converged independent-particles or mean-field calculation within the primitive cell and a simple fit to find the special twist along a specific direction in the Brillouin zone. We first assess the performances of EST in a simple correlated model such as the three-dimensional electron gas. Afterwards, we test its efficiency within ab initio quantum Monte Carlo simulations of metallic elements of increasing complexity. We show that EST displays an overall good performance in reducing finite-size errors comparable to the widely used twist average technique but at a much lower computational cost since it involves the evaluation of just one wave function. We also demonstrate that the EST method shows similar performances in the calculation of correlation functions, such as the ionic forces for structural relaxation and the pair radial distribution function in liquid hydrogen. Our conclusions point to the usefulness of EST for correlated supercell calculations; our method will be particularly relevant when the physical problem under consideration requires large periodic cells.
Diffusion Monte Carlo methods applied to Hamaker Constant evaluations
Hongo, Kenta
2016-01-01
We applied diffusion Monte Carlo (DMC) methods to evaluate Hamaker constants of liquids for wettabilities, with practical size of a liquid molecule, Si$_6$H$_{12}$ (cyclohexasilane). The evaluated constant would be justified in the sense that it lies within the expected dependence on molecular weights among similar kinds of molecules, though there is no reference experimental values available for this molecule. Comparing the DMC with vdW-DFT evaluations, we clarified that some of the vdW-DFT evaluations could not describe correct asymptotic decays and hence Hamaker constants even though they gave reasonable binding lengths and energies, and vice versa for the rest of vdW-DFTs. We also found the advantage of DMC for this practical purpose over CCSD(T) because of the large amount of BSSE/CBS corrections required for the latter under the limitation of basis set size applicable to the practical size of a liquid molecule, while the former is free from such limitations to the extent that only the nodal structure of...
Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters
Energy Technology Data Exchange (ETDEWEB)
Owen, R.K.
1990-12-01
Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) (0.1981), 0.1895(9) (0.1874(4)), 0.1530(34) (0.1599(73)), 0.1664(37) (0.1724(110)), 0.1613(43) (0.1675(110)) Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) (0.0203(12)), 0.0188(10) (0.0220(21)), 0.0247(8) (0.0310(12)), 0.0253(8) (0.0351(8)) Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.
Quantum Monte Carlo methods and lithium cluster properties
Energy Technology Data Exchange (ETDEWEB)
Owen, R.K.
1990-12-01
Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) [0.1981], 0.1895(9) [0.1874(4)], 0.1530(34) [0.1599(73)], 0.1664(37) [0.1724(110)], 0.1613(43) [0.1675(110)] Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) [0.0203(12)], 0.0188(10) [0.0220(21)], 0.0247(8) [0.0310(12)], 0.0253(8) [0.0351(8)] Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.
Safety assessment of infrastructures using a new Bayesian Monte Carlo method
Rajabalinejad, M.; Demirbilek, Z.
2011-01-01
A recently developed Bayesian Monte Carlo (BMC) method and its application to safety assessment of structures are described in this paper. We use a one-dimensional BMC method that was proposed in 2009 by Rajabalinejad in order to develop a weighted logical dependence between successive Monte Carlo s
Kinetic Monte Carlo method applied to nucleic acid hairpin folding.
Sauerwine, Ben; Widom, Michael
2011-12-01
Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure, is advantageous for being able to access behavior at long time scales, even minutes or hours. Transition rates between coarse-grained states depend upon intermediate barriers, which are not directly simulated. We propose an Arrhenius rate model and an intermediate energy model that incorporates the effects of the barrier between simulated states without enlarging the state space itself. Applying our Arrhenius rate model to DNA hairpin folding, we demonstrate improved agreement with experiment compared to the usual kinetic Monte Carlo model. Further improvement results from including rigidity of single-stranded stacking.
The Monte Carlo Simulation Method for System Reliability and Risk Analysis
Zio, Enrico
2013-01-01
Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergra...
Jiang, Xu; Deng, Yong; Luo, Zhaoyang; Wang, Kan; Lian, Lichao; Yang, Xiaoquan; Meglinski, Igor; Luo, Qingming
2014-12-29
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.
A survey of sequential Monte Carlo methods for economics and finance
Creal, D.D.
2009-01-01
This paper serves as an introduction and survey for economists to the field of sequential Monte Carlo methods which are also known as particle filters. Sequential Monte Carlo methods are simulation based algorithms used to compute the high-dimensional and/or complex integrals that arise regularly in applied work. These methods are becoming increasingly popular in economics and finance; from dynamic stochastic general equilibrium models in macro-economics to option pricing. The objective of th...
Quasi-Monte Carlo methods for lattice systems: a first look
Jansen, K; Nube, A; Griewank, A; Müller-Preussker, M
2013-01-01
We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like 1/Sqrt(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 up to 1/N. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
Firstenberg, H.
1971-01-01
The statistics are considered of the Monte Carlo method relative to the interpretation of the NUGAM2 and NUGAM3 computer code results. A numerical experiment using the NUGAM2 code is presented and the results are statistically interpreted.
Introducing Monte Carlo Methods with R Solutions to Odd-Numbered Exercises
Robert, Christian P.; Casella, George
2010-01-01
This is the solution manual to the odd-numbered exercises in our book "Introducing Monte Carlo Methods with R", published by Springer Verlag on December 10, 2009, and made freely available to everyone.
Directory of Open Access Journals (Sweden)
José Luiz Ferreira Martins
2011-09-01
Full Text Available O objetivo deste artigo é o de analisar a viabilidade da utilização do método de Monte Carlo para estimar a produtividade na soldagem de tubulações industriais de aço carbono com base em amostras pequenas. O estudo foi realizado através de uma análise de uma amostra de referência contendo dados de produtividade de 160 juntas soldadas pelo processo Eletrodo Revestido na REDUC (refinaria de Duque de Caxias, utilizando o software ControlTub 5.3. A partir desses dados foram retiradas de forma aleatória, amostras com, respectivamente, 10, 15 e 20 elementos e executadas simulações pelo método de Monte Carlo. Comparando-se os resultados da amostra com 160 elementos e os dados gerados por simulação se observa que bons resultados podem ser obtidos usando o método de Monte Carlo para estimativa da produtividade da soldagem. Por outro lado, na indústria da construção brasileira o valor da média de produtividade é normalmente usado como um indicador de produtividade e é baseado em dados históricos de outros projetos coletados e avaliados somente após a conclusão do projeto, o que é uma limitação. Este artigo apresenta uma ferramenta para avaliação da execução em tempo real, permitindo ajustes nas estimativas e monitoramento de produtividade durante o empreendimento. Da mesma forma, em licitações, orçamentos e estimativas de prazo, a utilização desta técnica permite a adoção de outras estimativas diferentes da produtividade média, que é comumente usada e como alternativa, se sugerem três critérios: produtividade otimista, média e pessimista.The aim of this article is to analyze the feasibility of using Monte Carlo method to estimate productivity in industrial pipes welding of carbon steel based on small samples. The study was carried out through an analysis of a reference sample containing productivity data of 160 welded joints by SMAW process in REDUC (Duque de Caxias Refinery, using ControlTub 5.3 software
Monte Carlo Criticality Methods and Analysis Capabilities in SCALE
Energy Technology Data Exchange (ETDEWEB)
Goluoglu, Sedat [ORNL; Petrie Jr, Lester M [ORNL; Dunn, Michael E [ORNL; Hollenbach, Daniel F [ORNL; Rearden, Bradley T [ORNL
2011-01-01
This paper describes the Monte Carlo codes KENO V.a and KENO-VI in SCALE that are primarily used to calculate multiplication factors and flux distributions of fissile systems. Both codes allow explicit geometric representation of the target systems and are used internationally for safety analyses involving fissile materials. KENO V.a has limiting geometric rules such as no intersections and no rotations. These limitations make KENO V.a execute very efficiently and run very fast. On the other hand, KENO-VI allows very complex geometric modeling. Both KENO codes can utilize either continuous-energy or multigroup cross-section data and have been thoroughly verified and validated with ENDF libraries through ENDF/B-VII.0, which has been first distributed with SCALE 6. Development of the Monte Carlo solution technique and solution methodology as applied in both KENO codes is explained in this paper. Available options and proper application of the options and techniques are also discussed. Finally, performance of the codes is demonstrated using published benchmark problems.
Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement.
Siswantoro, Joko; Prabuwono, Anton Satria; Abdullah, Azizi; Idrus, Bahari
2014-01-01
Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
MCHITS: Monte Carlo based Method for Hyperlink Induced Topic Search on Networks
Directory of Open Access Journals (Sweden)
Zhaoyan Jin
2013-10-01
Full Text Available Hyperlink Induced Topic Search (HITS is the most authoritative and most widely used personalized ranking algorithm on networks. The HITS algorithm ranks nodes on networks according to power iteration, and has high complexity of computation. This paper models the HITS algorithm with the Monte Carlo method, and proposes Monte Carlo based algorithms for the HITS computation. Theoretical analysis and experiments show that the Monte Carlo based approximate computing of the HITS ranking reduces computing resources a lot while keeping higher accuracy, and is significantly better than related works
B-splines smoothed rejection sampling method and its applications in quasi-Monte Carlo integration
Institute of Scientific and Technical Information of China (English)
雷桂媛
2002-01-01
The rejection sampling method is one of the most popular methods used in Monte Carlo methods. It turns out that the standard rejection method is closely related to the problem of quasi-Monte Carlo integration of characteristic functions, whose accuracy may be lost due to the discontinuity of the characteristic functions. We proposed a B-splines smoothed rejection sampling method, which smoothed the characteristic function by B-splines smoothing technique without changing the integral quantity. Numerical experiments showed that the convergence rate of nearly O(N-1) is regained by using the B-splines smoothed rejection method in importance sampling.
B-splines smoothed rejection sampling method and its applications in quasi-Monte Carlo integration
Institute of Scientific and Technical Information of China (English)
雷桂媛
2002-01-01
The rejection sampling method is one of the most popular methods used in Monte Carlo methods. It turns out that the standard rejection method is closely related to the problem of quasi-Monte Carlo integration of characteristic functions, whose accuracy may be lost due to the discontinuity of the characteristic functions. We proposed a B-splines smoothed rejection sampling method, which smoothed the characteristic function by B-splines smoothing technique without changing the integral quantity. Numerical experiments showed that the convergence rate of nearly O( N-1 ) is regained by using the B-splines smoothed rejection method in importance sampling.
Reliability analysis of tunnel surrounding rock stability by Monte-Carlo method
Institute of Scientific and Technical Information of China (English)
XI Jia-mi; YANG Geng-she
2008-01-01
Discussed advantages of improved Monte-Carlo method and feasibility aboutproposed approach applying in reliability analysis for tunnel surrounding rock stability. Onthe basis of deterministic parsing for tunnel surrounding rock, reliability computing methodof surrounding rock stability was derived from improved Monte-Carlo method. The com-puting method considered random of related parameters, and therefore satisfies relativityamong parameters. The proposed method can reasonably determine reliability of sur-rounding rock stability. Calculation results show that this method is a scientific method indiscriminating and checking surrounding rock stability.
Elhatisari, Serdar; Lee, Dean
2014-12-01
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.
Fermion-Dimer Scattering using Impurity Lattice Monte Carlo and the Adiabatic Projection Method
Elhatisari, Serdar
2014-01-01
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 L\\"uscher'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.
Criticality accident detector coverage analysis using the Monte Carlo Method
Energy Technology Data Exchange (ETDEWEB)
Zino, J.F.; Okafor, K.C.
1993-12-31
As a result of the need for a more accurate computational methodology, the Los Alamos developed Monte Carlo code MCNP is used to show the implementation of a more advanced and accurate methodology in criticality accident detector analysis. This paper will detail the application of MCNP for the analysis of the areas of coverage of a criticality accident alarm detector located inside a concrete storage vault at the Savannah River Site. The paper will discuss; (1) the generation of fixed-source representations of various criticality fission sources (for spherical geometries); (2) the normalization of these sources to the ``minimum criticality of concern`` as defined by ANS 8.3; (3) the optimization process used to determine which source produces the lowest total detector response for a given set of conditions; and (4) the use of this minimum source for the analysis of the areas of coverage of the criticality accident alarm detector.
Bold diagrammatic Monte Carlo method applied to fermionized frustrated spins.
Kulagin, S A; Prokof'ev, N; Starykh, O A; Svistunov, B; Varney, C N
2013-02-15
We demonstrate, by considering the triangular lattice spin-1/2 Heisenberg model, that Monte Carlo sampling of skeleton Feynman diagrams within the fermionization framework offers a universal first-principles tool for strongly correlated lattice quantum systems. We observe the fermionic sign blessing--cancellation of higher order diagrams leading to a finite convergence radius of the series. We calculate the magnetic susceptibility of the triangular-lattice quantum antiferromagnet in the correlated paramagnet regime and reveal a surprisingly accurate microscopic correspondence with its classical counterpart at all accessible temperatures. The extrapolation of the observed relation to zero temperature suggests the absence of the magnetic order in the ground state. We critically examine the implications of this unusual scenario.
Bakshi, A K; Chatterjee, S; Palani Selvam, T; Dhabekar, B S
2010-07-01
In the present study, the energy dependence of response of some popular thermoluminescent dosemeters (TLDs) have been investigated such as LiF:Mg,Ti, LiF:Mg,Cu,P and CaSO(4):Dy to synchrotron radiation in the energy range of 10-34 keV. The study utilised experimental, Monte Carlo and analytical methods. The Monte Carlo calculations were based on the EGSnrc and FLUKA codes. The calculated energy response of all the TLDs using the EGSnrc and FLUKA codes shows excellent agreement with each other. The analytically calculated response shows good agreement with the Monte Carlo calculated response in the low-energy region. In the case of CaSO(4):Dy, the Monte Carlo-calculated energy response is smaller by a factor of 3 at all energies in comparison with the experimental response when polytetrafluoroethylene (PTFE) (75 % by wt) is included in the Monte Carlo calculations. When PTFE is ignored in the Monte Carlo calculations, the difference between the calculated and experimental response decreases (both responses are comparable >25 keV). For the LiF-based TLDs, the Monte Carlo-based response shows reasonable agreement with the experimental response.
Radiation shielding design for neutron diffractometers assisted by Monte Carlo methods
Osborn, John C.; Ersez, Tunay; Braoudakis, George
2006-11-01
Monte Carlo simulations may be used to model radiation shielding for neutron diffractometers. The use of the MCNP computer program to assess shielding for a diffractometer is discussed. A comparison is made of shielding requirements for radiation generated by several materials commonly used in neutron optical elements and beam stops, including lithium-6 based absorbers where the Monte Carlo method can model the effects of fast neutrons generated by this material.
Equivalence of four Monte Carlo methods for photon migration in turbid media.
Sassaroli, Angelo; Martelli, Fabrizio
2012-10-01
In the field of photon migration in turbid media, different Monte Carlo methods are usually employed to solve the radiative transfer equation. We consider four different Monte Carlo methods, widely used in the field of tissue optics, that are based on four different ways to build photons' trajectories. We provide both theoretical arguments and numerical results showing the statistical equivalence of the four methods. In the numerical results we compare the temporal point spread functions calculated by the four methods for a wide range of the optical properties in the slab and semi-infinite medium geometry. The convergence of the methods is also briefly discussed.
Prediction of Protein-DNA binding by Monte Carlo method
Deng, Yuefan; Eisenberg, Moises; Korobka, Alex
1997-08-01
We present an analysis and prediction of protein-DNA binding specificity based on the hydrogen bonding between DNA, protein, and auxillary clusters of water molecules. Zif268, glucocorticoid receptor, λ-repressor mutant, HIN-recombinase, and tramtrack protein-DNA complexes are studied. Hydrogen bonds are approximated by the Lennard-Jones potential with a cutoff distance between the hydrogen and the acceptor atoms set to 3.2 Åand an angular component based on a dipole-dipole interaction. We use a three-stage docking algorithm: geometric hashing that matches pairs of hydrogen bonding sites; (2) least-squares minimization of pairwise distances to filter out insignificant matches; and (3) Monte Carlo stochastic search to minimize the energy of the system. More information can be obtained from our first paper on this subject [Y.Deng et all, J.Computational Chemistry (1995)]. Results show that the biologically correct base pair is selected preferentially when there are two or more strong hydrogen bonds (with LJ potential lower than -0.20) that bind it to the protein. Predicted sequences are less stable in the case of weaker bonding sites. In general the inclusion of water bridges does increase the number of base pairs for which correct specificity is predicted.
Application of advanced Monte Carlo Methods in numerical dosimetry.
Reichelt, U; Henniger, J; Lange, C
2006-01-01
Many tasks in different sectors of dosimetry are very complex and highly sensitive to changes in the radiation field. Often, only the simulation of radiation transport is capable of describing the radiation field completely. Down to sub-cellular dimensions the energy deposition by cascades of secondary electrons is the main pathway for damage induction in matter. A large number of interactions take place until such electrons are slowed down to thermal energies. Also for some problems of photon transport a large number of photon histories need to be processed. Thus the efficient non-analogue Monte Carlo program, AMOS, has been developed for photon and electron transport. Various applications and benchmarks are presented showing its ability. For radiotherapy purposes the radiation field of a brachytherapy source is calculated according to the American Association of Physicists in Medicine Task Group Report 43 (AAPM/TG43). As additional examples, results for the detector efficiency of a high-purity germanium (HPGe) detector and a dose estimation for an X-ray shielding for radiation protection are shown.
Energy Technology Data Exchange (ETDEWEB)
Morillon, B.
1996-12-31
With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.
Radiation Transport for Explosive Outflows: A Multigroup Hybrid Monte Carlo Method
Wollaeger, Ryan T; Graziani, Carlo; Couch, Sean M; Jordan, George C; Lamb, Donald Q; Moses, Gregory A
2013-01-01
We explore the application of Implicit Monte Carlo (IMC) and Discrete Diffusion Monte Carlo (DDMC) to radiation transport in strong fluid outflows with structured opacity. The IMC method of Fleck & Cummings is a stochastic computational technique for nonlinear radiation transport. IMC is partially implicit in time and may suffer in efficiency when tracking Monte Carlo particles through optically thick materials. The DDMC method of Densmore accelerates an IMC computation where the domain is diffusive. Recently, Abdikamalov extended IMC and DDMC to multigroup, velocity-dependent neutrino transport with the intent of modeling neutrino dynamics in core-collapse supernovae. Densmore has also formulated a multifrequency extension to the originally grey DDMC method. In this article we rigorously formulate IMC and DDMC over a high-velocity Lagrangian grid for possible application to photon transport in the post-explosion phase of Type Ia supernovae. The method described is suitable for a large variety of non-mono...
New simpler method of matching NLO corrections with parton shower Monte Carlo
Jadach, S; Sapeta, S; Siodmok, A; Skrzypek, M
2016-01-01
Next steps in development of the KrkNLO method of implementing NLO QCD corrections to hard processes in parton shower Monte Carlo programs are presented. This new method is a simpler alternative to other well-known approaches, such as MC@NLO and POWHEG. The KrkNLO method owns its simplicity to the use of parton distribution functions (PDFs) in a new, so-called Monte Carlo (MC), factorization scheme which was recently fully defined for the first time. Preliminary numerical results for the Higgs-boson production process are also presented.
Sampling uncertainty evaluation for data acquisition board based on Monte Carlo method
Ge, Leyi; Wang, Zhongyu
2008-10-01
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.
Accuracy Analysis for 6-DOF PKM with Sobol Sequence Based Quasi Monte Carlo Method
Institute of Scientific and Technical Information of China (English)
Jianguang Li; Jian Ding; Lijie Guo; Yingxue Yao; Zhaohong Yi; Huaijing Jing; Honggen Fang
2015-01-01
To improve the precisions of pose error analysis for 6⁃dof parallel kinematic mechanism ( PKM) during assembly quality control, a Sobol sequence based on Quasi Monte Carlo ( QMC) method is introduced and implemented in pose accuracy analysis for the PKM in this paper. The Sobol sequence based on Quasi Monte Carlo with the regularity and uniformity of samples in high dimensions, can prevail traditional Monte Carlo method with up to 98�59% and 98�25% enhancement for computational precision of pose error statistics. Then a PKM tolerance design system integrating this method is developed and with it pose error distributions of the PKM within a prescribed workspace are finally obtained and analyzed.
Monte Carlo Radiation Hydrodynamics: Methods, Tests and Application to Supernova Type Ia Ejecta
Noebauer, U M; Kromer, M; Röpke, F K; Hillebrandt, W
2012-01-01
In astrophysical systems, radiation-matter interactions are important in transferring energy and momentum between the radiation field and the surrounding material. This coupling often makes it necessary to consider the role of radiation when modelling the dynamics of astrophysical fluids. During the last few years, there have been rapid developments in the use of Monte Carlo methods for numerical radiative transfer simulations. Here, we present an approach to radiation hydrodynamics that is based on coupling Monte Carlo radiative transfer techniques with finite-volume hydrodynamical methods in an operator-split manner. In particular, we adopt an indivisible packet formalism to discretize the radiation field into an ensemble of Monte Carlo packets and employ volume-based estimators to reconstruct the radiation field characteristics. In this paper the numerical tools of this method are presented and their accuracy is verified in a series of test calculations. Finally, as a practical example, we use our approach...
Energy Technology Data Exchange (ETDEWEB)
Bredenstein, A.
2006-05-08
In this work we provide precision calculations for the processes {gamma}{gamma} {yields} 4 fermions and H {yields} WW/ZZ {yields} 4 fermions. At a {gamma}{gamma} collider precise theoretical predictions are needed for the {gamma}{gamma} {yields} WW {yields} 4f processes because of their large cross section. These processes allow a measurement of the gauge-boson couplings {gamma}WW and {gamma}{gamma}WW. Furthermore, the reaction {gamma}{gamma} {yields} H {yields} WW/ZZ {yields} 4f arises through loops of virtual charged, massive particles. Thus, the coupling {gamma}{gamma}H can be measured and Higgs bosons with a relatively large mass could be produced. For masses M{sub H} >or(sim) 135 GeV the Higgs boson predominantly decays into W- or Z-boson pairs and subsequently into four leptons. The kinematical reconstruction of these decays is influenced by quantum corrections, especially real photon radiation. Since off-shell effects of the gauge bosons have to be taken into account below M{sub H} {approx} 2M{sub W/Z}, the inclusion of the decays of the gauge bosons is important. In addition, the spin and the CP properties of the Higgs boson can be determined by considering angular and energy distributions of the decay fermions. For a comparison of theoretical predictions with experimental data Monte Carlo generators are useful tools. We construct such programs for the processes {gamma}{gamma} {yields} WW {yields} 4f and H {yields} WW/ZZ {yields} 4f. On the one hand, they provide the complete predictions at lowest order of perturbation theory. On the other hand, they contain quantum corrections, which ca be classified into real corrections, connected with photons bremsstrahlung, and virtual corrections. Whereas the virtual quantum corrections to {gamma}{gamma} {yields} WW {yields} 4f are calculated in the double-pole approximation, i.e. only doubly-resonant contributions are taken into account, we calculate the complete O({alpha}) corrections for the H {yields} WW/ZZ
Metric conjoint segmentation methods : A Monte Carlo comparison
Vriens, M; Wedel, M; Wilms, T
1996-01-01
The authors compare nine metric conjoint segmentation methods. Four methods concern two-stage procedures in which the estimation of conjoint models and the partitioning of the sample are performed separately; in five, the estimation and segmentation stages are integrated. The methods are compared co
A Monte Carlo Study of Eight Confidence Interval Methods for Coefficient Alpha
Romano, Jeanine L.; Kromrey, Jeffrey D.; Hibbard, Susan T.
2010-01-01
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…
Energy-Driven Kinetic Monte Carlo Method and Its Application in Fullerene Coalescence.
Ding, Feng; Yakobson, Boris I
2014-09-04
Mimicking the conventional barrier-based kinetic Monte Carlo simulation, an energy-driven kinetic Monte Carlo (EDKMC) method was developed to study the structural transformation of carbon nanomaterials. The new method is many orders magnitude faster than standard molecular dynamics or Monte Marlo (MC) simulations and thus allows us to explore rare events within a reasonable computational time. As an example, the temperature dependence of fullerene coalescence was studied. The simulation, for the first time, revealed that short capped single-walled carbon nanotubes (SWNTs) appear as low-energy metastable structures during the structural evolution.
Comparison of uncertainty in fatigue tests obtained by the Monte Carlo method in two softwares
Trevisan, Lisiane; Kapper Fabricio, Daniel Antonio; Reguly, Afonso
2016-07-01
The Supplement 1 to the “Guide to the expression of uncertainty in measurement” indicates the Monte Carlo method for calculating the expanded measurement uncertainty. The objective of this work is to compare the measurement uncertainty values obtained via Monte Carlo method through two commercial softwares (Matlab® and Crystal Ball®) for the parameter ‘adjusted strain’, obtained from fatigue tests. Simulations were carried out using different number of iterations and different levels of confidence. The results showed that there are short differences between the measurement uncertainty values generated by different software.
Quasi-Monte Carlo methods for lattice systems. A first look
Energy Technology Data Exchange (ETDEWEB)
Jansen, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Cyprus Univ., Nicosia (Cyprus). Dept. of Physics; Leovey, H.; Griewank, A. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Mathematik; Nube, A. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik; Mueller-Preussker, M. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Physik
2013-02-15
We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N{sup -1/2}, where N is the number of observations. By means of Quasi-Monte Carlo methods it is possible to improve this behavior for certain problems up to N{sup -1}. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling.
Quantum-trajectory Monte Carlo method for study of electron-crystal interaction in STEM.
Ruan, Z; Zeng, R G; Ming, Y; Zhang, M; Da, B; Mao, S F; Ding, Z J
2015-07-21
In this paper, a novel quantum-trajectory Monte Carlo simulation method is developed to study electron beam interaction with a crystalline solid for application to electron microscopy and spectroscopy. The method combines the Bohmian quantum trajectory method, which treats electron elastic scattering and diffraction in a crystal, with a Monte Carlo sampling of electron inelastic scattering events along quantum trajectory paths. We study in this work the electron scattering and secondary electron generation process in crystals for a focused incident electron beam, leading to understanding of the imaging mechanism behind the atomic resolution secondary electron image that has been recently achieved in experiment with a scanning transmission electron microscope. According to this method, the Bohmian quantum trajectories have been calculated at first through a wave function obtained via a numerical solution of the time-dependent Schrödinger equation with a multislice method. The impact parameter-dependent inner-shell excitation cross section then enables the Monte Carlo sampling of ionization events produced by incident electron trajectories travelling along atom columns for excitation of high energy knock-on secondary electrons. Following cascade production, transportation and emission processes of true secondary electrons of very low energies are traced by a conventional Monte Carlo simulation method to present image signals. Comparison of the simulated image for a Si(110) crystal with the experimental image indicates that the dominant mechanism of atomic resolution of secondary electron image is the inner-shell ionization events generated by a high-energy electron beam.
Markov chain Monte Carlo methods in directed graphical models
DEFF Research Database (Denmark)
Højbjerre, Malene
Directed graphical models present data possessing a complex dependence structure, and MCMC methods are computer-intensive simulation techniques to approximate high-dimensional intractable integrals, which emerge in such models with incomplete data. MCMC computations in directed graphical models...
Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources
Bie, Pei; Zhang, Buhan; Li, Hang; Deng, Weisi; Wu, Jiasi
2017-01-01
Probabilistic Power Flow (PPF) is a very useful tool for power system steady-state analysis. However, the correlation among different random injection power (like wind power) brings great difficulties to calculate PPF. Monte Carlo simulation (MCS) and analytical methods are two commonly used methods to solve PPF. MCS has high accuracy but is very time consuming. Analytical method like cumulants method (CM) has high computing efficiency but the cumulants calculating is not convenient when wind power output does not obey any typical distribution, especially when correlated wind sources are considered. In this paper, an Improved Monte Carlo simulation method (IMCS) is proposed. The joint empirical distribution is applied to model different wind power output. This method combines the advantages of both MCS and analytical method. It not only has high computing efficiency, but also can provide solutions with enough accuracy, which is very suitable for on-line analysis.
Power Analysis for Complex Mediational Designs Using Monte Carlo Methods
Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.
2010-01-01
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…
DEFF Research Database (Denmark)
Hey, Jody; Nielsen, Rasmus
2007-01-01
Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint......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...
Kumar, Sudhir; Srinivasan, P; Sharma, S D
2010-06-01
A cylindrical graphite ionization chamber of sensitive volume 1002.4 cm(3) was designed and fabricated at Bhabha Atomic Research Centre (BARC) for use as a reference dosimeter to measure the strength of high dose rate (HDR) (192)Ir brachytherapy sources. The air kerma calibration coefficient (N(K)) of this ionization chamber was estimated analytically using Burlin general cavity theory and by the Monte Carlo method. In the analytical method, calibration coefficients were calculated for each spectral line of an HDR (192)Ir source and the weighted mean was taken as N(K). In the Monte Carlo method, the geometry of the measurement setup and physics related input data of the HDR (192)Ir source and the surrounding material were simulated using the Monte Carlo N-particle code. The total photon energy fluence was used to arrive at the reference air kerma rate (RAKR) using mass energy absorption coefficients. The energy deposition rates were used to simulate the value of charge rate in the ionization chamber and N(K) was determined. The Monte Carlo calculated N(K) agreed within 1.77 % of that obtained using the analytical method. The experimentally determined RAKR of HDR (192)Ir sources, using this reference ionization chamber by applying the analytically estimated N(K), was found to be in agreement with the vendor quoted RAKR within 1.43%.
Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water
Gergely, John Robert
2009-01-01
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"…
The information-based complexity of approximation problem by adaptive Monte Carlo methods
Institute of Scientific and Technical Information of China (English)
2008-01-01
In this paper, we study the complexity of information of approximation problem on the multivariate Sobolev space with bounded mixed derivative MWpr,α(Td), 1 < p < ∞, in the norm of Lq(Td), 1 < q < ∞, by adaptive Monte Carlo methods. Applying the discretization technique and some properties of pseudo-s-scale, we determine the exact asymptotic orders of this problem.
Kim, Jee-Seon; Bolt, Daniel M.
2007-01-01
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…
Dumenci, Levent; Windle, Michael
2001-01-01
Used Monte Carlo methods to evaluate the adequacy of cluster analysis to recover group membership based on simulated latent growth curve (LCG) models. Cluster analysis failed to recover growth subtypes adequately when the difference between growth curves was shape only. Discusses circumstances under which it was more successful. (SLD)
The Monte Carlo Method and the Evaluation of Retrieval System Performance.
Burgin, Robert
1999-01-01
Introduces the Monte Carlo method which is shown to represent an attractive alternative to the hypergeometric model for identifying the levels at which random retrieval performance is exceeded in retrieval test collections and for overcoming some of the limitations of the hypergeometric model. Practical matters to consider when employing the Monte…
Ground bounce tracking for landmine detection using a sequential Monte Carlo method
Tang, Li; Torrione, Peter A.; Eldeniz, Cihat; Collins, Leslie M.
2007-04-01
A Sequential Monte Carlo (SMC) method is proposed to locate the ground bounce (GB) positions in 3D data collected by ground penetrating radar (GPR) system. The algorithm is verified utilizing real data and improved landmine detection performance is achieved compared with three other GB trackers.
Lee, Anthony; Yau, Christopher; Giles, Michael B; Doucet, Arnaud; Holmes, Christopher C
2010-12-01
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.
An Evaluation of a Markov Chain Monte Carlo Method for the Rasch Model.
Kim, Seock-Ho
2001-01-01
Examined the accuracy of the Gibbs sampling Markov chain Monte Carlo procedure for estimating item and person (theta) parameters in the one-parameter logistic model. Analyzed four empirical datasets using the Gibbs sampling, conditional maximum likelihood, marginal maximum likelihood, and joint maximum likelihood methods. Discusses the conditions…
A variance-reduced electrothermal Monte Carlo method for semiconductor device simulation
Energy Technology Data Exchange (ETDEWEB)
Muscato, Orazio; Di Stefano, Vincenza [Univ. degli Studi di Catania (Italy). Dipt. di Matematica e Informatica; Wagner, Wolfgang [Weierstrass-Institut fuer Angewandte Analysis und Stochastik (WIAS) Leibniz-Institut im Forschungsverbund Berlin e.V., Berlin (Germany)
2012-11-01
This paper is concerned with electron transport and heat generation in semiconductor devices. An improved version of the electrothermal Monte Carlo method is presented. This modification has better approximation properties due to reduced statistical fluctuations. The corresponding transport equations are provided and results of numerical experiments are presented.
Sequential Monte Carlo methods for nonlinear discrete-time filtering
Bruno, Marcelo GS
2013-01-01
In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable.We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in line
Monte-Carlo methods make Dempster-Shafer formalism feasible
Kreinovich, Vladik YA.; Bernat, Andrew; Borrett, Walter; Mariscal, Yvonne; Villa, Elsa
1991-01-01
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.
MONTE CARLO METHOD AND APPLICATION IN @RISK SIMULATION SYSTEM
Directory of Open Access Journals (Sweden)
Gabriela Ižaríková
2015-12-01
Full Text Available The article is an example of using the software simulation @Risk designed for simulation in Microsoft Excel spread sheet, demonstrated the possibility of its usage in order to show a universal method of solving problems. The simulation is experimenting with computer models based on the real production process in order to optimize the production processes or the system. The simulation model allows performing a number of experiments, analysing them, evaluating, optimizing and afterwards applying the results to the real system. A simulation model in general is presenting modelling system by using mathematical formulations and logical relations. In the model is possible to distinguish controlled inputs (for instance investment costs and random outputs (for instance demand, which are by using a model transformed into outputs (for instance mean value of profit. In case of a simulation experiment at the beginning are chosen controlled inputs and random (stochastic outputs are generated randomly. Simulations belong into quantitative tools, which can be used as a support for a decision making.
A measurement of the $ZZ \\rightarrow \\ell^{-}\\ell^{+}\
AUTHOR|(INSPIRE)INSPIRE-00236623
This thesis presents a measurement of the $ZZ$ diboson production cross section using the dataset from proton-proton collisions at $\\sqrt{s} = 8$ TeV collected in 2012 by the ATLAS experiment at the Large Hadron Collider at CERN, corresponding to a total integrated luminosity of $20.3$ fb$^{-1}$. The ATLAS detector and its component subsystems are described, with particular focus on the subsystems which have the largest impact on the analysis. Events are selected by requiring one pair of opposite-sign, same-flavour leptons and large missing transverse momentum, consistent with on-shell $ZZ$ production. Two separate measurements of the $pp \\rightarrow ZZ$ cross section are made, first in a restricted ("fiducial") phase space in each of the decay modes $ZZ \\rightarrow e^{-}e^{+}\
In silico prediction of the β-cyclodextrin complexation based on Monte Carlo method.
Veselinović, Aleksandar M; Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M
2015-11-10
In this study QSPR models were developed to predict the complexation of structurally diverse compounds with β-cyclodextrin based on SMILES notation optimal descriptors using Monte Carlo method. The predictive potential of the applied approach was tested with three random splits into the sub-training, calibration, test and validation sets and with different statistical methods. Obtained results demonstrate that Monte Carlo method based modeling is a very promising computational method in the QSPR studies for predicting the complexation of structurally diverse compounds with β-cyclodextrin. The SMILES attributes (structural features both local and global), defined as molecular fragments, which are promoters of the increase/decrease of molecular binding constants were identified. These structural features were correlated to the complexation process and their identification helped to improve the understanding for the complexation mechanisms of the host molecules.
Searching therapeutic agents for treatment of Alzheimer disease using the Monte Carlo method.
Toropova, Mariya A; Toropov, Andrey A; Raška, Ivan; Rašková, Mária
2015-09-01
Quantitative structure - activity relationships (QSARs) for the pIC50 (binding affinity) of gamma-secretase inhibitors can be constructed with the Monte Carlo method using CORAL software (http://www.insilico.eu/coral). The considerable influence of the presence of rings of various types with respect to the above endpoint has been detected. The mechanistic interpretation and the domain of applicability of the QSARs are discussed. Methods to select new potential gamma-secretase inhibitors are suggested.
Nguyen, Jennifer; Hayakawa, Carole K; Mourant, Judith R; Venugopalan, Vasan; Spanier, Jerome
2016-05-01
We present a polarization-sensitive, transport-rigorous perturbation Monte Carlo (pMC) method to model the impact of optical property changes on reflectance measurements within a discrete particle scattering model. The model consists of three log-normally distributed populations of Mie scatterers that approximate biologically relevant cervical tissue properties. Our method provides reflectance estimates for perturbations across wavelength and/or scattering model parameters. We test our pMC model performance by perturbing across number densities and mean particle radii, and compare pMC reflectance estimates with those obtained from conventional Monte Carlo simulations. These tests allow us to explore different factors that control pMC performance and to evaluate the gains in computational efficiency that our pMC method provides.
Study of dipole moments of LiSr and KRb molecules by quantum Monte Carlo methods
Guo, Shi; Mitas, Lubos; Reynolds, Peter J
2013-01-01
Heteronuclear dimers are of significant interest to experiments seeking to exploit ultracold polar molecules in a number of novel ways including precision measurement, quantum computing, and quantum simulation. We calculate highly accurate Born-Oppenheimer total energies and electric dipole moments as a function of internuclear separation for two such dimers, LiSr and KRb. We apply fully-correlated, high-accuracy quantum Monte Carlo methods for evaluating these molecular properties in a many-body framework. We use small-core effective potentials combined with multi-reference Slater-Jastrow trial wave functions to provide accurate nodes for the fixed-node diffusion Monte Carlo method. For reference and comparison, we calculate the same properties with Hartree-Fock and with restricted Configuration Interaction methods, and carefully assess the impact of the recovered many-body correlations on the calculated quantities.
Estimation of magnetocaloric properties by using Monte Carlo method for AMRR cycle
Arai, R.; Tamura, R.; Fukuda, H.; Li, J.; Saito, A. T.; Kaji, S.; Nakagome, H.; Numazawa, T.
2015-12-01
In order to achieve a wide refrigerating temperature range in magnetic refrigeration, it is effective to layer multiple materials with different Curie temperatures. It is crucial to have a detailed understanding of physical properties of materials to optimize the material selection and the layered structure. In the present study, we discuss methods for estimating a change in physical properties, particularly the Curie temperature when some of the Gd atoms are substituted for non-magnetic elements for material design, based on Gd as a ferromagnetic material which is a typical magnetocaloric material. For this purpose, whilst making calculations using the S=7/2 Ising model and the Monte Carlo method, we made a specific heat measurement and a magnetization measurement of Gd-R alloy (R = Y, Zr) to compare experimental values and calculated ones. The results showed that the magnetic entropy change, specific heat, and Curie temperature can be estimated with good accuracy using the Monte Carlo method.
Search for non-standard model signatures in the WZ/ZZ final state at CDF run II
Energy Technology Data Exchange (ETDEWEB)
Norman, Matthew [Univ. of California, San Diego, CA (United States)
2009-01-01
This thesis discusses a search for non-Standard Model physics in heavy diboson production in the dilepton-dijet final state, using 1.9 fb ^{-1} of data from the CDF Run II detector. New limits are set on the anomalous coupling parameters for ZZ and WZ production based on limiting the production cross-section at high š. Additionally limits are set on the direct decay of new physics to ZZ andWZ diboson pairs. The nature and parameters of the CDF Run II detector are discussed, as are the influences that it has on the methods of our analysis.
Monte Carlo method of radiative transfer applied to a turbulent flame modeling with LES
Zhang, Jin; Gicquel, Olivier; Veynante, Denis; Taine, Jean
2009-06-01
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).
Non-Standard ZZ Production with Leptonic Decays at the Large Hadron Collider
Institute of Scientific and Technical Information of China (English)
SUN Hao
2012-01-01
The prospects of anomalous ZZγ and ZZZ triple gauge boson couplings are investigated at the Large Hadron Collider (LHC) through an excess of events in ZZ diboson production. Two such channels are selected and the tree level results including leptonic final states are discussed: ZZ → e1 e1+ e2- e2+ and ZZ → e- e+v(v)(e, e1,2 = e, μ). The results in the full finite width method are compared with the narrow width approximation (NWA) method in detail. Besides the Z boson transverse momentum distributions, the azimuthal angle between the Z boson decay to fermions, △Φ, and their separations in the pseudo-rapidity-azimuthal angle plane, AR, as well as the sensitivity on anomalous couplings are displayed at the 14 TeV LHC.%The prospects of anomalous ZZγ and ZZZ triple gauge boson couplings are investigated at the Large Hadron Collider (LHC) through an excess of events in ZZ diboson production.Two such channels are selected and the tree level results including leptonic final states are discussed:Z Z → e-1e+1 e-2 e+2 and Z Z → e-e+v-(v)( e,e1,2 =e,μ).The results in the full finite width method are compared with the narrow width approximation (NWA) method in detail.Besides the Z boson transverse momentum distributions,the azimuthal angle between the Z boson decay to fermions,△ Φ,and their separations in the pseudo-rapidity-azimuthal angle plane,△R,as well as the sensitivity on anomalous couplings are displayed at the 14 TeV LHC.
Energy Technology Data Exchange (ETDEWEB)
Zychor, I. [Soltan Inst. for Nuclear Studies, Otwock-Swierk (Poland)
1994-12-31
The application of a Monte Carlo method to study a transport in matter of electron and photon beams is presented, especially for electrons with energies up to 18 MeV. The SHOWME Monte Carlo code, a modified version of GEANT3 code, was used on the CONVEX C3210 computer at Swierk. It was assumed that an electron beam is mono directional and monoenergetic. Arbitrary user-defined, complex geometries made of any element or material can be used in calculation. All principal phenomena occurring when electron beam penetrates the matter are taken into account. The use of calculation for a therapeutic electron beam collimation is presented. (author). 20 refs, 29 figs.
Application de la methode des sous-groupes au calcul Monte-Carlo multigroupe
Martin, Nicolas
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
Monte Carlo method for photon heating using temperature-dependent optical properties.
Slade, Adam Broadbent; Aguilar, Guillermo
2015-02-01
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.
Multilevel Monte Carlo methods for computing failure probability of porous media flow systems
Fagerlund, F.; Hellman, F.; Målqvist, A.; Niemi, A.
2016-08-01
We study improvements of the standard and multilevel Monte Carlo method for point evaluation of the cumulative distribution function (failure probability) applied to porous media two-phase flow simulations with uncertain permeability. To illustrate the methods, we study an injection scenario where we consider sweep efficiency of the injected phase as quantity of interest and seek the probability that this quantity of interest is smaller than a critical value. In the sampling procedure, we use computable error bounds on the sweep efficiency functional to identify small subsets of realizations to solve highest accuracy by means of what we call selective refinement. We quantify the performance gains possible by using selective refinement in combination with both the standard and multilevel Monte Carlo method. We also identify issues in the process of practical implementation of the methods. We conclude that significant savings in computational cost are possible for failure probability estimation in a realistic setting using the selective refinement technique, both in combination with standard and multilevel Monte Carlo.
GPU-accelerated Monte Carlo simulation of particle coagulation based on the inverse method
Wei, J.; Kruis, F. E.
2013-09-01
Simulating particle coagulation using Monte Carlo methods is in general a challenging computational task due to its numerical complexity and the computing cost. Currently, the lowest computing costs are obtained when applying a graphic processing unit (GPU) originally developed for speeding up graphic processing in the consumer market. In this article we present an implementation of accelerating a Monte Carlo method based on the Inverse scheme for simulating particle coagulation on the GPU. The abundant data parallelism embedded within the Monte Carlo method is explained as it will allow an efficient parallelization of the MC code on the GPU. Furthermore, the computation accuracy of the MC on GPU was validated with a benchmark, a CPU-based discrete-sectional method. To evaluate the performance gains by using the GPU, the computing time on the GPU against its sequential counterpart on the CPU were compared. The measured speedups show that the GPU can accelerate the execution of the MC code by a factor 10-100, depending on the chosen particle number of simulation particles. The algorithm shows a linear dependence of computing time with the number of simulation particles, which is a remarkable result in view of the n2 dependence of the coagulation.
Monte Carlo Methods Development and Applications in Conformational Sampling of Proteins
DEFF Research Database (Denmark)
Tian, Pengfei
sampling methods to address these two problems. First of all, a novel technique has been developed for reliably estimating diffusion coefficients for use in the enhanced sampling of molecular simulations. A broad applicability of this method is illustrated by studying various simulation problems...... are not sufficient to provide an accurate structural and dynamical description of certain properties of proteins, (2), it is difficult to obtain correct statistical weights of the samples generated, due to lack of equilibrium sampling. In this dissertation I present several new methodologies based on Monte Carlo...... such as protein folding and aggregation. Second, by combining Monte Carlo sampling with a flexible probabilistic model of NMR chemical shifts, a series of simulation strategies are developed to accelerate the equilibrium sampling of free energy landscapes of proteins. Finally, a novel approach is presented...
Path-integral Monte Carlo method for the local Z2 Berry phase.
Motoyama, Yuichi; Todo, Synge
2013-02-01
We present a loop cluster algorithm Monte Carlo method for calculating the local Z(2) Berry phase of the quantum spin models. The Berry connection, which is given as the inner product of two ground states with different local twist angles, is expressed as a Monte Carlo average on the worldlines with fixed spin configurations at the imaginary-time boundaries. The "complex weight problem" caused by the local twist is solved by adopting the meron cluster algorithm. We present the results of simulation on the antiferromagnetic Heisenberg model on an out-of-phase bond-alternating ladder to demonstrate that our method successfully detects the change in the valence bond pattern at the quantum phase transition point. We also propose that the gauge-fixed local Berry connection can be an effective tool to estimate precisely the quantum critical point.
A step beyond the Monte Carlo method in economics: Application of multivariate normal distribution
Kabaivanov, S.; Malechkova, A.; Marchev, A.; Milev, M.; Markovska, V.; Nikolova, K.
2015-11-01
In this paper we discuss the numerical algorithm of Milev-Tagliani [25] used for pricing of discrete double barrier options. The problem can be reduced to accurate valuation of an n-dimensional path integral with probability density function of a multivariate normal distribution. The efficient solution of this problem with the Milev-Tagliani algorithm is a step beyond the classical application of Monte Carlo for option pricing. We explore continuous and discrete monitoring of asset path pricing, compare the error of frequently applied quantitative methods such as the Monte Carlo method and finally analyze the accuracy of the Milev-Tagliani algorithm by presenting the profound research and important results of Honga, S. Leeb and T. Li [16].
Evaluation of Electron Swarm Parameters in SF6 Using Monte Carlo Method
Settaouti, Abdelrahmane [عبد الرحمن ساتوتو; Settaouti, Lahouaria [هورية ستاوتي
2005-01-01
The motion of electrons in sulfur hexafluoride (SFo) in uniform electric fields is simulated using a Monte Carlo method. The swarm parameters are evaluated and compared with experimental results of drift velocity, electron mean energy, ratio of ionization coefficient and attachment coefficient. The electron molecule collision cross sections adopted in the simulation result in a good agreement with the experimental values over the range of EA{ investigated (E is the electric field and N is the...
Green-Function-Based Monte Carlo Method for Classical Fields Coupled to Fermions
Weiße, Alexander
2009-01-01
Microscopic models of classical degrees of freedom coupled to non-interacting fermions occur in many different contexts. Prominent examples from solid state physics are descriptions of colossal magnetoresistance manganites and diluted magnetic semiconductors, or auxiliary field methods for correlated electron systems. Monte Carlo simulations are vital for an understanding of such systems, but notorious for requiring the solution of the fermion problem with each change in the classical field c...
SAFETY ANALYSIS AND RISK ASSESSMENT FOR BRIDGES HEALTH MONITORING WITH MONTE CARLO METHODS
2016-01-01
With the increasing requirements of building safety in the past few decades, healthy monitoring and risk assessment of structures is of more and more importance. Especially since traffic loads are heavier, risk Assessment for bridges are essential. In this paper we take advantage of Monte Carlo Methods to analysis the safety of bridge and monitoring the destructive risk. One main goal of health monitoring is to reduce the risk of unexpected damage of artificial objects
The information-based complexity of approximation problem by adaptive Monte Carlo methods
Institute of Scientific and Technical Information of China (English)
FANG GenSun; DUAN LiQin
2008-01-01
In this paper,we study the complexity of information of approximation problem on the multivariate Sobolev space with bounded mixed derivative MWTp,α(Td),1＜p＜∞,in the norm of Lq(Td),1＜q＜∞,by adaptive Monte Carlo methods.Applying the discretization technique and some properties of pseudo-s-scale,we determine the exact asymptotic orders of this problem.
Shahla Ahmadi; Hossein Rajabi; Farshid Babapoor; Faraz Kalantari
2011-01-01
Introduction: The main goal of SPECT imaging is to determine activity distribution inside the organs of the body. However, due to photon attenuation, it is almost impossible to do a quantitative study. In this paper, we suggest a mathematical relationship between activity distribution and its corresponding projections using a transfer matrix. Monte Carlo simulation was used to find a precise transfer matrix including the effects of photon attenuation. Material and Methods: List mode output o...
Multiplatform application for calculating a combined standard uncertainty using a Monte Carlo method
Niewinski, Marek; Gurnecki, Pawel
2016-12-01
The paper presents a new computer program for calculating a combined standard uncertainty. It implements the algorithm described in JCGM 101:20081 which is concerned with the use of a Monte Carlo method as an implementation of the propagation of distributions for uncertainty evaluation. The accuracy of the calculation has been obtained by using the high quality random number generators. The paper describes the main principles of the program and compares the obtained result with example problems presented in JCGM Supplement 1.
Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients
Teckentrup, A. L.; Scheichl, R.; Giles, M. B.; Ullmann, E
2012-01-01
We consider the application of multilevel Monte Carlo methods to elliptic PDEs with random coefficients. We focus on models of the random coefficient that lack uniform ellipticity and boundedness with respect to the random parameter, and that only have limited spatial regularity. We extend the finite element error analysis for this type of equation, carried out recently by Charrier, Scheichl and Teckentrup, to more difficult problems, posed on non--smooth domains and with discontinuities in t...
Simulations of a typical CMOS amplifier circuit using the Monte Carlo method
Borges, Jacques Cousteau da Silva
2016-01-01
In the present paper of Microelectronics, some simulations of a typical circuit of amplification, using a CMOS transistor, through the computational tools were performed. At that time, PSPICE® was used, where it was possible to observe the results, which are detailed in this work. The imperfections of the component due to manufacturing processes were obtained from simulations using the Monte Carlo method. The circuit operating point, mean and standard deviation were obtained and the influence...
Multilevel markov chain monte carlo method for high-contrast single-phase flow problems
Efendiev, Yalchin R.
2014-12-19
In this paper we propose a general framework for the uncertainty quantification of quantities of interest for high-contrast single-phase flow problems. It is based on the generalized multiscale finite element method (GMsFEM) and multilevel Monte Carlo (MLMC) methods. The former provides a hierarchy of approximations of different resolution, whereas the latter gives an efficient way to estimate quantities of interest using samples on different levels. The number of basis functions in the online GMsFEM stage can be varied to determine the solution resolution and the computational cost, and to efficiently generate samples at different levels. In particular, it is cheap to generate samples on coarse grids but with low resolution, and it is expensive to generate samples on fine grids with high accuracy. By suitably choosing the number of samples at different levels, one can leverage the expensive computation in larger fine-grid spaces toward smaller coarse-grid spaces, while retaining the accuracy of the final Monte Carlo estimate. Further, we describe a multilevel Markov chain Monte Carlo method, which sequentially screens the proposal with different levels of approximations and reduces the number of evaluations required on fine grids, while combining the samples at different levels to arrive at an accurate estimate. The framework seamlessly integrates the multiscale features of the GMsFEM with the multilevel feature of the MLMC methods following the work in [26], and our numerical experiments illustrate its efficiency and accuracy in comparison with standard Monte Carlo estimates. © Global Science Press Limited 2015.
A new fuzzy Monte Carlo method for solving SLAE with ergodic fuzzy Markov chains
Directory of Open Access Journals (Sweden)
Maryam Gharehdaghi
2015-05-01
Full Text Available In this paper we introduce a new fuzzy Monte Carlo method for solving system of linear algebraic equations (SLAE over the possibility theory and max-min algebra. To solve the SLAE, we first define a fuzzy estimator and prove that this is an unbiased estimator of the solution. To prove unbiasedness, we apply the ergodic fuzzy Markov chains. This new approach works even for cases with coefficients matrix with a norm greater than one.
Bratchenko, M I
2001-01-01
A novel method of Monte Carlo simulation of small-angle reflection of charged particles from solid surfaces has been developed. Instead of atomic-scale simulation of particle-surface collisions the method treats the reflection macroscopically as 'condensed history' event. Statistical parameters of reflection are sampled from the theoretical distributions upon energy and angles. An efficient sampling algorithm based on combination of inverse probability distribution function method and rejection method has been proposed and tested. As an example of application the results of statistical modeling of particles flux enhancement near the bottom of vertical Wehner cone are presented and compared with simple geometrical model of specular reflection.
Monte Carlo Methods in Materials Science Based on FLUKA and ROOT
Pinsky, Lawrence; Wilson, Thomas; Empl, Anton; Andersen, Victor
2003-01-01
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
Methods for Monte Carlo simulation of the exospheres of the moon and Mercury
Hodges, R. R., Jr.
1980-01-01
A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.
Quantum Monte Carlo method applied to non-Markovian barrier transmission
Hupin, Guillaume; Lacroix, Denis
2010-01-01
In nuclear fusion and fission, fluctuation and dissipation arise because of the coupling of collective degrees of freedom with internal excitations. Close to the barrier, quantum, statistical, and non-Markovian effects are expected to be important. In this work, a new approach based on quantum Monte Carlo addressing this problem is presented. The exact dynamics of a system coupled to an environment is replaced by a set of stochastic evolutions of the system density. The quantum Monte Carlo method is applied to systems with quadratic potentials. In all ranges of temperature and coupling, the stochastic method matches the exact evolution, showing that non-Markovian effects can be simulated accurately. A comparison with other theories, such as Nakajima-Zwanzig or time-convolutionless, shows that only the latter can be competitive if the expansion in terms of coupling constant is made at least to fourth order. A systematic study of the inverted parabola case is made at different temperatures and coupling constants. The asymptotic passing probability is estimated by different approaches including the Markovian limit. Large differences with an exact result are seen in the latter case or when only second order in the coupling strength is considered, as is generally assumed in nuclear transport models. In contrast, if fourth order in the coupling or quantum Monte Carlo method is used, a perfect agreement is obtained.
A Markov chain Monte Carlo method family in incomplete data analysis
Directory of Open Access Journals (Sweden)
Vasić Vladimir V.
2003-01-01
Full Text Available A Markov chain Monte Carlo method family is a collection of techniques for pseudorandom draws out of probability distribution function. In recent years, these techniques have been the subject of intensive interest of many statisticians. Roughly speaking, the essence of a Markov chain Monte Carlo method family is generating one or more values of a random variable Z, which is usually multidimensional. Let P(Z = f(Z denote a density function of a random variable Z, which we will refer to as a target distribution. Instead of sampling directly from the distribution f, we will generate [Z(1, Z(2..., Z(t,... ], in which each value is, in a way, dependant upon the previous value and where the stationary distribution will be a target distribution. For a sufficient value of t, Z(t will be approximately random sampling of the distribution f. A Markov chain Monte Carlo method family is useful when direct sampling is difficult, but when sampling of each value is not.
Hu, Xingzhi; Chen, Xiaoqian; Parks, Geoffrey T.; Yao, Wen
2016-10-01
Ever-increasing demands of uncertainty-based design, analysis, and optimization in aerospace vehicles motivate the development of Monte Carlo methods with wide adaptability and high accuracy. This paper presents a comprehensive review of typical improved Monte Carlo methods and summarizes their characteristics to aid the uncertainty-based multidisciplinary design optimization (UMDO). Among them, Bayesian inference aims to tackle the problems with the availability of prior information like measurement data. Importance sampling (IS) settles the inconvenient sampling and difficult propagation through the incorporation of an intermediate importance distribution or sequential distributions. Optimized Latin hypercube sampling (OLHS) is a stratified sampling approach to achieving better space-filling and non-collapsing characteristics. Meta-modeling approximation based on Monte Carlo saves the computational cost by using cheap meta-models for the output response. All the reviewed methods are illustrated by corresponding aerospace applications, which are compared to show their techniques and usefulness in UMDO, thus providing a beneficial reference for future theoretical and applied research.
MULTI-MONTE-CARLO METHOD FOR GENERAL DYNAMIC EQUATION CONSIDERING PARTICLE COAGULATION
Institute of Scientific and Technical Information of China (English)
ZHAO Hai-bo; ZHENG Chu-guang; XU Ming-hou
2005-01-01
Monte-Carlo (MC) method is widely adopted to take into account general dynamic equation (GDE) for particle coagulation, however popular MC method has high computation cost and statistical fatigue. A new Multi-Monte-Carlo (MMC)method, which has characteristics of time-driven MC method, constant number method and constant volume method, was promoted to solve GDE for coagulation. Firstly MMC method was described in details, including the introduction of weighted fictitious particle, the scheme of MMC method, the setting of time step, the judgment of the occurrence of coagulation event, the choice of coagulation partner and the consequential treatment of coagulation event. Secondly MMC method was validated by five special coagulation cases in which analytical solutions exist. The good agreement between the simulation results of MMC method and analytical solutions shows MMC method conserves high computation precision and has low computation cost. Lastly the different influence of different kinds of coagulation kernel on the process of coagulation was analyzed: constant coagulation kernel and Brownian coagulation kernel in continuum regime affect small particles much more than linear and quadratic coagulation kernel,whereas affect big particles much less than linear and quadratic coagulation kernel.
A method to reduce the rejection rate in Monte Carlo Markov chains
Baldassi, Carlo
2017-03-01
We present a method for Monte Carlo sampling on systems with discrete variables (focusing in the Ising case), introducing a prior on the candidate moves in a Metropolis–Hastings scheme which can significantly reduce the rejection rate, called the reduced-rejection-rate (RRR) method. The method employs same probability distribution for the choice of the moves as rejection-free schemes such as the method proposed by Bortz, Kalos and Lebowitz (BKL) (1975 J. Comput. Phys. 17 10–8) however, it uses it as a prior in an otherwise standard Metropolis scheme: it is thus not fully rejection-free, but in a wide range of scenarios it is nearly so. This allows to extend the method to cases for which rejection-free schemes become inefficient, in particular when the graph connectivity is not sparse, but the energy can nevertheless be expressed as a sum of two components, one of which is computed on a sparse graph and dominates the measure. As examples of such instances, we demonstrate that the method yields excellent results when performing Monte Carlo simulations of quantum spin models in presence of a transverse field in the Suzuki–Trotter formalism, and when exploring the so-called robust ensemble which was recently introduced in Baldassi et al (2016 Proc. Natl Acad. Sci. 113 E7655–62). Our code for the Ising case is publicly available (RRR Monte Carlo code https://github.com/carlobaldassi/RRRMC.jl), and extensible to user-defined models: it provides efficient implementations of standard Metropolis, the RRR method, the BKL method (extended to the case of continuous energy specra), and the waiting time method by Dall and Sibani (2001 Comput. Phys. Commun. 141 260–7).
DEFF Research Database (Denmark)
Anders, Annett; Nishijima, Kazuyoshi
The present paper aims at enhancing a solution approach proposed by Anders & Nishijima (2011) to real-time decision problems in civil engineering. The approach takes basis in the Least Squares Monte Carlo method (LSM) originally proposed by Longstaff & Schwartz (2001) for computing American option...... the improvement of the computational efficiency is to “best utilize” the least squares method; i.e. least squares method is applied for estimating the expected utility for terminal decisions, conditional on realizations of underlying random phenomena at respective times in a parametric way. The implementation...
Zhong, Zhaopeng; Talamo, Alberto; Gohar, Yousry
2013-07-01
The effective delayed neutron fraction β 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 β. 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 β 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
Electron density of states of Fe-based superconductors: Quantum trajectory Monte Carlo method
Kashurnikov, V. A.; Krasavin, A. V.; Zhumagulov, Ya. V.
2016-03-01
The spectral and total electron densities of states in two-dimensional FeAs clusters, which simulate iron-based superconductors, have been calculated using the generalized quantum Monte Carlo algorithm within the full two-orbital model. Spectra have been reconstructed by solving the integral equation relating the Matsubara Green's function and spectral density by the method combining the gradient descent and Monte Carlo algorithms. The calculations have been performed for clusters with dimensions up to 10 × 10 FeAs cells. The profiles of the Fermi surface for the entire Brillouin zone have been presented in the quasiparticle approximation. Data for the total density of states near the Fermi level have been obtained. The effect of the interaction parameter, size of the cluster, and temperature on the spectrum of excitations has been studied.
Path-integral Monte Carlo method for Rényi entanglement entropies.
Herdman, C M; Inglis, Stephen; Roy, P-N; Melko, R G; Del Maestro, A
2014-07-01
We introduce a quantum Monte Carlo algorithm to measure the Rényi 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.
Takahashi, F; Endo, A
2007-01-01
A system utilising radiation transport codes has been developed to derive accurate dose distributions in a human body for radiological accidents. A suitable model is quite essential for a numerical analysis. Therefore, two tools were developed to setup a 'problem-dependent' input file, defining a radiation source and an exposed person to simulate the radiation transport in an accident with the Monte Carlo calculation codes-MCNP and MCNPX. Necessary resources are defined by a dialogue method with a generally used personal computer for both the tools. The tools prepare human body and source models described in the input file format of the employed Monte Carlo codes. The tools were validated for dose assessment in comparison with a past criticality accident and a hypothesized exposure.
Effects of CT based Voxel Phantoms on Dose Distribution Calculated with Monte Carlo Method
Institute of Scientific and Technical Information of China (English)
Chen Chaobin; Huang Qunying; Wu Yican
2005-01-01
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.
Determination of cascade summing correction for HPGe spectrometers by the Monte Carlo method
Takeda, M N
2001-01-01
The present work describes the methodology developed for calculating the cascade sum correction to be applied to experimental efficiencies obtained by means of HPGe spectrometers. The detection efficiencies have been numerically calculated by the Monte Carlo Method for point sources. Another Monte Carlo algorithm has been developed to follow the path in the decay scheme from the beginning state at the precursor radionuclide decay level, down to the ground state of the daughter radionuclide. Each step in the decay scheme is selected by random numbers taking into account the transition probabilities and internal transition coefficients. The selected transitions are properly tagged according to the type of interaction has occurred, giving rise to a total or partial energy absorption events inside the detector crystal. Once the final state has been reached, the selected transitions were accounted for verifying each pair of transitions which occurred simultaneously. With this procedure it was possible to calculate...
Simulation model based on Monte Carlo method for traffic assignment in local area road network
Institute of Scientific and Technical Information of China (English)
Yuchuan DU; Yuanjing GENG; Lijun SUN
2009-01-01
For a local area road network, the available traffic data of traveling are the flow volumes in the key intersections, not the complete OD matrix. Considering the circumstance characteristic and the data availability of a local area road network, a new model for traffic assignment based on Monte Carlo simulation of intersection turning movement is provided in this paper. For good stability in temporal sequence, turning ratio is adopted as the important parameter of this model. The formulation for local area road network assignment problems is proposed on the assumption of random turning behavior. The traffic assignment model based on the Monte Carlo method has been used in traffic analysis for an actual urban road network. The results comparing surveying traffic flow data and determining flow data by the previous model verify the applicability and validity of the proposed methodology.
Search for WZ+ZZ Production with Missing Transverse Energy and b Jets at CDF
Energy Technology Data Exchange (ETDEWEB)
Poprocki, Stephen [Cornell Univ., Ithaca, NY (United States)
2013-01-01
Observation of diboson processes at hadron colliders is an important milestone on the road to discovery or exclusion of the standard model Higgs boson. Since the decay processes happen to be closely related, methods, tools, and insights obtained through the more common diboson decays can be incorporated into low-mass standard model Higgs searches. The combined WW + WZ + ZZ diboson cross section has been measured at the Tevatron in hadronic decay modes. In this thesis we take this one step closer to the Higgs by measuring just the WZ + ZZ cross section, exploiting a novel arti cial neural network based b-jet tagger to separate the WW background. The number of signal events is extracted from data events with large E_{T} using a simultaneous t in events with and without two jets consistent with B hadron decays. Using 5:2 fb^{-1} of data from the CDF II detector, we measure a cross section of (p $\\bar{p}$ → WZ,ZZ) = 5:8^{+3.6}_{ -3.0} pb, in agreement with the standard model.
On the Calculation of Reactor Time Constants Using the Monte Carlo Method
Energy Technology Data Exchange (ETDEWEB)
Leppaenen, Jaakko [VTT Technical Research Centre of Finland, P.O. Box 1000, FI-02044 VTT (Finland)
2008-07-01
Full-core reactor dynamics calculation involves the coupled modelling of thermal hydraulics and the time-dependent behaviour of core neutronics. The reactor time constants include prompt neutron lifetimes, neutron reproduction times, effective delayed neutron fractions and the corresponding decay constants, typically divided into six or eight precursor groups. The calculation of these parameters is traditionally carried out using deterministic lattice transport codes, which also produce the homogenised few-group constants needed for resolving the spatial dependence of neutron flux. In recent years, there has been a growing interest in the production of simulator input parameters using the stochastic Monte Carlo method, which has several advantages over deterministic transport calculation. This paper reviews the methodology used for the calculation of reactor time constants. The calculation techniques are put to practice using two codes, the PSG continuous-energy Monte Carlo reactor physics code and MORA, a new full-core Monte Carlo neutron transport code entirely based on homogenisation. Both codes are being developed at the VTT Technical Research Centre of Finland. The results are compared to other codes and experimental reference data in the CROCUS reactor kinetics benchmark calculation. (author)
Estimating Super Heavy Element Event Random Probabilities Using Monte Carlo Methods
Stoyer, Mark; Henderson, Roger; Kenneally, Jacqueline; Moody, Kenton; Nelson, Sarah; Shaughnessy, Dawn; Wilk, Philip
2009-10-01
Because superheavy element (SHE) experiments involve very low event rates and low statistics, estimating the probability that a given event sequence is due to random events is extremely important in judging the validity of the data. A Monte Carlo method developed at LLNL [1] is used on recent SHE experimental data to calculate random event probabilities. Current SHE experimental activities in collaboration with scientists at Dubna, Russia will be discussed. [4pt] [1] N.J. Stoyer, et al., Nucl. Instrum. Methods Phys. Res. A 455 (2000) 433.
Solution of the radiative transfer theory problems by the Monte Carlo method
Marchuk, G. I.; Mikhailov, G. A.
1974-01-01
The Monte Carlo method is used for two types of problems. First, there are interpretation problems of optical observations from meteorological satellites in the short wave part of the spectrum. The sphericity of the atmosphere, the propagation function, and light polarization are considered. Second, problems dealt with the theory of spreading narrow light beams. Direct simulation of light scattering and the mathematical form of medium radiation model representation are discussed, and general integral transfer equations are calculated. The dependent tests method, derivative estimates, and solution to the inverse problem are also considered.
Markov chain Monte Carlo methods for statistical analysis of RF photonic devices.
Piels, Molly; Zibar, Darko
2016-02-08
The microwave reflection coefficient is commonly used to characterize the impedance of high-speed optoelectronic devices. Error and uncertainty in equivalent circuit parameters measured using this data are systematically evaluated. The commonly used nonlinear least-squares method for estimating uncertainty is shown to give unsatisfactory and incorrect results due to the nonlinear relationship between the circuit parameters and the measured data. Markov chain Monte Carlo methods are shown to provide superior results, both for individual devices and for assessing within-die variation.
Sharma, Anupam; Long, Lyle N.
2004-10-01
A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented.
Energy Technology Data Exchange (ETDEWEB)
Datema, C.P. E-mail: c.datema@iri.tudelft.nl; Bom, V.R.; Eijk, C.W.E. van
2002-08-01
Experiments were carried out to investigate the possible use of neutron backscattering for the detection of landmines buried in the soil. Several landmines, buried in a sand-pit, were positively identified. A series of Monte Carlo simulations were performed to study the complexity of the neutron backscattering process and to optimize the geometry of a future prototype. The results of these simulations indicate that this method shows great potential for the detection of non-metallic landmines (with a plastic casing), for which so far no reliable method has been found.
Datema, C P; Eijk, C W E
2002-01-01
Experiments were carried out to investigate the possible use of neutron backscattering for the detection of landmines buried in the soil. Several landmines, buried in a sand-pit, were positively identified. A series of Monte Carlo simulations were performed to study the complexity of the neutron backscattering process and to optimize the geometry of a future prototype. The results of these simulations indicate that this method shows great potential for the detection of non-metallic landmines (with a plastic casing), for which so far no reliable method has been found.
Comparing Subspace Methods for Closed Loop Subspace System Identification by Monte Carlo Simulations
Directory of Open Access Journals (Sweden)
David Di Ruscio
2009-10-01
Full Text Available A novel promising bootstrap subspace system identification algorithm for both open and closed loop systems is presented. An outline of the SSARX algorithm by Jansson (2003 is given and a modified SSARX algorithm is presented. Some methods which are consistent for closed loop subspace system identification presented in the literature are discussed and compared to a recently published subspace algorithm which works for both open as well as for closed loop data, i.e., the DSR_e algorithm as well as the bootstrap method. Experimental comparisons are performed by Monte Carlo simulations.
A study of potential energy curves from the model space quantum Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Ohtsuka, Yuhki; Ten-no, Seiichiro, E-mail: tenno@cs.kobe-u.ac.jp [Department of Computational Sciences, Graduate School of System Informatics, Kobe University, Nada-ku, Kobe 657-8501 (Japan)
2015-12-07
We report on the first application of the model space quantum Monte Carlo (MSQMC) to potential energy curves (PECs) for the excited states of C{sub 2}, N{sub 2}, and O{sub 2} to validate the applicability of the method. A parallel MSQMC code is implemented with the initiator approximation to enable efficient sampling. The PECs of MSQMC for various excited and ionized states are compared with those from the Rydberg-Klein-Rees and full configuration interaction methods. The results indicate the usefulness of MSQMC for precise PECs in a wide range obviating problems concerning quasi-degeneracy.
Directory of Open Access Journals (Sweden)
Shahla Ahmadi
2011-09-01
Full Text Available Introduction: The main goal of SPECT imaging is to determine activity distribution inside the organs of the body. However, due to photon attenuation, it is almost impossible to do a quantitative study. In this paper, we suggest a mathematical relationship between activity distribution and its corresponding projections using a transfer matrix. Monte Carlo simulation was used to find a precise transfer matrix including the effects of photon attenuation. Material and Methods: List mode output of the SIMIND Monte Carlo simulator was used to find the relationship between activity distribution and pixel values in projections. The MLEM iterative reconstruction method was then used to reconstruct the activity distribution from the projections. Attenuation-free projections were also simulated. Reconstructed images from these projections were used as reference images. Our suggested attenuation correction method was evaluated using three different phantom configurations: uniform activity and uniform attenuation phantom, non-uniform activity and non-uniform attenuation phantom, and NCAT torso phantom. The mean pixel values and fits between profiles were used as quantitative parameters. Results: Images free from attenuation-related artifacts were reconstructed by our suggested method. A significant increase in pixel values was found after attenuation correction. Better fits between profiles of the corrected and reference images were also found for all phantom configurations. Discussion and Conclusion: Using a Monte Carlo method, it is possible to find the most precise relationship between activity distribution and its projections. Therefore, it is possible to create mathematical projections that include the effects of attenuation. This helps to have a more realistic comparison between mathematical and real projections, which is a necessary step for image reconstruction using MLEM. This results in images with much better quantitative accuracy at a cost of
Feng, X.; Lorton, C.
2017-03-01
This paper develops and analyzes an efficient Monte Carlo interior penalty discontinuous Galerkin (MCIP-DG) method for elastic wave scattering in random media. The method is constructed based on a multi-modes expansion of the solution of the governing random partial differential equations. It is proved that the mode functions satisfy a three-term recurrence system of partial differential equations (PDEs) which are nearly deterministic in the sense that the randomness only appears in the right-hand side source terms, not in the coefficients of the PDEs. Moreover, the same differential operator applies to all mode functions. A proven unconditionally stable and optimally convergent IP-DG method is used to discretize the deterministic PDE operator, an efficient numerical algorithm is proposed based on combining the Monte Carlo method and the IP-DG method with the $LU$ direct linear solver. It is shown that the algorithm converges optimally with respect to both the mesh size $h$ and the sampling number $M$, and practically its total computational complexity is only amount to solving very few deterministic elastic Helmholtz equations using the $LU$ direct linear solver. Numerically experiments are also presented to demonstrate the performance and key features of the proposed MCIP-DG method.
A method based on Monte Carlo simulation for the determination of the G(E) function.
Chen, Wei; Feng, Tiancheng; Liu, Jun; Su, Chuanying; Tian, Yanjie
2015-02-01
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 %.
The adaptation method in the Monte Carlo simulation for computed tomography
Energy Technology Data Exchange (ETDEWEB)
Lee, Hyoung Gun; Yoon, Chang Yeon; Lee, Won Ho [Dept. of Bio-convergence Engineering, Korea University, Seoul (Korea, Republic of); Cho, Seung Ryong [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Park, Sung Ho [Dept. of Neurosurgery, Ulsan University Hospital, Ulsan (Korea, Republic of)
2015-06-15
The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations-assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
Parsons, Tom
2008-01-01
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.
Hogerheijde, M R; Hogerheijde, Michiel R.; Tak, Floris F. S. van der
2000-01-01
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 ro...
Sanattalab, Ehsan; SalmanOgli, Ahmad; Piskin, Erhan
2016-04-01
We investigated the tumor-targeted nanoparticles that influence heat generation. We suppose that all nanoparticles are fully functionalized and can find the target using active targeting methods. Unlike the commonly used methods, such as chemotherapy and radiotherapy, the treatment procedure proposed in this study is purely noninvasive, which is considered to be a significant merit. It is found that the localized heat generation due to targeted nanoparticles is significantly higher than other areas. By engineering the optical properties of nanoparticles, including scattering, absorption coefficients, and asymmetry factor (cosine scattering angle), the heat generated in the tumor's area reaches to such critical state that can burn the targeted tumor. The amount of heat generated by inserting smart agents, due to the surface Plasmon resonance, will be remarkably high. The light-matter interactions and trajectory of incident photon upon targeted tissues are simulated by MIE theory and Monte Carlo method, respectively. Monte Carlo method is a statistical one by which we can accurately probe the photon trajectories into a simulation area.
Time-quantifiable Monte Carlo method for simulating a magnetization-reversal process
Cheng, X. Z.; Jalil, M. B. A.; Lee, H. K.; Okabe, Y.
2005-09-01
We propose a 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.
Institute of Scientific and Technical Information of China (English)
Du Gang; Liu Xiao-Yan; Han Ru-Qi
2006-01-01
A two-dimensional (2D) full band self-consistent ensemble Monte Carlo (MC) method for solving the quantum Boltzmann equation, including collision broadening and quantum potential corrections, is developed to extend the MC method to the study of nano-scale semiconductor devices with obvious quantum mechanical (QM) effects. The quantum effects both in real space and momentum space in nano-scale semiconductor devices can be simulated. The effective mobility in the inversion layer of n and p channel MOSFET is simulated and compared with experimental data to verify this method. With this method 50nm ultra thin body silicon on insulator MOSFET are simulated. Results indicate that this method can be used to simulate the 2D QM effects in semiconductor devices including tunnelling effect.
A numerical study of rays in random media. [Monte Carlo method simulation
Youakim, M. Y.; Liu, C. H.; Yeh, K. C.
1973-01-01
Statistics of electromagnetic rays in a random medium are studied numerically by the Monte Carlo method. Two dimensional random surfaces with prescribed correlation functions are used to simulate the random media. Rays are then traced in these sample media. Statistics of the ray properties such as the ray positions and directions are computed. Histograms showing the distributions of the ray positions and directions at different points along the ray path as well as at given points in space are given. The numerical experiment is repeated for different cases corresponding to weakly and strongly random media with isotropic and anisotropic irregularities. Results are compared with those derived from theoretical investigations whenever possible.
Three-dimensional hypersonic rarefied flow calculations using direct simulation Monte Carlo method
Celenligil, M. Cevdet; Moss, James N.
1993-01-01
A summary of three-dimensional simulations on the hypersonic rarefied flows in an effort to understand the highly nonequilibrium flows about space vehicles entering the Earth's atmosphere for a realistic estimation of the aerothermal loads is presented. Calculations are performed using the direct simulation Monte Carlo method with a five-species reacting gas model, which accounts for rotational and vibrational internal energies. Results are obtained for the external flows about various bodies in the transitional flow regime. For the cases considered, convective heating, flowfield structure and overall aerodynamic coefficients are presented and comparisons are made with the available experimental data. The agreement between the calculated and measured results are very good.
Volume Dispersion of Point Sets and Quasi-Monte Carlo Methods
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Measures of irregularity of a point set or sequence, such as discrepancy and dispersion, play a central role in quasi-Monte Carlo methods. In this paper, we introduce and study a new measure of irregularity, called volume dispersion. It is a measure of deviation of point sets from the uniform distribution. We then generalize the concept of volume dispersion to more general cases as measures of representation of point sets for general probability distributions. Various relations among these measures and the traditional discrepancy and dispersion are investigated.
Application of the direct simulation Monte Carlo method to the full shuttle geometry
Bird, G. A.
1990-01-01
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.
Shuttle vertical fin flowfield by the direct simulation Monte Carlo method
Hueser, J. E.; Brock, F. J.; Melfi, L. T.
1985-01-01
The flow properties in a model flowfield, simulating the shuttle vertical fin, determined using the Direct Simulation Monte Carlo method. The case analyzed corresponds to an orbit height of 225 km with the freestream velocity vector orthogonal to the fin surface. Contour plots of the flowfield distributions of density, temperature, velocity and flow angle are presented. The results also include mean molecular collision frequency (which reaches 1/60 sec near the surface), collision frequency density (approaches 7 x 10 to the 18/cu m sec at the surface) and the mean free path (19 m at the surface).
Reliability Assessment of Active Distribution System Using Monte Carlo Simulation Method
Directory of Open Access Journals (Sweden)
Shaoyun Ge
2014-01-01
Full Text Available In this paper we have treated the reliability assessment problem of low and high DG penetration level of active distribution system using the Monte Carlo simulation method. The problem is formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation. The load shedding strategy and the simulation process were introduced in detail during each FMEA process. Results indicate that the integration of DG can improve the reliability of the system if the system was operated actively.
On the Stability of Sequential Monte Carlo Methods in High Dimensions
Beskos, A.; D Crisan; Jasra, A.
2011-01-01
We investigate the stability of a Sequential Monte Carlo (SMC) method applied to the problem of sampling from a target distribution on $\\mathbb{R}^{d}$ for large $d$. It is well known [Bengtsson, Bickel and Li, In Probability and Statistics: Essays in Honor of David A. Freedman, D. Nolan and T. Speed, eds. (2008) 316–334 IMS; see also Pushing the Limits of Contemporary Statistics (2008) 318–329 IMS, Mon. Weather Rev. (2009) 136 (2009) 4629–4640] that using a single importance sampling step, o...
Simulations of a typical CMOS amplifier circuit using the Monte Carlo method
Directory of Open Access Journals (Sweden)
Borges, Jacques Cousteau da Silva
2016-11-01
Full Text Available In the present paper of Microelectronics, some simulations of a typical circuit of amplification, using a CMOS transistor, through the computational tools were performed. At that time, PSPICE® was used, where it was possible to observe the results, which are detailed in this work. The imperfections of the component due to manufacturing processes were obtained from simulations using the Monte Carlo method. The circuit operating point, mean and standard deviation were obtained and the influence of the threshold voltage Vth was analyzed.
The applicability of certain Monte Carlo methods to the analysis of interacting polymers
Energy Technology Data Exchange (ETDEWEB)
Krapp, D.M. Jr. [Univ. of California, Berkeley, CA (United States)
1998-05-01
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.
The applicability of certain Monte Carlo methods to the analysis of interacting polymers
Energy Technology Data Exchange (ETDEWEB)
Krapp, Jr., Donald M. [Univ. of California, Berkeley, CA (United States)
1998-05-01
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 β_{crit} ~ 0.99, and to recalculate the known value of the critical exponent η ~ 0.58 of the system for β = β_{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 η. 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 β_{crit} using smaller values of N is 1.01 ± 0.01, and the estimate for η at this value of β 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.
DYNAMIC PARAMETERS ESTIMATION OF INTERFEROMETRIC SIGNALS BASED ON SEQUENTIAL MONTE CARLO METHOD
Directory of Open Access Journals (Sweden)
M. A. Volynsky
2014-05-01
Full Text Available The paper deals with sequential Monte Carlo method applied to problem of interferometric signals parameters estimation. The method is based on the statistical approximation of the posterior probability density distribution of parameters. Detailed description of the algorithm is given. The possibility of using the residual minimum between prediction and observation as a criterion for the selection of multitude elements generated at each algorithm step is shown. Analysis of input parameters influence on performance of the algorithm has been conducted. It was found that the standard deviation of the amplitude estimation error for typical signals is about 10% of the maximum amplitude value. The phase estimation error was shown to have a normal distribution. Analysis of the algorithm characteristics depending on input parameters is done. In particular, the influence analysis for a number of selected vectors of parameters on evaluation results is carried out. On the basis of simulation results for the considered class of signals, it is recommended to select 30% of the generated vectors number. The increase of the generated vectors number over 150 does not give significant improvement of the obtained estimates quality. The sequential Monte Carlo method is recommended for usage in dynamic processing of interferometric signals for the cases when high immunity is required to non-linear changes of signal parameters and influence of random noise.
Directory of Open Access Journals (Sweden)
Shchekoturova S. D.
2015-04-01
Full Text Available The article presents an analysis of an innovative activity of four Russian metallurgical enterprises: "Ruspolimet", JSC "Ural Smithy", JSC "Stupino Metallurgical Company", JSC "VSMPO" via mathematical modeling using Monte Carlo method. The results of the assessment of innovative activity of Russian metallurgical companies were identified in five years dynamics. An assessment of the current innovative activity was made by the calculation of an integral index of the innovative activity. The calculation was based on such six indicators as the proportion of staff employed in R & D; the level of development of new technology; the degree of development of new products; share of material resources for R & D; degree of security of enterprise intellectual property; the share of investment in innovative projects and it was analyzed from 2007 to 2011. On the basis of this data the integral indicator of the innovative activity of metallurgical companies was calculated by well-known method of weighting coefficients. The comparative analysis of integral indicators of the innovative activity of considered companies made it possible to range their level of the innovative activity and to characterize the current state of their business. Based on Monte Carlo method a variation interval of the integral indicator was obtained and detailed instructions to choose the strategy of the innovative development of metallurgical enterprises were given as well
DEFF Research Database (Denmark)
Tycho, Andreas; Jørgensen, Thomas Martini; Andersen, Peter E.
2002-01-01
A Monte Carlo (MC) method for modeling optical coherence tomography (OCT) measurements of a diffusely reflecting discontinuity emb edded in a scattering medium is presented. For the first time to the authors' knowledge it is shown analytically that the applicability of an MC approach to this opti......A Monte Carlo (MC) method for modeling optical coherence tomography (OCT) measurements of a diffusely reflecting discontinuity emb edded in a scattering medium is presented. For the first time to the authors' knowledge it is shown analytically that the applicability of an MC approach...... to this optical geometry is firmly justified, because, as we show, in the conjugate image plane the field reflected from the sample is delta-correlated from which it follows that the heterodyne signal is calculated from the intensity distribution only. This is not a trivial result because, in general, the light...... focused beam, and it is shown that in free space the full three-dimensional intensity distribution of a Gaussian beam is obtained. The OCT signal and the intensity distribution in a scattering medium have been obtained for several geometries with the suggested MC method; when this model and a recently...
Directory of Open Access Journals (Sweden)
S. J. Noh
2011-10-01
Full Text Available Data assimilation techniques have received growing attention due to their capability to improve prediction. Among various data assimilation techniques, sequential Monte Carlo (SMC methods, known as "particle filters", are a Bayesian learning process that has the capability to handle non-linear and non-Gaussian state-space models. In this paper, we propose an improved particle filtering approach to consider different response times of internal state variables in a hydrologic model. The proposed method adopts a lagged filtering approach to aggregate model response until the uncertainty of each hydrologic process is propagated. The regularization with an additional move step based on the Markov chain Monte Carlo (MCMC methods is also implemented to preserve sample diversity under the lagged filtering approach. A distributed hydrologic model, water and energy transfer processes (WEP, is implemented for the sequential data assimilation through the updating of state variables. The lagged regularized particle filter (LRPF and the sequential importance resampling (SIR particle filter are implemented for hindcasting of streamflow at the Katsura catchment, Japan. Control state variables for filtering are soil moisture content and overland flow. Streamflow measurements are used for data assimilation. LRPF shows consistent forecasts regardless of the process noise assumption, while SIR has different values of optimal process noise and shows sensitive variation of confidential intervals, depending on the process noise. Improvement of LRPF forecasts compared to SIR is particularly found for rapidly varied high flows due to preservation of sample diversity from the kernel, even if particle impoverishment takes place.
Diffusion coefficients for LMFBR cells calculated with MOC and Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Rooijen, W.F.G. van, E-mail: rooijen@u-fukui.ac.j [Research Institute of Nuclear Energy, University of Fukui, Bunkyo 3-9-1, Fukui-shi, Fukui-ken 910-8507 (Japan); Chiba, G., E-mail: chiba.go@jaea.go.j [Japan Atomic Energy Agency, 2-4 Shirakata Shirane, Tokai-mura, Naka-gun, Ibaraki-ken 319-1195 (Japan)
2011-01-15
The present work discusses the calculation of the diffusion coefficient of a lattice of hexagonal cells, with both 'sodium present' and 'sodium absent' conditions. Calculations are performed in the framework of lattice theory (also known as fundamental mode approximation). Unlike the classical approaches, our heterogeneous leakage model allows the calculation of diffusion coefficients under all conditions, even if planar voids are present in the lattice. Equations resulting from this model are solved using the method of characteristics (MOC). Independent confirmation of the MOC result comes from Monte Carlo calculations, in which the diffusion coefficient is obtained without any of the assumptions of lattice theory. It is shown by comparison to the Monte Carlo results that the MOC solution yields correct values of the diffusion coefficient under all conditions, even in cases where the classic calculation of the diffusion coefficient fails. This work is a first step in the development of a robust method to calculate the diffusion coefficient of lattice cells. Adoption into production codes will require more development and validation of the method.
Sample Duplication Method for Monte Carlo Simulation of Large Reaction-Diffusion System
Institute of Scientific and Technical Information of China (English)
张红东; 陆建明; 杨玉良
1994-01-01
The sample duplication method for the Monte Carlo simulation of large reaction-diffusion system is proposed in this paper. It is proved that the sample duplication method will effectively raise the efficiency and statistical precision of the simulation without changing the kinetic behaviour of the reaction-diffusion system and the critical condition for the bifurcation of the steady-states. The method has been applied to the simulation of spatial and time dissipative structure of Brusselator under the Dirichlet boundary condition. The results presented in this paper definitely show that the sample duplication method provides a very efficient way to sol-’e the master equation of large reaction-diffusion system. For the case of two-dimensional system, it is found that the computation time is reduced at least by a factor of two orders of magnitude compared to the algorithm reported in literature.
Directory of Open Access Journals (Sweden)
Alhassid Y.
2014-04-01
Full Text Available 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.
Institute of Scientific and Technical Information of China (English)
LIU Bang-gui; ZHANG Kai-cheng; LI Ying
2007-01-01
The Kinetic Monte Carlo (KMC) method based on the transition-state theory, powerful and famous for sim-ulating atomic epitaxial growth of thin films and nanostruc-tures, was used recently to simulate the nanoferromagnetism and magnetization dynamics of nanomagnets with giant mag-netic anisotropy. We present a brief introduction to the KMC method and show how to reformulate it for nanoscale spin systems. Large enough magnetic anisotropy, observed exper-imentally and shown theoretically in terms of first-principle calculation, is not only essential to stabilize spin orientation but also necessary in making the transition-state barriers dur-ing spin reversals for spin KMC simulation. We show two applications of the spin KMC method to monatomic spin chains and spin-polarized-current controlled composite nano-magnets with giant magnetic anisotropy. This spin KMC method can be applied to other anisotropic nanomagnets and composite nanomagnets as long as their magnetic anisotropy energies are large enough.
Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin, E-mail: nzcho@kaist.ac.kr [Korea Advanced Institute of Science and Technology 291 Daehak-ro, Yuseong-gu, Daejeon, Korea 305-701 (Korea, Republic of)
2015-12-31
The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problem are presented.
Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method
Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin
2015-12-01
The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problem are presented.
Iakovidis, S.; Apostolidis, C.; Samaras, T.
2015-04-01
The objective of the present work is the application of the Monte Carlo method (GUMS1) for evaluating uncertainty in electromagnetic field measurements and the comparison of the results with the ones obtained using the 'standard' method (GUM). In particular, the two methods are applied in order to evaluate the field measurement uncertainty using a frequency selective radiation meter and the Total Exposure Quotient (TEQ) uncertainty. Comparative results are presented in order to highlight cases where GUMS1 results deviate significantly from the ones obtained using GUM, such as the presence of a non-linear mathematical model connecting the inputs with the output quantity (case of the TEQ model) or the presence of a dominant nonnormal distribution of an input quantity (case of U-shaped mismatch uncertainty). The deviation of the results obtained from the two methods can even lead to different decisions regarding the conformance with the exposure reference levels.
Energy Technology Data Exchange (ETDEWEB)
Jo, Yu Gwon; Yun, Sung Hwan; Cho, Nam Zin [KAIST, Daejeon (Korea, Republic of)
2011-10-15
Since the Monte Carlo method overcomes limitations in multi-group approximation and geometry description, it is gaining increasing use in reactor physics problems. Recently, a new leakage-corrected method was suggested by the authors, in which the critical spectrum is obtained by albedo-based leakage correction in the Monte Carlo method. In this paper, the critical spectrum based on the albedo-based leakage-corrected method will be compared with the critical spectrum by conventional B1 method (with condensed cross sections) and reference critical whole-core assembly spectrum. These two methods are implemented in our local MCNP5 (version 1.50)
A new algorithm for the fixed-node quantum Monte Carlo method
Institute of Scientific and Technical Information of China (English)
黄宏新; 曹泽星
1997-01-01
A novel algorithm is proposed for the fixed-node quantum Monte Carlo (FNQMC) method.In contrast to previous procedures,its "guiding function" is not optimized prior to diffusion quantum Monte Carlo (DMC) computation but synchronistically in the diffusion process The new algorithm can not only save CPU time,but also make both of the optimization and diffusion carried out according to the same sampling fashion,reaching the goal to improve each other This new optimizing procedure converges super-linearly,and thus can accelerate the particle diffusion During the diffusion process,the node of the "guiding function" changes incessantly,which is conducible to reducing the "fixed-node error" The new algorithm has been used to calculate the total energies of states X3B1 and a1A1 of CH2 as well as π-X2B1 and λ-2A1 of NH2 The singlet-triplet energy splitting (λEsT) in CH2 and π energy splitting in NH2 obtained with this present method are (45 542±1.840) and (141.644±1.589) kJ/mol,respectively The calculated
Directory of Open Access Journals (Sweden)
S. J. Noh
2011-04-01
Full Text Available Applications of data assimilation techniques have been widely used to improve hydrologic prediction. Among various data assimilation techniques, sequential Monte Carlo (SMC methods, known as "particle filters", provide the capability to handle non-linear and non-Gaussian state-space models. In this paper, we propose an improved particle filtering approach to consider different response time of internal state variables in a hydrologic model. The proposed method adopts a lagged filtering approach to aggregate model response until uncertainty of each hydrologic process is propagated. The regularization with an additional move step based on Markov chain Monte Carlo (MCMC is also implemented to preserve sample diversity under the lagged filtering approach. A distributed hydrologic model, WEP is implemented for the sequential data assimilation through the updating of state variables. Particle filtering is parallelized and implemented in the multi-core computing environment via open message passing interface (MPI. We compare performance results of particle filters in terms of model efficiency, predictive QQ plots and particle diversity. The improvement of model efficiency and the preservation of particle diversity are found in the lagged regularized particle filter.
Quantum Monte-Carlo method applied to Non-Markovian barrier transmission
Hupin, G
2010-01-01
In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be important. In this work, a new approach based on quantum Monte-Carlo addressing this problem is presented. The exact dynamics of a system coupled to an environment is replaced by a set of stochastic evolutions of the system density. The quantum Monte-Carlo method is applied to systems with quadratic potentials. In all range of temperature and coupling, the stochastic method matches the exact evolution showing that non-Markovian effects can be simulated accurately. A comparison with other theories like Nakajima-Zwanzig or Time-ConvolutionLess ones shows that only the latter can be competitive if the expansion in terms of coupling constant is made at least to fourth order. A systematic study of the inverted parabola case is made at different temperatures and coupling constants....
Wind Turbine Placement Optimization by means of the Monte Carlo Simulation Method
Directory of Open Access Journals (Sweden)
S. Brusca
2014-01-01
Full Text Available This paper defines a new procedure for optimising wind farm turbine placement by means of Monte Carlo simulation method. To verify the algorithm’s accuracy, an experimental wind farm was tested in a wind tunnel. On the basis of experimental measurements, the error on wind farm power output was less than 4%. The optimization maximises the energy production criterion; wind turbines’ ground positions were used as independent variables. Moreover, the mathematical model takes into account annual wind intensities and directions and wind turbine interaction. The optimization of a wind farm on a real site was carried out using measured wind data, dominant wind direction, and intensity data as inputs to run the Monte Carlo simulations. There were 30 turbines in the wind park, each rated at 20 kW. This choice was based on wind farm economics. The site was proportionally divided into 100 square cells, taking into account a minimum windward and crosswind distance between the turbines. The results highlight that the dominant wind intensity factor tends to overestimate the annual energy production by about 8%. Thus, the proposed method leads to a more precise annual energy evaluation and to a more optimal placement of the wind turbines.
A Deterministic-Monte Carlo Hybrid Method for Time-Dependent Neutron Transport Problems
Energy Technology Data Exchange (ETDEWEB)
Justin Pounders; Farzad Rahnema
2001-10-01
A new deterministic-Monte Carlo hybrid solution technique is derived for the time-dependent transport equation. This new approach is based on dividing the time domain into a number of coarse intervals and expanding the transport solution in a series of polynomials within each interval. The solutions within each interval can be represented in terms of arbitrary source terms by using precomputed response functions. In the current work, the time-dependent response function computations are performed using the Monte Carlo method, while the global time-step march is performed deterministically. This work extends previous work by coupling the time-dependent expansions to space- and angle-dependent expansions to fully characterize the 1D transport response/solution. More generally, this approach represents and incremental extension of the steady-state coarse-mesh transport method that is based on global-local decompositions of large neutron transport problems. An example of a homogeneous slab is discussed as an example of the new developments.
Simulating rotationally inelastic collisions using a Direct Simulation Monte Carlo method
Schullian, O; Vaeck, N; van der Avoird, A; Heazlewood, B R; Rennick, C J; Softley, T P
2015-01-01
A new approach to simulating rotational cooling using a direct simulation Monte Carlo (DSMC) method is described and applied to the rotational cooling of ammonia seeded into a helium supersonic jet. The method makes use of ab initio rotational state changing cross sections calculated as a function of collision energy. Each particle in the DSMC simulations is labelled with a vector of rotational populations that evolves with time. Transfer of energy into translation is calculated from the mean energy transfer for this population at the specified collision energy. The simulations are compared with a continuum model for the on-axis density, temperature and velocity; rotational temperature as a function of distance from the nozzle is in accord with expectations from experimental measurements. The method could be applied to other types of gas mixture dynamics under non-uniform conditions, such as buffer gas cooling of NH$_3$ by He.
Monte Carlo based statistical power analysis for mediation models: methods and software.
Zhang, Zhiyong
2014-12-01
The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.
Development of a Monte-Carlo based method for calculating the effect of stationary fluctuations
DEFF Research Database (Denmark)
Pettersen, E. E.; Demazire, C.; Jareteg, K.;
2015-01-01
This paper deals with the development of a novel method for performing Monte Carlo calculations of the effect, on the neutron flux, of stationary fluctuations in macroscopic cross-sections. The basic principle relies on the formulation of two equivalent problems in the frequency domain: one...... equivalent problems nevertheless requires the possibility to modify the macroscopic cross-sections, and we use the work of Kuijper, van der Marck and Hogenbirk to define group-wise macroscopic cross-sections in MCNP [1]. The method is illustrated in this paper at a frequency of 1 Hz, for which only the real...... part of the neutron balance plays a significant role and for driving fluctuations leading to neutron sources having the same sign in the two equivalent sub-critical problems. A semi-analytical diffusion-based solution is used to verily the implementation of the method on a test case representative...
Microsopic nuclear level densities by the shell model Monte Carlo method
Alhassid, Y; Gilbreth, C N; Nakada, H; Özen, C
2016-01-01
The configuration-interaction shell model approach provides an attractive framework for the calculation of nuclear level densities in the presence of correlations, but the large dimensionality of the model space has hindered its application in mid-mass and heavy nuclei. The shell model Monte Carlo (SMMC) method permits calculations in model spaces that are many orders of magnitude larger than spaces that can be treated by conventional diagonalization methods. We discuss recent progress in the SMMC approach to level densities, and in particular the calculation of level densities in heavy nuclei. We calculate the distribution of the axial quadrupole operator in the laboratory frame at finite temperature and demonstrate that it is a model-independent signature of deformation in the rotational invariant framework of the shell model. We propose a method to use these distributions for calculating level densities as a function of intrinsic deformation.
Study of the $ZZ$ diboson production at CDF II
Energy Technology Data Exchange (ETDEWEB)
Bauce, Matteo [Univ. of Padua (Italy)
2013-01-01
The subject of this Thesis is the production of a pair of massive Z vector bosons in the proton antiproton collisions at the Tevatron, at the center-of-mass energy √s = 1.96 TeV. We measure the ZZ production cross section in two different leptonic decay modes: into four charged leptons (e or μ) and into two charged leptons plus two neutrinos. The results are based on the whole dataset collected by the Collider Detector at Fermilab (CDF), corresponding to 9.7 fb^{-1} of data. The combination of the two cross section measurements gives (p$\\bar{p}$→ZZ) = 1.38^{+0.28} _{-0.27} pb, and is the most precise ZZ cross section measurement at the Tevatron to date. We further investigate the four lepton final state searching for the production of the scalar Higgs particle in the decay H →ZZ(*) →ℓℓℓ'ℓ'. No evidence of its production has been seen in the data, hence was set a 95% Confidence Level upper limit on its production cross section as a function of the Higgs particle mass, mH, in the range from 120 to 300 GeV/c^{2}.
Quantum Monte Carlo methods and strongly correlated electrons on honeycomb structures
Energy Technology Data Exchange (ETDEWEB)
Lang, Thomas C.
2010-12-16
In this thesis we apply recently developed, as well as sophisticated quantum Monte Carlo methods to numerically investigate models of strongly correlated electron systems on honeycomb structures. The latter are of particular interest owing to their unique properties when simulating electrons on them, like the relativistic dispersion, strong quantum fluctuations and their resistance against instabilities. This work covers several projects including the advancement of the weak-coupling continuous time quantum Monte Carlo and its application to zero temperature and phonons, quantum phase transitions of valence bond solids in spin-1/2 Heisenberg systems using projector quantum Monte Carlo in the valence bond basis, and the magnetic field induced transition to a canted antiferromagnet of the Hubbard model on the honeycomb lattice. The emphasis lies on two projects investigating the phase diagram of the SU(2) and the SU(N)-symmetric Hubbard model on the hexagonal lattice. At sufficiently low temperatures, condensed-matter systems tend to develop order. An exception are quantum spin-liquids, where fluctuations prevent a transition to an ordered state down to the lowest temperatures. Previously elusive in experimentally relevant microscopic two-dimensional models, we show by means of large-scale quantum Monte Carlo simulations of the SU(2) Hubbard model on the honeycomb lattice, that a quantum spin-liquid emerges between the state described by massless Dirac fermions and an antiferromagnetically ordered Mott insulator. This unexpected quantum-disordered state is found to be a short-range resonating valence bond liquid, akin to the one proposed for high temperature superconductors. Inspired by the rich phase diagrams of SU(N) models we study the SU(N)-symmetric Hubbard Heisenberg quantum antiferromagnet on the honeycomb lattice to investigate the reliability of 1/N corrections to large-N results by means of numerically exact QMC simulations. We study the melting of phases
Bianco, F. B.; Modjaz, M.; Oh, S. M.; Fierroz, D.; Liu, Y. Q.; Kewley, L.; Graur, O.
2016-07-01
We present the open-source Python code pyMCZ that determines oxygen abundance and its distribution from strong emission lines in the standard metallicity calibrators, based on the original IDL code of Kewley and Dopita (2002) with updates from Kewley and Ellison (2008), and expanded to include more recently developed calibrators. The standard strong-line diagnostics have been used to estimate the oxygen abundance in the interstellar medium through various emission line ratios (referred to as indicators) in many areas of astrophysics, including galaxy evolution and supernova host galaxy studies. We introduce a Python implementation of these methods that, through Monte Carlo sampling, better characterizes the statistical oxygen abundance confidence region including the effect due to the propagation of observational uncertainties. These uncertainties are likely to dominate the error budget in the case of distant galaxies, hosts of cosmic explosions. Given line flux measurements and their uncertainties, our code produces synthetic distributions for the oxygen abundance in up to 15 metallicity calibrators simultaneously, as well as for E(B- V) , and estimates their median values and their 68% confidence regions. We provide the option of outputting the full Monte Carlo distributions, and their Kernel Density estimates. We test our code on emission line measurements from a sample of nearby supernova host galaxies (z github.com/nyusngroup/pyMCZ.
Pavlyuchenkov, Ya; Henning, T; Guilloteau, St; Pietu, V; Launhardt, R; Dutrey, A
2007-01-01
We analyze the line radiative transfer in protoplanetary disks using several approximate methods and a well-tested Accelerated Monte Carlo code. A low-mass flaring disk model with uniform as well as stratified molecular abundances is adopted. Radiative transfer in low and high rotational lines of CO, C18O, HCO+, DCO+, HCN, CS, and H2CO is simulated. The corresponding excitation temperatures, synthetic spectra, and channel maps are derived and compared to the results of the Monte Carlo calculations. A simple scheme that describes the conditions of the line excitation for a chosen molecular transition is elaborated. We find that the simple LTE approach can safely be applied for the low molecular transitions only, while it significantly overestimates the intensities of the upper lines. In contrast, the Full Escape Probability (FEP) approximation can safely be used for the upper transitions ($J_{\\rm up} \\ga 3$) but it is not appropriate for the lowest transitions because of the maser effect. In general, the molec...
Intra-operative radiation therapy optimization using the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Rosetti, M. [ENEA, Bologna (Italy); Benassi, M.; Bufacchi, A.; D' Andrea, M. [Ist. Regina Elena, Rome (Italy); Bruzzaniti, V. [ENEA, S. Maria di Galeria (Rome) (Italy)
2001-07-01
The problem addressed with reference to the treatment head optimization has been the choice of the proper design of the head of a new 12 MeV linear accelerator in order to have the required dose uniformity on the target volume while keeping the dose rate sufficiently high and the photon production and the beam impact with the head walls within acceptable limits. The second part of the optimization work, concerning the TPS, is based on the rationale that the TPSs generally used in radiotherapy use semi-empirical algorithms whose accuracy can be inadequate particularly when irregular surfaces and/or inhomogeneities, such as air cavities or bone, are present. The Monte Carlo method, on the contrary, is capable of accurately calculating the dose distribution under almost all circumstances. Furthermore it offers the advantage of allowing to start the simulation of the radiation transport in the patient from the beam data obtained with the transport through the specific treatment head used. Therefore the Monte Carlo simulations, which at present are not yet widely used for routine treatment planning due to the required computing time, can be employed as a benchmark and as an optimization tool for conventional TPSs. (orig.)
On stochastic error and computational efficiency of the Markov Chain Monte Carlo method
Li, Jun
2014-01-01
In Markov Chain Monte Carlo (MCMC) simulations, thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples. These samples are selected in accordance with the probability distribution function, known from the partition function of equilibrium state. As the stochastic error of the simulation results is significant, it is desirable to understand the variance of the estimation by ensemble average, which depends on the sample size (i.e., the total number of samples in the set) and the sampling interval (i.e., cycle number between two consecutive samples). Although large sample sizes reduce the variance, they increase the computational cost of the simulation. For a given CPU time, the sample size can be reduced greatly by increasing the sampling interval, while having the corresponding increase in variance be negligible if the original sampling interval is very small. In this work, we report a few general rules that relate the variance with the sample size and the sampling interval. These results are observed and confirmed numerically. These variance rules are derived for theMCMCmethod but are also valid for the correlated samples obtained using other Monte Carlo methods. The main contribution of this work includes the theoretical proof of these numerical observations and the set of assumptions that lead to them. © 2014 Global-Science Press.
Sadi, M; Dabir, B
2003-01-01
Monte Carlo Method is one of the most powerful techniques to model different processes, such as polymerization reactions. By this method, without any need to solve moment equations, a very detailed information on the structure and properties of polymers are obtained. The number of algorithm repetitions (selected volumes of reactor for modelling which represent the number of initial molecules) is very important in this method. In Monte Carlo method calculations are based on the random number of generations and reaction probability determinations. so the number of algorithm repetition is very important. In this paper, the initiation reaction was considered alone and the importance of number of initiator molecules on the result were studied. It can be concluded that Monte Carlo method will not give accurate results if the number of molecules is not satisfied to be big enough, because in that case , selected volume would not be representative of the whole system.
A Variable Coefficient Method for Accurate Monte Carlo Simulation of Dynamic Asset Price
Li, Yiming; Hung, Chih-Young; Yu, Shao-Ming; Chiang, Su-Yun; Chiang, Yi-Hui; Cheng, Hui-Wen
2007-07-01
In this work, we propose an adaptive Monte Carlo (MC) simulation technique to compute the sample paths for the dynamical asset price. In contrast to conventional MC simulation with constant drift and volatility (μ,σ), our MC simulation is performed with variable coefficient methods for (μ,σ) in the solution scheme, where the explored dynamic asset pricing model starts from the formulation of geometric Brownian motion. With the method of simultaneously updated (μ,σ), more than 5,000 runs of MC simulation are performed to fulfills basic accuracy of the large-scale computation and suppresses statistical variance. Daily changes of stock market index in Taiwan and Japan are investigated and analyzed.
Heat-Flux Analysis of Solar Furnace Using the Monte Carlo Ray-Tracing Method
Energy Technology Data Exchange (ETDEWEB)
Lee, Hyun Jin; Kim, Jong Kyu; Lee, Sang Nam; Kang, Yong Heack [Korea Institute of Energy Research, Daejeon (Korea, Republic of)
2011-10-15
An understanding of the concentrated solar flux is critical for the analysis and design of solar-energy-utilization systems. The current work focuses on the development of an algorithm that uses the Monte Carlo ray-tracing method with excellent flexibility and expandability; this method considers both solar limb darkening and the surface slope error of reflectors, thereby analyzing the solar flux. A comparison of the modeling results with measurements at the solar furnace in Korea Institute of Energy Research (KIER) show good agreement within a measurement uncertainty of 10%. The model evaluates the concentration performance of the KIER solar furnace with a tracking accuracy of 2 mrad and a maximum attainable concentration ratio of 4400 sun. Flux variations according to measurement position and flux distributions depending on acceptance angles provide detailed information for the design of chemical reactors or secondary concentrators.
Monte Carlo method for polarized radiative transfer in gradient-index media
Zhao, J M; Liu, L H
2014-01-01
Light transfer in gradient-index media generally follows curved ray trajectories, which will cause light beam to converge or diverge during transfer and induce the rotation of polarization ellipse even when the medium is transparent. Furthermore, the combined process of scattering and transfer along curved ray path makes the problem more complex. In this paper, a Monte Carlo method is presented to simulate polarized radiative transfer in gradient-index media that only support planar ray trajectories. The ray equation is solved to the second order to address the effect induced by curved ray trajectories. Three types of test cases are presented to verify the performance of the method, which include transparent medium, Mie scattering medium with assumed gradient index distribution, and Rayleigh scattering with realistic atmosphere refractive index profile. It is demonstrated that the atmospheric refraction has significant effect for long distance polarized light transfer.
DSMC calculations for the double ellipse. [direct simulation Monte Carlo method
Moss, James N.; Price, Joseph M.; Celenligil, M. Cevdet
1990-01-01
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.
Monte Carlo method for predicting of cardiac toxicity: hERG blocker compounds.
Gobbi, Marco; Beeg, Marten; Toropova, Mariya A; Toropov, Andrey A; Salmona, Mario
2016-05-27
The estimation of the cardiotoxicity of compounds is an important task for the drug discovery as well as for the risk assessment in ecological aspect. The experimental estimation of the above endpoint is complex and expensive. Hence, the theoretical computational methods are very attractive alternative of the direct experiment. A model for cardiac toxicity of 400 hERG blocker compounds (pIC50) is built up using the Monte Carlo method. Three different splits into the visible training set (in fact, the training set plus the calibration set) and invisible validation sets examined. The predictive potential is very good for all examined splits. The statistical characteristics for the external validation set are (i) the coefficient of determination r(2)=(0.90-0.93); and (ii) root-mean squared error s=(0.30-0.40).
Analysis of vibrational-translational energy transfer using the direct simulation Monte Carlo method
Boyd, Iain D.
1991-01-01
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.
Rosenfeld, Anatoly; Wroe, Andrew; Carolan, Martin; Cornelius, Iwan
2006-01-01
In hadron therapy the spectra of secondary particles can be very broad in type and energy. The most accurate calculations of tissue equivalent (TE) absorbed dose and biological effect can be achieved using Monte Carlo (MC) simulations followed by the application of an appropriate radiobiological model. The verification of MC simulations is therefore an important quality assurance (QA) issue in dose planning. We propose a method of verification for MC dose calculations based on measurements of either the integral absorbed dose or the spectra of deposited energies from single secondary particles in non-TE material detectors embedded in a target of interest (phantom). This method was tested in boron neutron capture therapy and fast neutron therapy beams.
Brandão, Eric; Flesch, Rodolfo C C; Lenzi, Arcanjo; Flesch, Carlos A
2011-07-01
The pressure-particle velocity (PU) impedance measurement technique is an experimental method used to measure the surface impedance and the absorption coefficient of acoustic samples in situ or under free-field conditions. In this paper, the measurement uncertainty of the the absorption coefficient determined using the PU technique is explored applying the Monte Carlo method. It is shown that because of the uncertainty, it is particularly difficult to measure samples with low absorption and that difficulties associated with the localization of the acoustic centers of the sound source and the PU sensor affect the quality of the measurement roughly to the same extent as the errors in the transfer function between pressure and particle velocity do.
Markov Chain Monte Carlo (MCMC) methods for parameter estimation of a novel hybrid redundant robot
Energy Technology Data Exchange (ETDEWEB)
Wang Yongbo, E-mail: yongbo.wang@hotmail.com [Laboratory of Intelligent Machine, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland); Wu Huapeng; Handroos, Heikki [Laboratory of Intelligent Machine, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland)
2011-10-15
This paper presents a statistical method for the calibration of a redundantly actuated hybrid serial-parallel robot IWR (Intersector Welding Robot). The robot under study will be used to carry out welding, machining, and remote handing for the assembly of vacuum vessel of International Thermonuclear Experimental Reactor (ITER). The robot has ten degrees of freedom (DOF), among which six DOF are contributed by the parallel mechanism and the rest are from the serial mechanism. In this paper, a kinematic error model which involves 54 unknown geometrical error parameters is developed for the proposed robot. Based on this error model, the mean values of the unknown parameters are statistically analyzed and estimated by means of Markov Chain Monte Carlo (MCMC) approach. The computer simulation is conducted by introducing random geometric errors and measurement poses which represent the corresponding real physical behaviors. The simulation results of the marginal posterior distributions of the estimated model parameters indicate that our method is reliable and robust.
An improved random walk algorithm for the implicit Monte Carlo method
Keady, Kendra P.; Cleveland, Mathew A.
2017-01-01
In this work, we introduce a modified Implicit Monte Carlo (IMC) Random Walk (RW) algorithm, which increases simulation efficiency for multigroup radiative transfer problems with strongly frequency-dependent opacities. To date, the RW method has only been implemented in "fully-gray" form; that is, the multigroup IMC opacities are group-collapsed over the full frequency domain of the problem to obtain a gray diffusion problem for RW. This formulation works well for problems with large spatial cells and/or opacities that are weakly dependent on frequency; however, the efficiency of the RW method degrades when the spatial cells are thin or the opacities are a strong function of frequency. To address this inefficiency, we introduce a RW frequency group cutoff in each spatial cell, which divides the frequency domain into optically thick and optically thin components. In the modified algorithm, opacities for the RW diffusion problem are obtained by group-collapsing IMC opacities below the frequency group cutoff. Particles with frequencies above the cutoff are transported via standard IMC, while particles below the cutoff are eligible for RW. This greatly increases the total number of RW steps taken per IMC time-step, which in turn improves the efficiency of the simulation. We refer to this new method as Partially-Gray Random Walk (PGRW). We present numerical results for several multigroup radiative transfer problems, which show that the PGRW method is significantly more efficient than standard RW for several problems of interest. In general, PGRW decreases runtimes by a factor of ∼2-4 compared to standard RW, and a factor of ∼3-6 compared to standard IMC. While PGRW is slower than frequency-dependent Discrete Diffusion Monte Carlo (DDMC), it is also easier to adapt to unstructured meshes and can be used in spatial cells where DDMC is not applicable. This suggests that it may be optimal to employ both DDMC and PGRW in a single simulation.
Seismic wavefield imaging based on the replica exchange Monte Carlo method
Kano, Masayuki; Nagao, Hiromichi; Ishikawa, Daichi; Ito, Shin-ichi; Sakai, Shin'ichi; Nakagawa, Shigeki; Hori, Muneo; Hirata, Naoshi
2017-01-01
Earthquakes sometimes cause serious disasters not only directly by ground motion itself but also secondarily by infrastructure damage, particularly in densely populated urban areas that have capital functions. To reduce the number and severity of secondary disasters, it is important to evaluate seismic hazards rapidly by analysing the seismic responses of individual structures to input ground motions. We propose a method that integrates physics-based and data-driven approaches in order to obtain a seismic wavefield for use as input to a seismic response analysis. The new contribution of this study is the use of the replica exchange Monte Carlo (REMC) method, which is one of the Markov chain Monte Carlo (MCMC) methods, for estimation of a seismic wavefield, together with a 1-D local subsurface structure and source information. Numerical tests were conducted to verify the proposed method, using synthetic observation data obtained from analytical solutions for two horizontally layered subsurface structure models. The geometries of the observation sites were determined from the dense seismic observation array called the Metropolitan Seismic Observation network, which has been in operation in the Tokyo metropolitan area in Japan since 2007. The results of the numerical tests show that the proposed method is able to search the parameters related to the source and the local subsurface structure in a broader parameter space than the Metropolis method, which is an ordinary MCMC method. The proposed method successfully reproduces a seismic wavefield consistent with a true wavefield. In contrast, ordinary kriging, which is a classical data-driven interpolation method for spatial data, is hardly able to reproduce a true wavefield, even in the low frequency bands. This suggests that it is essential to employ both physics-based and data-driven approaches in seismic wavefield imaging, utilizing seismograms from a dense seismic array. The REMC method, which provides not only
Seismic wavefield imaging based on the replica exchange Monte Carlo method
Kano, Masayuki; Nagao, Hiromichi; Ishikawa, Daichi; Ito, Shin-ichi; Sakai, Shin'ichi; Nakagawa, Shigeki; Hori, Muneo; Hirata, Naoshi
2016-11-01
Earthquakes sometimes cause serious disasters not only directly by ground motion itself but also secondarily by infrastructure damage, particularly in densely populated urban areas that have capital functions. To reduce the number and severity of secondary disasters, it is important to evaluate seismic hazards rapidly by analyzing the seismic responses of individual structures to input ground motions. We propose a method that integrates physics-based and data-driven approaches in order to obtain a seismic wavefield for use as input to a seismic response analysis. The new contribution of this study is the use of the replica exchange Monte Carlo (REMC) method, which is one of the Markov chain Monte Carlo (MCMC) methods, for estimation of a seismic wavefield, together with a one-dimensional (1-D) local subsurface structure and source information. Numerical tests were conducted to verify the proposed method, using synthetic observation data obtained from analytical solutions for two horizontally-layered subsurface structure models. The geometries of the observation sites were determined from the dense seismic observation array called the Metropolitan Seismic Observation network (MeSO-net), which has been in operation in the Tokyo metropolitan area in Japan since 2007. The results of the numerical tests show that the proposed method is able to search the parameters related to the source and the local subsurface structure in a broader parameter space than the Metropolis method, which is an ordinary MCMC method. The proposed method successfully reproduces a seismic wavefield consistent with a true wavefield. In contrast, ordinary kriging, which is a classical data-driven interpolation method for spatial data, is hardly able to reproduce a true wavefield, even in the low frequency bands. This suggests that it is essential to employ both physics-based and data-driven approaches in seismic wavefield imaging, utilizing seismograms from a dense seismic array. The REMC method
Barrier heights of hydrogen-transfer reactions with diffusion quantum monte carlo method.
Zhou, Xiaojun; Wang, Fan
2017-04-30
Hydrogen-transfer reactions are an important class of reactions in many chemical and biological processes. Barrier heights of H-transfer reactions are underestimated significantly by popular exchange-correlation functional with density functional theory (DFT), while coupled-cluster (CC) method is quite expensive and can be applied only to rather small systems. Quantum Monte-Carlo method can usually provide reliable results for large systems. Performance of fixed-node diffusion quantum Monte-Carlo method (FN-DMC) on barrier heights of the 19 H-transfer reactions in the HTBH38/08 database is investigated in this study with the trial wavefunctions of the single-Slater-Jastrow form and orbitals from DFT using local density approximation. Our results show that barrier heights of these reactions can be calculated rather accurately using FN-DMC and the mean absolute error is 1.0 kcal/mol in all-electron calculations. Introduction of pseudopotentials (PP) in FN-DMC calculations improves efficiency pronouncedly. According to our results, error of the employed PPs is smaller than that of the present CCSD(T) and FN-DMC calculations. FN-DMC using PPs can thus be applied to investigate H-transfer reactions involving larger molecules reliably. In addition, bond dissociation energies of the involved molecules using FN-DMC are in excellent agreement with reference values and they are even better than results of the employed CCSD(T) calculations using the aug-cc-pVQZ basis set. © 2017 Wiley Periodicals, Inc.
Radiation Transport for Explosive Outflows: A Multigroup Hybrid Monte Carlo Method
Wollaeger, Ryan T.; van Rossum, Daniel R.; Graziani, Carlo; Couch, Sean M.; Jordan, George C., IV; Lamb, Donald Q.; Moses, Gregory A.
2013-12-01
We explore Implicit Monte Carlo (IMC) and discrete diffusion Monte Carlo (DDMC) for radiation transport in high-velocity outflows with structured opacity. The IMC method is a stochastic computational technique for nonlinear radiation transport. IMC is partially implicit in time and may suffer in efficiency when tracking MC particles through optically thick materials. DDMC accelerates IMC in diffusive domains. Abdikamalov extended IMC and DDMC to multigroup, velocity-dependent transport with the intent of modeling neutrino dynamics in core-collapse supernovae. Densmore has also formulated a multifrequency extension to the originally gray DDMC method. We rigorously formulate IMC and DDMC over a high-velocity Lagrangian grid for possible application to photon transport in the post-explosion phase of Type Ia supernovae. This formulation includes an analysis that yields an additional factor in the standard IMC-to-DDMC spatial interface condition. To our knowledge the new boundary condition is distinct from others presented in prior DDMC literature. The method is suitable for a variety of opacity distributions and may be applied to semi-relativistic radiation transport in simple fluids and geometries. Additionally, we test the code, called SuperNu, using an analytic solution having static material, as well as with a manufactured solution for moving material with structured opacities. Finally, we demonstrate with a simple source and 10 group logarithmic wavelength grid that IMC-DDMC performs better than pure IMC in terms of accuracy and speed when there are large disparities between the magnitudes of opacities in adjacent groups. We also present and test our implementation of the new boundary condition.
Numerical study of reflectance imaging using a parallel Monte Carlo method.
Chen, Cheng; Lu, Jun Q; Li, Kai; Zhao, Suisheng; Brock, R Scott; Hu, Xin-Hua
2007-07-01
Reflectance imaging of biological tissues with visible and near-infrared light has the significant potential to provide a noninvasive and safe imaging modality for diagnosis of dysplastic and malignant lesions in the superficial tissue layers. The difficulty in the extraction of optical and structural parameters lies in the lack of efficient methods for accurate modeling of light scattering in biological tissues of turbid nature. We present a parallel Monte Carlo method for accurate and efficient modeling of reflectance images from turbid tissue phantoms. A parallel Monte Carlo code has been developed with the message passing interface and evaluated on a computing cluster with 16 processing elements. The code was validated against the solutions of the radiative transfer equation on the bidirectional reflection and transmission functions. With this code we investigated numerically the dependence of reflectance image on the imaging system and phantom parameters. The contrasts of reflectance images were found to be nearly independent of the numerical aperture (NA) of the imaging camera despite the fact that reflectance depends on the NA. This enables efficient simulations of the reflectance images using an NA at 1.00. Using heterogeneous tissue phantoms with an embedded region simulating a lesion, we investigated the correlation between the reflectance image profile or contrast and the phantom parameters. It has been shown that the image contrast approaches 0 when the single-scattering albedos of the two regions in the heterogeneous phantoms become matched. Furthermore, a zone of detection has been demonstrated for determination of the thickness of the embedded region and optical parameters from the reflectance image profile and contrast. Therefore, the utility of the reflectance imaging method with visible and near-infrared light has been firmly established. We conclude from these results that the optical parameters of the embedded region can be determined inversely
Determination of phase equilibria in confined systems by open pore cell Monte Carlo method.
Miyahara, Minoru T; Tanaka, Hideki
2013-02-28
We present a modification of the molecular dynamics simulation method with a unit pore cell with imaginary gas phase [M. Miyahara, T. Yoshioka, and M. Okazaki, J. Chem. Phys. 106, 8124 (1997)] designed for determination of phase equilibria in nanopores. This new method is based on a Monte Carlo technique and it combines the pore cell, opened to the imaginary gas phase (open pore cell), with a gas cell to measure the equilibrium chemical potential of the confined system. The most striking feature of our new method is that the confined system is steadily led to a thermodynamically stable state by forming concave menisci in the open pore cell. This feature of the open pore cell makes it possible to obtain the equilibrium chemical potential with only a single simulation run, unlike existing simulation methods, which need a number of additional runs. We apply the method to evaluate the equilibrium chemical potentials of confined nitrogen in carbon slit pores and silica cylindrical pores at 77 K, and show that the results are in good agreement with those obtained by two conventional thermodynamic integration methods. Moreover, we also show that the proposed method can be particularly useful for determining vapor-liquid and vapor-solid coexistence curves and the triple point of the confined system.
基于Monte Carlo method的均衡度确定模型%Equilibrium Degree Determine Model based on the Monte Carlo method
Institute of Scientific and Technical Information of China (English)
朱颖; 程纪品
2012-01-01
The Monte Carlo method,also known as the statistical simulation method,is a very important kind of numerical methods guided by the theory of probability and statistics.It is applied to solve many computational problems using the random number （or pseudo-random number）.%蒙特卡罗方法（Monte Carlo method）,也称统计模拟方法,是一种以概率统计理论为指导的一类非常重要的数值计算方法,是指使用随机数（或更常见的伪随机数）来解决很多计算问题的方法,本文尝试建立警察服务平台的均衡度模型并用蒙特卡罗方法求解,实验结果可以满足一般的应用需求。
The FLUKA code for application of Monte Carlo methods to promote high precision ion beam therapy
Parodi, K; Cerutti, F; Ferrari, A; Mairani, A; Paganetti, H; Sommerer, F
2010-01-01
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...
Ma, X. B.; Qiu, R. M.; Chen, Y. X.
2017-02-01
Uncertainties regarding fission fractions are essential in understanding antineutrino flux predictions in reactor antineutrino experiments. A new Monte Carlo-based method to evaluate the covariance coefficients between isotopes is proposed. The covariance coefficients are found to vary with reactor burnup and may change from positive to negative because of balance effects in fissioning. For example, between 235U and 239Pu, the covariance coefficient changes from 0.15 to -0.13. Using the equation relating fission fraction and atomic density, consistent uncertainties in the fission fraction and covariance matrix were obtained. The antineutrino flux uncertainty is 0.55%, which does not vary with reactor burnup. The new value is about 8.3% smaller.
Azizi, Sajad
2016-01-01
We have investigated the quantum dynamics of two ultracold bosons inside an atomic waveguide for two different confinement geometries (cigar-shaped and toroidal waveguides) by quantum Monte Carlo methods. For quasi-1D gases, the confining potential of the waveguide leads to the so-called confinement induced resonance (CIR), results in the phase transition of the gas to the impenetrable bosonic regime (known as TG gas). In this regime the bosons repel each other strongly and behave like fermions. We reproduce CIR for a cigar-shaped waveguide and analyze the behavior of the system for different conditions. Moreover, our analysis demonstrates appearance of CIR for a toroidal waveguide. Particularly, we show that the resonance position is dependent on the size of the waveguide, which is in contrast to the cigar shaped waveguides for which it is universal.
Haviland, J. K.
1974-01-01
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.
An Efficient Monte Carlo Method for Modeling Radiative Transfer in Protoplanetary Disks
Kim, Stacy
2011-01-01
Monte Carlo methods have been shown to be effective and versatile in modeling radiative transfer processes to calculate model temperature profiles for protoplanetary disks. Temperatures profiles are important for connecting physical structure to observation and for understanding the conditions for planet formation and migration. However, certain areas of the disk such as the optically thick disk interior are under-sampled, or are of particular interest such as the snow line (where water vapor condenses into ice) and the area surrounding a protoplanet. To improve the sampling, photon packets can be preferentially scattered and reemitted toward the preferred locations at the cost of weighting packet energies to conserve the average energy flux. Here I report on the weighting schemes developed, how they can be applied to various models, and how they affect simulation mechanics and results. We find that improvements in sampling do not always imply similar improvements in temperature accuracies and calculation speeds.
A Monte Carlo method for critical systems in infinite volume: the planar Ising model
Herdeiro, Victor
2016-01-01
In this paper we propose a Monte Carlo method for generating finite-domain marginals of critical distributions of statistical models in infinite volume. The algorithm corrects the problem of the long-range effects of boundaries associated to generating critical distributions on finite lattices. It uses the advantage of scale invariance combined with ideas of the renormalization group in order to construct a type of "holographic" boundary condition that encodes the presence of an infinite volume beyond it. We check the quality of the distribution obtained in the case of the planar Ising model by comparing various observables with their infinite-plane prediction. We accurately reproduce planar two-, three- and four-point functions of spin and energy operators. We also define a lattice stress-energy tensor, and numerically obtain the associated conformal Ward identities and the Ising central charge.
Directory of Open Access Journals (Sweden)
A. Sosa
2012-03-01
Full Text Available 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.
Bayesian Inference for LISA Pathfinder using Markov Chain Monte Carlo Methods
Ferraioli, Luigi; Plagnol, Eric
2012-01-01
We present a parameter estimation procedure based on a Bayesian framework by applying a Markov Chain Monte Carlo algorithm to the calibration of the dynamical parameters of a space based gravitational wave detector. The method is based on the Metropolis-Hastings algorithm and a two-stage annealing treatment in order to ensure an effective exploration of the parameter space at the beginning of the chain. We compare two versions of the algorithm with an application to a LISA Pathfinder data analysis problem. The two algorithms share the same heating strategy but with one moving in coordinate directions using proposals from a multivariate Gaussian distribution, while the other uses the natural logarithm of some parameters and proposes jumps in the eigen-space of the Fisher Information matrix. The algorithm proposing jumps in the eigen-space of the Fisher Information matrix demonstrates a higher acceptance rate and a slightly better convergence towards the equilibrium parameter distributions in the application to...
Bianco, Federica B; Oh, Seung Man; Fierroz, David; Liu, Yuqian; Kewley, Lisa; Graur, Or
2015-01-01
We present the open-source Python code pyMCZ that determines oxygen abundance and its distribution from strong emission lines in the standard metallicity scales, based on the original IDL code of Kewley & Dopita (2002) with updates from Kewley & Ellison (2008), and expanded to include more recently developed scales. The standard strong-line diagnostics have been used to estimate the oxygen abundance in the interstellar medium through various emission line ratios in many areas of astrophysics, including galaxy evolution and supernova host galaxy studies. We introduce a Python implementation of these methods that, through Monte Carlo (MC) sampling, better characterizes the statistical reddening-corrected oxygen abundance confidence region. Given line flux measurements and their uncertainties, our code produces synthetic distributions for the oxygen abundance in up to 13 metallicity scales simultaneously, as well as for E(B-V), and estimates their median values and their 66% confidence regions. In additi...
Monte Carlo method for critical systems in infinite volume: The planar Ising model.
Herdeiro, Victor; Doyon, Benjamin
2016-10-01
In this paper we propose a Monte Carlo method for generating finite-domain marginals of critical distributions of statistical models in infinite volume. The algorithm corrects the problem of the long-range effects of boundaries associated to generating critical distributions on finite lattices. It uses the advantage of scale invariance combined with ideas of the renormalization group in order to construct a type of "holographic" boundary condition that encodes the presence of an infinite volume beyond it. We check the quality of the distribution obtained in the case of the planar Ising model by comparing various observables with their infinite-plane prediction. We accurately reproduce planar two-, three-, and four-point of spin and energy operators. We also define a lattice stress-energy tensor, and numerically obtain the associated conformal Ward identities and the Ising central charge.
Nonequilibrium hypersonic flows simulations with asymptotic-preserving Monte Carlo methods
Ren, Wei; Liu, Hong; Jin, Shi
2014-12-01
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.
Armas-Pérez, Julio C; Hernández-Ortiz, Juan P; de Pablo, Juan J
2015-12-28
A theoretically informed Monte Carlo method is proposed for Monte Carlo simulation of liquid crystals on the basis of theoretical representations in terms of coarse-grained free energy functionals. The free energy functional is described in the framework of the Landau-de Gennes formalism. A piecewise finite element discretization is used to approximate the alignment field, thereby providing an excellent geometrical representation of curved interfaces and accurate integration of the free energy. The method is suitable for situations where the free energy functional includes highly non-linear terms, including chirality or high-order deformation modes. The validity of the method is established by comparing the results of Monte Carlo simulations to traditional Ginzburg-Landau minimizations of the free energy using a finite difference scheme, and its usefulness is demonstrated in the context of simulations of chiral liquid crystal droplets with and without nanoparticle inclusions.
Multi-Physics Markov Chain Monte Carlo Methods for Subsurface Flows
Rigelo, J.; Ginting, V.; Rahunanthan, A.; Pereira, F.
2014-12-01
For CO2 sequestration in deep saline aquifers, contaminant transport in subsurface, and oil or gas recovery, we often need to forecast flow patterns. Subsurface characterization is a critical and challenging step in flow forecasting. To characterize subsurface properties we establish a statistical description of the subsurface properties that are conditioned to existing dynamic and static data. A Markov Chain Monte Carlo (MCMC) algorithm is used in a Bayesian statistical description to reconstruct the spatial distribution of rock permeability and porosity. The MCMC algorithm requires repeatedly solving a set of nonlinear partial differential equations describing displacement of fluids in porous media for different values of permeability and porosity. The time needed for the generation of a reliable MCMC chain using the algorithm can be too long to be practical for flow forecasting. In this work we develop fast and effective computational methods for generating MCMC chains in the Bayesian framework for the subsurface characterization. Our strategy consists of constructing a family of computationally inexpensive preconditioners based on simpler physics as well as on surrogate models such that the number of fine-grid simulations is drastically reduced in the generated MCMC chains. In particular, we introduce a huff-puff technique as screening step in a three-stage multi-physics MCMC algorithm to reduce the number of expensive final stage simulations. The huff-puff technique in the algorithm enables a better characterization of subsurface near wells. We assess the quality of the proposed multi-physics MCMC methods by considering Monte Carlo simulations for forecasting oil production in an oil reservoir.
Development of a software package for solid-angle calculations using the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Zhang, Jie, E-mail: zhangjie_scu@163.com [Key Laboratory for Neutron Physics of Chinese Academy of Engineering Physics, Institute of Nuclear Physics and Chemistry, Mianyang 621900 (China); College of Physical Science and Technology, Sichuan University, Chengdu 610064 (China); Chen, Xiulian [College of Physical Science and Technology, Sichuan University, Chengdu 610064 (China); Zhang, Changsheng [Key Laboratory for Neutron Physics of Chinese Academy of Engineering Physics, Institute of Nuclear Physics and Chemistry, Mianyang 621900 (China); Li, Gang [College of Physical Science and Technology, Sichuan University, Chengdu 610064 (China); Xu, Jiayun, E-mail: xjy@scu.edu.cn [College of Physical Science and Technology, Sichuan University, Chengdu 610064 (China); Sun, Guangai [Key Laboratory for Neutron Physics of Chinese Academy of Engineering Physics, Institute of Nuclear Physics and Chemistry, Mianyang 621900 (China)
2014-02-01
Solid-angle calculations play an important role in the absolute calibration of radioactivity measurement systems and in the determination of the activity of radioactive sources, which are often complicated. In the present paper, a software package is developed to provide a convenient tool for solid-angle calculations in nuclear physics. The proposed software calculates solid angles using the Monte Carlo method, in which a new type of variance reduction technique was integrated. The package, developed under the environment of Microsoft Foundation Classes (MFC) in Microsoft Visual C{sup ++}, has a graphical user interface, in which, the visualization function is integrated in conjunction with OpenGL. One advantage of the proposed software package is that it can calculate the solid angle subtended by a detector with different geometric shapes (e.g., cylinder, square prism, regular triangular prism or regular hexagonal prism) to a point, circular or cylindrical source without any difficulty. The results obtained from the proposed software package were compared with those obtained from previous studies and calculated using Geant4. It shows that the proposed software package can produce accurate solid-angle values with a greater computation speed than Geant4. -- Highlights: • This software package (SAC) can give accurate solid-angle values. • SAC calculate solid angles using the Monte Carlo method and it has higher computation speed than Geant4. • A simple but effective variance reduction technique which was put forward by the authors has been applied in SAC. • A visualization function and a graphical user interface are also integrated in SAC.
A Monte Carlo Method for Summing Modeled and Background Pollutant Concentrations.
Dhammapala, Ranil; Bowman, Clint; Schulte, Jill
2017-02-23
Air quality analyses for permitting new pollution sources often involve modeling dispersion of pollutants using models like AERMOD. Representative background pollutant concentrations must be added to modeled concentrations to determine compliance with air quality standards. Summing 98(th) (or 99(th)) percentiles of two independent distributions that are unpaired in time, overestimates air quality impacts and could needlessly burden sources with restrictive permit conditions. This problem is exacerbated when emissions and background concentrations peak during different seasons. Existing methods addressing this matter either require much input data, disregard source and background seasonality, or disregard the variability of the background by utilizing a single concentration for each season, month, hour-of-day, day-of-week or wind direction. Availability of representative background concentrations are another limitation. Here we report on work to improve permitting analyses, with the development of (1) daily gridded, background concentrations interpolated from 12km-CMAQ forecasts and monitored data. A two- step interpolation reproduced measured background concentrations to within 6.2%; and (2) a Monte Carlo (MC) method to combine AERMOD output and background concentrations while respecting their seasonality. The MC method randomly combines, with replacement, data from the same months, and calculates 1000 estimates of the 98(th) or 99(th) percentiles. The design concentration of background + new source is the median of these 1000 estimates. We found that the AERMOD design value (DV) + background DV lay at the upper end of the distribution of these thousand 99(th) percentiles, while measured DVs were at the lower end. Our MC method sits between these two metrics and is sufficiently protective of public health in that it overestimates design concentrations somewhat. We also calculated probabilities of exceeding specified thresholds at each receptor, better informing
Physics and computer architecture informed improvements to the Implicit Monte Carlo method
Long, Alex Roberts
The Implicit Monte Carlo (IMC) method has been a standard method for thermal radiative transfer for the past 40 years. In this time, the hydrodynamics methods that are coupled to IMC have evolved and improved, as have the supercomputers used to run large simulations with IMC. Several modern hydrodynamics methods use unstructured non-orthogonal meshes and high-order spatial discretizations. The IMC method has been used primarily with simple Cartesian meshes and always has a first order spatial discretization. Supercomputers are now made up of compute nodes that have a large number of cores. Current IMC parallel methods have significant problems with load imbalance. To utilize many core systems, algorithms must move beyond simple spatial decomposition parallel algorithms. To make IMC better suited for large scale multiphysics simulations in high energy density physics, new spatial discretizations and parallel strategies are needed. Several modifications are made to the IMC method to facilitate running on node-centered, unstructured tetrahedral meshes. These modifications produce results that converge to the expected solution under mesh refinement. A new finite element IMC method is also explored on these meshes, which offer a simulation runtime benefit but does not perform correctly in the diffusion limit. A parallel algorithm that utilizes on-node parallelism and respects memory hierarchies is studied. This method scales almost linearly when using physical cores on a node and benefits from multiple threads per core. A multi-compute node algorithm for domain decomposed IMC that passes mesh data instead of particles is explored as a means to solve load balance issues. This method scales better than the particle passing method on highly scattering problems with short time steps.
Solution of deterministic-stochastic epidemic models by dynamical Monte Carlo method
Aièllo, O. E.; Haas, V. J.; daSilva, M. A. A.; Caliri, A.
2000-07-01
This work is concerned with dynamical Monte Carlo (MC) method and its application to models originally formulated in a continuous-deterministic approach. Specifically, a susceptible-infected-removed-susceptible (SIRS) model is used in order to analyze aspects of the dynamical MC algorithm and achieve its applications in epidemic contexts. We first examine two known approaches to the dynamical interpretation of the MC method and follow with the application of one of them in the SIRS model. The working method chosen is based on the Poisson process where hierarchy of events, properly calculated waiting time between events, and independence of the events simulated, are the basic requirements. To verify the consistence of the method, some preliminary MC results are compared against exact steady-state solutions and other general numerical results (provided by Runge-Kutta method): good agreement is found. Finally, a space-dependent extension of the SIRS model is introduced and treated by MC. The results are interpreted under and in accordance with aspects of the herd-immunity concept.
A deterministic alternative to the full configuration interaction quantum Monte Carlo method
Tubman, Norm M.; Lee, Joonho; Takeshita, Tyler Y.; Head-Gordon, Martin; Whaley, K. Birgitta
2016-07-01
Development of exponentially scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, is a useful algorithm that allows exact diagonalization through stochastically sampling determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, along with a stochastic projected wave function, to find the important parts of Hilbert space. However, the stochastic representation of the wave function is not required to search Hilbert space efficiently, and here we describe a highly efficient deterministic method that can achieve chemical accuracy for a wide range of systems, including the difficult Cr2 molecule. We demonstrate for systems like Cr2 that such calculations can be performed in just a few cpu hours which makes it one of the most efficient and accurate methods that can attain chemical accuracy for strongly correlated systems. In addition our method also allows efficient calculation of excited state energies, which we illustrate with benchmark results for the excited states of C2.
Implementation of the probability table method in a continuous-energy Monte Carlo code system
Energy Technology Data Exchange (ETDEWEB)
Sutton, T.M.; Brown, F.B. [Lockheed Martin Corp., Schenectady, NY (United States)
1998-10-01
RACER is a particle-transport Monte Carlo code that utilizes a continuous-energy treatment for neutrons and neutron cross section data. Until recently, neutron cross sections in the unresolved resonance range (URR) have been treated in RACER using smooth, dilute-average representations. This paper describes how RACER has been modified to use probability tables to treat cross sections in the URR, and the computer codes that have been developed to compute the tables from the unresolved resonance parameters contained in ENDF/B data files. A companion paper presents results of Monte Carlo calculations that demonstrate the effect of the use of probability tables versus the use of dilute-average cross sections for the URR. The next section provides a brief review of the probability table method as implemented in the RACER system. The production of the probability tables for use by RACER takes place in two steps. The first step is the generation of probability tables from the nuclear parameters contained in the ENDF/B data files. This step, and the code written to perform it, are described in Section 3. The tables produced are at energy points determined by the ENDF/B parameters and/or accuracy considerations. The tables actually used in the RACER calculations are obtained in the second step from those produced in the first. These tables are generated at energy points specific to the RACER calculation. Section 4 describes this step and the code written to implement it, as well as modifications made to RACER to enable it to use the tables. Finally, some results and conclusions are presented in Section 5.
Predicting low-temperature free energy landscapes with flat-histogram Monte Carlo methods
Mahynski, Nathan A.; Blanco, Marco A.; Errington, Jeffrey R.; Shen, Vincent K.
2017-02-01
We present a method for predicting the free energy landscape of fluids at low temperatures from flat-histogram grand canonical Monte Carlo simulations performed at higher ones. We illustrate our approach for both pure and multicomponent systems using two different sampling methods as a demonstration. This allows us to predict the thermodynamic behavior of systems which undergo both first order and continuous phase transitions upon cooling using simulations performed only at higher temperatures. After surveying a variety of different systems, we identify a range of temperature differences over which the extrapolation of high temperature simulations tends to quantitatively predict the thermodynamic properties of fluids at lower ones. Beyond this range, extrapolation still provides a reasonably well-informed estimate of the free energy landscape; this prediction then requires less computational effort to refine with an additional simulation at the desired temperature than reconstruction of the surface without any initial estimate. In either case, this method significantly increases the computational efficiency of these flat-histogram methods when investigating thermodynamic properties of fluids over a wide range of temperatures. For example, we demonstrate how a binary fluid phase diagram may be quantitatively predicted for many temperatures using only information obtained from a single supercritical state.
Improving Higgs coupling measurements through ZZ Fusion at the ILC
Han, Tao; Qian, Zhuoni; Sayre, Joshua
2015-01-01
We evaluate the $e^- e^+ \\to e^- e^+ +h $ process through the $ZZ$ fusion channel at the International Linear Collider (ILC) operating at $500$ GeV and $1$ TeV center of mass energies. We perform realistic simulations on the signal process and background processes. With judicious kinematic cuts, we find that the inclusive cross section can be measured to $2.9\\%$ after combining the $500$ GeV at $500 ~\\text{fb}^{-1}$ and $1$ TeV at $1~ \\text{ab}^{-1}$ runs. A multivariate log-likelihood analysis further improves the precision of the cross section measurement to $2.3\\%$. We discuss the overall improvement to model-independent Higgs width and coupling determinations and demonstrate the use of different channels in distinguishing new physics effects in Higgs physics. Our study demonstrates the importance of the $ZZ$ fusion channel to Higgs precision physics, which has often been neglected in the literature.
Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks
Ben Hammouda, Chiheb
2015-05-12
In biochemical systems, stochastic e↵ects can be caused by the presence of small numbers of certain reactant molecules. In this setting, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti↵ness. For such problems, the existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap method, can be very slow. Therefore, implicit tau-leap approxima- tions were developed to improve the numerical stability and provide more e cient simulation algorithms for these systems. One of the interesting tasks for SRNs is to approximate the expected values of some observables of the process at a certain fixed time T. This is can be achieved using Monte Carlo (MC) techniques. However, in a recent work, Anderson and Higham in 2013, proposed a more computationally e cient method which combines multi-level Monte Carlo (MLMC) technique with explicit tau-leap schemes. In this MSc thesis, we propose new fast stochastic algorithm, particularly designed 5 to address sti↵ systems, for approximating the expected values of some observables of SRNs. In fact, we take advantage of the idea of MLMC techniques and drift-implicit tau-leap approximation to construct a drift-implicit MLMC tau-leap estimator. In addition to accurately estimating the expected values of a given observable of SRNs at a final time T , our proposed estimator ensures the numerical stability with a lower cost than the MLMC explicit tau-leap algorithm, for systems including simultane- ously fast and slow species. The key contribution of our work is the coupling of two drift-implicit tau-leap paths, which is the basic brick for
Calculation of photon pulse height distribution using deterministic and Monte Carlo methods
Akhavan, Azadeh; Vosoughi, Naser
2015-12-01
Radiation transport techniques which are used in radiation detection systems comprise one of two categories namely probabilistic and deterministic. However, probabilistic methods are typically used in pulse height distribution simulation by recreating the behavior of each individual particle, the deterministic approach, which approximates the macroscopic behavior of particles by solution of Boltzmann transport equation, is being developed because of its potential advantages in computational efficiency for complex radiation detection problems. In current work linear transport equation is solved using two methods including collided components of the scalar flux algorithm which is applied by iterating on the scattering source and ANISN deterministic computer code. This approach is presented in one dimension with anisotropic scattering orders up to P8 and angular quadrature orders up to S16. Also, multi-group gamma cross-section library required for this numerical transport simulation is generated in a discrete appropriate form. Finally, photon pulse height distributions are indirectly calculated by deterministic methods that approvingly compare with those from Monte Carlo based codes namely MCNPX and FLUKA.
Hueser, J. E.; Brock, F. J.; Melfi, L. T., Jr.; Bird, G. A.
1984-01-01
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).
Energy Technology Data Exchange (ETDEWEB)
Debe, D.A.; Carlson, M.J.; Chan, S.I; Goddard, W.A. III [California Inst. of Tech., Pasadena, CA (United States); Sadanobu, Jiro [Teijin Limited, Iwakuni, Yamaguchi (Japan). Polymer and Materials Research Labs.
1999-04-15
The authors present the generate-and-select hierarchy for tertiary protein structure prediction. The foundation of this hierarchy is the Restrained Generic Protein (RGP) Direct Monte Carlo method. The RGP method is a highly efficient off-lattice residue buildup procedure that can quickly generate the complete set of topologies that satisfy a very small number of interresidue distance restraints. For three restraints uniformly distributed in a 72-residue protein, the authors demonstrate that the size of this set is {approximately}10{sup 4}. The RGP method can generate this set of structures in less than 1 h using a Silicon Graphics R10000 single processor workstation. Following structure generation, a simple criterion that measures the burial of hydrophobic and hydrophilic residues can reliably select a reduced set of {approximately}10{sup 2} structures that contains the native topology. A minimization of the structures in the reduced set typically ranks the native topology in the five lowest energy folds. Thus, using this hierarchical approach, the authors suggest that de novo prediction of moderate resolution globular protein structure can be achieved in just a few hours on a single processor workstation.
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
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
2014-06-07
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.
Guerra, Marta L.
2009-02-23
We calculate the efficiency of a rejection-free dynamic Monte Carlo method for d -dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential r-p. Theoretically we find the algorithmic efficiency in the limit of low temperatures and/or high densities is asymptotically proportional to ρ (p+2) /2 T-d/2 with the particle density ρ and the temperature T. Dynamic Monte Carlo simulations are performed in one-, two-, and three-dimensional systems with different powers p, and the results agree with the theoretical predictions. © 2009 The American Physical Society.
Yong, Wang; Wen-Gan, Ma; Xiao-Zhou, Li; Lei, Guo
2016-01-01
In this paper we present the full NLO QCD + NLO EW corrections to the $Z$-boson pair production in association with a hard jet at the LHC. The subsequent $Z$-boson leptonic decays are included by adopting both the naive NWA and MadSpin methods for comparison. Since the $ZZ+{\\rm jet}$ production is an important background for single Higgs boson production and new physics search at hadron colliders, the theoretical predictions with high accuracy for the hadronic production of $ZZ+{\\rm jet}$ are necessary. We present the numerical results of the integrated cross section and various kinematic distributions of final particles, and conclude that it is necessary to take into account the spin correlation and finite width effects from the $Z$-boson leptonic decays. We also find that the NLO EW correction is quantitatively nonnegligible in matching the experimental accuracy at the LHC, particularly is significant in high transverse momentum region.
Model-independent Higgs coupling measurements at the LHC using the H \\to ZZ \\to 4l lineshape
Logan, Heather E
2011-01-01
We show that combining a direct measurement of the Higgs total width from the H \\to ZZ \\to 4l lineshape with Higgs signal rate measurements allows Higgs couplings to be extracted in a model-independent way from CERN Large Hadron Collider (LHC) data. Using existing experimental studies with 30 fb-1 at one detector of the 14 TeV LHC, we show that the couplings-squared of a 190 GeV Higgs to WW, ZZ, and gg can be extracted with statistical precisions of about 10%, and a 95% confidence level upper limit on an unobserved component of the Higgs decay width of about 22% of the SM Higgs width can be set. The method can also be applied for heavier Higgs masses.
欧式期权定价的Monte-Carlo方法%Monte-Carlo methods for Pricing European-style options
Institute of Scientific and Technical Information of China (English)
张丽虹
2015-01-01
We discuss Monte-Carlo methods for pricing European options.Based on the famous Black-Scholes model,we first discuss the Monte-Carlo simulation method to pricing standard European options according to Risk neutral theory.Methods to improve the Monte-Carlo simulation performance including introducing control variates and antithetic variates are also discussed.Finally we apply the proposed Monte-Carlo methods to price the European binary options,European lookback options and European Asian options.%讨论各种欧式期权价格的Monte-Carlo方法。根据Black-Scholes期权定价模型以及风险中性理论，首先详细地讨论如何利用Monte-Carlo方法来计算标准欧式期权价格；然后讨论如何引入控制变量以及对称变量来提高Monte-Carlo方法的精确性；最后用Monte-Carlo方法来计算标准欧式期权、欧式—两值期权、欧式—回望期权以及欧式—亚式期权的价格，并讨论相关方法的优缺点。
Institute of Scientific and Technical Information of China (English)
Jiang Wei; Xiang Haige
2004-01-01
This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.
DEFF Research Database (Denmark)
Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe;
2010-01-01
limit requirements. The method combines the Genetic Algorithm (GA), gradient-based constrained nonlinear optimization algorithm and sequential Monte Carlo simulation (MCS). The GA searches for the optimal locations and capacities of WTs. The gradient-based optimization finds the optimal power factor...
Kadoura, Ahmad
2011-06-06
Lennard‐Jones (L‐J) and Buckingham exponential‐6 (exp‐6) potential models were used to produce isotherms for methane at temperatures below and above critical one. Molecular simulation approach, particularly Monte Carlo simulations, were employed to create these isotherms working with both canonical and Gibbs ensembles. Experiments in canonical ensemble with each model were conducted to estimate pressures at a range of temperatures above methane critical temperature. Results were collected and compared to experimental data existing in literature; both models showed an elegant agreement with the experimental data. In parallel, experiments below critical temperature were run in Gibbs ensemble using L‐J model only. Upon comparing results with experimental ones, a good fit was obtained with small deviations. The work was further developed by adding some statistical studies in order to achieve better understanding and interpretation to the estimated quantities by the simulation. Methane phase diagrams were successfully reproduced by an efficient molecular simulation technique with different potential models. This relatively simple demonstration shows how powerful molecular simulation methods could be, hence further applications on more complicated systems are considered. Prediction of phase behavior of elemental sulfur in sour natural gases has been an interesting and challenging field in oil and gas industry. Determination of elemental sulfur solubility conditions helps avoiding all kinds of problems caused by its dissolution in gas production and transportation processes. For this purpose, further enhancement to the methods used is to be considered in order to successfully simulate elemental sulfur phase behavior in sour natural gases mixtures.
Institute of Scientific and Technical Information of China (English)
ZHANG Jun; GUO Fan
2015-01-01
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system’s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system’s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
Cu-Au Alloys Using Monte Carlo Simulations and the BFS Method for Alloys
Bozzolo, Guillermo; Good, Brian; Ferrante, John
1996-01-01
Semi empirical methods have shown considerable promise in aiding in the calculation of many properties of materials. Materials used in engineering applications have defects that occur for various reasons including processing. In this work we present the first application of the BFS method for alloys to describe some aspects of microstructure due to processing for the Cu-Au system (Cu-Au, CuAu3, and Cu3Au). We use finite temperature Monte Carlo calculations, in order to show the influence of 'heat treatment' in the low-temperature phase of the alloy. Although relatively simple, it has enough features that could be used as a first test of the reliability of the technique. The main questions to be answered in this work relate to the existence of low temperature ordered structures for specific concentrations, for example, the ability to distinguish between rather similar phases for equiatomic alloys (CuAu I and CuAu II, the latter characterized by an antiphase boundary separating two identical phases).
Monte Carlo Methods for Top-k Personalized PageRank Lists and Name Disambiguation
Avrachenkov, Konstantin; Nemirovsky, Danil A; Smirnova, Elena; Sokol, Marina
2010-01-01
We study a problem of quick detection of top-k Personalized PageRank lists. This problem has a number of important applications such as finding local cuts in large graphs, estimation of similarity distance and name disambiguation. In particular, we apply our results to construct efficient algorithms for the person name disambiguation problem. We argue that when finding top-k Personalized PageRank lists two observations are important. Firstly, it is crucial that we detect fast the top-k most important neighbours of a node, while the exact order in the top-k list as well as the exact values of PageRank are by far not so crucial. Secondly, a little number of wrong elements in top-k lists do not really degrade the quality of top-k lists, but it can lead to significant computational saving. Based on these two key observations we propose Monte Carlo methods for fast detection of top-k Personalized PageRank lists. We provide performance evaluation of the proposed methods and supply stopping criteria. Then, we apply ...
Systematic hierarchical coarse-graining with the inverse Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Lyubartsev, Alexander P., E-mail: alexander.lyubartsev@mmk.su.se [Division of Physical Chemistry, Arrhenius Laboratory, Stockholm University, S 106 91 Stockholm (Sweden); Naômé, Aymeric, E-mail: aymeric.naome@unamur.be [Division of Physical Chemistry, Arrhenius Laboratory, Stockholm University, S 106 91 Stockholm (Sweden); UCPTS Division, University of Namur, 61 Rue de Bruxelles, B 5000 Namur (Belgium); Vercauteren, Daniel P., E-mail: daniel.vercauteren@unamur.be [UCPTS Division, University of Namur, 61 Rue de Bruxelles, B 5000 Namur (Belgium); Laaksonen, Aatto, E-mail: aatto@mmk.su.se [Division of Physical Chemistry, Arrhenius Laboratory, Stockholm University, S 106 91 Stockholm (Sweden); Science for Life Laboratory, 17121 Solna (Sweden)
2015-12-28
We outline our coarse-graining strategy for linking micro- and mesoscales of soft matter and biological systems. The method is based on effective pairwise interaction potentials obtained in detailed ab initio or classical atomistic Molecular Dynamics (MD) simulations, which can be used in simulations at less accurate level after scaling up the size. The effective potentials are obtained by applying the inverse Monte Carlo (IMC) method [A. P. Lyubartsev and A. Laaksonen, Phys. Rev. E 52(4), 3730–3737 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. An in-house software package MagiC is developed to obtain the effective potentials for arbitrary molecular systems. In this work we compute effective potentials to model DNA-protein interactions (bacterial LiaR regulator bound to a 26 base pairs DNA fragment) at physiological salt concentration at a coarse-grained (CG) level. Normally the IMC CG pair-potentials are used directly as look-up tables but here we have fitted them to five Gaussians and a repulsive wall. Results show stable association between DNA and the model protein as well as similar position fluctuation profile.
Verification of Transformer Restricted Earth Fault Protection by using the Monte Carlo Method
Directory of Open Access Journals (Sweden)
KRSTIVOJEVIC, J. P.
2015-08-01
Full Text Available The results of a comprehensive investigation of the influence of current transformer (CT saturation on restricted earth fault (REF protection during power transformer magnetization inrush are presented. Since the inrush current during switch-on of unloaded power transformer is stochastic, its values are obtained by: (i laboratory measurements and (ii calculations based on the input data obtained by the Monte Carlo (MC simulation. To make a detailed assessment of the current transformer performance the uncertain input data for the CT model were obtained by applying the MC method. In this way, different levels of remanent flux in CT core are taken into consideration. By the generated CT secondary currents, the algorithm for REF protection based on phase comparison in time domain is tested. On the basis of the obtained results, a method of adjustment of the triggering threshold in order to ensure safe operation during transients, and thereby improve the algorithm security, has been proposed. The obtained results indicate that power transformer REF protection would be enhanced by using the proposed adjustment of triggering threshold in the algorithm which is based on phase comparison in time domain.
Calculation of Credit Valuation Adjustment Based on Least Square Monte Carlo Methods
Directory of Open Access Journals (Sweden)
Qian Liu
2015-01-01
Full Text Available Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.
Systematic hierarchical coarse-graining with the inverse Monte Carlo method
Lyubartsev, Alexander P.; Naômé, Aymeric; Vercauteren, Daniel P.; Laaksonen, Aatto
2015-12-01
We outline our coarse-graining strategy for linking micro- and mesoscales of soft matter and biological systems. The method is based on effective pairwise interaction potentials obtained in detailed ab initio or classical atomistic Molecular Dynamics (MD) simulations, which can be used in simulations at less accurate level after scaling up the size. The effective potentials are obtained by applying the inverse Monte Carlo (IMC) method [A. P. Lyubartsev and A. Laaksonen, Phys. Rev. E 52(4), 3730-3737 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. An in-house software package MagiC is developed to obtain the effective potentials for arbitrary molecular systems. In this work we compute effective potentials to model DNA-protein interactions (bacterial LiaR regulator bound to a 26 base pairs DNA fragment) at physiological salt concentration at a coarse-grained (CG) level. Normally the IMC CG pair-potentials are used directly as look-up tables but here we have fitted them to five Gaussians and a repulsive wall. Results show stable association between DNA and the model protein as well as similar position fluctuation profile.
Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods
Energy Technology Data Exchange (ETDEWEB)
Godfrey, Andrew T [ORNL; Gehin, Jess C [ORNL; Bekar, Kursat B [ORNL; Celik, Cihangir [ORNL
2014-01-01
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.
Energy Technology Data Exchange (ETDEWEB)
Agudelo-Giraldo, J.D. [PCM Computational Applications, Universidad Nacional de Colombia-Sede Manizales, Km. 9 vía al aeropuerto, Manizales (Colombia); Restrepo-Parra, E., E-mail: erestrepopa@unal.edu.co [PCM Computational Applications, Universidad Nacional de Colombia-Sede Manizales, Km. 9 vía al aeropuerto, Manizales (Colombia); Restrepo, J. [Grupo de Magnetismo y Simulación, Instituto de Física, Universidad de Antioquia, A.A. 1226, Medellín (Colombia)
2015-10-01
The Metropolis algorithm and the classical Heisenberg approximation were implemented by the Monte Carlo method to design a computational approach to the magnetization and resistivity of La{sub 2/3}Ca{sub 1/3}MnO{sub 3}, which depends on the Mn ion vacancies as the external magnetic field increases. This compound is ferromagnetic, and it exhibits the colossal magnetoresistance (CMR) effect. The monolayer was built with L×L×d dimensions, and it had L=30 umc (units of magnetic cells) for its dimension in the x–y plane and was d=12 umc in thickness. The Hamiltonian that was used contains interactions between first neighbors, the magnetocrystalline anisotropy effect and the external applied magnetic field response. The system that was considered contains mixed-valence bonds: Mn{sup 3+eg’}–O–Mn{sup 3+eg}, Mn{sup 3+eg}–O–Mn{sup 4+d3} and Mn{sup 3+eg’}–O–Mn{sup 4+d3}. The vacancies were placed randomly in the sample, replacing any type of Mn ion. The main result shows that without vacancies, the transitions T{sub C} (Curie temperature) and T{sub MI} (metal–insulator temperature) are similar, whereas with the increase in the vacancy percentage, T{sub MI} presented lower values than T{sub C}. This situation is caused by the competition between the external magnetic field, the vacancy percentage and the magnetocrystalline anisotropy, which favors the magnetoresistive effect at temperatures below T{sub MI}. Resistivity loops were also observed, which shows a direct correlation with the hysteresis loops of magnetization at temperatures below T{sub C}. - Highlights: • Changes in the resistivity of FM materials as a function of the temperature and external magnetic field can be obtained by the Monte Carlo method, Metropolis algorithm, classical Heisenberg and Kronig–Penney approximation for magnetic clusters. • Increases in the magnetoresistive effect were observed at temperatures below T{sub MI} by the vacancies effect. • The resistive hysteresis
Directory of Open Access Journals (Sweden)
Joko Siswantoro
2014-11-01
Full Text Available Volume is one of important issues in the production and processing of food product. Traditionally, volume measurement can be performed using water displacement method based on Archimedes’ principle. Water displacement method is inaccurate and considered as destructive method. Computer vision offers an accurate and nondestructive method in measuring volume of food product. This paper proposes algorithm for volume measurement of irregular shape food product using computer vision based on Monte Carlo method. Five images of object were acquired from five different views and then processed to obtain the silhouettes of object. From the silhouettes of object, Monte Carlo method was performed to approximate the volume of object. The simulation result shows that the algorithm produced high accuracy and precision for volume measurement.
On-the-fly nuclear data processing methods for Monte Carlo simulations of fast spectrum systems
Energy Technology Data Exchange (ETDEWEB)
Walsh, Jon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-08-31
The presentation summarizes work performed over summer 2015 related to Monte Carlo simulations. A flexible probability table interpolation scheme has been implemented and tested with results comparing favorably to the continuous phase-space on-the-fly approach.
Olynick, David P.; Hassan, H. A.; Moss, James N.
1988-01-01
A grid generation and adaptation procedure based on the method of transfinite interpolation is incorporated into the Direct Simulation Monte Carlo Method of Bird. In addition, time is advanced based on a local criterion. The resulting procedure is used to calculate steady flows past wedges and cones. Five chemical species are considered. In general, the modifications result in a reduced computational effort. Moreover, preliminary results suggest that the simulation method is time step dependent if requirements on cell sizes are not met.
Energy Technology Data Exchange (ETDEWEB)
Favorite, J.A.
1999-09-01
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.
Chen, Hsing-Ta; Cohen, Guy; Reichman, David R.
2017-02-01
In this second paper of a two part series, we present extensive benchmark results for two different inchworm Monte Carlo expansions for the spin-boson model. Our results are compared to previously developed numerically exact approaches for this problem. A detailed discussion of convergence and error propagation is presented. Our results and analysis allow for an understanding of the benefits and drawbacks of inchworm Monte Carlo compared to other approaches for exact real-time non-adiabatic quantum dynamics.
Chen, Hsing-Ta; Reichman, David R
2016-01-01
In this second paper of a two part series, we present extensive benchmark results for two different inchworm Monte Carlo expansions for the spin-boson model. Our results are compared to previously developed numerically exact approaches for this problem. A detailed discussion of convergence and error propagation is presented. Our results and analysis allow for an understanding of the benefits and drawbacks of inchworm Monte Carlo compared to other approaches for exact real-time non-adiabatic quantum dynamics.
Zhu, Caigang; Liu, Quan
2012-01-01
We present a hybrid method that combines a multilayered scaling method and a perturbation method to speed up the Monte Carlo simulation of diffuse reflectance from a multilayered tissue model with finite-size tumor-like heterogeneities. The proposed method consists of two steps. In the first step, a set of photon trajectory information generated from a baseline Monte Carlo simulation is utilized to scale the exit weight and exit distance of survival photons for the multilayered tissue model. In the second step, another set of photon trajectory information, including the locations of all collision events from the baseline simulation and the scaling result obtained from the first step, is employed by the perturbation Monte Carlo method to estimate diffuse reflectance from the multilayered tissue model with tumor-like heterogeneities. Our method is demonstrated to shorten simulation time by several orders of magnitude. Moreover, this hybrid method works for a larger range of probe configurations and tumor models than the scaling method or the perturbation method alone.
Energy Technology Data Exchange (ETDEWEB)
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); 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); 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); 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)
2013-06-07
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.; Mao, S. F.; Zhang, Z. M.; Jin, H.; Yoshikawa, H.; Tanuma, S.; Ding, Z. J.
2013-06-01
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 SiO2 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.
Efendiev, Yalchin R.
2013-08-21
In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed multiscale finite element methods and (2) a novel use of mixed multiscale finite element methods within multilevel Monte Carlo techniques to speed up the computations. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. In this paper, we consider two ensemble level mixed multiscale finite element methods: (1) the no-local-solve-online ensemble level method (NLSO); and (2) the local-solve-online ensemble level method (LSO). The first approach was proposed in Aarnes and Efendiev (SIAM J. Sci. Comput. 30(5):2319-2339, 2008) while the second approach is new. Both mixed multiscale methods use a number of snapshots of the permeability media in generating multiscale basis functions. As a result, in the off-line stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method, one uses the whole set of precomputed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method, one uses the precomputed functions to construct a multiscale basis for a particular realization. With this basis, the solution corresponding to this particular realization is approximated in LSO mixed multiscale finite element method (MsFEM). In both approaches, the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to precompute a multiscale basis. In this paper, ensemble level multiscale methods are used in multilevel Monte Carlo methods (Giles 2008a, Oper.Res. 56(3):607-617, b). In multilevel Monte Carlo methods, more accurate
Absorbed Dose Calculations Using Mesh-based Human Phantoms And Monte Carlo Methods
Kramer, Richard
2011-08-01
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.
Velazquez, L.; Castro-Palacio, J. C.
2015-03-01
Velazquez and Curilef [J. Stat. Mech. (2010) P02002, 10.1088/1742-5468/2010/02/P02002; J. Stat. Mech. (2010) P04026, 10.1088/1742-5468/2010/04/P04026] have proposed a methodology to extend Monte Carlo algorithms that are based on canonical ensemble. According to our previous study, their proposal allows us to overcome slow sampling problems in systems that undergo any type of temperature-driven phase transition. After a comprehensive review about ideas and connections of this framework, we discuss the application of a reweighting technique to improve the accuracy of microcanonical calculations, specifically, the well-known multihistograms method of Ferrenberg and Swendsen [Phys. Rev. Lett. 63, 1195 (1989), 10.1103/PhysRevLett.63.1195]. As an example of application, we reconsider the study of the four-state Potts model on the square lattice L ×L with periodic boundary conditions. This analysis allows us to detect the existence of a very small latent heat per site qL during the occurrence of temperature-driven phase transition of this model, whose size dependence seems to follow a power law qL(L ) ∝(1/L ) z with exponent z ≃0 .26 ±0 .02. Discussed is the compatibility of these results with the continuous character of temperature-driven phase transition when L →+∞ .
Yet another application of the Monte Carlo method for modeling in the field of biomedicine.
Cassia-Moura, R; Sousa, C S; Ramos, A D; Coelho, L C B B; Valença, M M
2005-06-01
By means of Monte Carlo simulations performed in the C programming language, an example of scientific programming for the generation of pseudorandom numbers relevant to both teaching and research in the field of biomedicine is presented. The relatively simple algorithm proposed makes possible the statistical analysis of sequences of random numbers. The following three generators of pseudorandom numbers were used: the rand function contained in the stdlib.h library of the C programming language, Marsaglia's generator, and a chaotic function. The statistical properties of the sequences generated were compared, identical parameter values being adopted for this purpose. The properties of two estimators in finite samples of the pseudorandom numbers were also evaluated and, under suitable conditions, both the maximum-likelihood and method of moments proved to be good estimators. The findings demonstrated that the proposed algorithm appears to be suitable for the analysis of data from random experiments, indicating that it has a large variety of possible applications in the clinical practice.
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
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Slattery, Stuart R., E-mail: slatterysr@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831 (United States); Evans, Thomas M., E-mail: evanstm@ornl.gov [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831 (United States); Wilson, Paul P.H., E-mail: wilsonp@engr.wisc.edu [University of Wisconsin - Madison, 1500 Engineering Dr., Madison, WI 53706 (United States)
2015-12-15
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 random walks 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 in numerical experiments to test the models for symmetric operators with spectral qualities similar to light water reactor problems. In general, the derived approximations show good agreement with random walk lengths and leakage fractions computed by the numerical experiments.
Kumar, A; Chauhan, S
2017-03-08
Obesity is one of the most provoking health burdens in the developed countries. One of the strategies to prevent obesity is the inhibition of pancreatic lipase enzyme. The aim of this study was to build QSAR models for natural lipase inhibitors by using the Monte Carlo method. The molecular structures were represented by the simplified molecular input line entry system (SMILES) notation and molecular graphs. Three sets - training, calibration and test set of three splits - were examined and validated. Statistical quality of all the described models was very good. The best QSAR model showed the following statistical parameters: r(2) = 0.864 and Q(2) = 0.836 for the test set and r(2) = 0.824 and Q(2) = 0.819 for the validation set. Structural attributes for increasing and decreasing the activity (expressed as pIC50) were also defined. Using defined structural attributes, the design of new potential lipase inhibitors is also presented. Additionally, a molecular docking study was performed for the determination of binding modes of designed molecules.
Živković, Jelena V; Trutić, Nataša V; Veselinović, Jovana B; Nikolić, Goran M; Veselinović, Aleksandar M
2015-09-01
The Monte Carlo method was used for QSAR modeling of maleimide derivatives as glycogen synthase kinase-3β inhibitors. The first QSAR model was developed for a series of 74 3-anilino-4-arylmaleimide derivatives. The second QSAR model was developed for a series of 177 maleimide derivatives. QSAR models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system. Two splits have been examined: one split into the training and test set for the first QSAR model, and one split into the training, test and validation set for the second. The statistical quality of the developed model is very good. The calculated model for 3-anilino-4-arylmaleimide derivatives had following statistical parameters: r(2)=0.8617 for the training set; r(2)=0.8659, and r(m)(2)=0.7361 for the test set. The calculated model for maleimide derivatives had following statistical parameters: r(2)=0.9435, for the training, r(2)=0.9262 and r(m)(2)=0.8199 for the test and r(2)=0.8418, r(av)(m)(2)=0.7469 and ∆r(m)(2)=0.1476 for the validation set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new potential glycogen synthase kinase-3β inhibitors has been presented by using defined structural alerts.
Monte carlo method-based QSAR modeling of penicillins binding to human serum proteins.
Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M; Veselinović, Aleksandar M
2015-01-01
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.
Agudelo-Giraldo, J. D.; Restrepo-Parra, E.; Restrepo, J.
2015-10-01
The Metropolis algorithm and the classical Heisenberg approximation were implemented by the Monte Carlo method to design a computational approach to the magnetization and resistivity of La2/3Ca1/3MnO3, which depends on the Mn ion vacancies as the external magnetic field increases. This compound is ferromagnetic, and it exhibits the colossal magnetoresistance (CMR) effect. The monolayer was built with L×L×d dimensions, and it had L=30 umc (units of magnetic cells) for its dimension in the x-y plane and was d=12 umc in thickness. The Hamiltonian that was used contains interactions between first neighbors, the magnetocrystalline anisotropy effect and the external applied magnetic field response. The system that was considered contains mixed-valence bonds: Mn3+eg'-O-Mn3+eg, Mn3+eg-O-Mn4+d3 and Mn3+eg'-O-Mn4+d3. The vacancies were placed randomly in the sample, replacing any type of Mn ion. The main result shows that without vacancies, the transitions TC (Curie temperature) and TMI (metal-insulator temperature) are similar, whereas with the increase in the vacancy percentage, TMI presented lower values than TC. This situation is caused by the competition between the external magnetic field, the vacancy percentage and the magnetocrystalline anisotropy, which favors the magnetoresistive effect at temperatures below TMI. Resistivity loops were also observed, which shows a direct correlation with the hysteresis loops of magnetization at temperatures below TC.
Monte Carlo studies of 3d N=6 SCFT via localization method
Honda, Masazumi; Honma, Yoshinori; Nishimura, Jun; Shiba, Shotaro; Yoshida, Yutaka
2012-01-01
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.
Dynamic measurements and uncertainty estimation of clinical thermometers using Monte Carlo method
Ogorevc, Jaka; Bojkovski, Jovan; Pušnik, Igor; Drnovšek, Janko
2016-09-01
Clinical thermometers in intensive care units are used for the continuous measurement of body temperature. This study describes a procedure for dynamic measurement uncertainty evaluation in order to examine the requirements for clinical thermometer dynamic properties in standards and recommendations. In this study thermistors were used as temperature sensors, transient temperature measurements were performed in water and air and the measurement data were processed for the investigation of thermometer dynamic properties. The thermometers were mathematically modelled. A Monte Carlo method was implemented for dynamic measurement uncertainty evaluation. The measurement uncertainty was analysed for static and dynamic conditions. Results showed that dynamic uncertainty is much larger than steady-state uncertainty. The results of dynamic uncertainty analysis were applied on an example of clinical measurements and were compared to current requirements in ISO standard for clinical thermometers. It can be concluded that there was no need for dynamic evaluation of clinical thermometers for continuous measurement, while dynamic measurement uncertainty was within the demands of target uncertainty. Whereas in the case of intermittent predictive thermometers, the thermometer dynamic properties had a significant impact on the measurement result. Estimation of dynamic uncertainty is crucial for the assurance of traceable and comparable measurements.
Beam neutron energy optimization for boron neutron capture therapy using Monte Carlo method
Directory of Open Access Journals (Sweden)
Ali Pazirandeh
2006-06-01
Full Text Available In last two decades the optimal neutron energy for the treatment of deep seated tumors in boron neutron capture therapy in view of neutron physics and chemical compounds of boron carrier has been under thorough study. Although neutron absorption cross section of boron is high (3836b, the treatment of deep seated tumors such as gliobelastoma multiform (GBM requires beam of neutrons of higher energy that can penetrate deeply into the brain and thermalize in the proximity of the tumor. Dosage from recoil proton associated with fast neutrons however poses some constraints on maximum neutron energy that can be used in the treatment. For this reason neutrons in the epithermal energy range of 10eV-10keV are generally to be the most appropriate. The simulation carried out by Monte Carlo methods using MCBNCT and MCNP4C codes along with the cross section library in 290 groups extracted from ENDF/B6 main library. The optimal neutron energy for deep seated tumors depends on the size and depth of tumor. Our estimated optimized energy for the tumor of 5cm wide and 1-2cm thick stands at 5cm depth is in the range of 3-5keV
Evaluation of the scattered radiation components produced in a gamma camera using Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Polo, Ivon Oramas, E-mail: ivonoramas67@gmail.com [Department of Nuclear Engineering, Faculty of Nuclear Sciences and Technologies, Higher Institute of Applied Science and Technology (InSTEC), La Habana (Cuba)
2014-07-01
Introduction: this paper presents a simulation for evaluation of the scattered radiation components produced in a gamma camera PARK using Monte Carlo code SIMIND. It simulates a whole body study with MDP (Methylene Diphosphonate) radiopharmaceutical based on Zubal anthropomorphic phantom, with some spinal lesions. Methods: the simulation was done by comparing 3 configurations for the detected photons. The corresponding energy spectra were obtained using Low Energy High Resolution collimator. The parameters related with the interactions and the fraction of events in the energy window, the simulated events of the spectrum and scatter events were calculated. Results: the simulation confirmed that the images without influence of scattering events have a higher number of valid recorded events and it improved the statistical quality of them. A comparison among different collimators was made. The parameters and detector energy spectrum were calculated for each simulation configuration with these collimators using {sup 99m}Tc. Conclusion: the simulation corroborated that LEHS collimator has higher sensitivity and HEHR collimator has lower sensitivity when they are used with low energy photons. (author)
Boron film thickness determination to develop a low cost neutron using Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Costa, Priscila; Raele, Marcus P.; Yoriyaz, Helio; Siqueira, Paulo de T.D.; Zahn, Guilherme S.; Genezini, Frederico A., E-mail: fredzini@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2015-07-01
Neutron measurement is important for safety and security of workers at nuclear facilities. As neutron is an uncharged particle, for its detection is necessary to use a converter material that interacts with the neutron and produce a charged particle, which is easy to detect. One of the converter candidates is natural boron composed by about 20% of Boron-10, which capture a low energy neutron ejecting an energetic alpha particle and a lithium ion. A neutron detector can be developed applying a boron thin film over a silicon photodiode, which is charged particle sensitive. For this reason is important to determine the optimal film thickness. We have used an empirical solution for the boron film thickness evaluation; furthermore we developed, using Monte Carlo method (MCNP6), a model to simulate the alpha particles propagation through the detector. Our goal was to ensure the best production and transference of alpha particles to silicon region. The film thickness ranged between 0 to 5.5 μm, the neutron energy was also varied. The optimal thickness value will be used to develop a prototype of a low cost neutron detector. (author)
Analysis of probabilistic short run marginal cost using Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Gutierrez-Alcaraz, G.; Navarrete, N.; Tovar-Hernandez, J.H.; Fuerte-Esquivel, C.R. [Inst. Tecnologico de Morelia, Michoacan (Mexico). Dept. de Ing. Electrica y Electronica; Mota-Palomino, R. [Inst. Politecnico Nacional (Mexico). Escuela Superior de Ingenieria Mecanica y Electrica
1999-11-01
The structure of the Electricity Supply Industry is undergoing dramatic changes to provide new services options. The main aim of this restructuring is allowing generating units the freedom of selling electricity to anybody they wish at a price determined by market forces. Several methodologies have been proposed in order to quantify different costs associated with those new services offered by electrical utilities operating under a deregulated market. The new wave of pricing is heavily influenced by economic principles designed to price products to elastic market segments on the basis of marginal costs. Hence, spot pricing provides the economic structure for many of new services. At the same time, the pricing is influenced by uncertainties associated to the electric system state variables which defined its operating point. In this paper, nodal probabilistic short run marginal costs are calculated, considering as random variables the load, the production cost and availability of generators. The effect of the electrical network is evaluated taking into account linearized models. A thermal economic dispatch is used to simulate each operational condition generated by Monte Carlo method on small fictitious power system in order to assess the effect of the random variables on the energy trading. First, this is carry out by introducing each random variable one by one, and finally considering the random interaction of all of them.
Zhang, Guannan; Del-Castillo-Negrete, Diego
2016-10-01
Kinetic descriptions of RE are usually based on the bounced-averaged Fokker-Planck model that determines the PDFs of RE in the 2 dimensional momentum space. Despite of the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches (e.g., continuum and particle-based Monte Carlo (MC)) can be time consuming specially in the computation of asymptotic-type observable including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. Here we present a novel backward MC approach to these problems based on backward stochastic differential equations (BSDEs). The BSDE model can simultaneously describe the PDF of RE and the runaway probabilities by means of the well-known Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than the brute-force MC methods, which can significantly reduce the number of particles required to achieve a prescribed accuracy. Moreover, our algorithm can be parallelized as easy as the direct MC code, which paves the way for conducting large-scale RE simulation. This work is supported by DOE FES and ASCR under the Contract Numbers ERKJ320 and ERAT377.
Non-Local effective SU(2) Polyakov-loop models from inverse Monte-Carlo methods
Bahrampour, Bardiya; von Smekal, Lorenz
2016-01-01
The strong-coupling expansion of the lattice gauge action leads to Polyakov-loop models that effectively describe gluodynamics at low temperatures, and together with the hopping expansion of the fermion determinant provides insight into the QCD phase diagram at finite density and low temperatures, although for rather heavy quarks. At higher temperatures the strong-coupling expansion breaks down and it is expected that the interactions between Polyakov loops become non-local. Here, we therefore test how well pure SU(2) gluodynamics can be mapped onto different non-local Polyakov models with inverse Monte-Carlo methods. We take into account Polyakov loops in higher representations and gradually add interaction terms at larger distances. We are particularly interested in extrapolating the range of non-local terms in sufficiently large volumes and higher representations. We study the characteristic fall-off in strength of the non-local couplings with the interaction distance, and its dependence on the gauge coupl...
Energy Technology Data Exchange (ETDEWEB)
Avrorin, E. N.; Tsvetokhin, A. G.; Xenofontov, A. I.; Kourbatova, E. I.; Regens, J. L.
2002-02-26
This paper presents the results of an ongoing research and development project conducted by Russian institutions in Moscow and Snezhinsk, supported by the International Science and Technology Center (ISTC), in collaboration with the University of Oklahoma. The joint study focuses on developing and applying analytical tools to effectively characterize contaminant transport and assess risks associated with migration of radionuclides and heavy metals in the water column and sediments of large reservoirs or lakes. The analysis focuses on the development and evaluation of theoretical-computational models that describe the distribution of radioactive wastewater within a reservoir and characterize the associated radiation field as well as estimate doses received from radiation exposure. The analysis focuses on the development and evaluation of Monte Carlo-based, theoretical-computational methods that are applied to increase the precision of results and to reduce computing time for estimating the characteristics the radiation field emitted from the contaminated wastewater layer. The calculated migration of radionuclides is used to estimate distributions of radiation doses that could be received by an exposed population based on exposure to radionuclides from specified volumes of discrete aqueous sources. The calculated dose distributions can be used to support near-term and long-term decisions about priorities for environmental remediation and stewardship.
Development of a software package for solid-angle calculations using the Monte Carlo method
Zhang, Jie; Chen, Xiulian; Zhang, Changsheng; Li, Gang; Xu, Jiayun; Sun, Guangai
2014-02-01
Solid-angle calculations play an important role in the absolute calibration of radioactivity measurement systems and in the determination of the activity of radioactive sources, which are often complicated. In the present paper, a software package is developed to provide a convenient tool for solid-angle calculations in nuclear physics. The proposed software calculates solid angles using the Monte Carlo method, in which a new type of variance reduction technique was integrated. The package, developed under the environment of Microsoft Foundation Classes (MFC) in Microsoft Visual C++, has a graphical user interface, in which, the visualization function is integrated in conjunction with OpenGL. One advantage of the proposed software package is that it can calculate the solid angle subtended by a detector with different geometric shapes (e.g., cylinder, square prism, regular triangular prism or regular hexagonal prism) to a point, circular or cylindrical source without any difficulty. The results obtained from the proposed software package were compared with those obtained from previous studies and calculated using Geant4. It shows that the proposed software package can produce accurate solid-angle values with a greater computation speed than Geant4.
Monte Carlo 方法及其在统计物理中的应用%Monte Carlo Method and Its Application in Statistical Physics
Institute of Scientific and Technical Information of China (English)
申传胜
2013-01-01
近年来，计算机技术和互联网的快速发展，使得计算机模拟成为仿真实验、验证理论以及理解自然规律的一种有效研究手段。本文简要地总结了一种有效且成熟的计算机模拟方法 Monte Carlo（MC）方法的基本思想，以平衡体系和非平衡体系的两个代表模型：Potts 模型和钙振荡模型为例，介绍了 MC 和 kinetic MC（kMC）模拟的基本算法。此外，还介绍了上述两种 MC 方法的发展及应用，即粗粒化 MC 和粗粒化 kMC 模拟方法，并以常见的 Fortran 语言为例给出其计算机模拟程序。%Recently, with the rapid advances of the computer industry and the internet, computer simulation has been one of efficient methods to predict and understand the laws of nature.Monte Carlo (MC) method is one of those common simulation meth-ods and has attracted extensive attention.In the present paper, we briefly summarize the basic idea of the MC method, and intro-duce the primary algorithm of MC method and kinetic MC (kMC) method with Potts model and calcium dynamics as the examples of equilibrium and unequilibrium systems respectively.In addition, we also present the other two evolutionary MC methods, coarse-graining MC method and coarse -graining kMC method, and their computer programs.
Bonfiglio, Andrea; Francesco CHELLI
2007-01-01
The paper aims to analyse the tendency of a battery of non-survey techniques of constructing regional I-O tables to over-(under-)estimate impact. The behaviour of the regionalization methods is assessed relatively to the techniques analysed. For this aim, a Monte Carlo simulation has been carried out. Then, a multidimensional scaling procedure has been applied to search for a common and repeated structure of differences among the methods and to give an immediate picture of possible implicatio...
Range verification methods in particle therapy: underlying physics and Monte Carlo modelling
Directory of Open Access Journals (Sweden)
Aafke Christine Kraan
2015-07-01
Full Text Available Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients.Non-invasive in-vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including beta+ emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC predictions is a key issue. Correctly modelling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modelling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.
Ghita, Gabriel M.
Our study aim to design a useful neutron signature characterization device based on 3He detectors, a standard neutron detection methodology used in homeland security applications. Research work involved simulation of the generation, transport, and detection of the leakage radiation from Special Nuclear Materials (SNM). To accomplish research goals, we use a new methodology to fully characterize a standard "1-Ci" Plutonium-Beryllium (Pu-Be) neutron source based on 3-D computational radiation transport methods, employing both deterministic SN and Monte Carlo methodologies. Computational model findings were subsequently validated through experimental measurements. Achieved results allowed us to design, build, and laboratory-test a Nickel composite alloy shield that enables the neutron leakage spectrum from a standard Pu-Be source to be transformed, through neutron scattering interactions in the shield, into a very close approximation of the neutron spectrum leaking from a large, subcritical mass of Weapons Grade Plutonium (WGPu) metal. This source will make possible testing with a nearly exact reproduction of the neutron spectrum from a 6.67 kg WGPu mass equivalent, but without the expense or risk of testing detector components with real materials. Moreover, over thirty moderator materials were studied in order to characterize their neutron energy filtering potential. Specific focus was made to establish the limits of He-3 spectroscopy using ideal filter materials. To demonstrate our methodology, we present the optimally detected spectral differences between SNM materials (Plutonium and Uranium), metal and oxide, using ideal filter materials. Finally, using knowledge gained from previous studies, the design of a He-3 spectroscopy system neutron detector, simulated entirely via computational methods, is proposed to resolve the spectra from SNM neutron sources of high interest. This was accomplished by replacing ideal filters with real materials, and comparing reaction
Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling.
Kraan, Aafke Christine
2015-01-01
Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients. Non-invasive in vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including β (+) emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC) predictions is a key issue. Correctly modeling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modeling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then, we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects.
MC-Net: a method for the construction of phylogenetic networks based on the Monte-Carlo method
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Eslahchi Changiz
2010-08-01
Full Text Available Abstract Background A phylogenetic network is a generalization of phylogenetic trees that allows the representation of conflicting signals or alternative evolutionary histories in a single diagram. There are several methods for constructing these networks. Some of these methods are based on distances among taxa. In practice, the methods which are based on distance perform faster in comparison with other methods. The Neighbor-Net (N-Net is a distance-based method. The N-Net produces a circular ordering from a distance matrix, then constructs a collection of weighted splits using circular ordering. The SplitsTree which is a program using these weighted splits makes a phylogenetic network. In general, finding an optimal circular ordering is an NP-hard problem. The N-Net is a heuristic algorithm to find the optimal circular ordering which is based on neighbor-joining algorithm. Results In this paper, we present a heuristic algorithm to find an optimal circular ordering based on the Monte-Carlo method, called MC-Net algorithm. In order to show that MC-Net performs better than N-Net, we apply both algorithms on different data sets. Then we draw phylogenetic networks corresponding to outputs of these algorithms using SplitsTree and compare the results. Conclusions We find that the circular ordering produced by the MC-Net is closer to optimal circular ordering than the N-Net. Furthermore, the networks corresponding to outputs of MC-Net made by SplitsTree are simpler than N-Net.
Monte Carlo particle-in-cell methods for the simulation of the Vlasov-Maxwell gyrokinetic equations
Bottino, A.; Sonnendrücker, E.
2015-10-01
> The particle-in-cell (PIC) algorithm is the most popular method for the discretisation of the general 6D Vlasov-Maxwell problem and it is widely used also for the simulation of the 5D gyrokinetic equations. The method consists of coupling a particle-based algorithm for the Vlasov equation with a grid-based method for the computation of the self-consistent electromagnetic fields. In this review we derive a Monte Carlo PIC finite-element model starting from a gyrokinetic discrete Lagrangian. The variations of the Lagrangian are used to obtain the time-continuous equations of motion for the particles and the finite-element approximation of the field equations. The Noether theorem for the semi-discretised system implies a certain number of conservation properties for the final set of equations. Moreover, the PIC method can be interpreted as a probabilistic Monte Carlo like method, consisting of calculating integrals of the continuous distribution function using a finite set of discrete markers. The nonlinear interactions along with numerical errors introduce random effects after some time. Therefore, the same tools for error analysis and error reduction used in Monte Carlo numerical methods can be applied to PIC simulations.
Kumada, H; Saito, K; Nakamura, T; Sakae, T; Sakurai, H; Matsumura, A; Ono, K
2011-12-01
Treatment planning for boron neutron capture therapy generally utilizes Monte-Carlo methods for calculation of the dose distribution. The new treatment planning system JCDS-FX employs the multi-purpose Monte-Carlo code PHITS to calculate the dose distribution. JCDS-FX allows to build a precise voxel model consisting of pixel based voxel cells in the scale of 0.4×0.4×2.0 mm(3) voxel in order to perform high-accuracy dose estimation, e.g. for the purpose of calculating the dose distribution in a human body. However, the miniaturization of the voxel size increases calculation time considerably. The aim of this study is to investigate sophisticated modeling methods which can perform Monte-Carlo calculations for human geometry efficiently. Thus, we devised a new voxel modeling method "Multistep Lattice-Voxel method," which can configure a voxel model that combines different voxel sizes by utilizing the lattice function over and over. To verify the performance of the calculation with the modeling method, several calculations for human geometry were carried out. The results demonstrated that the Multistep Lattice-Voxel method enabled the precise voxel model to reduce calculation time substantially while keeping the high-accuracy of dose estimation.
Watanabe, Hiroshi; Yukawa, Satoshi; Novotny, M A; Ito, Nobuyasu
2006-08-01
We construct asymptotic arguments for the relative efficiency of rejection-free Monte Carlo (MC) methods compared to the standard MC method. We find that the efficiency is proportional to exp(constbeta) in the Ising, sqrt[beta] in the classical XY, and beta in the classical Heisenberg spin systems with inverse temperature beta, regardless of the dimension. The efficiency in hard particle systems is also obtained, and found to be proportional to (rho(cp)-rho)(-d) with the closest packing density rho(cp), density rho, and dimension d of the systems. We construct and implement a rejection-free Monte Carlo method for the hard-disk system. The RFMC has a greater computational efficiency at high densities, and the density dependence of the efficiency is as predicted by our arguments.
Automating methods to improve precision in Monte-Carlo event generation for particle colliders
Energy Technology Data Exchange (ETDEWEB)
Gleisberg, Tanju
2008-07-01
The subject of this thesis was the development of tools for the automated calculation of exact matrix elements, which are a key for the systematic improvement of precision and confidence for theoretical predictions. Part I of this thesis concentrates on the calculations of cross sections at tree level. A number of extensions have been implemented in the matrix element generator AMEGIC++, namely new interaction models such as effective loop-induced couplings of the Higgs boson with massless gauge bosons, required for a number of channels for the Higgs boson search at LHC and anomalous gauge couplings, parameterizing a number of models beyond th SM. Further a special treatment to deal with complicated decay chains of heavy particles has been constructed. A significant effort went into the implementation of methods to push the limits on particle multiplicities. Two recursive methods have been implemented, the Cachazo-Svrcek-Witten recursion and the colour dressed Berends-Giele recursion. For the latter the new module COMIX has been added to the SHERPA framework. The Monte-Carlo phase space integration techniques have been completely revised, which led to significantly reduced statistical error estimates when calculating cross sections and a greatly improved unweighting efficiency for the event generation. Special integration methods have been developed to cope with the newly accessible final states. The event generation framework SHERPA directly benefits from those new developments, improving the precision and the efficiency. Part II was addressed to the automation of QCD calculations at next-to-leading order. A code has been developed, that, for the first time fully automates the real correction part of a NLO calculation. To calculate the correction for a m-parton process obeying the Catani-Seymour dipole subtraction method the following components are provided: 1. the corresponding m+1-parton tree level matrix elements, 2. a number dipole subtraction terms to remove
A Projector Quantum Monte Carlo Method for non-linear wavefunctions
Schwarz, Lauretta R; Booth, George H
2016-01-01
We reformulate the projected imaginary-time evolution of Full Configuration Interaction Quantum Monte Carlo in terms of a Lagrangian minimization. This naturally leads to the admission of polynomial complex wavefunction parameterizations, circumventing the exponential scaling of the approach. While previously these functions have traditionally inhabited the domain of Variational Monte Carlo, we consider recently developments for the identification of deep-learning neural networks to optimize this Lagrangian, which can be written as a modification of the propagator for the wavefunction dynamics. We demonstrate this approach with a form of Tensor Network State, and use it to find solutions to the strongly-correlated Hubbard model, as well as its application to a fully periodic ab-initio Graphene sheet. The number of variables which can be simultaneously optimized greatly exceeds alternative formulations of Variational Monte Carlo, allowing for systematic improvability of the wavefunction flexibility towards exa...
Directory of Open Access Journals (Sweden)
M. Kotbi
2013-03-01
Full Text Available The choice of appropriate interaction models is among the major disadvantages of conventional methods such as Molecular Dynamics (MD and Monte Carlo (MC 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 BaMnMF7 (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 (PDFs. 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.
Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues
Energy Technology Data Exchange (ETDEWEB)
Harris, G.; Van Horn, R.
1996-06-01
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.
Environmental dose rate assessment of ITER using the Monte Carlo method
Directory of Open Access Journals (Sweden)
Karimian Alireza
2014-01-01
Full Text Available Exposure to radiation is one of the main sources of risk to staff employed in reactor facilities. The staff of a tokamak is exposed to a wide range of neutrons and photons around the tokamak hall. The International Thermonuclear Experimental Reactor (ITER is a nuclear fusion engineering project and the most advanced experimental tokamak in the world. From the radiobiological point of view, ITER dose rates assessment is particularly important. The aim of this study is the assessment of the amount of radiation in ITER during its normal operation in a radial direction from the plasma chamber to the tokamak hall. To achieve this goal, the ITER system and its components were simulated by the Monte Carlo method using the MCNPX 2.6.0 code. Furthermore, the equivalent dose rates of some radiosensitive organs of the human body were calculated by using the medical internal radiation dose phantom. Our study is based on the deuterium-tritium plasma burning by 14.1 MeV neutron production and also photon radiation due to neutron activation. As our results show, the total equivalent dose rate on the outside of the bioshield wall of the tokamak hall is about 1 mSv per year, which is less than the annual occupational dose rate limit during the normal operation of ITER. Also, equivalent dose rates of radiosensitive organs have shown that the maximum dose rate belongs to the kidney. The data may help calculate how long the staff can stay in such an environment, before the equivalent dose rates reach the whole-body dose limits.
Numerical simulations of blast-impact problems using the direct simulation Monte Carlo method
Sharma, Anupam
There is an increasing need to design protective structures that can withstand or mitigate the impulsive loading due to the impact of a blast or a shock wave. A preliminary step in designing such structures is the prediction of the pressure loading on the structure. This is called the "load definition." This thesis is focused on a numerical approach to predict the load definition on arbitrary geometries for a given strength of the incident blast/shock wave. A particle approach, namely the Direct Simulation Monte Carlo (DSMC) method, is used as the numerical model. A three-dimensional, time-accurate DSMC flow solver is developed as a part of this study. Embedded surfaces, modeled as triangulations, are used to represent arbitrary-shaped structures. Several techniques to improve the computational efficiency of the algorithm of particle-structure interaction are presented. The code is designed using the Object Oriented Programming (OOP) paradigm. Domain decomposition with message passing is used to solve large problems in parallel. The solver is extensively validated against analytical results and against experiments. Two kinds of geometries, a box and an I-shaped beam are investigated for blast impact. These simulations are performed in both two- and three-dimensions. A major portion of the thesis is dedicated to studying the uncoupled fluid dynamics problem where the structure is assumed to remain stationary and intact during the simulation. A coupled, fluid-structure dynamics problem is solved in one spatial dimension using a simple, spring-mass-damper system to model the dynamics of the structure. A parametric study, by varying the mass, spring constant, and the damping coefficient, to study their effect on the loading and the displacement of the structure is also performed. Finally, the parallel performance of the solver is reported for three sample-size problems on two Beowulf clusters.
Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method
Basire, M.; Soudan, J.-M.; Angelié, C.
2014-09-01
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 σ-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 potential clusters studied in Paper I.
Energy Technology Data Exchange (ETDEWEB)
Matsumiya, T. [Nippon Steel Corporation, Tokyo (Japan)
1996-08-20
The Monte Carlo method was used to simulate an equilibrium diagram, and structural formation of transformation and recrystallization. In simulating the Cu-A equilibrium diagram, the calculation was performed by laying 24 face centered cubic lattices including four lattice points in all of the three directions, and using a simulation cell consisting of lattice points of a total of 24{sup 3}{times}4 points. Although this method has a possibility to discover existence of an unknown phase as a result of the calculation, problems were found left in handling of lattice mitigation, and in simulation of phase diagrams over phases with different crystal structures. In simulation of the transformation and recrystallization, discussions were given on correspondence of 1MCS to time when the lattice point size is increased, and on handling of nucleus formation. As a result, it was estimated that in three-dimensional grain growth, the average grain size is proportional to 1/3 power of the MCS number, and the real time against 1MCS is proportional to three power of the lattice point size. 11 refs., 8 figs., 2 tabs.
Energy Technology Data Exchange (ETDEWEB)
Cho, S; Shin, E H; Kim, J; Ahn, S H; Chung, K; Kim, D-H; Han, Y; Choi, D H [Samsung Medical Center, Seoul (Korea, Republic of)
2015-06-15
Purpose: To evaluate the shielding wall design to protect patients, staff and member of the general public for secondary neutron using a simply analytic solution, multi-Monte Carlo code MCNPX, ANISN and FLUKA. Methods: An analytical and multi-Monte Carlo method were calculated for proton facility (Sumitomo Heavy Industry Ltd.) at Samsung Medical Center in Korea. The NCRP-144 analytical evaluation methods, which produced conservative estimates on the dose equivalent values for the shielding, were used for analytical evaluations. Then, the radiation transport was simulated with the multi-Monte Carlo code. The neutron dose at evaluation point is got by the value using the production of the simulation value and the neutron dose coefficient introduced in ICRP-74. Results: The evaluation points of accelerator control room and control room entrance are mainly influenced by the point of the proton beam loss. So the neutron dose equivalent of accelerator control room for evaluation point is 0.651, 1.530, 0.912, 0.943 mSv/yr and the entrance of cyclotron room is 0.465, 0.790, 0.522, 0.453 mSv/yr with calculation by the method of NCRP-144 formalism, ANISN, FLUKA and MCNP, respectively. The most of Result of MCNPX and FLUKA using the complicated geometry showed smaller values than Result of ANISN. Conclusion: The neutron shielding for a proton therapy facility has been evaluated by the analytic model and multi-Monte Carlo methods. We confirmed that the setting of shielding was located in well accessible area to people when the proton facility is operated.
Measurements of the ZZ production cross sections in the $2\\ell2\
Khachatryan, Vardan; Tumasyan, Armen; Adam, Wolfgang; Bergauer, Thomas; Dragicevic, Marko; Erö, Janos; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hartl, Christian; Hörmann, Natascha; Hrubec, Josef; Jeitler, Manfred; Kiesenhofer, Wolfgang; Knünz, Valentin; Krammer, Manfred; Krätschmer, Ilse; Liko, Dietrich; Mikulec, Ivan; Rabady, Dinyar; Rahbaran, Babak; Rohringer, Herbert; Schöfbeck, Robert; Strauss, Josef; Treberer-Treberspurg, Wolfgang; Waltenberger, Wolfgang; Wulz, Claudia-Elisabeth; Mossolov, Vladimir; Shumeiko, Nikolai; Suarez Gonzalez, Juan; Alderweireldt, Sara; Bansal, Sunil; Cornelis, Tom; De Wolf, Eddi A; Janssen, Xavier; Knutsson, Albert; Lauwers, Jasper; Luyckx, Sten; Ochesanu, Silvia; Rougny, Romain; Van De Klundert, Merijn; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Van Spilbeeck, Alex; Blekman, Freya; Blyweert, Stijn; D'Hondt, Jorgen; Daci, Nadir; Heracleous, Natalie; Keaveney, James; Lowette, Steven; Maes, Michael; Olbrechts, Annik; Python, Quentin; Strom, Derek; Tavernier, Stefaan; Van Doninck, Walter; Van Mulders, Petra; Van Onsem, Gerrit Patrick; Villella, Ilaria; Caillol, Cécile; Clerbaux, Barbara; De Lentdecker, Gilles; Dobur, Didar; Favart, Laurent; Gay, Arnaud; Grebenyuk, Anastasia; Léonard, Alexandre; Mohammadi, Abdollah; Perniè, Luca; Randle-conde, Aidan; Reis, Thomas; Seva, Tomislav; Thomas, Laurent; Vander Velde, Catherine; Vanlaer, Pascal; Wang, Jian; Zenoni, Florian; Adler, Volker; Beernaert, Kelly; Benucci, Leonardo; Cimmino, Anna; Costantini, Silvia; Crucy, Shannon; Dildick, Sven; Fagot, Alexis; Garcia, Guillaume; Mccartin, Joseph; Ocampo Rios, Alberto Andres; Ryckbosch, Dirk; Salva Diblen, Sinem; Sigamani, Michael; Strobbe, Nadja; Thyssen, Filip; Tytgat, Michael; Yazgan, Efe; Zaganidis, Nicolas; Basegmez, Suzan; Beluffi, Camille; Bruno, Giacomo; Castello, Roberto; Caudron, Adrien; Ceard, Ludivine; Da Silveira, Gustavo Gil; Delaere, Christophe; Du Pree, Tristan; Favart, Denis; Forthomme, Laurent; Giammanco, Andrea; Hollar, Jonathan; Jafari, Abideh; Jez, Pavel; Komm, Matthias; Lemaitre, Vincent; Nuttens, Claude; Pagano, Davide; Perrini, Lucia; Pin, Arnaud; Piotrzkowski, Krzysztof; Popov, Andrey; Quertenmont, Loic; Selvaggi, Michele; Vidal Marono, Miguel; Vizan Garcia, Jesus Manuel; Beliy, Nikita; Caebergs, Thierry; Daubie, Evelyne; Hammad, Gregory Habib; Aldá Júnior, Walter Luiz; Alves, Gilvan; Brito, Lucas; Correa Martins Junior, Marcos; Dos Reis Martins, Thiago; Mora Herrera, Clemencia; Pol, Maria Elena; Rebello Teles, Patricia; Carvalho, Wagner; Chinellato, Jose; Custódio, Analu; Melo Da Costa, Eliza; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Malbouisson, Helena; Matos Figueiredo, Diego; Mundim, Luiz; Nogima, Helio; Prado Da Silva, Wanda Lucia; Santaolalla, Javier; Santoro, Alberto; Sznajder, Andre; Tonelli Manganote, Edmilson José; Vilela Pereira, Antonio; Bernardes, Cesar Augusto; Dogra, Sunil; Tomei, Thiago; De Moraes Gregores, Eduardo; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Aleksandrov, Aleksandar; Genchev, Vladimir; Hadjiiska, Roumyana; Iaydjiev, Plamen; Marinov, Andrey; Piperov, Stefan; Rodozov, Mircho; Sultanov, Georgi; Vutova, Mariana; Dimitrov, Anton; Glushkov, Ivan; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Chen, Mingshui; Cheng, Tongguang; Du, Ran; Jiang, Chun-Hua; Plestina, Roko; Romeo, Francesco; Tao, Junquan; Wang, Zheng; Asawatangtrakuldee, Chayanit; Ban, Yong; Li, Qiang; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Wang, Dayong; Xu, Zijun; Zou, Wei; Avila, Carlos; Cabrera, Andrés; Chaparro Sierra, Luisa Fernanda; Florez, Carlos; Gomez, Juan Pablo; Gomez Moreno, Bernardo; Sanabria, Juan Carlos; Godinovic, Nikola; Lelas, Damir; Polic, Dunja; Puljak, Ivica; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Kadija, Kreso; Luetic, Jelena; Mekterovic, Darko; Sudic, Lucija; Attikis, Alexandros; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Bodlak, Martin; Finger, Miroslav; Finger Jr, Michael; Assran, Yasser; Ellithi Kamel, Ali; Mahmoud, Mohammed; Radi, Amr; Kadastik, Mario; Murumaa, Marion; Raidal, Martti; Tiko, Andres; Eerola, Paula; Fedi, Giacomo; Voutilainen, Mikko; Härkönen, Jaakko; Karimäki, Veikko; Kinnunen, Ritva; Kortelainen, Matti J; Lampén, Tapio; Lassila-Perini, Kati; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Peltola, Timo; Tuominen, Eija; Tuominiemi, Jorma; Tuovinen, Esa; Wendland, Lauri; Talvitie, Joonas; Tuuva, Tuure; Besancon, Marc; Couderc, Fabrice; Dejardin, Marc; Denegri, Daniel; Fabbro, Bernard; Faure, Jean-Louis; Favaro, Carlotta; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Locci, Elizabeth; Malcles, Julie; Rander, John; Rosowsky, André; Titov, Maksym; Baffioni, Stephanie; Beaudette, Florian; Busson, Philippe; Charlot, Claude; Dahms, Torsten; Dalchenko, Mykhailo; Dobrzynski, Ludwik; Filipovic, Nicolas; Florent, Alice; Granier de Cassagnac, Raphael; Mastrolorenzo, Luca; Miné, Philippe; Mironov, Camelia; Naranjo, Ivo Nicolas; Nguyen, Matthew; Ochando, Christophe; Ortona, Giacomo; Paganini, Pascal; Regnard, Simon; Salerno, Roberto; Sauvan, Jean-Baptiste; Sirois, Yves; Veelken, Christian; Yilmaz, Yetkin; Zabi, Alexandre; Agram, Jean-Laurent; Andrea, Jeremy; Aubin, Alexandre; Bloch, Daniel; Brom, Jean-Marie; Chabert, Eric Christian; Collard, Caroline; Conte, Eric; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Goetzmann, Christophe; Le Bihan, Anne-Catherine; Skovpen, Kirill; Van Hove, Pierre; Gadrat, Sébastien; Beauceron, Stephanie; Beaupere, Nicolas; Bernet, Colin; Boudoul, Gaelle; Bouvier, Elvire; Brochet, Sébastien; Carrillo Montoya, Camilo Andres; Chasserat, Julien; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fan, Jiawei; Fay, Jean; Gascon, Susan; Gouzevitch, Maxime; Ille, Bernard; Kurca, Tibor; Lethuillier, Morgan; Mirabito, Laurent; Perries, Stephane; Ruiz Alvarez, José David; Sabes, David; Sgandurra, Louis; Sordini, Viola; Vander Donckt, Muriel; Verdier, Patrice; Viret, Sébastien; Xiao, Hong; Tsamalaidze, Zviad; Autermann, Christian; Beranek, Sarah; Bontenackels, Michael; Edelhoff, Matthias; Feld, Lutz; Heister, Arno; Hindrichs, Otto; Klein, Katja; Ostapchuk, Andrey; Preuten, Marius; Raupach, Frank; Sammet, Jan; Schael, Stefan; Schulte, Jan-Frederik; Weber, Hendrik; Wittmer, Bruno; Zhukov, Valery; Ata, Metin; Brodski, Michael; Dietz-Laursonn, Erik; Duchardt, Deborah; Erdmann, Martin; Fischer, Robert; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Klingebiel, Dennis; Knutzen, Simon; Kreuzer, Peter; Merschmeyer, Markus; Meyer, Arnd; Millet, Philipp; Olschewski, Mark; Padeken, Klaas; Papacz, Paul; Reithler, Hans; Schmitz, Stefan Antonius; Sonnenschein, Lars; Teyssier, Daniel; Thüer, Sebastian; Weber, Martin; Cherepanov, Vladimir; Erdogan, Yusuf; Flügge, Günter; Geenen, Heiko; Geisler, Matthias; Haj Ahmad, Wael; Hoehle, Felix; Kargoll, Bastian; Kress, Thomas; Kuessel, Yvonne; Künsken, Andreas; Lingemann, Joschka; Nowack, Andreas; Nugent, Ian Michael; Pooth, Oliver; Stahl, Achim; Aldaya Martin, Maria; Asin, Ivan; Bartosik, Nazar; Behr, Joerg; Behrens, Ulf; Bell, Alan James; Bethani, Agni; Borras, Kerstin; Burgmeier, Armin; Cakir, Altan; Calligaris, Luigi; Campbell, Alan; Choudhury, Somnath; Costanza, Francesco; Diez Pardos, Carmen; Dolinska, Ganna; Dooling, Samantha; Dorland, Tyler; Eckerlin, Guenter; Eckstein, Doris; Eichhorn, Thomas; Flucke, Gero; Garay Garcia, Jasone; Geiser, Achim; Gunnellini, Paolo; Hauk, Johannes; Hempel, Maria; Jung, Hannes; Kalogeropoulos, Alexis; Kasemann, Matthias; Katsas, Panagiotis; Kieseler, Jan; Kleinwort, Claus; Korol, Ievgen; Krücker, Dirk; Lange, Wolfgang; Leonard, Jessica; Lipka, Katerina; Lobanov, Artur; Lohmann, Wolfgang; Lutz, Benjamin; Mankel, Rainer; Marfin, Ihar; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mittag, Gregor; Mnich, Joachim; Mussgiller, Andreas; Naumann-Emme, Sebastian; Nayak, Aruna; Ntomari, Eleni; Perrey, Hanno; Pitzl, Daniel; Placakyte, Ringaile; Raspereza, Alexei; Ribeiro Cipriano, Pedro M; Roland, Benoit; Ron, Elias; Sahin, Mehmet Özgür; Salfeld-Nebgen, Jakob; Saxena, Pooja; Schoerner-Sadenius, Thomas; Schröder, Matthias; Seitz, Claudia; Spannagel, Simon; Vargas Trevino, Andrea Del Rocio; Walsh, Roberval; Wissing, Christoph; Blobel, Volker; Centis Vignali, Matteo; Draeger, Arne-Rasmus; Erfle, Joachim; Garutti, Erika; Goebel, Kristin; Görner, Martin; Haller, Johannes; Hoffmann, Malte; Höing, Rebekka Sophie; Junkes, Alexandra; Kirschenmann, Henning; Klanner, Robert; Kogler, Roman; Lange, Jörn; Lapsien, Tobias; Lenz, Teresa; Marchesini, Ivan; Ott, Jochen; Peiffer, Thomas; Perieanu, Adrian; Pietsch, Niklas; Poehlsen, Jennifer; Pöhlsen, Thomas; Rathjens, Denis; Sander, Christian; Schettler, Hannes; Schleper, Peter; Schlieckau, Eike; Schmidt, Alexander; Seidel, Markus; Sola, Valentina; Stadie, Hartmut; Steinbrück, Georg; Troendle, Daniel; Usai, Emanuele; Vanelderen, Lukas; Vanhoefer, Annika; Barth, Christian; Baus, Colin; Berger, Joram; Böser, Christian; Butz, Erik; Chwalek, Thorsten; De Boer, Wim; Descroix, Alexis; Dierlamm, Alexander; Feindt, Michael; Frensch, Felix; Giffels, Manuel; Gilbert, Andrew; Hartmann, Frank; Hauth, Thomas; Husemann, Ulrich; Katkov, Igor; Kornmayer, Andreas; Kuznetsova, Ekaterina; Lobelle Pardo, Patricia; Mozer, Matthias Ulrich; Müller, Thomas; Müller, Thomas; Nürnberg, Andreas; Quast, Gunter; Rabbertz, Klaus; Röcker, Steffen; Simonis, Hans-Jürgen; Stober, Fred-Markus Helmut; Ulrich, Ralf; Wagner-Kuhr, Jeannine; Wayand, Stefan; Weiler, Thomas; Wolf, Roger; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Giakoumopoulou, Viktoria Athina; Kyriakis, Aristotelis; Loukas, Demetrios; Markou, Athanasios; Markou, Christos; Psallidas, Andreas; Topsis-Giotis, Iasonas; Agapitos, Antonis; Kesisoglou, Stilianos; Panagiotou, Apostolos; Saoulidou, Niki; Stiliaris, Efstathios; Aslanoglou, Xenofon; Evangelou, Ioannis; Flouris, Giannis; Foudas, Costas; Kokkas, Panagiotis; Manthos, Nikolaos; Papadopoulos, Ioannis; Paradas, Evangelos; Strologas, John; Bencze, Gyorgy; Hajdu, Csaba; Hidas, Pàl; Horvath, Dezso; Sikler, Ferenc; Veszpremi, Viktor; Vesztergombi, Gyorgy; Zsigmond, Anna Julia; Beni, Noemi; Czellar, Sandor; Karancsi, János; Molnar, Jozsef; Palinkas, Jozsef; Szillasi, Zoltan; Makovec, Alajos; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Swain, Sanjay Kumar; Beri, Suman Bala; Bhatnagar, Vipin; Gupta, Ruchi; Bhawandeep, Bhawandeep; Kalsi, Amandeep Kaur; Kaur, Manjit; Kumar, Ramandeep; Mittal, Monika; Nishu, Nishu; Singh, Jasbir; Kumar, Ashok; Kumar, Arun; Ahuja, Sudha; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Kumar, Ajay; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Sharma, Varun; Banerjee, Sunanda; Bhattacharya, Satyaki; Chatterjee, Kalyanmoy; Dutta, Suchandra; Gomber, Bhawna; Jain, Sandhya; Jain, Shilpi; Khurana, Raman; Modak, Atanu; Mukherjee, Swagata; Roy, Debarati; Sarkar, Subir; Sharan, Manoj; Abdulsalam, Abdulla; Dutta, Dipanwita; Kumar, Vineet; Mohanty, Ajit Kumar; Pant, Lalit Mohan; Shukla, Prashant; Topkar, Anita; Aziz, Tariq; Banerjee, Sudeshna; Bhowmik, Sandeep; Chatterjee, Rajdeep Mohan; Dewanjee, Ram Krishna; Dugad, Shashikant; Ganguly, Sanmay; Ghosh, Saranya; Guchait, Monoranjan; Gurtu, Atul; Kole, Gouranga; Kumar, Sanjeev; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Mohanty, Gagan Bihari; Parida, Bibhuti; Sudhakar, Katta; Wickramage, Nadeesha; Bakhshiansohi, Hamed; Behnamian, Hadi; Etesami, Seyed Mohsen; Fahim, Ali; Goldouzian, Reza; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Naseri, Mohsen; Paktinat Mehdiabadi, Saeid; Rezaei Hosseinabadi, Ferdos; Safarzadeh, Batool; Zeinali, Maryam; Felcini, Marta; Grunewald, Martin; Abbrescia, Marcello; Calabria, Cesare; Chhibra, Simranjit Singh; Colaleo, Anna; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Fiore, Luigi; Iaselli, Giuseppe; Maggi, Giorgio; Maggi, Marcello; My, Salvatore; Nuzzo, Salvatore; Pompili, Alexis; Pugliese, Gabriella; Radogna, Raffaella; Selvaggi, Giovanna; Sharma, Archana; Silvestris, Lucia; Venditti, Rosamaria; Verwilligen, Piet; Abbiendi, Giovanni; Benvenuti, Alberto; Bonacorsi, Daniele; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Campanini, Renato; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Codispoti, Giuseppe; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Montanari, Alessandro; Navarria, Francesco; Perrotta, Andrea; Primavera, Federica; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Travaglini, Riccardo; Albergo, Sebastiano; Cappello, Gigi; Chiorboli, Massimiliano; Costa, Salvatore; Giordano, Ferdinando; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Gallo, Elisabetta; Gonzi, Sandro; Gori, Valentina; Lenzi, Piergiulio; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Tropiano, Antonio; Benussi, Luigi; Bianco, Stefano; Fabbri, Franco; Piccolo, Davide; Ferretti, Roberta; Ferro, Fabrizio; Lo Vetere, Maurizio; Robutti, Enrico; Tosi, Silvano; Dinardo, Mauro Emanuele; Fiorendi, Sara; Gennai, Simone; Gerosa, Raffaele; Ghezzi, Alessio; Govoni, Pietro; Lucchini, Marco Toliman; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Martelli, Arabella; Marzocchi, Badder; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Redaelli, Nicola; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Cavallo, Nicola; Di Guida, Salvatore; Fabozzi, Francesco; Iorio, Alberto Orso Maria; Lista, Luca; Meola, Sabino; Merola, Mario; Paolucci, Pierluigi; Azzi, Patrizia; Bacchetta, Nicola; Bisello, Dario; Branca, Antonio; Carlin, Roberto; Checchia, Paolo; Dall'Osso, Martino; Dorigo, Tommaso; Galanti, Mario; Gasparini, Fabrizio; Gasparini, Ugo; Gonella, Franco; Gozzelino, Andrea; Kanishchev, Konstantin; Lacaprara, Stefano; Margoni, Martino; Meneguzzo, Anna Teresa; Pazzini, Jacopo; Pozzobon, Nicola; Ronchese, Paolo; Simonetto, Franco; Torassa, Ezio; Tosi, Mia; Zotto, Pierluigi; Zucchetta, Alberto; Zumerle, Gianni; Gabusi, Michele; Ratti, Sergio P; Re, Valerio; Riccardi, Cristina; Salvini, Paola; Vitulo, Paolo; Biasini, Maurizio; Bilei, Gian Mario; Ciangottini, Diego; Fanò, Livio; Lariccia, Paolo; Mantovani, Giancarlo; Menichelli, Mauro; Saha, Anirban; Santocchia, Attilio; Spiezia, Aniello; Androsov, Konstantin; Azzurri, Paolo; Bagliesi, Giuseppe; Bernardini, Jacopo; Boccali, Tommaso; Broccolo, Giuseppe; Castaldi, Rino; Ciocci, Maria Agnese; Dell'Orso, Roberto; Donato, Silvio; Fiori, Francesco; Foà, Lorenzo; Giassi, Alessandro; Grippo, Maria Teresa; Ligabue, Franco; Lomtadze, Teimuraz; Martini, Luca; Messineo, Alberto; Moon, Chang-Seong; Palla, Fabrizio; Rizzi, Andrea; Savoy-Navarro, Aurore; Serban, Alin Titus; Spagnolo, Paolo; Squillacioti, Paola; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Vernieri, Caterina; Barone, Luciano; Cavallari, Francesca; D'imperio, Giulia; Del Re, Daniele; Diemoz, Marcella; Jorda, Clara; Longo, Egidio; Margaroli, Fabrizio; Meridiani, Paolo; Micheli, Francesco; Organtini, Giovanni; Paramatti, Riccardo; Rahatlou, Shahram; Rovelli, Chiara; Santanastasio, Francesco; Soffi, Livia; Traczyk, Piotr; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Bellan, Riccardo; Biino, Cristina; Cartiglia, Nicolo; Casasso, Stefano; Costa, Marco; De Remigis, Paolo; Degano, Alessandro; Demaria, Natale; Finco, Linda; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Musich, Marco; Obertino, Maria Margherita; Pacher, Luca; Pastrone, Nadia; Pelliccioni, Mario; Pinna Angioni, Gian Luca; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Solano, Ada; Staiano, Amedeo; Tamponi, Umberto; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Gobbo, Benigno; La Licata, Chiara; Marone, Matteo; Schizzi, Andrea; Umer, Tomo; Zanetti, Anna; Chang, Sunghyun; Kropivnitskaya, Anna; Nam, Soon-Kwon; Kim, Dong Hee; Kim, Gui Nyun; Kim, Min Suk; Kong, Dae Jung; Lee, Sangeun; Oh, Young Do; Park, Hyangkyu; Sakharov, Alexandre; Son, Dong-Chul; Kim, Tae Jeong; Kim, Jae Yool; Moon, Dong Ho; Song, Sanghyeon; Choi, Suyong; Gyun, Dooyeon; Hong, Byung-Sik; Jo, Mihee; Kim, Hyunchul; Kim, Yongsun; Lee, Byounghoon; Lee, Kyong Sei; Park, Sung Keun; Roh, Youn; Yoo, Hwi Dong; Choi, Minkyoo; Kim, Ji Hyun; Park, Inkyu; Ryu, Geonmo; Ryu, Min Sang; Choi, Young-Il; Choi, Young Kyu; Goh, Junghwan; Kim, Donghyun; Kwon, Eunhyang; Lee, Jongseok; Yu, Intae; Juodagalvis, Andrius; Komaragiri, Jyothsna Rani; Md Ali, Mohd Adli Bin; Casimiro Linares, Edgar; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-de La Cruz, Ivan; Hernandez-Almada, Alberto; Lopez-Fernandez, Ricardo; Sánchez Hernández, Alberto; Carrillo Moreno, Salvador; Vazquez Valencia, Fabiola; Pedraza, Isabel; Salazar Ibarguen, Humberto Antonio; Morelos Pineda, Antonio; Krofcheck, David; Butler, Philip H; Reucroft, Steve; Ahmad, Ashfaq; Ahmad, Muhammad; Hassan, Qamar; Hoorani, Hafeez R; Khan, Wajid Ali; Khurshid, Taimoor; Shoaib, Muhammad; Bialkowska, Helena; Bluj, Michal; Boimska, Bożena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Romanowska-Rybinska, Katarzyna; Szleper, Michal; Zalewski, Piotr; Brona, Grzegorz; Bunkowski, Karol; Cwiok, Mikolaj; Dominik, Wojciech; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Olszewski, Michal; Bargassa, Pedrame; Beirão Da Cruz E Silva, Cristóvão; Faccioli, Pietro; Ferreira Parracho, Pedro Guilherme; Gallinaro, Michele; Lloret Iglesias, Lara; Nguyen, Federico; Rodrigues Antunes, Joao; Seixas, Joao; Varela, Joao; Vischia, Pietro; Afanasiev, Serguei; Golutvin, Igor; Karjavin, Vladimir; Konoplyanikov, Viktor; Korenkov, Vladimir; Kozlov, Guennady; Lanev, Alexander; Malakhov, Alexander; Matveev, Viktor; Mitsyn, Valeri Valentinovitch; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Shmatov, Sergey; Skatchkov, Nikolai; Smirnov, Vitaly; Tikhonenko, Elena; Zarubin, Anatoli; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Vorobyev, Andrey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Kirsanov, Mikhail; Krasnikov, Nikolai; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Gavrilov, Vladimir; Lychkovskaya, Natalia; Popov, Vladimir; Pozdnyakov, Ivan; Safronov, Grigory; Semenov, Sergey; Spiridonov, Alexander; Stolin, Viatcheslav; Vlasov, Evgueni; Zhokin, Alexander; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Leonidov, Andrey; Mesyats, Gennady; Rusakov, Sergey V; Vinogradov, Alexey; Belyaev, Andrey; Boos, Edouard; Dubinin, Mikhail; Dudko, Lev; Ershov, Alexander; Gribushin, Andrey; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Obraztsov, Stepan; Petrushanko, Sergey; Savrin, Viktor; Snigirev, Alexander; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Kachanov, Vassili; Kalinin, Alexey; Konstantinov, Dmitri; Krychkine, Victor; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Tourtchanovitch, Leonid; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Ekmedzic, Marko; Milosevic, Jovan; Rekovic, Vladimir; Alcaraz Maestre, Juan; Battilana, Carlo; Calvo, Enrique; Cerrada, Marcos; Chamizo Llatas, Maria; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Domínguez Vázquez, Daniel; Escalante Del Valle, Alberto; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Flix, Jose; Fouz, Maria Cruz; Garcia-Abia, Pablo; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Navarro De Martino, Eduardo; Pérez-Calero Yzquierdo, Antonio María; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Senghi Soares, Mara; Albajar, Carmen; de Trocóniz, Jorge F; Missiroli, Marino; Moran, Dermot; Brun, Hugues; Cuevas, Javier; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; Brochero Cifuentes, Javier Andres; Cabrillo, Iban Jose; Calderon, Alicia; Duarte Campderros, Jordi; Fernandez, Marcos; Gomez, Gervasio; Graziano, Alberto; Lopez Virto, Amparo; Marco, Jesus; Marco, Rafael; Martinez Rivero, Celso; Matorras, Francisco; Munoz Sanchez, Francisca Javiela; Piedra Gomez, Jonatan; Rodrigo, Teresa; Rodríguez-Marrero, Ana Yaiza; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Auffray, Etiennette; Auzinger, Georg; Bachtis, Michail; Baillon, Paul; Ball, Austin; Barney, David; Benaglia, Andrea; Bendavid, Joshua; Benhabib, Lamia; Benitez, Jose F; Bloch, Philippe; Bocci, Andrea; Bonato, Alessio; Bondu, Olivier; Botta, Cristina; Breuker, Horst; Camporesi, Tiziano; Cerminara, Gianluca; Colafranceschi, Stefano; D'Alfonso, Mariarosaria; D'Enterria, David; Dabrowski, Anne; David Tinoco Mendes, Andre; De Guio, Federico; De Roeck, Albert; De Visscher, Simon; Di Marco, Emanuele; Dobson, Marc; Dordevic, Milos; Dorney, Brian; Dupont-Sagorin, Niels; Elliott-Peisert, Anna; Franzoni, Giovanni; Funk, Wolfgang; Gigi, Dominique; Gill, Karl; Giordano, Domenico; Girone, Maria; Glege, Frank; Guida, Roberto; Gundacker, Stefan; Guthoff, Moritz; Hammer, Josef; Hansen, Magnus; Harris, Philip; Hegeman, Jeroen; Innocente, Vincenzo; Janot, Patrick; Kousouris, Konstantinos; Krajczar, Krisztian; Lecoq, Paul; Lourenco, Carlos; Magini, Nicolo; Malgeri, Luca; Mannelli, Marcello; Marrouche, Jad; Masetti, Lorenzo; Meijers, Frans; Mersi, Stefano; Meschi, Emilio; Moortgat, Filip; Morovic, Srecko; Mulders, Martijn; Orsini, Luciano; Pape, Luc; Perez, Emmanuelle; Petrilli, Achille; Petrucciani, Giovanni; Pfeiffer, Andreas; Pimiä, Martti; Piparo, Danilo; Plagge, Michael; Racz, Attila; Rolandi, Gigi; Rovere, Marco; Sakulin, Hannes; Schäfer, Christoph; Schwick, Christoph; Sharma, Archana; Siegrist, Patrice; Silva, Pedro; Simon, Michal; Sphicas, Paraskevas; Spiga, Daniele; Steggemann, Jan; Stieger, Benjamin; Stoye, Markus; Takahashi, Yuta; Treille, Daniel; Tsirou, Andromachi; Veres, Gabor Istvan; Wardle, Nicholas; Wöhri, Hermine Katharina; Wollny, Heiner; Zeuner, Wolfram Dietrich; Bertl, Willi; Deiters, Konrad; Erdmann, Wolfram; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; Kotlinski, Danek; Langenegger, Urs; Renker, Dieter; Rohe, Tilman; Bachmair, Felix; Bäni, Lukas; Bianchini, Lorenzo; Buchmann, Marco-Andrea; Casal, Bruno; Chanon, Nicolas; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dünser, Marc; Eller, Philipp; Grab, Christoph; Hits, Dmitry; Hoss, Jan; Lustermann, Werner; Mangano, Boris; Marini, Andrea Carlo; Marionneau, Matthieu; Martinez Ruiz del Arbol, Pablo; Masciovecchio, Mario; Meister, Daniel; Mohr, Niklas; Musella, Pasquale; Nägeli, Christoph; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pauss, Felicitas; Perrozzi, Luca; Peruzzi, Marco; Quittnat, Milena; Rebane, Liis; Rossini, Marco; Starodumov, Andrei; Takahashi, Maiko; Theofilatos, Konstantinos; Wallny, Rainer; Weber, Hannsjoerg Artur; Amsler, Claude; Canelli, Maria Florencia; Chiochia, Vincenzo; De Cosa, Annapaola; Hinzmann, Andreas; Hreus, Tomas; Kilminster, Benjamin; Lange, Clemens; Millan Mejias, Barbara; Ngadiuba, Jennifer; Pinna, Deborah; Robmann, Peter; Ronga, Frederic Jean; Taroni, Silvia; Verzetti, Mauro; Yang, Yong; Cardaci, Marco; Chen, Kuan-Hsin; Ferro, Cristina; Kuo, Chia-Ming; Lin, Willis; Lu, Yun-Ju; Volpe, Roberta; Yu, Shin-Shan; Chang, Paoti; Chang, You-Hao; Chang, Yu-Wei; Chao, Yuan; Chen, Kai-Feng; Chen, Po-Hsun; Dietz, Charles; Grundler, Ulysses; Hou, George Wei-Shu; Kao, Kai-Yi; Liu, Yueh-Feng; Lu, Rong-Shyang; Majumder, Devdatta; Petrakou, Eleni; Tzeng, Yeng-Ming; Wilken, Rachel; Asavapibhop, Burin; Singh, Gurpreet; Srimanobhas, Norraphat; Suwonjandee, Narumon; Adiguzel, Aytul; Bakirci, Mustafa Numan; Cerci, Salim; Dozen, Candan; Dumanoglu, Isa; Eskut, Eda; Girgis, Semiray; Gokbulut, Gul; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Kayis Topaksu, Aysel; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Polatoz, Ayse; Sunar Cerci, Deniz; Tali, Bayram; Topakli, Huseyin; Vergili, Mehmet; Akin, Ilina Vasileva; Bilin, Bugra; Bilmis, Selcuk; Gamsizkan, Halil; Isildak, Bora; Karapinar, Guler; Ocalan, Kadir; Sekmen, Sezen; Surat, Ugur Emrah; Yalvac, Metin; Zeyrek, Mehmet; Albayrak, Elif Asli; Gülmez, Erhan; Kaya, Mithat; Kaya, Ozlem; Yetkin, Taylan; Cankocak, Kerem; Vardarlı, Fuat Ilkehan; Levchuk, Leonid; Sorokin, Pavel; Brooke, James John; Clement, Emyr; Cussans, David; Flacher, Henning; Goldstein, Joel; Grimes, Mark; Heath, Greg P; Heath, Helen F; Jacob, Jeson; Kreczko, Lukasz; Lucas, Chris; Meng, Zhaoxia; Newbold, Dave M; Paramesvaran, Sudarshan; Poll, Anthony; Sakuma, Tai; Seif El Nasr-storey, Sarah; Senkin, Sergey; Smith, Vincent J; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Olaiya, Emmanuel; Petyt, David; Shepherd-Themistocleous, Claire; Thea, Alessandro; Tomalin, Ian R; Williams, Thomas; Womersley, William John; Worm, Steven; Baber, Mark; Bainbridge, Robert; Buchmuller, Oliver; Burton, Darren; Colling, David; Cripps, Nicholas; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Dunne, Patrick; Ferguson, William; Fulcher, Jonathan; Futyan, David; Hall, Geoffrey; Iles, Gregory; Jarvis, Martyn; Karapostoli, Georgia; Kenzie, Matthew; Lane, Rebecca; Lucas, Robyn; Lyons, Louis; Magnan, Anne-Marie; Malik, Sarah; Mathias, Bryn; Nash, Jordan; Nikitenko, Alexander; Pela, Joao; Pesaresi, Mark; Petridis, Konstantinos; Raymond, David Mark; Rogerson, Samuel; Rose, Andrew; Seez, Christopher; Sharp, Peter; Tapper, Alexander; Vazquez Acosta, Monica; Virdee, Tejinder; Zenz, Seth Conrad; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Leggat, Duncan; Leslie, Dawn; Reid, Ivan; Symonds, Philip; Teodorescu, Liliana; Turner, Mark; Dittmann, Jay; Hatakeyama, Kenichi; Kasmi, Azeddine; Liu, Hongxuan; Scarborough, Tara; Charaf, Otman; Cooper, Seth; Henderson, Conor; Rumerio, Paolo; Avetisyan, Aram; Bose, Tulika; Fantasia, Cory; Lawson, Philip; Richardson, Clint; Rohlf, James; St John, Jason; Sulak, Lawrence; Alimena, Juliette; Berry, Edmund; Bhattacharya, Saptaparna; Christopher, Grant; Cutts, David; Demiragli, Zeynep; Dhingra, Nitish; Ferapontov, Alexey; Garabedian, Alex; Heintz, Ulrich; Kukartsev, Gennadiy; Laird, Edward; Landsberg, Greg; Luk, Michael; Narain, Meenakshi; Segala, Michael; Sinthuprasith, Tutanon; Speer, Thomas; Swanson, Joshua; Breedon, Richard; Breto, Guillermo; Calderon De La Barca Sanchez, Manuel; Chauhan, Sushil; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Erbacher, Robin; Gardner, Michael; Ko, Winston; Lander, Richard; Mulhearn, Michael; Pellett, Dave; Pilot, Justin; Ricci-Tam, Francesca; Shalhout, Shalhout; Smith, John; Squires, Michael; Stolp, Dustin; Tripathi, Mani; Wilbur, Scott; Yohay, Rachel; Cousins, Robert; Everaerts, Pieter; Farrell, Chris; Hauser, Jay; Ignatenko, Mikhail; Rakness, Gregory; Takasugi, Eric; Valuev, Vyacheslav; Weber, Matthias; Burt, Kira; Clare, Robert; Ellison, John Anthony; Gary, J William; Hanson, Gail; Heilman, Jesse; Ivova Rikova, Mirena; Jandir, Pawandeep; Kennedy, Elizabeth; Lacroix, Florent; Long, Owen Rosser; Luthra, Arun; Malberti, Martina; Olmedo Negrete, Manuel; Shrinivas, Amithabh; Sumowidagdo, Suharyo; Wimpenny, Stephen; Branson, James G; Cerati, Giuseppe Benedetto; Cittolin, Sergio; D'Agnolo, Raffaele Tito; Holzner, André; Kelley, Ryan; Klein, Daniel; Kovalskyi, Dmytro; Letts, James; Macneill, Ian; Olivito, Dominick; Padhi, Sanjay; Palmer, Christopher; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Tu, Yanjun; Vartak, Adish; Welke, Charles; Würthwein, Frank; Yagil, Avraham; Barge, Derek; Bradmiller-Feld, John; Campagnari, Claudio; Danielson, Thomas; Dishaw, Adam; Dutta, Valentina; Flowers, Kristen; Franco Sevilla, Manuel; Geffert, Paul; George, Christopher; Golf, Frank; Gouskos, Loukas; Incandela, Joe; Justus, Christopher; Mccoll, Nickolas; Richman, Jeffrey; Stuart, David; To, Wing; West, Christopher; Yoo, Jaehyeok; Apresyan, Artur; Bornheim, Adolf; Bunn, Julian; Chen, Yi; Duarte, Javier; Mott, Alexander; Newman, Harvey B; Pena, Cristian; Pierini, Maurizio; Spiropulu, Maria; Vlimant, Jean-Roch; Wilkinson, Richard; Xie, Si; Zhu, Ren-Yuan; Azzolini, Virginia; Calamba, Aristotle; Carlson, Benjamin; Ferguson, Thomas; Iiyama, Yutaro; Paulini, Manfred; Russ, James; Vogel, Helmut; Vorobiev, Igor; Cumalat, John Perry; Ford, William T; Gaz, Alessandro; Krohn, Michael; Luiggi Lopez, Eduardo; Nauenberg, Uriel; Smith, James; Stenson, Kevin; Wagner, Stephen Robert; Alexander, James; Chatterjee, Avishek; Chaves, Jorge; Chu, Jennifer; Dittmer, Susan; Eggert, Nicholas; Mirman, Nathan; Nicolas Kaufman, Gala; Patterson, Juliet Ritchie; Ryd, Anders; Salvati, Emmanuele; Skinnari, Louise; Sun, Werner; Teo, Wee Don; Thom, Julia; Thompson, Joshua; Tucker, Jordan; Weng, Yao; Winstrom, Lucas; Wittich, Peter; Winn, Dave; Abdullin, Salavat; Albrow, Michael; Anderson, Jacob; Apollinari, Giorgio; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Bolla, Gino; Burkett, Kevin; Butler, Joel Nathan; Cheung, Harry; Chlebana, Frank; Cihangir, Selcuk; Elvira, Victor Daniel; Fisk, Ian; Freeman, Jim; Gao, Yanyan; Gottschalk, Erik; Gray, Lindsey; Green, Dan; Grünendahl, Stefan; Gutsche, Oliver; Hanlon, Jim; Hare, Daryl; Harris, Robert M; Hirschauer, James; Hooberman, Benjamin; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Klima, Boaz; Kreis, Benjamin; Kwan, Simon; Linacre, Jacob; Lincoln, Don; Lipton, Ron; Liu, Tiehui; Lykken, Joseph; Maeshima, Kaori; Marraffino, John Michael; Martinez Outschoorn, Verena Ingrid; Maruyama, Sho; Mason, David; McBride, Patricia; Merkel, Petra; Mishra, Kalanand; Mrenna, Stephen; Nahn, Steve; Newman-Holmes, Catherine; O'Dell, Vivian; Prokofyev, Oleg; Sexton-Kennedy, Elizabeth; Sharma, Seema; Soha, Aron; Spalding, William J; Spiegel, Leonard; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vidal, Richard; Whitbeck, Andrew; Whitmore, Juliana; Yang, Fan; Acosta, Darin; Avery, Paul; Bortignon, Pierluigi; Bourilkov, Dimitri; Carver, Matthew; Curry, David; Das, Souvik; De Gruttola, Michele; Di Giovanni, Gian Piero; Field, Richard D; Fisher, Matthew; Furic, Ivan-Kresimir; Hugon, Justin; Konigsberg, Jacobo; Korytov, Andrey; Kypreos, Theodore; Low, Jia Fu; Matchev, Konstantin; Mei, Hualin; Milenovic, Predrag; Mitselmakher, Guenakh; Muniz, Lana; Rinkevicius, Aurelijus; Shchutska, Lesya; Snowball, Matthew; Sperka, David; Yelton, John; Zakaria, Mohammed; Hewamanage, Samantha; Linn, Stephan; Markowitz, Pete; Martinez, German; Rodriguez, Jorge Luis; Adams, Todd; Askew, Andrew; Bochenek, Joseph; Diamond, Brendan; Haas, Jeff; Hagopian, Sharon; Hagopian, Vasken; Johnson, Kurtis F; Prosper, Harrison; Veeraraghavan, Venkatesh; Weinberg, Marc; Baarmand, Marc M; Hohlmann, Marcus; Kalakhety, Himali; Yumiceva, Francisco; Adams, Mark Raymond; Apanasevich, Leonard; Berry, Douglas; Betts, Russell Richard; Bucinskaite, Inga; Cavanaugh, Richard; Evdokimov, Olga; Gauthier, Lucie; Gerber, Cecilia Elena; Hofman, David Jonathan; Kurt, Pelin; O'Brien, Christine; Sandoval Gonzalez, Irving Daniel; Silkworth, Christopher; Turner, Paul; Varelas, Nikos; Bilki, Burak; Clarida, Warren; Dilsiz, Kamuran; Haytmyradov, Maksat; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Ogul, Hasan; Onel, Yasar; Ozok, Ferhat; Penzo, Aldo; Rahmat, Rahmat; Sen, Sercan; Tan, Ping; Tiras, Emrah; Wetzel, James; Yi, Kai; Barnett, Bruce Arnold; Blumenfeld, Barry; Bolognesi, Sara; Fehling, David; Gritsan, Andrei; Maksimovic, Petar; Martin, Christopher; Swartz, Morris; Baringer, Philip; Bean, Alice; Benelli, Gabriele; Bruner, Christopher; Gray, Julia; Kenny III, Raymond Patrick; Malek, Magdalena; Murray, Michael; Noonan, Daniel; Sanders, Stephen; Sekaric, Jadranka; Stringer, Robert; Wang, Quan; Wood, Jeffrey Scott; Chakaberia, Irakli; Ivanov, Andrew; Kaadze, Ketino; Khalil, Sadia; Makouski, Mikhail; Maravin, Yurii; Saini, Lovedeep Kaur; Skhirtladze, Nikoloz; Svintradze, Irakli; Gronberg, Jeffrey; Lange, David; Rebassoo, Finn; Wright, Douglas; Baden, Drew; Belloni, Alberto; Calvert, Brian; Eno, Sarah Catherine; Gomez, Jaime; Hadley, Nicholas John; Kellogg, Richard G; Kolberg, Ted; Lu, Ying; Mignerey, Alice; Pedro, Kevin; Skuja, Andris; Tonjes, Marguerite; Tonwar, Suresh C; Apyan, Aram; Barbieri, Richard; Busza, Wit; Cali, Ivan Amos; Chan, Matthew; Di Matteo, Leonardo; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Gulhan, Doga; Klute, Markus; Lai, Yue Shi; Lee, Yen-Jie; Levin, Andrew; Luckey, Paul David; Paus, Christoph; Ralph, Duncan; Roland, Christof; Roland, Gunther; Stephans, George; Sumorok, Konstanty; Velicanu, Dragos; Veverka, Jan; Wyslouch, Bolek; Yang, Mingming; Zanetti, Marco; Zhukova, Victoria; Dahmes, Bryan; Gude, Alexander; Kao, Shih-Chuan; Klapoetke, Kevin; Kubota, Yuichi; Mans, Jeremy; Nourbakhsh, Shervin; Pastika, Nathaniel; Rusack, Roger; Singovsky, Alexander; Tambe, Norbert; Turkewitz, Jared; Acosta, John Gabriel; Oliveros, Sandra; Avdeeva, Ekaterina; Bloom, Kenneth; Bose, Suvadeep; Claes, Daniel R; Dominguez, Aaron; Gonzalez Suarez, Rebeca; Keller, Jason; Knowlton, Dan; Kravchenko, Ilya; Lazo-Flores, Jose; Meier, Frank; Ratnikov, Fedor; Snow, Gregory R; Zvada, Marian; Dolen, James; Godshalk, Andrew; Iashvili, Ia; Kharchilava, Avto; Kumar, Ashish; Rappoccio, Salvatore; Alverson, George; Barberis, Emanuela; Baumgartel, Darin; Chasco, Matthew; Massironi, Andrea; Morse, David Michael; Nash, David; Orimoto, Toyoko; Trocino, Daniele; Wang, Ren-Jie; Wood, Darien; Zhang, Jinzhong; Hahn, Kristan Allan; Kubik, Andrew; Mucia, Nicholas; Odell, Nathaniel; Pollack, Brian; Pozdnyakov, Andrey; Schmitt, Michael Henry; Stoynev, Stoyan; Sung, Kevin; Velasco, Mayda; Won, Steven; Brinkerhoff, Andrew; Chan, Kwok Ming; Drozdetskiy, Alexey; Hildreth, Michael; Jessop, Colin; Karmgard, Daniel John; Kellams, Nathan; Lannon, Kevin; Lynch, Sean; Marinelli, Nancy; Musienko, Yuri; Pearson, Tessa; Planer, Michael; Ruchti, Randy; Smith, Geoffrey; Valls, Nil; Wayne, Mitchell; Wolf, Matthias; Woodard, Anna; Antonelli, Louis; Brinson, Jessica; Bylsma, Ben; Durkin, Lloyd Stanley; Flowers, Sean; Hart, Andrew; Hill, Christopher; Hughes, Richard; Kotov, Khristian; Ling, Ta-Yung; Luo, Wuming; Puigh, Darren; Rodenburg, Marissa; Winer, Brian L; Wolfe, Homer; Wulsin, Howard Wells; Driga, Olga; Elmer, Peter; Hardenbrook, Joshua; Hebda, Philip; Koay, Sue Ann; Lujan, Paul; Marlow, Daniel; Medvedeva, Tatiana; Mooney, Michael; Olsen, James; Piroué, Pierre; Quan, Xiaohang; Saka, Halil; Stickland, David; Tully, Christopher; Werner, Jeremy Scott; Zuranski, Andrzej; Brownson, Eric; Malik, Sudhir; Mendez, Hector; Ramirez Vargas, Juan Eduardo; Barnes, Virgil E; Benedetti, Daniele; Bortoletto, Daniela; De Mattia, Marco; Gutay, Laszlo; Hu, Zhen; Jha, Manoj; Jones, Matthew; Jung, Kurt; Kress, Matthew; Leonardo, Nuno; Miller, David Harry; Neumeister, Norbert; Radburn-Smith, Benjamin Charles; Shi, Xin; Shipsey, Ian; Silvers, David; Svyatkovskiy, Alexey; Wang, Fuqiang; Xie, Wei; Xu, Lingshan; Zablocki, Jakub; Parashar, Neeti; Stupak, John; Adair, Antony; Akgun, Bora; Ecklund, Karl Matthew; Geurts, Frank J.M.; Li, Wei; Michlin, Benjamin; Padley, Brian Paul; Redjimi, Radia; Roberts, Jay; Zabel, James; Betchart, Burton; Bodek, Arie; Covarelli, Roberto; de Barbaro, Pawel; Demina, Regina; Eshaq, Yossof; Ferbel, Thomas; Garcia-Bellido, Aran; Goldenzweig, Pablo; Han, Jiyeon; Harel, Amnon; Khukhunaishvili, Aleko; Korjenevski, Sergey; Petrillo, Gianluca; Vishnevskiy, Dmitry; Ciesielski, Robert; Demortier, Luc; Goulianos, Konstantin; Mesropian, Christina; Arora, Sanjay; Barker, Anthony; Chou, John Paul; Contreras-Campana, Christian; Contreras-Campana, Emmanuel; Duggan, Daniel; Ferencek, Dinko; Gershtein, Yuri; Gray, Richard; Halkiadakis, Eva; Hidas, Dean; Kaplan, Steven; Lath, Amitabh; Panwalkar, Shruti; Park, Michael; Patel, Rishi; Salur, Sevil; Schnetzer, Steve; Sheffield, David; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Thomassen, Peter; Walker, Matthew; Rose, Keith; Spanier, Stefan; York, Andrew; Bouhali, Othmane; Castaneda Hernandez, Alfredo; Eusebi, Ricardo; Flanagan, Will; Gilmore, Jason; Kamon, Teruki; Khotilovich, Vadim; Krutelyov, Vyacheslav; Montalvo, Roy; Osipenkov, Ilya; Pakhotin, Yuriy; Perloff, Alexx; Roe, Jeffrey; Rose, Anthony; Safonov, Alexei; Suarez, Indara; Tatarinov, Aysen; Ulmer, Keith; Akchurin, Nural; Cowden, Christopher; Damgov, Jordan; Dragoiu, Cosmin; Dudero, Phillip Russell; Faulkner, James; Kovitanggoon, Kittikul; Kunori, Shuichi; Lee, Sung Won; Libeiro, Terence; Volobouev, Igor; Appelt, Eric; Delannoy, Andrés G; Greene, Senta; Gurrola, Alfredo; Johns, Willard; Maguire, Charles; Mao, Yaxian; Melo, Andrew; Sharma, Monika; Sheldon, Paul; Snook, Benjamin; Tuo, Shengquan; Velkovska, Julia; Arenton, Michael Wayne; Boutle, Sarah; Cox, Bradley; Francis, Brian; Goodell, Joseph; Hirosky, Robert; Ledovskoy, Alexander; Li, Hengne; Lin, Chuanzhe; Neu, Christopher; Wood, John; Clarke, Christopher; Harr, Robert; Karchin, Paul Edmund; Kottachchi Kankanamge Don, Chamath; Lamichhane, Pramod; Sturdy, Jared; Belknap, Donald; Carlsmith, Duncan; Cepeda, Maria; Dasu, Sridhara; Dodd, Laura; Duric, Senka; Friis, Evan; Hall-Wilton, Richard; Herndon, Matthew; Hervé, Alain; Klabbers, Pamela; Lanaro, Armando; Lazaridis, Christos; Levine, Aaron; Loveless, Richard; Mohapatra, Ajit; Ojalvo, Isabel; Perry, Thomas; Pierro, Giuseppe Antonio; Polese, Giovanni; Ross, Ian; Sarangi, Tapas; Savin, Alexander; Smith, Wesley H; Taylor, Devin; Vuosalo, Carl; Woods, Nathaniel
2015-01-01
Measurements of the ZZ production cross sections in proton-proton collisions at center-of-mass energies of 7 and 8 TeV are presented. Candidate events for the leptonic decay mode $\\mathrm{ZZ} \\to 2\\ell2\
Spray cooling simulation implementing time scale analysis and the Monte Carlo method
Kreitzer, Paul Joseph
Spray cooling research is advancing the field of heat transfer and heat rejection in high power electronics. Smaller and more capable electronics packages are producing higher amounts of waste heat, along with smaller external surface areas, and the use of active cooling is becoming a necessity. Spray cooling has shown extremely high levels of heat rejection, of up to 1000 W/cm 2 using water. Simulations of spray cooling are becoming more realistic, but this comes at a price. A previous researcher has used CFD to successfully model a single 3D droplet impact into a liquid film using the level set method. However, the complicated multiphysics occurring during spray impingement and surface interactions increases computation time to more than 30 days. Parallel processing on a 32 processor system has reduced this time tremendously, but still requires more than a day. The present work uses experimental and computational results in addition to numerical correlations representing the physics occurring on a heated impingement surface. The current model represents the spray behavior of a Spraying Systems FullJet 1/8-g spray nozzle. Typical spray characteristics are indicated as follows: flow rate of 1.05x10-5 m3/s, normal droplet velocity of 12 m/s, droplet Sauter mean diameter of 48 microm, and heat flux values ranging from approximately 50--100 W/cm2 . This produces non-dimensional numbers of: We 300--1350, Re 750--3500, Oh 0.01--0.025. Numerical and experimental correlations have been identified representing crater formation, splashing, film thickness, droplet size, and spatial flux distributions. A combination of these methods has resulted in a Monte Carlo spray impingement simulation model capable of simulating hundreds of thousands of droplet impingements or approximately one millisecond. A random sequence of droplet impingement locations and diameters is generated, with the proper radial spatial distribution and diameter distribution. Hence the impingement, lifetime
A Bayesian analysis of rare B decays with advanced Monte Carlo methods
Energy Technology Data Exchange (ETDEWEB)
Beaujean, Frederik
2012-11-12
Searching for new physics in rare B meson decays governed by b {yields} s transitions, we perform a model-independent global fit of the short-distance couplings C{sub 7}, C{sub 9}, and C{sub 10} of the {Delta}B=1 effective field theory. We assume the standard-model set of b {yields} s{gamma} and b {yields} sl{sup +}l{sup -} operators with real-valued C{sub i}. A total of 59 measurements by the experiments BaBar, Belle, CDF, CLEO, and LHCb of observables in B{yields}K{sup *}{gamma}, B{yields}K{sup (*)}l{sup +}l{sup -}, and B{sub s}{yields}{mu}{sup +}{mu}{sup -} decays are used in the fit. Our analysis is the first of its kind to harness the full power of the Bayesian approach to probability theory. All main sources of theory uncertainty explicitly enter the fit in the form of nuisance parameters. We make optimal use of the experimental information to simultaneously constrain theWilson coefficients as well as hadronic form factors - the dominant theory uncertainty. Generating samples from the posterior probability distribution to compute marginal distributions and predict observables by uncertainty propagation is a formidable numerical challenge for two reasons. First, the posterior has multiple well separated maxima and degeneracies. Second, the computation of the theory predictions is very time consuming. A single posterior evaluation requires O(1s), and a few million evaluations are needed. Population Monte Carlo (PMC) provides a solution to both issues; a mixture density is iteratively adapted to the posterior, and samples are drawn in a massively parallel way using importance sampling. The major shortcoming of PMC is the need for cogent knowledge of the posterior at the initial stage. In an effort towards a general black-box Monte Carlo sampling algorithm, we present a new method to extract the necessary information in a reliable and automatic manner from Markov chains with the help of hierarchical clustering. Exploiting the latest 2012 measurements, the fit
Versluis, R.; Dorsman, R.; Thielen, L.; Roos, M.E.
2009-01-01
A new approach for performing numerical direct simulation Monte Carlo (DSMC) simulations on turbomolecular pumps in the free molecular and transitional flow regimes is described. The chosen approach is to use surfaces that move relative to the grid to model the effect of rotors and stators on a gas
A study of the XY model by the Monte Carlo method
Suranyi, Peter; Harten, Paul
1987-01-01
The massively parallel processor is used to perform Monte Carlo simulations for the two dimensional XY model on lattices of sizes up to 128 x 128. A parallel random number generator was constructed, finite size effects were studied, and run times were compared with those on a CRAY X-MP supercomputer.
Makarevich, K. O.; Minenko, V. F.; Verenich, K. A.; Kuten, S. A.
2016-05-01
This work is dedicated to modeling dental radiographic examinations to assess the absorbed doses of patients and effective doses. For simulating X-ray spectra, the TASMIP empirical model is used. Doses are assessed on the basis of the Monte Carlo method by using MCNP code for voxel phantoms of ICRP. The results of the assessment of doses to individual organs and effective doses for different types of dental examinations and features of X-ray tube are presented.
Energy Technology Data Exchange (ETDEWEB)
Mendonca, Dalila; Neves, Lucio P.; Perini, Ana P., E-mail: anapaula.perini@ufu.br [Universidade Federal de Uberlandia (INFIS/UFU), Uberlandia, MG (Brazil). Instituto de Fisica; Santos, William S.; Caldas, Linda V.E. [Instituto de Pesquisas Energeticas e Nucleres (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2015-07-01
A special pencil type ionization chamber, developed at the Instituto de Pesquisas Energeticas e Nucleares, was characterized by means of Monte Carlo simulation to determine the influence of its components on its response. The main differences between this ionization chamber and commercial ionization chambers are related to its configuration and constituent materials. The simulations were made employing the MCNP-4C Monte Carlo code. The highest influence was obtained for the body of PMMA: 7.0%. (author)
The-wiZZ: Clustering redshift estimation for everyone
Morrison, Christopher B; Schmidt, Samuel J; Baldry, Ivan K; Bilicki, Maciej; Choi, Ami; Erben, Thomas; Schneider, Peter
2016-01-01
We present The-wiZZ, an open source and user-friendly software for estimating the redshift distributions of photometric galaxies with unknown redshifts by spatially cross-correlating them against a reference sample with known redshifts. The main benefit of The-wiZZ is in separating the angular pair finding and correlation estimation from the computation of the output clustering redshifts allowing anyone to create a clustering redshift for their sample without the intervention of an "expert". It allows the end user of a given survey to select any sub-sample of photometric galaxies with unknown redshifts, match this sample's catalog indices into a value-added data file, and produce a clustering redshift estimation for this sample in a fraction of the time it would take to run all the angular correlations needed to produce a clustering redshift. We show results with this software using photometric data from the Kilo-Degree Survey (KiDS) and spectroscopic redshifts from the Galaxy and Mass Assembly (GAMA) survey ...
KIC11911480: the second ZZ Ceti in the $Kepler$ field
Greiss, S; Hermes, J J; Steeghs, D; Koester, D; Ramsay, G; Barclay, T; Townsley, D M
2013-01-01
We report the discovery of the second pulsating hydrogen-rich (DA) white dwarf in the $Kepler$ field, KIC11911480. It was selected from the $Kepler$-INT Survey (KIS) on the basis of its colours and its variable nature was confirmed using ground-based time-series photometry. An atmosphere model fit to an intermediate-resolution spectrum of KIC11911480 places this DA white dwarf close to the blue edge of the empirical boundaries of the ZZ Ceti instability strip: $T_\\mathrm{eff} = 12\\,160 \\pm 250$ K and $\\log{g} = 7.94 \\pm 0.10 $. Assuming a mass-radius relation and cooling models for DA white dwarfs, the atmospheric parameters yield: M$_{\\rm WD}$ = 0.57 $\\pm$ 0.06 M$_\\odot$. We also obtained two quarters (Q12 and Q16) of nearly uninterrupted short-cadence $Kepler$ data on this star. We detect a total of six independent pulsation modes with a $\\geq$ 3$\\sigma$ confidence in its amplitude power spectrum. These pulsations have periods ranging between 172.9 s and 324.5 s, typical of the hotter ZZ Ceti stars. Our pre...
New chemical profiles for the asteroseismology of ZZ Ceti stars
Althaus, L G; Bischoff-Kim, A; Romero, A D; Renedo, I; García-Berro, E; Bertolami, M M Miller
2010-01-01
We compute new chemical profiles for the core and envelope of white dwarfs appropriate for pulsational studies of ZZ Ceti stars. These profiles are extracted from the complete evolution of progenitor stars, evolved through the main sequence and the thermally-pulsing asymptotic giant branch (AGB) stages, and from time-dependent element diffusion during white dwarf evolution. We discuss the importance of the initial-final mass relationship for the white dwarf carbon-oxygen composition. In particular, we find that the central oxygen abundance may be underestimated by about 15% if the white dwarf mass is assumed to be the hydrogen-free core mass before the first thermal pulse. We also discuss the importance for the chemical profiles expected in the outermost layers of ZZ Ceti stars of the computation of the thermally-pulsing AGB phase and of the phase in which element diffusion is relevant. We find a strong dependence of the outer layer chemical stratification on the stellar mass. In particular, in the less massi...
Nakayama, Hiroshi; Furuichi, Akihisa; Kita, Takashi; Nishino, Taneo
1997-04-01
Structural phase transition of epitaxial growing layer is quite important to understand the atomic scale mechanism of molecular beam epitaxy (MBE). GaAs and related alloy semiconductors are typical systems which show variety of such structural transitions during MBE. Structural evolution of surface reconstruction phases and an order-disorder transition in III-V alloy semiconductors are typical cases where such phase transitions appear during epitaxial processes. In this work, a stochastic theory and the Monte-Carlo simulation have been presented to describe the structural evolution of epitaxial growth in binary system. This method, known here as the 'Monte-Carlo master equation (MCME) method', couples a master equation for epitaxial growth kinetics with an Ising Hamiltonian of growing surface. The Monte-Carlo (MC) simulation of binary growing surface with atom-correlation effects has successfully revealed the evolution of atomic structure and the formation of short-range ordering (SRO) during epitaxy. This demonstrates the usefulness of the MCME method in describing the atomic-structural dynamics as compared with a conventional theory of epitaxy based on a diffusion equation and standard nucleation theory.
Kumar, Sudhir; Srinivasan, P; Sharma, S D; Saxena, Sanjay Kumar; Bakshi, A K; Dash, Ashutosh; Babu, D A R; Sharma, D N
2015-09-01
Isotope production and Application Division of Bhabha Atomic Research Center developed (32)P patch sources for treatment of superficial tumors. Surface dose rate of a newly developed (32)P patch source of nominal diameter 25 mm was measured experimentally using standard extrapolation ionization chamber and Gafchromic EBT film. Monte Carlo model of the (32)P patch source along with the extrapolation chamber was also developed to estimate the surface dose rates from these sources. The surface dose rates to tissue (cGy/min) measured using extrapolation chamber and radiochromic films are 82.03±4.18 (k=2) and 79.13±2.53 (k=2) respectively. The two values of the surface dose rates measured using the two independent experimental methods are in good agreement to each other within a variation of 3.5%. The surface dose rate to tissue (cGy/min) estimated using the MCNP Monte Carlo code works out to be 77.78±1.16 (k=2). The maximum deviation between the surface dose rates to tissue obtained by Monte Carlo and the extrapolation chamber method is 5.2% whereas the difference between the surface dose rates obtained by radiochromic film measurement and the Monte Carlo simulation is 1.7%. The three values of the surface dose rates of the (32)P patch source obtained by three independent methods are in good agreement to one another within the uncertainties associated with their measurements and calculation. This work has demonstrated that MCNP based electron transport simulations are accurate enough for determining the dosimetry parameters of the indigenously developed (32)P patch sources for contact brachytherapy applications.
Current impulse response of thin InP p+-i-n+ diodes using full band structure Monte Carlo method
You, A. H.; Cheang, P. L.
2007-02-01
A random response time model to compute the statistics of the avalanche buildup time of double-carrier multiplication in avalanche photodiodes (APDs) using full band structure Monte Carlo (FBMC) method is discussed. The effect of feedback impact ionization process and the dead-space effect on random response time are included in order to simulate the speed of APD. The time response of InP p+-i-n+ diodes with the multiplication region of 0.2μm is presented. Finally, the FBMC model is used to calculate the current impulse response of the thin InP p+-i-n+ diodes with multiplication lengths of 0.05 and 0.2μm using Ramo's theorem [Proc. IRE 27, 584 (1939)]. The simulated current impulse response of the FBMC model is compared to the results simulated from a simple Monte Carlo model.
Prytkova, Vera; Heyden, Matthias; Khago, Domarin; Freites, J Alfredo; Butts, Carter T; Martin, Rachel W; Tobias, Douglas J
2016-08-25
We present a novel multi-conformation Monte Carlo simulation method that enables the modeling of protein-protein interactions and aggregation in crowded protein solutions. This approach is relevant to a molecular-scale description of realistic biological environments, including the cytoplasm and the extracellular matrix, which are characterized by high concentrations of biomolecular solutes (e.g., 300-400 mg/mL for proteins and nucleic acids in the cytoplasm of Escherichia coli). Simulation of such environments necessitates the inclusion of a large number of protein molecules. Therefore, computationally inexpensive methods, such as rigid-body Brownian dynamics (BD) or Monte Carlo simulations, can be particularly useful. However, as we demonstrate herein, the rigid-body representation typically employed in simulations of many-protein systems gives rise to certain artifacts in protein-protein interactions. Our approach allows us to incorporate molecular flexibility in Monte Carlo simulations at low computational cost, thereby eliminating ambiguities arising from structure selection in rigid-body simulations. We benchmark and validate the methodology using simulations of hen egg white lysozyme in solution, a well-studied system for which extensive experimental data, including osmotic second virial coefficients, small-angle scattering structure factors, and multiple structures determined by X-ray and neutron crystallography and solution NMR, as well as rigid-body BD simulation results, are available for comparison.
Development of CT scanner models for patient organ dose calculations using Monte Carlo methods
Gu, Jianwei
There is a serious and growing concern about the CT dose delivered by diagnostic CT examinations or image-guided radiation therapy imaging procedures. To better understand and to accurately quantify radiation dose due to CT imaging, Monte Carlo based CT scanner models are needed. This dissertation describes the development, validation, and application of detailed CT scanner models including a GE LightSpeed 16 MDCT scanner and two image guided radiation therapy (IGRT) cone beam CT (CBCT) scanners, kV CBCT and MV CBCT. The modeling process considered the energy spectrum, beam geometry and movement, and bowtie filter (BTF). The methodology of validating the scanner models using reported CTDI values was also developed and implemented. Finally, the organ doses to different patients undergoing CT scan were obtained by integrating the CT scanner models with anatomically-realistic patient phantoms. The tube current modulation (TCM) technique was also investigated for dose reduction. It was found that for RPI-AM, thyroid, kidneys and thymus received largest dose of 13.05, 11.41 and 11.56 mGy/100 mAs from chest scan, abdomen-pelvis scan and CAP scan, respectively using 120 kVp protocols. For RPI-AF, thymus, small intestine and kidneys received largest dose of 10.28, 12.08 and 11.35 mGy/100 mAs from chest scan, abdomen-pelvis scan and CAP scan, respectively using 120 kVp protocols. The dose to the fetus of the 3 month pregnant patient phantom was 0.13 mGy/100 mAs and 0.57 mGy/100 mAs from the chest and kidney scan, respectively. For the chest scan of the 6 month patient phantom and the 9 month patient phantom, the fetal doses were 0.21 mGy/100 mAs and 0.26 mGy/100 mAs, respectively. For MDCT with TCM schemas, the fetal dose can be reduced with 14%-25%. To demonstrate the applicability of the method proposed in this dissertation for modeling the CT scanner, additional MDCT scanner was modeled and validated by using the measured CTDI values. These results demonstrated that the
Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Basire, M.; Soudan, J.-M.; Angelié, C., E-mail: christian.angelie@cea.fr [Laboratoire Francis Perrin, CNRS-URA 2453, CEA/DSM/IRAMIS/LIDyL, F-91191 Gif-sur-Yvette Cedex (France)
2014-09-14
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 σ-mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, g{sub p}(E{sub p}) 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 S{sub ij} 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 T{sub m} is plotted in terms of the cluster atom number N{sub at}. The standard N{sub at}{sup −1/3} linear dependence (Pawlow law) is observed for N{sub at} >300, allowing an extrapolation up to the bulk metal at 1940 ±50 K. For N{sub at} <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.
The effects of weekly augmentation therapy in patients with PiZZ α1-antitrypsin deficiency
Directory of Open Access Journals (Sweden)
Schmid ST
2012-09-01
Full Text Available ST Schmid,1 J Koepke,1 M Dresel,1 A Hattesohl,1 E Frenzel,2 J Perez,3 DA Lomas,4 E Miranda,5 T Greulich,1 S Noeske,1 M Wencker,6 H Teschler,6 C Vogelmeier,1 S Janciauskiene,2,* AR Koczulla1,*1Department of Internal Medicine, Division for Pulmonary Diseases, University Hospital Marburg, Marburg, Germany; 2Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany; 3Department of Cellular Biology, University of Malaga, Malaga, Spain; 4Department of Medicine, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom; 5Department of Biology and Biotechnology, Istituto Pasteur – Fondazione Cenci Bolognetti, Sapienza University of Rome, Rome, Italy; 6Department of Pneumology, West German Lung Clinic, Essen University Hospital, Essen, Germany*These authors contributed equally to this workBackground: The major concept behind augmentation therapy with human α1-antitrypsin (AAT is to raise the levels of AAT in patients with protease inhibitor phenotype ZZ (Glu342Lys-inherited AAT deficiency and to protect lung tissues from proteolysis and progression of emphysema.Objective: To evaluate the short-term effects of augmentation therapy (Prolastin® on plasma levels of AAT, C-reactive protein, and chemokines/cytokines.Materials and methods: Serum and exhaled breath condensate were collected from individuals with protease inhibitor phenotype ZZ AAT deficiency-related emphysema (n = 12 on the first, third, and seventh day after the infusion of intravenous Prolastin. Concentrations of total and polymeric AAT, interleukin-8 (IL-8, monocyte chemotactic protein-1, IL-6, tumor necrosis factor-α, vascular endothelial growth factor, and C-reactive protein were determined. Blood neutrophils and primary epithelial cells were also exposed to Prolastin (1 mg/mL.Results: There were significant fluctuations in serum (but not in exhaled breath condensate levels of AAT polymers, IL-8, monocyte chemotactic protein-1, IL
Directory of Open Access Journals (Sweden)
Wagner Fernando Delfino Angelotti
2008-01-01
Full Text Available The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo techniques are discussed.
Measurement of the Standard Model $ZZ$ Cross-Section in the $ZZ \\to \\ell\\ell\\ell\\ell$ Channel
Energy Technology Data Exchange (ETDEWEB)
Rodriguez, Tatiana Isabel [Univ. of Pennsylvania, Philadelphia, PA (United States)
2011-01-01
In this thesis we study one of the last corners of the Standard Model to be thoroughly investigated in a hadron collider, the production of two simultaneous Z bosons. We analyze 6.1 fb^{-1} of data produced at Fermilab at a center-of-mass energy √s = 1.96 TeV and recorded by the CDF experiment. The predicted cross-section is 1.4 pb and we measured 2.18^{+0.64 }_{-0.63} pb (stat) 0:30 (syst) using 14 observed events. This is the largest set of candidate events in this channel yet found and with our estimated signal in the sample of 9.54 events provides the smallest percentage uncertainty on the ZZ cross-section to date. We also use this large set of events to yield kinematic plots and measure ZZ properties that will be of use in probing for new physics in the future.
Energy Technology Data Exchange (ETDEWEB)
Cirrone, G.A.P., E-mail: cirrone@lns.infn.it [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Bucciolini, M. [Department of ' Fisiopatologia Clinica' , University of Florence, V.le Morgagni 85, I-50134 Florence (Italy); Bruzzi, M. [Energetic Department, University of Florence, Via S. Marta 3, I-50139 Florence (Italy); Candiano, G. [Laboratorio di Tecnologie Oncologiche HSR, Giglio Contrada, Pietrapollastra-Pisciotto, 90015 Cefalu, Palermo (Italy); Civinini, C. [National Institute for Nuclear Physics INFN, Section of Florence, Via G. Sansone 1, Sesto Fiorentino, I-50019 Florence (Italy); Cuttone, G. [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Guarino, P. [Nuclear Engineering Department, University of Palermo, Via... Palermo (Italy); Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Lo Presti, D. [Physics Department, University of Catania, Via S. Sofia 64, I-95123, Catania (Italy); Mazzaglia, S.E. [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Pallotta, S. [Department of ' Fisiopatologia Clinica' , University of Florence, V.le Morgagni 85, I-50134 Florence (Italy); Randazzo, N. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); Sipala, V. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); Physics Department, University of Catania, Via S. Sofia 64, I-95123, Catania (Italy); Stancampiano, C. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); and others
2011-12-01
In this paper the use of the Filtered Back Projection (FBP) Algorithm, in order to reconstruct tomographic images using the high energy (200-250 MeV) proton beams, is investigated. The algorithm has been studied in detail with a Monte Carlo approach and image quality has been analysed and compared with the total absorbed dose. A proton Computed Tomography (pCT) apparatus, developed by our group, has been fully simulated to exploit the power of the Geant4 Monte Carlo toolkit. From the simulation of the apparatus, a set of tomographic images of a test phantom has been reconstructed using the FBP at different absorbed dose values. The images have been evaluated in terms of homogeneity, noise, contrast, spatial and density resolution.
Modeling and simulation of radiation from hypersonic flows with Monte Carlo methods
Sohn, Ilyoup
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
Efficient 3D Kinetic Monte Carlo Method for Modeling of Molecular Structure and Dynamics
DEFF Research Database (Denmark)
Panshenskov, Mikhail; Solov'yov, Ilia; Solov'yov, Andrey V.
2014-01-01
Self-assembly of molecular systems is an important and general problem that intertwines physics, chemistry, biology, and material sciences. Through understanding of the physical principles of self-organization, it often becomes feasible to control the process and to obtain complex structures with...... the kinetic Monte Carlo approach in a three-dimensional space. We describe the computational side of the developed code, discuss its efficiency, and apply it for studying an exemplary system....
Single-cluster-update Monte Carlo method for the random anisotropy model
Rößler, U. K.
1999-06-01
A Wolff-type cluster Monte Carlo algorithm for random magnetic models is presented. The algorithm is demonstrated to reduce significantly the critical slowing down for planar random anisotropy models with weak anisotropy strength. Dynamic exponents zcluster algorithms are estimated for models with ratio of anisotropy to exchange constant D/J=1.0 on cubic lattices in three dimensions. For these models, critical exponents are derived from a finite-size scaling analysis.
Evaluation of the material assignment method used by a Monte Carlo treatment planning system.
Isambert, A; Brualla, L; Lefkopoulos, D
2009-12-01
An evaluation of the conversion process from Hounsfield units (HU) to material composition in computerised tomography (CT) images, employed by the Monte Carlo based treatment planning system ISOgray (DOSIsoft), is presented. A boundary in the HU for the material conversion between "air" and "lung" materials was determined based on a study using 22 patients. The dosimetric consequence of the new boundary was quantitatively evaluated for a lung patient plan.
A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT.
Lalonde, Arthur; Bouchard, Hugo
2016-11-21
To develop a general method for human tissue characterization with dual- and multi-energy CT and evaluate its performance in determining elemental compositions and quantities relevant to radiotherapy Monte Carlo dose calculation. Ideal materials to describe human tissue are obtained applying principal component analysis on elemental weight and density data available in literature. The theory is adapted to elemental composition for solving tissue information from CT data. A novel stoichiometric calibration method is integrated to the technique to make it suitable for a clinical environment. The performance of the method is compared with two techniques known in literature using theoretical CT data. In determining elemental weights with dual-energy CT, the method is shown to be systematically superior to the water-lipid-protein material decomposition and comparable to the parameterization technique. In determining proton stopping powers and energy absorption coefficients with dual-energy CT, the method generally shows better accuracy and unbiased results. The generality of the method is demonstrated simulating multi-energy CT data to show the potential to extract more information with multiple energies. The method proposed in this paper shows good performance to determine elemental compositions from dual-energy CT data and physical quantities relevant to radiotherapy dose calculation. The method is particularly suitable for Monte Carlo calculations and shows promise in using more than two energies to characterize human tissue with CT.
A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT
Lalonde, Arthur; Bouchard, Hugo
2016-11-01
To develop a general method for human tissue characterization with dual- and multi-energy CT and evaluate its performance in determining elemental compositions and quantities relevant to radiotherapy Monte Carlo dose calculation. Ideal materials to describe human tissue are obtained applying principal component analysis on elemental weight and density data available in literature. The theory is adapted to elemental composition for solving tissue information from CT data. A novel stoichiometric calibration method is integrated to the technique to make it suitable for a clinical environment. The performance of the method is compared with two techniques known in literature using theoretical CT data. In determining elemental weights with dual-energy CT, the method is shown to be systematically superior to the water-lipid-protein material decomposition and comparable to the parameterization technique. In determining proton stopping powers and energy absorption coefficients with dual-energy CT, the method generally shows better accuracy and unbiased results. The generality of the method is demonstrated simulating multi-energy CT data to show the potential to extract more information with multiple energies. The method proposed in this paper shows good performance to determine elemental compositions from dual-energy CT data and physical quantities relevant to radiotherapy dose calculation. The method is particularly suitable for Monte Carlo calculations and shows promise in using more than two energies to characterize human tissue with CT.
A highly heterogeneous 3D PWR core benchmark: deterministic and Monte Carlo method comparison
Jaboulay, J.-C.; Damian, F.; Douce, S.; Lopez, F.; Guenaut, C.; Aggery, A.; Poinot-Salanon, C.
2014-06-01
Physical analyses of the LWR potential performances with regards to the fuel utilization require an important part of the work dedicated to the validation of the deterministic models used for theses analyses. Advances in both codes and computer technology give the opportunity to perform the validation of these models on complex 3D core configurations closed to the physical situations encountered (both steady-state and transient configurations). In this paper, we used the Monte Carlo Transport code TRIPOLI-4®; to describe a whole 3D large-scale and highly-heterogeneous LWR core. The aim of this study is to validate the deterministic CRONOS2 code to Monte Carlo code TRIPOLI-4®; in a relevant PWR core configuration. As a consequence, a 3D pin by pin model with a consistent number of volumes (4.3 millions) and media (around 23,000) is established to precisely characterize the core at equilibrium cycle, namely using a refined burn-up and moderator density maps. The configuration selected for this analysis is a very heterogeneous PWR high conversion core with fissile (MOX fuel) and fertile zones (depleted uranium). Furthermore, a tight pitch lattice is selcted (to increase conversion of 238U in 239Pu) that leads to harder neutron spectrum compared to standard PWR assembly. In these conditions two main subjects will be discussed: the Monte Carlo variance calculation and the assessment of the diffusion operator with two energy groups for the core calculation.
Jin, Shengye; Tamura, Masayuki
2013-10-01
Monte Carlo Ray Tracing (MCRT) method is a versatile application for simulating radiative transfer regime of the Solar - Atmosphere - Landscape system. Moreover, it can be used to compute the radiation distribution over a complex landscape configuration, as an example like a forest area. Due to its robustness to the complexity of the 3-D scene altering, MCRT method is also employed for simulating canopy radiative transfer regime as the validation source of other radiative transfer models. In MCRT modeling within vegetation, one basic step is the canopy scene set up. 3-D scanning application was used for representing canopy structure as accurately as possible, but it is time consuming. Botanical growth function can be used to model the single tree growth, but cannot be used to express the impaction among trees. L-System is also a functional controlled tree growth simulation model, but it costs large computing memory. Additionally, it only models the current tree patterns rather than tree growth during we simulate the radiative transfer regime. Therefore, it is much more constructive to use regular solid pattern like ellipsoidal, cone, cylinder etc. to indicate single canopy. Considering the allelopathy phenomenon in some open forest optical images, each tree in its own `domain' repels other trees. According to this assumption a stochastic circle packing algorithm is developed to generate the 3-D canopy scene in this study. The canopy coverage (%) and the tree amount (N) of the 3-D scene are declared at first, similar to the random open forest image. Accordingly, we randomly generate each canopy radius (rc). Then we set the circle central coordinate on XY-plane as well as to keep circles separate from each other by the circle packing algorithm. To model the individual tree, we employ the Ishikawa's tree growth regressive model to set the tree parameters including DBH (dt), tree height (H). However, the relationship between canopy height (Hc) and trunk height (Ht) is
Assaraf, Roland; Domin, Dominik
2014-03-01
We study the efficiency of quantum Monte Carlo (QMC) methods in computing space localized ground state properties (properties which do not depend on distant degrees of freedom) as a function of the system size N. We prove that for the commonly used correlated sampling with reweighting method, the statistical fluctuations σ2(N) do not obey the locality property. σ2(N) grow at least linearly with N and with a slope that is related to the fluctuations of the reweighting factors. We provide numerical illustrations of these tendencies in the form of QMC calculations on linear chains of hydrogen atoms.
Hirvijoki, Eero; Äkäslompolo, Simppa; Varje, Jari; Koskela, Tuomas; Miettunen, Juho
2015-01-01
This paper explains how to obtain the distribution function of minority ions in tokamak plasmas using the Monte Carlo method. Since the emphasis is on energetic ions, the guiding-center transformation is outlined, including also the transformation of the collision operator. Even within the guiding-center formalism, the fast particle simulations can still be very CPU intensive and, therefore, we introduce the reader also to the world of high-performance computing. The paper is concluded with a few examples where the presented method has been applied.
Geochemical Characterization Using Geophysical Data and Markov Chain Monte Carlo Methods
Chen, J.; Hubbard, S.; Rubin, Y.; Murray, C.; Roden, E.; Majer, E.
2002-12-01
if they were available from direct measurements or as variables otherwise. To estimate the geochemical parameters, we first assigned a prior model for each variable and a likelihood model for each type of data, which together define posterior probability distributions for each variable on the domain. Since the posterior probability distribution may involve hundreds of variables, we used a Markov Chain Monte Carlo (MCMC) method to explore each variable by generating and subsequently evaluating hundreds of realizations. Results from this case study showed that although geophysical attributes are not necessarily directly related to geochemical parameters, geophysical data could be very useful for providing accurate and high-resolution information about geochemical parameter distribution through their joint and indirect connections with hydrogeological properties such as lithofacies. This case study also demonstrated that MCMC methods were particularly useful for geochemical parameter estimation using geophysical data because they allow incorporation into the procedure of spatial correlation information, measurement errors, and cross correlations among different types of parameters.
The period structure of the ZZ Ceti variables
Mcgraw, J. T.
1980-01-01
The current observational status of the period structure of ZZ Ceti stars is reviewed, and in particular those features which appear to be the most important for theory to explain, or which may be relevant to the directions of theoretical development are discussed. Mechanisms to explain the broad range of period structure are suggested. Multiple nonradial modes, probably corresponding to different radial overtones, may be simultaneously excited in each star. The excitation energy of individual stars is distributed among permitted modes by nonlinear resonant coupling. In addition, rotational splitting of the nonradial modes can produce closely spaced periods which results in modulation of the light curve. Amplitude/spectral complexity correlation results from the appearance in the power spectrum of harmonics and cross-frequencies which are the effects brought on by increasing nonlinearity of the pulsations.
Seismology of an Ensemble of ZZ Ceti Stars
Clemens, J C; Dunlap, Bart H; Hermes, J J
2016-01-01
We combine all the reliably-measured eigenperiods for hot, short-period ZZ Ceti stars onto one diagram and show that it has the features expected from evolutionary and pulsation theory. To make a more detailed comparison with theory we concentrate on a subset of 16 stars for which rotational splitting or other evidence gives clues to the spherical harmonic index (l) of the modes. The suspected l=1 periods in this subset of stars form a pattern of consecutive radial overtones that allow us to conduct ensemble seismology using published theoretical model grids. We find that the best-matching models have hydrogen layer masses most consistent with the canonically thick limit calculated from nuclear burning. We also find that the evolutionary models with masses and temperatures from spectroscopic fits cannot correctly reproduce the periods of the k=1 to 4 mode groups in these stars, and speculate that the mass of the helium layer in the models is too large.
Proprietes Adiabatiques des Naines Blanches Pulsantes de Type ZZ Ceti
Brassard, Pierre
1992-01-01
Cette these a pour but d'etudier les proprietes des oscillation non-radiales des etoiles ZZ Ceti, appelees aussi etoiles DA variables, dans le contexte de la theorie adiabatique des petites oscillations. Ces oscillations sont observables, pour ce type d'etoiles, sous forme de variations periodiques de la luminosite. A partir d'une analyse de modeles stellaires, analyse qui consiste principalement a calculer et a interpreter les periodes d'oscillations des modeles, nous voulons mieux connai tre les proprietes physiques fondamentales des ZZ Ceti. Nous developpons tout d'abord divers outils pour entreprendre cette etude. Apres avoir presente le formalisme mathematique de base decrivant les oscillations non-radiales d'une etoile, nous discutons des difficultes pouvant etre rencontrees dans le calcul de la frequence de Brunt-Vaisala, une quantite fondamentale pour le calcul des periodes d'oscillations. Par la suite, nous developpons un modele theorique simple permettant d'analyser et d'interpreter la structure des periodes calculees (ou observees) en termes des proprietes de structure de l'etoile. Nous presentons aussi les outils numeriques tout a fait originaux utilises pour calculer nos periodes a partir de modeles stellaires. Finalement, nous presentons les resultats d'ensemble de l'analyse de nos modeles, et discutons de l'interpretation des observations de periodes et du taux de variation de ces periodes en termes de structure de l'etoile et de composition du noyau de l'etoile, respectivement. Ces resultats representent l'etude la plus complete a ce jour de la seismologie des naines blanches.
Mizutani, Shohei; Takada, Yoshihisa; Kohno, Ryosuke; Hotta, Kenji; Tansho, Ryohei; Akimoto, Tetsuo
2016-03-01
Full Monte Carlo (FMC) calculation of dose distribution has been recognized to have superior accuracy, compared with the pencil beam algorithm (PBA). However, since the FMC methods require long calculation time, it is difficult to apply them to routine treatment planning at present. In order to improve the situation, a simplified Monte Carlo (SMC) method has been introduced to the dose kernel calculation applicable to dose optimization procedure for the proton pencil beam scanning. We have evaluated accuracy of the SMC calculation by comparing a result of the dose kernel calculation using the SMC method with that using the FMC method in an inhomogeneous phantom. The dose distribution obtained by the SMC method was in good agreement with that obtained by the FMC method. To assess the usefulness of SMC calculation in clinical situations, we have compared results of the dose calculation using the SMC with those using the PBA method for three clinical cases of tumor treatment. The dose distributions calculated with the PBA dose kernels appear to be homogeneous in the planning target volumes (PTVs). In practice, the dose distributions calculated with the SMC dose kernels with the spot weights optimized with the PBA method show largely inhomogeneous dose distributions in the PTVs, while those with the spot weights optimized with the SMC method have moderately homogeneous distributions in the PTVs. Calculation using the SMC method is faster than that using the GEANT4 by three orders of magnitude. In addition, the graphic processing unit (GPU) boosts the calculation speed by 13 times for the treatment planning using the SMC method. Thence, the SMC method will be applicable to routine clinical treatment planning for reproduction of the complex dose distribution more accurately than the PBA method in a reasonably short time by use of the GPU-based calculation engine. PACS number(s): 87.55.Gh.
Energy Technology Data Exchange (ETDEWEB)
Zhaoyuan Liu; Kord Smith; Benoit Forget; Javier Ortensi
2016-05-01
A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices. Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.
TRIGA IPR-R1 reactor simulation using Monte Carlo transport methods
Hugo Moura Dalle
2005-01-01
Resumo: A utilização do método Monte Carlo na simulação do transporte de partículas em reatores nucleares é crescente e constitui uma tendência mundial. O maior inconveniente dessa técnica, a grande exigência de capacidade de processamento, vem sendo superado pelo contínuo desenvolvimento de processadores cada vez mais rápidos. Esse contexto permitiu o desenvolvimento de metodologias de cálculo neutrônico de reatores nas quais se acopla a parte do transporte de partículas, feita com um código...
Monte-Carlo tree search method for the board game Scotland Yard
BELEJ, NEŽA
2015-01-01
In the thesis we learn about the field of artificial intelligence that investigates board games and their program-based solutions. We examine Monte-Carlo tree search algorithm and transfer it to well-known board game Scotland Yard, considering advices from Nijssen and Winands. We focus mainly on the third phase of the algorithm, playout, and decide to implement it in three different ways (from less to more advanced techniques). We compare these three aproaches. We compare the win rates and co...
Prediction of rocket plume radiative heating using backward Monte-Carlo method
Wang, K. C.
1993-01-01
A backward Monte-Carlo plume radiation code has been developed to predict rocket plume radiative heating to the rocket base region. This paper provides a description of this code and provides sample results. The code was used to predict radiative heating to various locations during test firings of 48-inch solid rocket motors at NASA Marshall Space Flight Center. Comparisons with test measurements are provided. Predictions of full scale sea level Redesigned Solid Rocket Motor (RSRM) and Advanced Solid Rocket Motor (ASRM) plume radiative heating to the Space Shuttle external tank (ET) dome center were also made. A comparison with the Development Flight Instrumentation (DFI) measurements is also provided.
Random vibration analysis of switching apparatus based on Monte Carlo method
Institute of Scientific and Technical Information of China (English)
ZHAI Guo-fu; CHEN Ying-hua; REN Wan-bin
2007-01-01
The performance in vibration environment of switching apparatus containing mechanical contact is an important element when judging the apparatus's reliability. A piecewise linear two-degrees-of-freedom mathematical model considering contact loss was built in this work, and the vibration performance of the model under random external Gaussian white noise excitation was investigated by using Monte Carlo simulation in Matlab/Simulink. Simulation showed that the spectral content and statistical characters of the contact force coincided strongly with reality. The random vibration character of the contact system was solved using time (numerical) domain simulation in this paper. Conclusions reached here are of great importance for reliability design of switching apparatus.
Directory of Open Access Journals (Sweden)
Bruno MarceloGS
2008-01-01
Full Text Available We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS particle filter and an auxiliary particle filter (APF. Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.
Nuclear Level Density of ${}^{161}$Dy in the Shell Model Monte Carlo Method
Özen, Cem; Nakada, Hitoshi
2012-01-01
We extend the shell-model Monte Carlo applications to the rare-earth region to include the odd-even nucleus ${}^{161}$Dy. The projection on an odd number of particles leads to a sign problem at low temperatures making it impractical to extract the ground-state energy in direct calculations. We use level counting data at low energies and neutron resonance data to extract the shell model ground-state energy to good precision. We then calculate the level density of ${}^{161}$Dy and find it in very good agreement with the level density extracted from experimental data.
Directory of Open Access Journals (Sweden)
Anton G. Pavlov
2008-02-01
Full Text Available We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact/association approach found in the literature, the proposed methodology enables integrated, multiframe target detection and tracking incorporating the statistical models for target aspect, target motion, and background clutter. Two implementations of the proposed algorithm are discussed using, respectively, a resample-move (RS particle filter and an auxiliary particle filter (APF. Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets.
Clement, S D; Choi, J R; Zamenhof, R G; Yanch, J C; Harling, O K
1990-01-01
Monte Carlo methods of coupled neutron/photon transport are being used in the design of filtered beams for Neutron Capture Therapy (NCT). This method of beam analysis provides segregation of each individual dose component, and thereby facilitates beam optimization. The Monte Carlo method is discussed in some detail in relation to NCT epithermal beam design. Ideal neutron beams (i.e., plane-wave monoenergetic neutron beams with no primary gamma-ray contamination) have been modeled both for comparison and to establish target conditions for a practical NCT epithermal beam design. Detailed models of the 5 MWt Massachusetts Institute of Technology Research Reactor (MITR-II) together with a polyethylene head phantom have been used to characterize approximately 100 beam filter and moderator configurations. Using the Monte Carlo methodology of beam design and benchmarking/calibrating our computations with measurements, has resulted in an epithermal beam design which is useful for therapy of deep-seated brain tumors. This beam is predicted to be capable of delivering a dose of 2000 RBE-cGy (cJ/kg) to a therapeutic advantage depth of 5.7 cm in polyethylene assuming 30 micrograms/g 10B in tumor with a ten-to-one tumor-to-blood ratio, and a beam diameter of 18.4 cm. The advantage ratio (AR) is predicted to be 2.2 with a total irradiation time of approximately 80 minutes. Further optimization work on the MITR-II epithermal beams is expected to improve the available beams.
Hart, Vern P; Doyle, Timothy E
2013-09-01
A Monte Carlo method was derived from the optical scattering properties of spheroidal particles and used for modeling diffuse photon migration in biological tissue. The spheroidal scattering solution used a separation of variables approach and numerical calculation of the light intensity as a function of the scattering angle. A Monte Carlo algorithm was then developed which utilized the scattering solution to determine successive photon trajectories in a three-dimensional simulation of optical diffusion and resultant scattering intensities in virtual tissue. Monte Carlo simulations using isotropic randomization, Henyey-Greenstein phase functions, and spherical Mie scattering were additionally developed and used for comparison to the spheroidal method. Intensity profiles extracted from diffusion simulations showed that the four models differed significantly. The depth of scattering extinction varied widely among the four models, with the isotropic, spherical, spheroidal, and phase function models displaying total extinction at depths of 3.62, 2.83, 3.28, and 1.95 cm, respectively. The results suggest that advanced scattering simulations could be used as a diagnostic tool by distinguishing specific cellular structures in the diffused signal. For example, simulations could be used to detect large concentrations of deformed cell nuclei indicative of early stage cancer. The presented technique is proposed to be a more physical description of photon migration than existing phase function methods. This is attributed to the spheroidal structure of highly scattering mitochondria and elongation of the cell nucleus, which occurs in the initial phases of certain cancers. The potential applications of the model and its importance to diffusive imaging techniques are discussed.
Directory of Open Access Journals (Sweden)
Amir Kariznoee
2015-06-01
Full Text Available Making decision to choose the appropriate target market is one of the key decisions in the success of firms, which has direct effect in the amount of their profits. The aim of this paper is to introduce and use of new hybrid method of AHP, Monte Carlo simulation and PROMETHEE to prioritize cities to establish retailers, considering different indices. The problem of this study is related to a factory, constructing premade pieces of buildings, that to introduce and distribute its new products is searching the new retailers in different cities. To prioritize cities, with the interview with experts and the studying of the previous works the indices have been determined and the hierarchy pattern has been made. Then using the hybrid method of AHP and Monte Carlo simulation the weights of the indices have been determined and then using PROMETHEE method the best city has been chosen and the other ones have been prioritized. From the benefits of the new introduced hybrid method with respect to other ways of selecting target markets is decreasing the risk and increasing the power of decision making.
Hasan, Mahmudul; Tycner, Christopher; Sigut, Aaron; Zavala, Robert T.
2017-01-01
We describe a modified bootstrap Monte Carlo method that was developed to assess quantitatively the impact of systematic residual errors on calibrated optical interferometry data from the Navy Precision Optical Interferometer. A variety of atmospheric and instrumental effects represent the sources of residual systematic errors that remain in the data after calibration, for example when there are atmospheric fluctuations with shorter time scales than the time scale between the observations of calibrator-target pairs. The modified bootstrap Monte Carlo method retains the inherent structure of how the underlying data set was acquired, by accounting for the fact that groups of data points are obtained simultaneously instead of individual data points. When telescope pairs (baselines) and spectral channels corresponding to a specific output beam from a beam combiner are treated as groups, this method provides a more realistic (and typically larger) uncertainties associated with the fitted model parameters, such as angular diameters of resolved stars, than the standard method based solely on formal errors.This work has been supported by NSF grant AST-1614983.
Morera-Gómez, Yasser; Cartas-Aguila, Héctor A; Alonso-Hernández, Carlos M; Bernal-Castillo, Jose L; Guillén-Arruebarrena, Aniel
2015-03-01
Monte Carlo efficiency transfer method was used to determine the full energy peak efficiency of a coaxial n-type HPGe detector. The efficiencies calibration curves for three Certificate Reference Materials were determined by efficiency transfer using a (152)Eu reference source. The efficiency values obtained after efficiency transfer were used to calculate the activity concentration of the radionuclides detected in the three materials, which were measured in a low-background gamma spectrometry system. Reported and calculated activity concentration show a good agreement with mean deviations of 5%, which is satisfactory for environmental samples measurement.
Žukauskaite, A; Plukiene, R; Plukis, A
2007-01-01
Particle accelerators and other high energy facilities produce penetrating ionizing radiation (neutrons and γ-rays) that must be shielded. The objective of this work was to model photon and neutron transport in various materials, usually used as shielding, such as concrete, iron or graphite. Monte Carlo method allows obtaining answers by simulating individual particles and recording some aspects of their average behavior. In this work several nuclear experiments were modeled: AVF 65 – γ-ray beams (1-10 MeV), HIMAC and ISIS-800 – high energy neutrons (20-800 MeV) transport in iron and concrete. The results were then compared with experimental data.
Zhang, Hua-Yu; Guo, Guang-Can; Sun, Fang-Wen
2016-01-01
The nitrogen vacancy (NV) center in diamond has been widely applied for quantum information and sensing in last decade. Based on the laser polarization dependent excitation of fluorescence emission, we propose a super-resolution microscopy of NV center. A series of wide field images of NV centers are taken with different polarizations of the linear polarized excitation laser. The fluorescence intensity of NV center is changed with the relative angle between excitation laser polarization and the orientation of NV center dipole. The images pumped by different excitation laser polarizations are analyzed with Monte Carlo method. Then the symmetry axis and position of NV center are obtained with sub-diffraction resolution.
Mellado, B; Quayle, W; Wu, S
2004-01-01
In this note a full electron-based calibration of the Electromagnetic Barrel Calorimeter is performed. The improvement in resolution and linearity for electrons of energies ranging from 10 GeV up to the TeV scale is demostrated. A new general method is proposed which can be applied in multi-lepton final states where detector level information is exploited to discriminate between signal and background. The method is applied to the H->ZZ(*)->4e channel.
Shinn, Judy L.; Wilson, John W.; Nealy, John E.; Cucinotta, Francis A.
1990-01-01
Continuing efforts toward validating the buildup factor method and the BRYNTRN code, which use the deterministic approach in solving radiation transport problems and are the candidate engineering tools in space radiation shielding analyses, are presented. A simplified theory of proton buildup factors assuming no neutron coupling is derived to verify a previously chosen form for parameterizing the dose conversion factor that includes the secondary particle buildup effect. Estimates of dose in tissue made by the two deterministic approaches and the Monte Carlo method are intercompared for cases with various thicknesses of shields and various types of proton spectra. The results are found to be in reasonable agreement but with some overestimation by the buildup factor method when the effect of neutron production in the shield is significant. Future improvement to include neutron coupling in the buildup factor theory is suggested to alleviate this shortcoming. Impressive agreement for individual components of doses, such as those from the secondaries and heavy particle recoils, are obtained between BRYNTRN and Monte Carlo results.
Curis, Emmanuel; Bénazeth, Simone
2005-05-01
An important step in X-ray absorption spectroscopy (XAS) analysis is the fitting of a model to the experimental spectra, with a view to obtaining structural parameters. It is important to estimate the errors on these parameters, and three methods are used for this purpose. This article presents the conditions for applying these methods. It is shown that the usual equation Sigma = 2H(-1) is not applicable for fitting in R space or on filtered XAS data; a formula is established to treat these cases, and the equivalence between the usual formula and the brute-force method is evidenced. Lastly, the problem of the nonlinearity of the XAS models and a comparison with Monte Carlo methods are addressed.
Energy Technology Data Exchange (ETDEWEB)
Oramas Polo, I.
2014-07-01
This paper presents the simulation of the gamma camera Park Isocam II by Monte Carlo code SIMIND. This simulation allows detailed assessment of the functioning of the gamma camera. The parameters evaluated by means of the simulation are: the intrinsic uniformity with different window amplitudes, the system uniformity, the extrinsic spatial resolution, the maximum rate of counts, the intrinsic sensitivity, the system sensitivity, the energy resolution and the pixel size. The results of the simulation are compared and evaluated against the specifications of the manufacturer of the gamma camera and taking into account the National Protocol for Quality Control of Nuclear Medicine Instruments of the Cuban Medical Equipment Control Center. The simulation reported here demonstrates the validity of the SIMIND Monte Carlo code to evaluate the performance of the gamma camera Park Isocam II and as result a computational model of the camera has been obtained. (Author)
New developments of the ZZ Ceti instability strip: The discovery of eleven new variables
Castanheira, B G; Kleinman, S J; Nitta, A; Fraga, L; 10.1111/j.1365-2966.2010.16633.x
2010-01-01
Using the SOAR 4.1 m telescope, we report on the discovery of low amplitude pulsations for three stars previously reported as Not-Observed-to-Vary (NOV) by Mukadam et al. (2004) and Mullally et al. (2005), which are inside the ZZ Ceti instability strip. With the two pulsators discovered by Castanheira et al. (2007), we have now found variability in a total of five stars previously reported as NOVs. We also report the variability of eight new pulsating stars, not previously observed, bringing the total number of known ZZ Ceti stars to 148. In addition, we lowered the detection limit for ten NOVs located near the edges of the ZZ Ceti instability strip. Our results are consistent with a pure mass dependent ZZ Ceti instability strip.
Simulation of Cone Beam CT System Based on Monte Carlo Method
Wang, Yu; Cao, Ruifen; Hu, Liqin; Li, Bingbing
2014-01-01
Adaptive Radiation Therapy (ART) was developed based on Image-guided Radiation Therapy (IGRT) and it is the trend of photon radiation therapy. To get a better use of Cone Beam CT (CBCT) images for ART, the CBCT system model was established based on Monte Carlo program and validated against the measurement. The BEAMnrc program was adopted to the KV x-ray tube. Both IOURCE-13 and ISOURCE-24 were chosen to simulate the path of beam particles. The measured Percentage Depth Dose (PDD) and lateral dose profiles under 1cm water were compared with the dose calculated by DOSXYZnrc program. The calculated PDD was better than 1% within the depth of 10cm. More than 85% points of calculated lateral dose profiles was within 2%. The correct CBCT system model helps to improve CBCT image quality for dose verification in ART and assess the CBCT image concomitant dose risk.
AN IMPROVED MARKOV CHAIN MONTE CARLO METHOD FOR MIMO ITERATIVE DETECTION AND DECODING
Institute of Scientific and Technical Information of China (English)
Han Xiang; Wei Jibo
2008-01-01
Recently, a new soft-in soft-out detection algorithm based on the Markov Chain Monte Carlo (MCMC) simulation technique for Multiple-Input Multiple-Output (MIMO) systems is proposed,which is shown to perform significantly better than their sphere decoding counterparts with relatively low complexity. However, the MCMC simulator is likely to get trapped in a fixed state when the channel SNR is high, thus lots of repetitive samples are observed and the accuracy of A Posteriori Probability (APP) estimation deteriorates. To solve this problem, an improved version of MCMC simulator, named forced-dispersed MCMC algorithm is proposed. Based on the a posteriori variance of each bit, the Gibbs sampler is monitored. Once the trapped state is detected, the sample is dispersed intentionally according to the a posteriori variance. Extensive simulation shows that, compared with the existing solution, the proposed algorithm enables the markov chain to travel more states, which ensures a near-optimal performance.
ASSESSING CONVERGENCE OF THE MARKOV CHAIN MONTE CARLO METHOD IN MULTIVARIATE CASE
Directory of Open Access Journals (Sweden)
Daniel Furtado Ferreira
2012-01-01
Full Text Available The formal convergence diagnosis of the Markov Chain Monte Carlo (MCMC is made using univariate and multivariate criteria. In 1998, a multivariate extension of the univariate criterion of multiple sequences was proposed. However, due to some problems of that multivariate criterion, an alternative form of calculation was proposed in addition to the two new alternatives for multivariate convergence criteria. In this study, two models were used, one related to time series with two interventions and ARMA (2, 2 error and another related to a trivariate normal distribution, considering three different cases for the covariance matrix. In both the cases, the Gibbs sampler and the proposed criteria to monitor the convergence were used. Results revealed the proposed criteria to be adequate, besides being easy to implement.
Energy Technology Data Exchange (ETDEWEB)
McGraw, David [Desert Research Inst. (DRI), Reno, NV (United States); Hershey, Ronald L. [Desert Research Inst. (DRI), Reno, NV (United States)
2016-06-01
Methods were developed to quantify uncertainty and sensitivity for NETPATH inverse water-rock reaction models and to calculate dissolved inorganic carbon, carbon-14 groundwater travel times. The NETPATH models calculate upgradient groundwater mixing fractions that produce the downgradient target water chemistry along with amounts of mineral phases that are either precipitated or dissolved. Carbon-14 groundwater travel times are calculated based on the upgradient source-water fractions, carbonate mineral phase changes, and isotopic fractionation. Custom scripts and statistical code were developed for this study to facilitate modifying input parameters, running the NETPATH simulations, extracting relevant output, postprocessing the results, and producing graphs and summaries. The scripts read userspecified values for each constituent’s coefficient of variation, distribution, sensitivity parameter, maximum dissolution or precipitation amounts, and number of Monte Carlo simulations. Monte Carlo methods for analysis of parametric uncertainty assign a distribution to each uncertain variable, sample from those distributions, and evaluate the ensemble output. The uncertainty in input affected the variability of outputs, namely source-water mixing, phase dissolution and precipitation amounts, and carbon-14 travel time. Although NETPATH may provide models that satisfy the constraints, it is up to the geochemist to determine whether the results are geochemically reasonable. Two example water-rock reaction models from previous geochemical reports were considered in this study. Sensitivity analysis was also conducted to evaluate the change in output caused by a small change in input, one constituent at a time. Results were standardized to allow for sensitivity comparisons across all inputs, which results in a representative value for each scenario. The approach yielded insight into the uncertainty in water-rock reactions and travel times. For example, there was little
Qin, Mingpu; Zhang, Shiwei
2016-01-01
Ground state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum distribution are calculated for interaction strengths of U/t from 2 to 8, for a range of densities including half-filling and n = 0.3, 0.5, 0.6, 0.75, and 0.875. At half-filling, the results are numerically exact. Away from half-filling, the constrained path Monte Carlo method is employed to control the sign problem. Our results are obtained with several advances in the computational algorithm, which are described in detail. We discuss the advantages of generalized Hartree-Fock trial wave functions and its connection to pairing wave functions, as well as the interplay with different forms of Hubbard-Stratonovich decompositions. We study the use of different twist angle sets when applying the twist averaged boundary conditions. We propose the use of quasi-random sequences, whi...
Wang, Wenlong; Machta, Jonathan; Katzgraber, Helmut G
2015-07-01
Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of population-annealing Monte Carlo by computing ground states of the three-dimensional Ising spin glass with Gaussian disorder, while comparing to simulated-annealing and parallel-tempering Monte Carlo. Our results suggest that population annealing Monte Carlo is significantly more efficient than simulated annealing but comparable to parallel-tempering Monte Carlo for finding spin-glass ground states.
Wang, Wenlong; Machta, Jonathan; Katzgraber, Helmut G.
2015-07-01
Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of population-annealing Monte Carlo by computing ground states of the three-dimensional Ising spin glass with Gaussian disorder, while comparing to simulated-annealing and parallel-tempering Monte Carlo. Our results suggest that population annealing Monte Carlo is significantly more efficient than simulated annealing but comparable to parallel-tempering Monte Carlo for finding spin-glass ground states.
Williams, Michael S; Ebel, Eric D
2014-11-18
The fitting of statistical distributions to chemical and microbial contamination data is a common application in risk assessment. These distributions are used to make inferences regarding even the most pedestrian of statistics, such as the population mean. The reason for the heavy reliance on a fitted distribution is the presence of left-, right-, and interval-censored observations in the data sets, with censored observations being the result of nondetects in an assay, the use of screening tests, and other practical limitations. Considerable effort has been expended to develop statistical distributions and fitting techniques for a wide variety of applications. Of the various fitting methods, Markov Chain Monte Carlo methods are common. An underlying assumption for many of the proposed Markov Chain Monte Carlo methods is that the data represent independent and identically distributed (iid) observations from an assumed distribution. This condition is satisfied when samples are collected using a simple random sampling design. Unfortunately, samples of food commodities are generally not collected in accordance with a strict probability design. Nevertheless, pseudosystematic sampling efforts (e.g., collection of a sample hourly or weekly) from a single location in the farm-to-table continuum are reasonable approximations of a simple random sample. The assumption that the data represent an iid sample from a single distribution is more difficult to defend if samples are collected at multiple locations in the farm-to-table continuum or risk-based sampling methods are employed to preferentially select samples that are more likely to be contaminated. This paper develops a weighted bootstrap estimation framework that is appropriate for fitting a distribution to microbiological samples that are collected with unequal probabilities of selection. An example based on microbial data, derived by the Most Probable Number technique, demonstrates the method and highlights the
Energy Technology Data Exchange (ETDEWEB)
Vieira, Jose Wilson
2001-08-01
Brachytherapy is a special form of cancer treatment in which the radioactive source is very close to or inside the tumor with the objective of causing the necrosis of the cancerous tissue. The intensity of cell response to the radiation varies according to the tissue type and degree of differentiation. Since the malign cells are less differentiated than the normal ones, they are more sensitive to the radiation. This is the basis for radiotherapy techniques. Institutes that work with the application of high dose rates use sophisticated computer programs to calculate the necessary dose to achieve the necrosis of the tumor and the same time, minimizing the irradiation of tissues and organs of the neighborhood. With knowledge the characteristics of the source and the tumor, it is possible to trace isodose curves with the necessary information for planning the brachytherapy in patients. The objective of this work is, using Monte Carlo techniques, to develop a computer program - the ISODOSE - which allows to determine isodose curves in turn of linear radioactive sources used in brachytherapy. The development of ISODOSE is important because the available commercial programs, in general, are very expensive and practically inaccessible to small clinics. The use of Monte Carlo techniques is viable because they avoid problems inherent to analytic solutions as, for instance , the integration of functions with singularities in its domain. The results of ISODOSE were compared with similar data found in the literature and also with those obtained at the institutes of radiotherapy of the 'Hospital do Cancer do Recife' and of the 'Hospital Portugues do Recife'. ISODOSE presented good performance, mainly, due to the Monte Carlo techniques, that allowed a quite detailed drawing of the isodose curves in turn of linear sources. (author)
Zhang, Yong; Chen, Bin; Li, Dong
2016-04-01
To investigate the influence of polarization on the polarized light propagation in biological tissue, a polarized geometric Monte Carlo method is developed. The Stokes-Mueller formalism is expounded to describe the shifting of light polarization during propagation events, including scattering and interface interaction. The scattering amplitudes and optical parameters of different tissue structures are obtained using Mie theory. Through simulations of polarized light (pulsed dye laser at wavelength of 585 nm) propagation in an infinite slab tissue model and a discrete vessel tissue model, energy depositions in tissue structures are calculated and compared with those obtained through general geometric Monte Carlo simulation under the same parameters but without consideration of polarization effect. It is found that the absorption depth of the polarized light is about one half of that determined by conventional simulations. In the discrete vessel model, low penetrability manifests in three aspects: diffuse reflection became the main contributor to the energy escape, the proportion of epidermal energy deposition increased significantly, and energy deposition in the blood became weaker and more uneven. This may indicate that the actual thermal damage of epidermis during the real-world treatment is higher and the deep buried blood vessels are insufficiently damaged by consideration of polarization effect, compared with the conventional prediction.
Chetty, Indrin J; Moran, Jean M; McShan, Daniel L; Fraass, Benedick A; Wilderman, Scott J; Bielajew, Alex F
2002-06-01
A comprehensive set of measurements and calculations has been conducted to investigate the accuracy of the Dose Planning Method (DPM) Monte Carlo code for dose calculations from 10 and 50 MeV scanned electron beams produced from a racetrack microtron. Central axis depth dose measurements and a series of profile scans at various depths were acquired in a water phantom using a Scanditronix type RK ion chamber. Source spatial distributions for the Monte Carlo calculations were reconstructed from in-air ion chamber measurements carried out across the two-dimensional beam profile at 100 cm downstream from the source. The in-air spatial distributions were found to have full width at half maximum of 4.7 and 1.3 cm, at 100 cm from the source, for the 10 and 50 MeV beams, respectively. Energy spectra for the 10 and 50 MeV beams were determined by simulating the components of the microtron treatment head using the code MCNP4B. DPM calculations are on average within +/- 2% agreement with measurement for all depth dose and profile comparisons conducted in this study. The accuracy of the DPM code illustrated in this work suggests that DPM may be used as a valuable tool for electron beam dose calculations.
Multicomponent adsorption in mesoporous flexible materials with flat-histogram Monte Carlo methods
Mahynski, Nathan A.; Shen, Vincent K.
2016-11-01
We demonstrate an extensible flat-histogram Monte Carlo simulation methodology for studying the adsorption of multicomponent fluids in flexible porous solids. This methodology allows us to easily obtain the complete free energy landscape for the confined fluid-solid system in equilibrium with a bulk fluid of any arbitrary composition. We use this approach to study the adsorption of a prototypical coarse-grained binary fluid in "Hookean" solids, where the free energy of the solid may be described as a simple spring. However, our approach is fully extensible to solids with arbitrarily complex free energy profiles. We demonstrate that by tuning the fluid-solid interaction ranges, the inhomogeneous fluid structure inside the pore can give rise to enhanced selective capture of a larger species through cooperative adsorption with a smaller one. The maximum enhancement in selectivity is observed at low to intermediate pressures and is especially pronounced when the larger species is very dilute in the bulk. This suggest a mechanism by which the selective capture of a minor component from a bulk fluid may be enhanced.
DSMC calculations for the delta wing. [Direct Simulation Monte Carlo method
Celenligil, M. Cevdet; Moss, James N.
1990-01-01
Results are reported from three-dimensional direct simulation Monte Carlo (DSMC) computations, using a variable-hard-sphere molecular model, of hypersonic flow on a delta wing. The body-fitted grid is made up of deformed hexahedral cells divided into six tetrahedral subcells with well defined triangular faces; the simulation is carried out for 9000 time steps using 150,000 molecules. The uniform freestream conditions include M = 20.2, T = 13.32 K, rho = 0.00001729 kg/cu m, and T(wall) = 620 K, corresponding to lambda = 0.00153 m and Re = 14,000. The results are presented in graphs and briefly discussed. It is found that, as the flow expands supersonically around the leading edge, an attached leeside flow develops around the wing, and the near-surface density distribution has a maximum downstream from the stagnation point. Coefficients calculated include C(H) = 0.067, C(DP) = 0.178, C(DF) = 0.110, C(L) = 0.714, and C(D) = 1.089. The calculations required 56 h of CPU time on the NASA Langley Voyager CRAY-2 supercomputer.
Specific Absorbed Fractions of Electrons and Photons for Rad-HUMAN Phantom Using Monte Carlo Method
Wang, Wen; Long, Peng-cheng; Hu, Li-qin
2014-01-01
The specific absorbed fractions (SAF) for self- and cross-irradiation are effective tools for the internal dose estimation of inhalation and ingestion intakes of radionuclides. A set of SAFs of photon and electron were calculated using the Rad-HUMAN phantom, a computational voxel phantom of Chinese adult female and created using the color photographic image of the Chinese Visible Human (CVH) data set. The model can represent most of Chinese adult female anatomical characteristics and can be taken as an individual phantom to investigate the difference of internal dose with Caucasians. In this study, the emission of mono-energetic photons and electrons of 10keV to 4MeV energy were calculated using the Monte Carlo particle transport calculation code MCNP. Results were compared with the values from ICRP reference and ORNL models. The results showed that SAF from Rad-HUMAN have the similar trends but larger than those from the other two models. The differences were due to the racial and anatomical differences in o...
Specific absorbed fractions of electrons and photons for Rad-HUMAN phantom using Monte Carlo method
Institute of Scientific and Technical Information of China (English)
WANG Wen; CHENG Meng-Yun; LONG Peng-Cheng; HU Li-Qin
2015-01-01
The specific absorbed fractions (SAF) for self-and cross-irradiation are effective tools for the internal dose estimation of inhalation and ingestion intakes of radionuclides.A set of SAFs of photons and electrons were calculated using the Rad-HUMAN phantom,which is a computational voxel phantom of a Chinese adult female that was created using the color photographic image of the Chinese Visible Human (CVH) data set by the FDS Team.The model can represent most Chinese adult female anatomical characteristics and can be taken as an individual phantom to investigate the difference of internal dose with Caucasians.In this study,the emission of mono-energetic photons and electrons of 10 keV to 4 MeV energy were calculated using the Monte Carlo particle transport calculation code MCNP.Results were compared with the values from ICRP reference and ORNL models.The results showed that SAF from the Rad-HUMAN have similar trends but are larger than those from the other two models.The differences were due to the racial and anatomical differences in organ mass and inter-organ distance.The SAFs based on the Rad-HUMAN phantom provide an accurate and reliable data for internal radiation dose calculations for Chinese females.
Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange.
Directory of Open Access Journals (Sweden)
Andreas Hula
2015-06-01
Full Text Available Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent's preference for equity with their partner, beliefs about the partner's appetite for equity, beliefs about the partner's model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP. However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference.
Size dependence study of the ordering temperature in the Fast Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Velasquez, E. A., E-mail: eavelas@gmail.com [Universidad de San Buenaventura Seccional Medellin, Grupo de Investigacion en Modelamiento y Simulacion Computacional, Facultad de Ingenierias (Colombia); Mazo-Zuluaga, J., E-mail: johanmazo@gmail.com [Universidad de Antioquia, Grupo de Estado Solido, Grupo de Instrumentacion Cientifica y Microelectronica, Instituto de Fisica-FCEN (Colombia); Mejia-Lopez, J., E-mail: jmejia@puc.cl [Universidad de Antioquia, Instituto de Fisica-FCEN (Colombia)
2013-02-15
Based on the framework of the Fast Monte Carlo approach, we study the diameter dependence of the ordering temperature in magnetic nanostructures of cylindrical shape. For the purposes of this study, Fe cylindrical-shaped samples of different sizes (20 nm height, 30-100 nm in diameter) have been chosen, and their magnetic properties have been computed as functions of the scaled temperature. Two main set of results are concluded: (a) the ordering temperature of nanostructures follows a linear scaling relationship as a function of the scaling factor x, for all the studied sizes. This finding rules out a scaling relation T Prime {sub c} = x{sup 3{eta}}T{sub c} (where {eta} is a scaling exponent, and T Prime {sub c} and T{sub c} are the scaled and true ordering temperatures) that has been proposed in the literature, and suggests that temperature should scale linearly with the scaling factor x. (b) For the nanostructures, there are three different order-disorder magnetic transition modes depending on the system's size, in very good agreement with previous experimental reports.
Was, Z
2016-01-01
Status of tau lepton decay Monte Carlo generator TAUOLA, its main applications and recent developments are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care: lesson from comparison and fits to the BaBar and Belle data is recalled. It was found, that as in the past at a time of comparisons with CLEO and ALEPH data, proper fitting, to as detailed as possible representation of the experimental data, is essential for appropriate developments of models of tau decay dynamic. This multi-dimensional nature of distributions is also important for observables where tau leptons are used to constrain experimental data. In later part of the presentation,use of the TAUOLA program for phenomenology of W,Z,H decays at LHC is addressed, in particular in the context of the Higgs boson parity measurements. Some new results, relevant for QED lepton pair emission are mentioned as well.
Atmospheric correction of Earth-observation remote sensing images by Monte Carlo method
Indian Academy of Sciences (India)
Hanane Hadjit; Abdelaziz Oukebdane; Ahmad Hafid Belbachir
2013-10-01
In earth observation, the atmospheric particles contaminate severely, through absorption and scattering, the reflected electromagnetic signal from the earth surface. It will be greatly beneficial for land surface characterization if we can remove these atmospheric effects from imagery and retrieve surface reflectance that characterizes the surface properties with the purpose of atmospheric correction. Giving the geometric parameters of the studied image and assessing the parameters describing the state of the atmosphere, it is possible to evaluate the atmospheric reflectance, and upward and downward transmittances which take part in the garbling data obtained from the image. To that end, an atmospheric correction algorithm for high spectral resolution data over land surfaces has been developed. It is designed to obtain the main atmospheric parameters needed in the image correction and the interpretation of optical observations. It also estimates the optical characteristics of the Earth-observation imagery (LANDSAT and SPOT). The physics underlying the problem of solar radiation propagations that takes into account multiple scattering and sphericity of the atmosphere has been treated using Monte Carlo techniques.
Bui, Khoa; Papavassiliou, Dimitrios
2012-02-01
The effective thermal conductivity (Keff) of carbon nanotube (CNT) composites is affected by the thermal boundary resistance (TBR) and by the dispersion pattern and geometry of the CNTs. We have previously modeled CNTs as straight cylinders and found that the TBR between CNTs (TBRCNT-CNT) can suppress Keff at high volume fractions of CNTs [1]. Effective medium theory results assume that the CNTs are in a perfect dispersion state and exclude the TBRCNT-CNT [2]. In this work, we report on the development of an algorithm for generating CNTs with worm-like geometry in 3D, and with different persistence lengths. These worm-like CNTs are then randomly placed in a periodic box representing a realistic state, since the persistence length of a CNT can be obtained from microscopic images. The use of these CNT geometries in conjunction with off-lattice Monte Carlo simulations [1] in order to study the effective thermal properties of nanocomposites will be discussed, as well as the effects of the persistence length on Keff and comparisons to straight cylinder models. References [1] K. Bui, B.P. Grady, D.V. Papavassiliou, Chem. Phys. Let., 508(4-6), 248-251, 2011 [2] C.W. Nan, G. Liu, Y. Lin, M. Li, App. Phys. Let., 85(16), 3549-3551, 2006
Energy Technology Data Exchange (ETDEWEB)
Santos, William S.; Neves, Lucio P.; Perini, Ana P.; Caldas, Linda V.E., E-mail: williathan@yahoo.com.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Belinato, Walmir; Maia, Ana F. [Universidade Federal de Sergipe (UFS), Sao Cristovao, SE (Brazil). Departamento de Fisica
2014-07-01
This study presents a computational model of exposure for a patient, cardiologist and nurse in a typical scenario of cardiac interventional procedures. In this case a set of conversion coefficient (CC) for effective dose (E) in terms of kerma-area product (KAP) for all individuals involved using seven different energy spectra and eight beam projections. The CC was also calculated for the entrance skin dose (ESD) normalized to the PKA for the patient. All individuals were represented by anthropomorphic phantoms incorporated in a radiation transport code based on Monte Carlo simulation. (author)
Directory of Open Access Journals (Sweden)
Vernieri Caterina
2012-06-01
Full Text Available Observing WZ/ZZ production at the Tevatron in a final state with a lepton, missing transverse energy and jets is extremely difficult because of the low signal rate and the huge background. In an attempt to increase the acceptance we study the sample where three high-energy jets are reconstructed, where about 1/3 of the diboson signal events are expected to end. Rather than choosing the two ET-leading jets to detect a Z signal, we make use of the information carried by all jets. To qualify the potential of our method, we estimate the probability of observing an inclusive diboson signal at the three standard deviations level (P3σ to be about four times larger than when using the two leading jets only. Aiming at applying the method to the search for the exclusive WZ/ZZ → ℓνqq¯ $qar q$ channel in the three jets sample, we analyzed separately the sample with at least one b-tagged jet and the sample with no tags. In WZ/ZZ → ℓνbb¯ $bar b$ search, we observe a modest improvement in sensitivity over the option of building the Z-mass from the two leading jets in ET. Studies for improving the method further are on-going.
Huthmacher, Klaus; Molberg, Andreas K.; Rethfeld, Bärbel; Gulley, Jeremy R.
2016-10-01
A split-step numerical method for calculating ultrafast free-electron dynamics in dielectrics is introduced. The two split steps, independently programmed in C++11 and FORTRAN 2003, are interfaced via the presented open source wrapper. The first step solves a deterministic extended multi-rate equation for the ionization, electron-phonon collisions, and single photon absorption by free-carriers. The second step is stochastic and models electron-electron collisions using Monte-Carlo techniques. This combination of deterministic and stochastic approaches is a unique and efficient method of calculating the nonlinear dynamics of 3D materials exposed to high intensity ultrashort pulses. Results from simulations solving the proposed model demonstrate how electron-electron scattering relaxes the non-equilibrium electron distribution on the femtosecond time scale.
Directory of Open Access Journals (Sweden)
Zhe Zhang
Full Text Available The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches.
Energy Technology Data Exchange (ETDEWEB)
Betzler, Benjamin R., E-mail: betzlerbr@ornl.gov [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Boulevard, Ann Arbor, MI 48109 (United States); Kiedrowski, Brian C., E-mail: bckiedro@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Boulevard, Ann Arbor, MI 48109 (United States); Brown, Forrest B., E-mail: fbrown@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663, MS A143, Los Alamos, NM 87545 (United States); Martin, William R., E-mail: wrm@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Boulevard, Ann Arbor, MI 48109 (United States)
2015-12-15
Highlights: • A transition rate matrix method for calculating α-eigenvalues is formulated. • Verification of this method is performed using multigroup infinite-medium problems. • Applications to continuous-energy media examine the slowing down of neutrons. • The effect of the α-eigenvalue spectrum on the short-time flux behavior is discussed. - Abstract: The time-dependent behavior of the energy spectrum in neutron transport was investigated with a formulation, based on continuous-time Markov processes, for computing α eigenvalues and eigenvectors in an infinite medium. For this, a research Monte Carlo code called “TORTE” (To Obtain Real Time Eigenvalues) was created and used to estimate elements of a transition rate matrix. TORTE is capable of using both multigroup and continuous-energy nuclear data, and verification was performed. Eigenvalue spectra for infinite homogeneous mixtures were obtained, and an eigenfunction expansion was used to investigate transient behavior of the neutron energy spectrum.
A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions
Liang, Yihao; Li, Yaohang
2016-01-01
In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures. It adopts the sequential updating scheme of Metropolis algorithm, and makes no approximation in the computation of energy. It reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We use this method to simulate primitive model electrolytes. We measure very precisely all ion-ion pair correlation functions at high concentrations, and extract renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.
Energy Technology Data Exchange (ETDEWEB)
Huthmacher, Klaus [Department of Physics and OPTIMAS Research Center, University of Kaiserslautern (Germany); Molberg, Andreas K. [Department of Chemistry and OPTIMAS Research Center, University of Kaiserslautern (Germany); Rethfeld, Bärbel [Department of Physics and OPTIMAS Research Center, University of Kaiserslautern (Germany); Gulley, Jeremy R., E-mail: jgulley@kennesaw.edu [Department of Physics, Kennesaw State University, Kennesaw, GA 30144 (United States)
2016-10-01
A split-step numerical method for calculating ultrafast free-electron dynamics in dielectrics is introduced. The two split steps, independently programmed in C++11 and FORTRAN 2003, are interfaced via the presented open source wrapper. The first step solves a deterministic extended multi-rate equation for the ionization, electron–phonon collisions, and single photon absorption by free-carriers. The second step is stochastic and models electron–electron collisions using Monte-Carlo techniques. This combination of deterministic and stochastic approaches is a unique and efficient method of calculating the nonlinear dynamics of 3D materials exposed to high intensity ultrashort pulses. Results from simulations solving the proposed model demonstrate how electron–electron scattering relaxes the non-equilibrium electron distribution on the femtosecond time scale.
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Ramos M, D.; Yera S, Y.; Lopez B, G. M.; Acosta R, N.; Vergara G, A., E-mail: dayana@cphr.edu.cu [Centro de Proteccion e Higiene de las Radiaciones, Calle 20 No. 4113 e/ 41 y 47, Playa, 10600 La Habana (Cuba)
2014-08-15
This work is based on the determination of the detection efficiency of {sup 125}I and {sup 131}I in thyroid of the identiFINDER detector using the Monte Carlo method. The suitability of the calibration method is analyzed, when comparing the results of the direct Monte Carlo method with the corrected, choosing the latter because the differences with the real efficiency stayed below 10%. To simulate the detector their geometric parameters were optimized using a tomographic study, what allowed the uncertainties minimization of the estimates. Finally were obtained the simulations of the detector geometry-point source to find the correction factors to 5 cm, 15 cm and 25 cm, and those corresponding to the detector-simulator arrangement for the method validation and final calculation of the efficiency, demonstrating that in the Monte Carlo method implementation if simulates at a greater distance than the used in the Laboratory measurements an efficiency overestimation can be obtained, while if simulates at a shorter distance this will be underestimated, so should be simulated at the same distance to which will be measured in the reality. Also, is achieved the obtaining of the efficiency curves and minimum detectable activity for the measurement of {sup 131}I and {sup 125}I. In general is achieved the implementation of the Monte Carlo methodology for the identiFINDER calibration with the purpose of estimating the measured activity of iodine in thyroid. This method represents an ideal way to replace the lack of patterns solutions and simulators assuring the capacities of the Internal Contamination Laboratory of the Centro de Proteccion e Higiene de las Radiaciones are always calibrated for the iodine measurement in thyroid. (author)
Shen, Y.; Van der Weide, J.A.M.; Anderluh, J.H.M.
2013-01-01
An advanced method, which we call Monte Carlo-COS method, is proposed for computing the counterparty credit exposure profile of Bermudan options under Lévy process. The different exposure profiles and exercise intensity under different mea- sures, P and Q, are discussed. Since the COS method [1] del
Energy Technology Data Exchange (ETDEWEB)
Hsu, Shih-Chieh [Univ. of California, San Diego, CA (United States)
2008-01-01
We report on a search for Standard Model (SM) production of Higgs to WW* in the two charged lepton (e, μ) and two neutrino final state in p$\\bar{p}$ collisions at a center of mass energy √s = 1.96 TeV. The data were collected with the CDF II detector at the Fermilab Tevatron and correspond to an integrated luminosity of 1.9fb^{-1}. The Matrix Element method is developed to calculate the event probability and to construct a likelihood ratio discriminator. There are 522 candidates observed with an expectation of 513 ± 41 background events and 7.8 ± 0.6 signal events for Higgs mass 160GeV/c^{2} at next-to-next-to-leading logarithmic level calculation. The observed 95% C.L. upper limit is 0.8 pb which is 2.0 times the SM prediction while the median expected limit is 3.1$+1.3\\atop{-0.9}$ with systematics included. Results for 9 other Higgs mass hypotheses ranging from 110GeV/c^{2} to 200GeV/c^{2} are also presented. The same dilepton plus large transverse energy imbalance (E_{T}) final state is used in the SM ZZ production search and the WW production study. The observed significance of ZZ → llvv channel is 1.2σ. It adds extra significance to the ZZ → 4l channel and leads to a strong evidence of ZZ production with 4.4 σ significance. The potential improvement of the anomalous triple gauge coupling measurement by using the Matrix Element method in WW production is also studied.
Ustinov, E. A.
2017-01-01
The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.
1983-10-31
tranal. Sykes and Bell) pp. 342-51 12. J. M. McKinley and P. P. Schmidt, Che. Phys. Letters, submitted. and ref. (4) 13. G. Arfken . Mathematical Methods ...Transfer of Atoms, Ions and Molecular Groups Nf in Solution.III. Monte Carlo methods for the evaluation of rate constants I by P. P. Schmidt Prepared...technical Groups in Solution.poilI. Monte Carlo methods for the evaluation of rate a. PERFORMING ORG. REPORT NUMBER congtant 7, AUTHOR(e) B. CONTRACT Oft
Wang, Zhen; Cui, Shengcheng; Yang, Jun; Gao, Haiyang; Liu, Chao; Zhang, Zhibo
2017-03-01
We present a novel hybrid scattering order-dependent variance reduction method to accelerate the convergence rate in both forward and backward Monte Carlo radiative transfer simulations involving highly forward-peaked scattering phase function. This method is built upon a newly developed theoretical framework that not only unifies both forward and backward radiative transfer in scattering-order-dependent integral equation, but also generalizes the variance reduction formalism in a wide range of simulation scenarios. In previous studies, variance reduction is achieved either by using the scattering phase function forward truncation technique or the target directional importance sampling technique. Our method combines both of them. A novel feature of our method is that all the tuning parameters used for phase function truncation and importance sampling techniques at each order of scattering are automatically optimized by the scattering order-dependent numerical evaluation experiments. To make such experiments feasible, we present a new scattering order sampling algorithm by remodeling integral radiative transfer kernel for the phase function truncation method. The presented method has been implemented in our Multiple-Scaling-based Cloudy Atmospheric Radiative Transfer (MSCART) model for validation and evaluation. The main advantage of the method is that it greatly improves the trade-off between numerical efficiency and accuracy order by order.
Benacka, Jan
2016-08-01
This paper reports on lessons in which 18-19 years old high school students modelled random processes with Excel. In the first lesson, 26 students formulated a hypothesis on the area of ellipse by using the analogy between the areas of circle, square and rectangle. They verified the hypothesis by the Monte Carlo method with a spreadsheet model developed in the lesson. In the second lesson, 27 students analysed the dice poker game. First, they calculated the probability of the hands by combinatorial formulae. Then, they verified the result with a spreadsheet model developed in the lesson. The students were given a questionnaire to find out if they found the lesson interesting and contributing to their mathematical and technological knowledge.
Inglis, Stephen; Melko, Roger G
2013-01-01
We implement a Wang-Landau sampling technique in quantum Monte Carlo (QMC) simulations for the purpose of calculating the Rényi entanglement entropies and associated mutual information. The algorithm converges an estimate for an analog to the density of states for stochastic series expansion QMC, allowing a direct calculation of Rényi entropies without explicit thermodynamic integration. We benchmark results for the mutual information on two-dimensional (2D) isotropic and anisotropic Heisenberg models, a 2D transverse field Ising model, and a three-dimensional Heisenberg model, confirming a critical scaling of the mutual information in cases with a finite-temperature transition. We discuss the benefits and limitations of broad sampling techniques compared to standard importance sampling methods.
Dark matter in disk galaxies I: a Markov Chain Monte Carlo method and application to DDO 154
Hague, Peter R
2013-01-01
We present a new method to constrain the dark matter halo density profiles of disk galaxies. Our algorithm employs a Markov Chain Monte Carlo (MCMC) approach to explore the parameter space of a general family of dark matter profiles. We improve upon previous analyses by considering a wider range of halo profiles and by explicitly identifying cases in which the data are insufficient to break the degeneracies between the model parameters. We demonstrate the robustness of our algorithm using artificial data sets and show that reliable estimates of the halo density profile can be obtained from data of comparable quality to those currently available for low surface brightness (LSB) galaxies. We present our results in terms of physical quantities which are constrained by the data, and find that the logarithmic slope of the halo density profile at the radius of the innermost data point of a measured rotation curve can be strongly constrained in LSB galaxies. High surface brightness galaxies require additional inform...
Study of carrier dynamics and radiative efficiency in InGaN/GaN LEDs with Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Lu, I. Lin; Wu, Yuh-Renn [Institute of Photonics and Optoelectronics and Department of Electrical Engineering, National Taiwan University, Taipei (China); Singh, Jasprit [Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI (United States)
2011-07-15
In this paper, we have applied the Monte Carlo method to study carrier dynamics in InGaN quantum well. Vertical and lateral transport and its impact on device radiative efficiency is studied for different In compositions, dislocation densities, temperatures, and carrier densities. Our results show that the non-radiative recombination caused by the defect trapping plays a dominating role for higher indium composition and this limits the internal quantum efficiency (IQE). For lower indium composition cases, carrier leakage plays some role in the mid to high injection conditions and carrier leakage is strong in very high carrier density in all cases. Our results suggest that reducing the trap density and QCSE are still the key factors to improve the IQE. The paper examines the relative roles of leakage and non-radiative processes on IQE. (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Predicting the Dielectric Strength of c-C4F8 and SF6 Gas Mixtures by Monte Carlo Method
Institute of Scientific and Technical Information of China (English)
WU Bian-tao; XIAO Deng-ming
2007-01-01
An improved Monte Carlo method was used to simulate the motion of electrons in c-C4F8 and SF6 gas mixtures for pulsed townsend discharge. The electron swarm parameters such as effective ionization coefficient, (-α) and drift velocity over the E/N range from 280～700 Td(1Td= 10-21 V·m2) were calculated by employing a set of cross sections available in literature. From the variation cure of (-α) with SF6 partial pressure p, the limiting field (E/N)lim of gas mixture at different gas content was determined. It is found that the limiting field of c-C4F8 and SF6gas mixture is higher than that of pure SF6 at any SF6 mixture ratio. Simulation results show excellent agreement with experiment data available in previous literature.
Pasini, J M; Cordero, P
2001-04-01
We study a one-dimensional granular gas of pointlike particles not subject to gravity between two walls at temperatures T(left) and T(right). The system exhibits two distinct regimes, depending on the normalized temperature difference Delta=(T(right)-T(left))/(T(right)+T(left)): one completely fluidized and one in which a cluster coexists with the fluidized gas. When Delta is above a certain threshold, cluster formation is fully inhibited, obtaining a completely fluidized state. The mechanism that produces these two phases is explained. In the fluidized state the velocity distribution function exhibits peculiar non-Gaussian features. For this state, comparison between integration of the Boltzmann equation using the direct-simulation Monte Carlo method and results stemming from microscopic Newtonian molecular dynamics gives good coincidence, establishing that the non-Gaussian features observed do not arise from the onset of correlations.
Žukauskaitėa, A; Plukienė, R; Ridikas, D
2007-01-01
Particle accelerators and other high energy facilities produce penetrating ionizing radiation (neutrons and γ-rays) that must be shielded. The objective of this work was to model photon and neutron transport in various materials, usually used as shielding, such as concrete, iron or graphite. Monte Carlo method allows obtaining answers by simulating individual particles and recording some aspects of their average behavior. In this work several nuclear experiments were modeled: AVF 65 (AVF cyclotron of Research Center of Nuclear Physics, Osaka University, Japan) – γ-ray beams (1-10 MeV), HIMAC (heavy-ion synchrotron of the National Institute of Radiological Sciences in Chiba, Japan) and ISIS-800 (ISIS intensive spallation neutron source facility of the Rutherford Appleton laboratory, UK) – high energy neutron (20-800 MeV) transport in iron and concrete. The calculation results were then compared with experimental data.compared with experimental data.
Absorbed dose measurements in mammography using Monte Carlo method and ZrO{sub 2}+PTFE dosemeters
Energy Technology Data Exchange (ETDEWEB)
Duran M, H. A.; Hernandez O, M. [Departamento de Investigacion en Polimeros y Materiales, Universidad de Sonora, Blvd. Luis Encinas y Rosales s/n, Col. Centro, 83190 Hermosillo, Sonora (Mexico); Salas L, M. A.; Hernandez D, V. M.; Vega C, H. R. [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Cipres 10, Fracc. La Penuela, 98068 Zacatecas (Mexico); Pinedo S, A.; Ventura M, J.; Chacon, F. [Hospital General de Zona No. 1, IMSS, Interior Alameda 45, 98000 Zacatecas (Mexico); Rivera M, T. [Centro de Investigacion en Ciencia Aplicada y Tecnologia Avanzada, IPN, Av. Legaria 694, Col. Irrigacion, 11500 Mexico D. F.(Mexico)], e-mail: hduran20_1@hotmail.com
2009-10-15
Mammography test is a central tool for breast cancer diagnostic. In addition, programs are conducted periodically to detect the asymptomatic women in certain age groups; these programs have shown a reduction on breast cancer mortality. Early detection of breast cancer is achieved through a mammography, which contrasts the glandular and adipose tissue with a probable calcification. The parameters used for mammography are based on the thickness and density of the breast, their values depend on the voltage, current, focal spot and anode-filter combination. To achieve an image clear and a minimum dose must be chosen appropriate irradiation conditions. Risk associated with mammography should not be ignored. This study was performed in the General Hospital No. 1 IMSS in Zacatecas. Was used a glucose phantom and measured air Kerma at the entrance of the breast that was calculated using Monte Carlo methods and ZrO{sub 2}+PTFE thermoluminescent dosemeters, this calculation was completed with calculating the absorbed dose. (author)
Kovtanyuk, Andrey E.
2012-01-01
Radiative-conductive heat transfer in a medium bounded by two reflecting and radiating plane surfaces is considered. This process is described by a nonlinear system of two differential equations: an equation of the radiative heat transfer and an equation of the conductive heat exchange. The problem is characterized by anisotropic scattering of the medium and by specularly and diffusely reflecting boundaries. For the computation of solutions of this problem, two approaches based on iterative techniques are considered. First, a recursive algorithm based on some modification of the Monte Carlo method is proposed. Second, the diffusion approximation of the radiative transfer equation is utilized. Numerical comparisons of the approaches proposed are given in the case of isotropic scattering. © 2011 Elsevier Ltd. All rights reserved.
Palmer, Grant; Prabhu, Dinesh; Cruden, Brett A.
2013-01-01
The 2013-2022 Decaedal survey for planetary exploration has identified probe missions to Uranus and Saturn as high priorities. This work endeavors to examine the uncertainty for determining aeroheating in such entry environments. Representative entry trajectories are constructed using the TRAJ software. Flowfields at selected points on the trajectories are then computed using the Data Parallel Line Relaxation (DPLR) Computational Fluid Dynamics Code. A Monte Carlo study is performed on the DPLR input parameters to determine the uncertainty in the predicted aeroheating, and correlation coefficients are examined to identify which input parameters show the most influence on the uncertainty. A review of the present best practices for input parameters (e.g. transport coefficient and vibrational relaxation time) is also conducted. It is found that the 2(sigma) - uncertainty for heating on Uranus entry is no more than 2.1%, assuming an equilibrium catalytic wall, with the uncertainty being determined primarily by diffusion and H(sub 2) recombination rate within the boundary layer. However, if the wall is assumed to be partially or non-catalytic, this uncertainty may increase to as large as 18%. The catalytic wall model can contribute over 3x change in heat flux and a 20% variation in film coefficient. Therefore, coupled material response/fluid dynamic models are recommended for this problem. It was also found that much of this variability is artificially suppressed when a constant Schmidt number approach is implemented. Because the boundary layer is reacting, it is necessary to employ self-consistent effective binary diffusion to obtain a correct thermal transport solution. For Saturn entries, the 2(sigma) - uncertainty for convective heating was less than 3.7%. The major uncertainty driver was dependent on shock temperature/velocity, changing from boundary layer thermal conductivity to diffusivity and then to shock layer ionization rate as velocity increases. While
Paul, Sudeshna; Friedman, Alan M; Bailey-Kellogg, Chris; Craig, Bruce A
2013-04-01
The interatomic distance distribution, P(r), is a valuable tool for evaluating the structure of a molecule in solution and represents the maximum structural information that can be derived from solution scattering data without further assumptions. Most current instrumentation for scattering experiments (typically CCD detectors) generates a finely pixelated two-dimensional image. In contin-uation of the standard practice with earlier one-dimensional detectors, these images are typically reduced to a one-dimensional profile of scattering inten-sities, I(q), by circular averaging of the two-dimensional image. Indirect Fourier transformation methods are then used to reconstruct P(r) from I(q). Substantial advantages in data analysis, however, could be achieved by directly estimating the P(r) curve from the two-dimensional images. This article describes a Bayesian framework, using a Markov chain Monte Carlo method, for estimating the parameters of the indirect transform, and thus P(r), directly from the two-dimensional images. Using simulated detector images, it is demonstrated that this method yields P(r) curves nearly identical to the reference P(r). Furthermore, an approach for evaluating spatially correlated errors (such as those that arise from a detector point spread function) is evaluated. Accounting for these errors further improves the precision of the P(r) estimation. Experimental scattering data, where no ground truth reference P(r) is available, are used to demonstrate that this method yields a scattering and detector model that more closely reflects the two-dimensional data, as judged by smaller residuals in cross-validation, than P(r) obtained by indirect transformation of a one-dimensional profile. Finally, the method allows concurrent estimation of the beam center and Dmax, the longest interatomic distance in P(r), as part of the Bayesian Markov chain Monte Carlo method, reducing experimental effort and providing a well defined protocol for these
Jensen, K. A.; Ripoll, J.-F.; Wray, A. A.; Joseph, D.; ElHafi, M.
2004-01-01
Five computational methods for solution of the radiative transfer equation in an absorbing-emitting and non-scattering gray medium were compared on a 2 m JP-8 pool fire. The temperature and absorption coefficient fields were taken from a synthetic fire due to the lack of a complete set of experimental data for fires of this size. These quantities were generated by a code that has been shown to agree well with the limited quantity of relevant data in the literature. Reference solutions to the governing equation were determined using the Monte Carlo method and a ray tracing scheme with high angular resolution. Solutions using the discrete transfer method, the discrete ordinate method (DOM) with both S(sub 4) and LC(sub 11) quadratures, and moment model using the M(sub 1) closure were compared to the reference solutions in both isotropic and anisotropic regions of the computational domain. DOM LC(sub 11) is shown to be the more accurate than the commonly used S(sub 4) quadrature technique, especially in anisotropic regions of the fire domain. This represents the first study where the M(sub 1) method was applied to a combustion problem occurring in a complex three-dimensional geometry. The M(sub 1) results agree well with other solution techniques, which is encouraging for future applications to similar problems since it is computationally the least expensive solution technique. Moreover, M(sub 1) results are comparable to DOM S(sub 4).
Monte Carlo comparison of preliminary methods for ordering multiple genetic loci.
Olson, J M; Boehnke, M
1990-09-01
We carried out a simulation study to compare the power of eight methods for preliminary ordering of multiple genetic loci. Using linkage groups of six loci and a simple pedigree structure, we considered the effects on method performance of locus informativity, interlocus spacing, total distance along the chromosome, and sample size. Method performance was assessed using the mean rank of the true order, the proportion of replicates in which the true order was the best order, and the number of orders that needed to be considered for subsequent multipoint linkage analysis in order to include the true order with high probability. A new method which maximizes the sum of adjacent two-point maximum lod scores divided by the equivalent number of informative meioses and the previously described method which minimizes the sum of adjacent recombination fraction estimates were found to be the best overall locus-ordering methods for the situations considered, although several other methods also performed well.
Monte Carlo comparison of preliminary methods for ordering multiple genetic loci.
Olson, J.M.; Boehnke, M
1990-01-01
We carried out a simulation study to compare the power of eight methods for preliminary ordering of multiple genetic loci. Using linkage groups of six loci and a simple pedigree structure, we considered the effects on method performance of locus informativity, interlocus spacing, total distance along the chromosome, and sample size. Method performance was assessed using the mean rank of the true order, the proportion of replicates in which the true order was the best order, and the number of ...
Energy Technology Data Exchange (ETDEWEB)
Olaya D, H.; Diaz M, J. A.; Martinez O, S. A. [Universidad Pedagogica y Tecnologica de Colombia, Grupo de Fisica Nuclear Aplicada y Simulacion, 150003 Tunja, Boyaca (Colombia); Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas, Zac. (Mexico)
2016-10-15
Were performed experimental setups using an X-ray equipment continuous emission Pantak DXT-3000 and three types of leaded aprons with thickness of 0.25, 0.5 and 0.75 mm coated with Mylar Fiber coated Mylar on its surface. Apron was located at a distance of 2.5 m with respect focus in order to cover a radiation field size of a meter in diameter. At the beam output were added aluminum filtration in order to reproduce qualities of narrow beams N-40 (E{sub efective} = 33 keV), N-80 (E{sub efective} = 65 keV) and N-100 (E{sub efective} = 83 keV) according to the ISO standard 4037 (1-3). Each lead apron were fixed 10 TLD dosimeters over its surface, 5 dosimeters before and 5 dosimeters after with respect to X-ray beam and were calibrated for Harshaw 4500 thermoluminescent reader system order to assess the attenuation of each apron. Were performed dosimeters readings and were calculated the attenuation coefficients for each effective energy of X-ray quality. In order to confirm the method of effective energy of ISO-4037 and evaluate effectiveness of lead aprons based on energy range for each medical practice was made a Monte Carlo simulation using code GEANT-4, calculating the fluence and absorbed dose in each one of the dosimeters Monte Carlo, then coefficients of linear attenuation were calculated and compared with the experimental data and reported by the National Institute of Standards and Technology (Nist). Finally, results are consistent between theoretical calculation and experimental measures. This work will serve to make assessments for other personalized leaded protections. (Author)
Sharma, Diksha; Badal, Andreu; Badano, Aldo
2012-04-21
The computational modeling of medical imaging systems often requires obtaining a large number of simulated images with low statistical uncertainty which translates into prohibitive computing times. We describe a novel hybrid approach for Monte Carlo simulations that maximizes utilization of CPUs and GPUs in modern workstations. We apply the method to the modeling of indirect x-ray detectors using a new and improved version of the code MANTIS, an open source software tool used for the Monte Carlo simulations of indirect x-ray imagers. We first describe a GPU implementation of the physics and geometry models in fastDETECT2 (the optical transport model) and a serial CPU version of the same code. We discuss its new features like on-the-fly column geometry and columnar crosstalk in relation to the MANTIS code, and point out areas where our model provides more flexibility for the modeling of realistic columnar structures in large area detectors. Second, we modify PENELOPE (the open source software package that handles the x-ray and electron transport in MANTIS) to allow direct output of location and energy deposited during x-ray and electron interactions occurring within the scintillator. This information is then handled by optical transport routines in fastDETECT2. A load balancer dynamically allocates optical transport showers to the GPU and CPU computing cores. Our hybridMANTIS approach achieves a significant speed-up factor of 627 when compared to MANTIS and of 35 when compared to the same code running only in a CPU instead of a GPU. Using hybridMANTIS, we successfully hide hours of optical transport time by running it in parallel with the x-ray and electron transport, thus shifting the computational bottleneck from optical tox-ray transport. The new code requires much less memory than MANTIS and, asa result, allows us to efficiently simulate large area detectors.
Gallardo, Sergio; Pozuelo, Fausto; Querol, Andrea; Ródenas, José; Verdú, Gumersindo
2014-06-01
An accurate knowledge of the photon spectra emitted by X-ray tubes in radiodiagnostic is essential to better estimate the imparted dose to patients and to improve the quality image obtained with these devices. In this work, it is proposed the use of a flat panel detector together with a PMMA wedge to estimate the actual X-ray spectrum using the Monte Carlo method and unfolding techniques. The MCNP5 code has been used to model different flat panels (based on indirect and direct methods to produce charge carriers from absorbed X-rays) and to obtain the dose curves and system response functions. Most of the actual flat panel devices use scintillator materials that present K-edge discontinuities in the mass energy-absorption coefficient, which strongly affect the response matrix. In this paper, the applicability of different flat panels for reconstructing X-ray spectra is studied. The effect of the mass energy-absorption coefficient of the scintillator material has been studied on the response matrix and consequently, in the reconstructed spectra. Different unfolding methods are tested to reconstruct the actual X-ray spectrum knowing the dose curve and the response function. It has been concluded that the regularization method MTSVD is appropriate to unfold X-ray spectra in all the scintillators studied.
Quantum Monte Carlo simulation
Wang, Yazhen
2011-01-01
Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating analytically intractable quantities. We derive the bias and variance for the proposed Monte Carlo quantum simulation estimator and establish the asymptotic theory for the estimator. The theory is used to design a computational scheme for minimizing the mean square er...
Carsey, Thomas M.; Harden, Jeffrey J.
2015-01-01
Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…
The Dynamic Monte Carlo Method for Transient Analysis of Nuclear Reactors
Sjenitzer, B.L.
2013-01-01
In this thesis a new method for the analysis of power transients in a nuclear reactor is developed, which is more accurate than the present state-of-the-art methods. Transient analysis is important tool when designing nuclear reactors, since they predict the behaviour of a reactor during changing co
Monte Carlo Evaluation of a New Track-Finding Method for the VENUS Muon Detector
Asano, Yuzo; Hatanaka, Makoto; Koseki, Tadashi; Mori, Shigeki; Shirakata, Masashi; Yamamoto, Kazumichi
1989-10-01
A new method of finding a track is devised for the VENUS muon detector composed of eight-cell drift-tube modules, each cell having a rectangular cross section of 5× 7 cm2. The new method, in which fourth-order equations are solved by the Ferarri-Cardano method, is especially powerful for a track having a large incident angle with respect to the line normal to the anode-wire plane of a drift tube, compared to the presently used method in which a track is determined by the intersecting points of an equi-drift-distance circle and the anode-wire plane. Cosmic-ray test data for the forward-backward part muon detector support these simulation results.
Monte Carlo evaluation of a new track-finding method for the VENUS muon detector
Energy Technology Data Exchange (ETDEWEB)
Asano, Yuzo; Hatanaka, Makoto; Koseki, Tadashi; Mori, Shigeki; Shirakata, Masashi; Yamamoto, Kazumichi (Tsukuba Univ., Ibaraki (Japan). Inst. of Applied Physics)
1989-10-01
A new method of finding a track is devised for the VENUS muon detector composed of eight-cell drift-tube modules, each cell having a rectangular cross section of 5 x 7 cm{sup 2}. The new method, in which fourth-order equations are solved by the Ferarri-Cardano method, is especially powerful for a track having a large incident angle with respect to the line normal to the anode-wire plane of a drift tube, compared to the presently used method in which a track is determined by the intersecting points of an equi-drift-distance circle and the anode-wire plane. Cosmic-ray test data for the forward-backward part muon detector support these simulation results. (author).
Morningstar, Alan
2015-01-01
Since the discovery of the Higgs boson in 2012, the most recently confirmed and final piece of the Standard Model has been rigorously studied in various production modes and decay channels. However, Run 1 of the LHC did not yield sufficient statistics to resolve production modes in the $H\\to ZZ^{*}\\to4l$ channel. Current and future runs of the LHC will offer sufficient data to do so, thus machine learning techniques used to separate the two most frequent Higgs boson production modes - gluon fusion and vector boson fusion - were studied and the findings are presented in this report. An optimization of boosted decision trees trained on $\\sqrt{s}=\\text{8 TeV}$ ATLAS Monte Carlo data is presented. The feasibility of improving classification efficiency by using deep neural networks is also studied and detailed below.
Precision study on $ZZ\\gamma$ production including $Z$-boson leptonic decays at the ILC
Yu, Zhang; Wen-Gan, Ma; Ren-You, Zhang; Chong, Chen
2015-01-01
We report on the precision predictions for the \\eezzr process including $Z$-boson leptonic decays at the ILC in the standard model (SM). The calculation includes the full next-to-leading (NLO) electroweak (EW) corrections and high order initial state radiation (h.o.ISR) contributions. We find that the NLO EW corrections heavily suppress the LO cross section, and the h.o.ISR effects are notable near the threshold while become small in high energy region. We present the LO and the NLO EW+h.o.ISR corrected distributions of the transverse momenta of final $Z$-boson and photon as well as the $Z$-pair invariant mass, and investigate the corresponding NLO EW and h.o.ISR relative corrections. We also study the leptonic decays of the final $Z$-boson pair by adopting the {\\sc MadSpin} method where the spin correlation effect is involved. We conclude that both the h.o.ISR effects and the NLO EW corrections are important in exploring the $ZZ\\gamma$ production at the ILC.
Precision studies of the Higgs boson decay channel H -> ZZ -> 4l with MEKD
Avery, Paul; Chen, Mingshui; Cheng, Tongguang; Drozdetskiy, Alexey; Gainer, James S; Korytov, Andrey; Matchev, Konstantin T; Milenovic, Predrag; Mitselmakher, Guenakh; Park, Myeonghun; Rinkevicius, Aurelijus; Snowball, Matthew
2013-01-01
The importance of the H -> ZZ* -> 4l "golden" channel has recently been proven by its major role in the discovery, by the ATLAS and CMS collaborations, of an apparently Higgs-like resonance with mass near 125 GeV. Much previous phenomenological work on this channel focuses on its use in determining the spin and CP properties of a purported Higgs boson. Significantly less attention has been paid to the logically prior question of distinguishing signal from background events in this channel, which is especially important for a 125 GeV Higgs boson. We show the advantages of using a multivariate analysis, such as the Matrix Element Method (MEM) that will be discussed here, in separating the Higgs signal from the irreducible Standard Model background. We discuss a number of issues that may arise in the use of the MEM and compare existing leading order MEM-based approaches and software. We also provide a code to calculate a kinematic discriminant, KD, based on the full leading order matrix elements, which would aid...
Properties of the Higgs boson with the H $\\rightarrow$ ZZ $\\rightarrow$ 4 leptons channel
Ochando, Christophe
2013-01-01
On 2012 July 4th, the ATLAS and CMS experiments reported the discovery of a new boson. The measurement of its properties is now of prime interest to determine whether its the standard model (SM) Higgs or not. In the X$\\rightarrow$ ZZ$\\rightarrow$ 4 leptons (electrons or muons) channel, the final state can be fully reconstructed and with high precision, thanks to the excellent performances of the CMS detector. It therefore offers a unique opportunity to precisely measure the properties of the new boson. The analysis reported here uses pp collisions data recorded by the CMS experiment at the LHC, corresponding to the full Run I statistics (5.1 fb$^{-1}$ at $\\sqrt{s}$=7 TeV, 19.6 fb$^{-1}$ at $\\sqrt{s}$=8 TeV). The mass of the new boson is measured. The spin-parity state is studied using Matrix Element methods, where the SM Higgs hypothesis is confronted to other spin-parity hypothesis. Measurement of the cross-sections, relative the SM expectations, from the different production modes, either via fermions (gl...
Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method
Jadach, S.
2017-01-01
We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton shower Monte Carlo generators. This method was described in detail in our previous publications, where its advantages over other approaches, such as MCatNLO and POWHEG, were pointed out. Here we concentrate on presenting some numerical results (cross sections and distributions) for $Z/\\gamma^*$ (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell--Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then, we present the first results of the KrkNLO method for the Higgs production in gluon--gluon fusion at the LHC and compare them with the predictions of other programs, such as MCFM, MCatNLO, POWHEG and HNNLO, as w...
Bozzolo, Guillermo H.; Good, Brian; Noebe, Ronald D.; Honecy, Frank; Abel, Phillip
1999-01-01
Large-scale simulations of dynamic processes at the atomic level have developed into one of the main areas of work in computational materials science. Until recently, severe computational restrictions, as well as the lack of accurate methods for calculating the energetics, resulted in slower growth in the area than that required by current alloy design programs. The Computational Materials Group at the NASA Lewis Research Center is devoted to the development of powerful, accurate, economical tools to aid in alloy design. These include the BFS (Bozzolo, Ferrante, and Smith) method for alloys (ref. 1) and the development of dedicated software for large-scale simulations based on Monte Carlo- Metropolis numerical techniques, as well as state-of-the-art visualization methods. Our previous effort linking theoretical and computational modeling resulted in the successful prediction of the microstructure of a five-element intermetallic alloy, in excellent agreement with experimental results (refs. 2 and 3). This effort also produced a complete description of the role of alloying additions in intermetallic binary, ternary, and higher order alloys (ref. 4).
A Simple Monte Carlo Method for Locating the Three-dimensional Critical Slip Surface of a Slope
Institute of Scientific and Technical Information of China (English)
XIE Mowen
2004-01-01
Based on the assumption of the plain-strain problem, various optimization or random search methods have been developed for locating the critical slip surfaces in slope-stability analysis, but none of such methods is applicable to the 3D case. In this paper, a simple Monte Carlo random simulation method is proposed to identify the 3D critical slip surface. Assuming the initial slip to be the lower part of a slip ellipsoid, the 3D critical slip surface is located by means of a minimized 3D safety factor. A column-based 3D slope stability analysis model is used to calculate this factor. In this study, some practical cases of known minimum safety factors and critical slip surfaces in 2D analysis are extended to 3D slope problems to locate the critical slip surfaces. Compared with the 2D result, the resulting 3D critical slip surface has no apparent difference in terms of only cross section, but the associated 3D safety factor is definitely higher.
Monte Carlo simulations of Higgs-boson production at the LHC with the KrkNLO method
Jadach, S; Placzek, W; Sapeta, S; Siodmok, A; Skrzypek, M
2016-01-01
We present numerical tests and predictions of the KrkNLO method for matching of NLO QCD corrections to hard processes with LO parton shower Monte Carlo generators. This method was described in detail in our previous publications, where its advantages over other approaches, such as MCatNLO and POWHEG, were pointed out. Here we concentrate on presenting some numerical results (cross sections and distributions) for $Z/\\gamma^*$ (Drell-Yan) and Higgs-boson production processes at the LHC. The Drell--Yan process is used mainly to validate the KrkNLO implementation in the Herwig 7 program with respect to the previous implementation in Sherpa. We also show predictions for this process with the new, complete, MC-scheme parton distribution functions and compare them with our previously published results. Then, we present the first results of the KrkNLO method for the Higgs production in gluon--gluon fusion at the LHC and compare them with the predictions of other programs, such as MCFM, MCatNLO, POWHEG and HNNLO, as w...
Pan, J.; Durand, M. T.; Vanderjagt, B. J.
2015-12-01
Markov Chain Monte Carlo (MCMC) method is a retrieval algorithm based on Bayes' rule, which starts from an initial state of snow/soil parameters, and updates it to a series of new states by comparing the posterior probability of simulated snow microwave signals before and after each time of random walk. It is a realization of the Bayes' rule, which gives an approximation to the probability of the snow/soil parameters in condition of the measured microwave TB signals at different bands. Although this method could solve all snow parameters including depth, density, snow grain size and temperature at the same time, it still needs prior information of these parameters for posterior probability calculation. How the priors will influence the SWE retrieval is a big concern. Therefore, in this paper at first, a sensitivity test will be carried out to study how accurate the snow emission models and how explicit the snow priors need to be to maintain the SWE error within certain amount. The synthetic TB simulated from the measured snow properties plus a 2-K observation error will be used for this purpose. It aims to provide a guidance on the MCMC application under different circumstances. Later, the method will be used for the snowpits at different sites, including Sodankyla, Finland, Churchill, Canada and Colorado, USA, using the measured TB from ground-based radiometers at different bands. Based on the previous work, the error in these practical cases will be studied, and the error sources will be separated and quantified.
Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming
2011-02-01
High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.
Energy Technology Data Exchange (ETDEWEB)
Albuquerque, M.A.G.; David, M.G.; Almeida, C.E. de; Magalhaes, L.A.G., E-mail: malbuqueque@hotmail.com [Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ (Brazil). Lab. de Ciencias Radiologicas; Bernal, M. [Universidade Estadual de Campinas (UNICAMP), SP (Brazil); Braz, D. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)
2015-07-01
Breast cancer is the most common type of cancer among women. The main strategy to increase the long-term survival of patients with this disease is the early detection of the tumor, and mammography is the most appropriate method for this purpose. Despite the reduction of cancer deaths, there is a big concern about the damage caused by the ionizing radiation to the breast tissue. To evaluate these measures it was modeled a mammography equipment, and obtained the depth spectra using the Monte Carlo method - PENELOPE code. The average energies of the spectra in depth and the half value layer of the mammography output spectrum. (author)
The search for ZZ Ceti stars in the original Kepler mission
Greiss, S.; Hermes, J. J.; Gänsicke, B. T.; Steeghs, D. T. H.; Bell, Keaton J.; Raddi, R.; Tremblay, P.-E.; Breedt, E.; Ramsay, G.; Koester, D.; Carter, P. J.; Vanderbosch, Z.; Winget, D. E.; Winget, K. I.
2016-04-01
We report the discovery of 42 white dwarfs in the original Kepler mission field, including nine new confirmed pulsating hydrogen-atmosphere white dwarfs (ZZ Ceti stars). Guided by the Kepler-Isaac Newton Telescope Survey, we selected white dwarf candidates on the basis of their U - g, g - r, and r - Hα photometric colours. We followed up these candidates with high-signal-to-noise optical spectroscopy from the 4.2-m William Herschel Telescope. Using ground-based, time series photometry, we put our sample of new spectroscopically characterized white dwarfs in the context of the empirical ZZ Ceti instability strip. Prior to our search, only two pulsating white dwarfs had been observed by Kepler. Ultimately, four of our new ZZ Cetis were observed from space. These rich data sets are helping initiate a rapid advancement in the asteroseismic investigation of pulsating white dwarfs, which continues with the extended Kepler mission, K2.
Çatli, Serap
2015-09-08
High atomic number and density of dental implants leads to major problems at providing an accurate dose distribution in radiotherapy and contouring tumors and organs caused by the artifact in head and neck tumors. The limits and deficiencies of the algorithms using in the treatment planning systems can lead to large errors in dose calculation, and this may adversely affect the patient's treatment. In the present study, four commercial dental implants were used: pure titanium, titanium alloy (Ti-6Al-4V), amalgam, and crown. The effects of dental implants on dose distribution are determined with two methods: pencil beam convolution (PBC) algorithm and Monte Carlo code for 6 MV photon beam. The central axis depth doses were calculated on the phantom for a source-skin distance (SSD) of 100 cm and a 10 × 10 cm2 field using both of algorithms. The results of Monte Carlo method and Eclipse TPS were compared to each other and to those previously reported. In the present study, dose increases in tissue at a distance of 2 mm in front of the dental implants were seen due to the backscatter of electrons for dental implants at 6 MV using the Monte Carlo method. The Eclipse treatment planning system (TPS) couldn't precisely account for the backscatter radiation caused by the dental prostheses. TPS underestimated the back scatter dose and overestimated the dose after the dental implants. The large errors found for TPS in this study are due to the limits and deficiencies of the algorithms. The accuracy of the PBC algorithm of Eclipse TPS was evaluated in comparison to Monte Carlo calculations in consideration of the recommendations of the American Association of Physicists in Medicine Radiation Therapy Committee Task Group 65. From the comparisons of the TPS and Monte Carlo calculations, it is verified that the Monte Carlo simulation is a good approach to derive the dose distribution in heterogeneous media.
Çatli, Serap
2015-09-01
High atomic number and density of dental implants leads to major problems at providing an accurate dose distribution in radiotherapy and contouring tumors and organs caused by the artifact in head and neck tumors. The limits and deficiencies of the algorithms using in the treatment planning systems can lead to large errors in dose calculation, and this may adversely affect the patient's treatment. In the present study, four commercial dental implants were used: pure titanium, titanium alloy (Ti-6Al-4V), amalgam, and crown. The effects of dental implants on dose distribution are determined with two methods: pencil beam convolution (PBC) algorithm and Monte Carlo code for 6 MV photon beam. The central axis depth doses were calculated on the phantom for a source-skin distance (SSD) of 100 cm and a 10×10 cm2 field using both of algorithms. The results of Monte Carlo method and Eclipse TPS were compared to each other and to those previously reported. In the present study, dose increases in tissue at a distance of 2 mm in front of the dental implants were seen due to the backscatter of electrons for dental implants at 6 MV using the Monte Carlo method. The Eclipse treatment planning system (TPS) couldn't precisely account for the backscatter radiation caused by the dental prostheses. TPS underestimated the back scatter dose and overestimated the dose after the dental implants. The large errors found for TPS in this study are due to the limits and deficiencies of the algorithms. The accuracy of the PBC algorithm of Eclipse TPS was evaluated in comparison to Monte Carlo calculations in consideration of the recommendations of the American Association of Physicists in Medicine Radiation Therapy Committee Task Group 65. From the comparisons of the TPS and Monte Carlo calculations, it is verified that the Monte Carlo simulation is a good approach to derive the dose distribution in heterogeneous media. PACS numbers: 87.55.K.
Iftimie, R; Schofield, J P; Iftimie, Radu; Salahub, Dennis; Schofield, Jeremy
2003-01-01
In this article, we propose an efficient method for sampling the relevant state space in condensed phase reactions. In the present method, the reaction is described by solving the electronic Schr\\"{o}dinger equation for the solute atoms in the presence of explicit solvent molecules. The sampling algorithm uses a molecular mechanics guiding potential in combination with simulated tempering ideas and allows thorough exploration of the solvent state space in the context of an ab initio calculation even when the dielectric relaxation time of the solvent is long. The method is applied to the study of the double proton transfer reaction that takes place between a molecule of acetic acid and a molecule of methanol in tetrahydrofuran. It is demonstrated that calculations of rates of chemical transformations occurring in solvents of medium polarity can be performed with an increase in the cpu time of factors ranging from 4 to 15 with respect to gas-phase calculations.
Cepeda, Jose; Luna, Byron Quan; Nadim, Farrokh
2013-04-01
An essential component of a quantitative landslide hazard assessment is establishing the extent of the endangered area. This task requires accurate prediction of the run-out behaviour of a landslide, which includes the estimation of the run-out distance, run-out width, velocities, pressures, and depth of the moving mass and the final configuration of the deposits. One approach to run-out modelling is to reproduce accurately the dynamics of the propagation processes. A number of dynamic numerical models are able to compute the movement of the flow over irregular topographic terrains (3-D) controlled by a complex interaction between mechanical properties that may vary in space and time. Given the number of unknown parameters and the fact that most of the rheological parameters cannot be measured in the laboratory or field, the parametrization of run-out models is very difficult in practice. For this reason, the application of run-out models is mostly used for back-analysis of past events and very few studies have attempted to achieve forward predictions. Consequently all models are based on simplified descriptions that attempt to reproduce the general features of the failed mass motion through the use of parameters (mostly controlling shear stresses at the base of the moving mass) which account for aspects not explicitly described or oversimplified. The uncertainties involved in the run-out process have to be approached in a stochastic manner. It is of significant importance to develop methods for quantifying and properly handling the uncertainties in dynamic run-out models, in order to allow a more comprehensive approach to quantitative risk assessment. A method was developed to compute the variation in run-out intensities by using a dynamic run-out model (MassMov2D) and a probabilistic framework based on a Monte Carlo simulation in order to analyze the effect of the uncertainty of input parameters. The probability density functions of the rheological parameters
Markov chain Monte Carlo methods for statistical analysis of RF photonic devices
DEFF Research Database (Denmark)
Piels, Molly; Zibar, Darko
2016-01-01
The microwave reflection coefficient is commonly used to characterize the impedance of high-speed optoelectronic devices. Error and uncertainty in equivalent circuit parameters measured using this data are systematically evaluated. The commonly used nonlinear least-squares method for estimating u...
Monte Carlo methods in PageRank computation: When one iteration is sufficient
Avrachenkov, K.; Litvak, N.; Nemirovsky, D.; Osipova, N.
2007-01-01
PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer, and thus it reflects the popularity of a Web page. Google computes the PageRank using the power iteration method, which requires
Monte Carlo methods in PageRank computation: When one iteration is sufficient
Avrachenkov, K.; Litvak, N.; Nemirovsky, D.; Osipova, N.
2005-01-01
PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer and thus it reflects the popularity of a Web page. Google computes the PageRank using the power iteration method which requires ab
A New Monte Carlo Filtering Method for the Diagnosis of Mission-Critical Failures
Gay, Gregory; Menzies, Tim; Davies, Misty; Gundy-Burlet, Karen
2009-01-01
Testing large-scale systems is expensive in terms of both time and money. Running simulations early in the process is a proven method of finding the design faults likely to lead to critical system failures, but determining the exact cause of those errors is still time-consuming and requires access to a limited number of domain experts. It is desirable to find an automated method that explores the large number of combinations and is able to isolate likely fault points. Treatment learning is a subset of minimal contrast-set learning that, rather than classifying data into distinct categories, focuses on finding the unique factors that lead to a particular classification. That is, they find the smallest change to the data that causes the largest change in the class distribution. These treatments, when imposed, are able to identify the settings most likely to cause a mission-critical failure. This research benchmarks two treatment learning methods against standard optimization techniques across three complex systems, including two projects from the Robust Software Engineering (RSE) group within the National Aeronautics and Space Administration (NASA) Ames Research Center. It is shown that these treatment learners are both faster than traditional methods and show demonstrably better results.
La Budde, R. A.
1972-01-01
Sampling techniques have been used previously to evaluate Jacobian determinants that occur in classical mechanical descriptions of molecular scattering. These determinants also occur in the quasiclassical approximation. A new technique is described which can be used to evaluate Jacobian determinants which occur in either description. This method is expected to be valuable in the study of reactive scattering using the quasiclassical approximation.
DEFF Research Database (Denmark)
Møller, Jesper; Pettitt, A. N.; Reeves, R.
2006-01-01
is presented which requires only that independent samples can be drawn from the unnormalised density at any particular parameter value. The proposal distribution is constructed so that the normalising constant cancels from the Metropolis–Hastings ratio. The method is illustrated by producing posterior samples...... for parameters of the Ising model given a particular lattice realisation....
Fourier Path Integral Monte Carlo Method for the Calculation of the Microcanonical Density of States
Freeman, D L; Freeman, David L.
1994-01-01
Using a Hubbard-Stratonovich transformation coupled with Fourier path integral methods, expressions are derived for the numerical evaluation of the microcanonical density of states for quantum particles obeying Boltzmann statistics. A numerical algorithmis suggested to evaluate the quantum density of states and illustrated on a one-dimensional model system.
测最不确定度的评定中的蒙特卡罗方法%Uncertainty Evaluation in Measurement of Monte Carlo Method
Institute of Scientific and Technical Information of China (English)
陈雅
2012-01-01
该文介绍了蒙特卡罗法以及不确定度问题，当采用不确定度传递律进行测量不确定度评定（GUM方法）有困难或不方便时，蒙特卡罗法是实用的替代方法。%The Monte Carlo method and the question of measurement uncertainty are given ,When it is difficult to apply the GUM uncertainty framework that uses the law of propagation of uncertainty to evaluate uncertainty in measurement, the Monte Carlo Method（MCM）is a practical alternative.
Phase space modulation method for EPID-based Monte Carlo dosimetry of IMRT and RapidArc plans
Energy Technology Data Exchange (ETDEWEB)
Berman, Avery; Townson, Reid; Bush, Karl; Zavgorodni, Sergei, E-mail: szavgorodni@bccancer.bc.c
2010-11-01
Quality assurance for IMRT and VMAT require 3D evaluation of the dose distributions from the treatment planning system as compared to the distributions reconstructed from signals acquired during the plan delivery. This study presents the results of the dose reconstruction based on a novel method of Monte Carlo (MC) phase space modulation. Typically, in MC dose calculations the linear accelerator (linac) is modelled for each field in the plan and a phase space file (PSF) containing all relevant particle information is written for each field. Particles from the PSFs are then used in the dose calculation. This study investigates a method of omitting the modelling of the linac in cases where the treatment has been measured by an electronic portal imaging device. In this method each portal image is deconvolved using an empirically fit scatter kernel to obtain the primary photon fluence. The Phase Space Modulation (PSM) method consists of simulating the linac just once to create a large PSF for an open field and then modulating it using the delivered primary particle fluence. Reconstructed dose distributions in phantoms were produced using MC and the modulated PSFs. The kernel derived for this method accurately reproduced the dose distributions for 3x3, 10x10, and 15x15 cm{sup 2} field sizes (mean relative dose-difference along the beam central axis is under 1%). The method has been applied to IMRT pre-treatment verification of 10 patients (including one RapidArc{sup TM} case), mean dose in the structures of interest agreed with that calculated by MC directly within 1%, and 95% of the voxels passed 2%/2mm criteria.
Understanding Systematics in ZZ Ceti Model Fitting to Enable Differential Seismology
Fuchs, J. T.; Dunlap, B. H.; Clemens, J. C.; Meza, J. A.; Dennihy, E.; Koester, D.
2017-03-01
We are conducting a large spectroscopic survey of over 130 Southern ZZ Cetis with the Goodman Spectrograph on the SOAR Telescope. Because it employs a single instrument with high UV throughput, this survey will both improve the signal-to-noise of the sample of SDSS ZZ Cetis and provide a uniform dataset for model comparison. We are paying special attention to systematics in the spectral fitting and quantify three of those systematics here. We show that relative positions in the log g -Teff plane are consistent for these three systematics.
Understanding Systematics in ZZ Ceti Model Fitting to Enable Differential Seismology
Fuchs, J T; Clemens, J C; Meza, J A; Dennihy, E; Koester, D
2016-01-01
We are conducting a large spectroscopic survey of over 130 Southern ZZ Cetis with the Goodman Spectrograph on the SOAR Telescope. Because it employs a single instrument with high UV throughput, this survey will both improve the signal-to-noise of the sample of SDSS ZZ Cetis and provide a uniform dataset for model comparison. We are paying special attention to systematics in the spectral fitting and quantify three of those systematics here. We show that relative positions in the $\\log{g}$-$T_{\\rm eff}$ plane are consistent for these three systematics.
de Graaf, J.; Filion, L.C.; Marechal, M.A.T.; van Roij, R.H.H.G.; Dijkstra, M.
2012-01-01
In this paper, we describe the way to set up the floppy-box Monte Carlo (FBMC) method [L. Filion, M. Marechal, B. van Oorschot, D. Pelt, F. Smallenburg, and M. Dijkstra, Phys. Rev. Lett. 103, 188302 (2009)10.1103/PhysRevLett.103.188302] to predict crystal-structure candidates for colloidal particles
Niccolini, G.; Alcolea, J.
Solving the radiative transfer problem is a common problematic to may fields in astrophysics. With the increasing angular resolution of spatial or ground-based telescopes (VLTI, HST) but also with the next decade instruments (NGST, ALMA, ...), astrophysical objects reveal and will certainly reveal complex spatial structures. Consequently, it is necessary to develop numerical tools being able to solve the radiative transfer equation in three dimensions in order to model and interpret these observations. I present a 3D radiative transfer program, using a new method for the construction of an adaptive spatial grid, based on the Monte Claro method. With the help of this tools, one can solve the continuum radiative transfer problem (e.g. a dusty medium), computes the temperature structure of the considered medium and obtain the flux of the object (SED and images).
An automated Monte-Carlo based method for the calculation of cascade summing factors
Jackson, M. J.; Britton, R.; Davies, A. V.; McLarty, J. L.; Goodwin, M.
2016-10-01
A versatile method has been developed to calculate cascade summing factors for use in quantitative gamma-spectrometry analysis procedures. The proposed method is based solely on Evaluated Nuclear Structure Data File (ENSDF) nuclear data, an X-ray energy library, and accurate efficiency characterisations for single detector counting geometries. The algorithm, which accounts for γ-γ, γ-X, γ-511 and γ-e- coincidences, can be applied to any design of gamma spectrometer and can be expanded to incorporate any number of nuclides. Efficiency characterisations can be derived from measured or mathematically modelled functions, and can accommodate both point and volumetric source types. The calculated results are shown to be consistent with an industry standard gamma-spectrometry software package. Additional benefits including calculation of cascade summing factors for all gamma and X-ray emissions, not just the major emission lines, are also highlighted.
Numerical calculation of radiation protective clothing efficiency by using Monte Carlo method
Моргунов, Владимир Викторович; Диденко, Наталья Викторовна; Трищ, Роман Михайлович
2016-01-01
The article presents the results of numerical experiments on modeling of absorption of gamma-radiation with/without using the proposed radiation-protective suit and radiation-shielding material (lead glass in the form of microspheres). The proposed method numerical experiments leads to the reduction of human, time and financial resources. When conducting numerical experiments we used the software package GEANT4. When conducting numerical experiments, we used a phantom of the human body (total...
Accelerated kinetics of amorphous silicon using an on-the-fly off-lattice kinetic Monte-Carlo method
Joly, Jean-Francois; El-Mellouhi, Fedwa; Beland, Laurent Karim; Mousseau, Normand
2011-03-01
The time evolution of a series of well relaxed amorphous silicon models was simulated using the kinetic Activation-RelaxationTechnique (kART), an on-the-fly off-lattice kinetic Monte Carlo method. This novel algorithm uses the ART nouveau algorithm to generate activated events and links them with local topologies. It was shown to work well for crystals with few defects but this is the first time it is used to study an amorphous material. A parallel implementation allows us to increase the speed of the event generation phase. After each KMC step, new searches are initiated for each new topology encountered. Well relaxed amorphous silicon models of 1000 atoms described by a modified version of the empirical Stillinger-Weber potential were used as a starting point for the simulations. Initial results show that the method is faster by orders of magnitude compared to conventional MD simulations up to temperatures of 500 K. Vacancy-type defects were also introduced in this system and their stability and lifetimes are calculated.
Harvey, J.-P.; Gheribi, A. E.; Chartrand, P.
2011-08-01
The design of multicomponent alloys used in different applications based on specific thermo-physical properties determined experimentally or predicted from theoretical calculations is of major importance in many engineering applications. A procedure based on Monte Carlo simulations (MCS) and the thermodynamic integration (TI) method to improve the quality of the predicted thermodynamic properties calculated from classical thermodynamic calculations is presented in this study. The Gibbs energy function of the liquid phase of the Cu-Zr system at 1800 K has been determined based on this approach. The internal structure of Cu-Zr melts and amorphous alloys at different temperatures, as well as other physical properties were also obtained from MCS in which the phase trajectory was modeled by the modified embedded atom model formalism. A rigorous comparison between available experimental data and simulated thermo-physical properties obtained from our MCS is presented in this work. The modified quasichemical model in the pair approximation was parameterized using the internal structure data obtained from our MCS and the precise Gibbs energy function calculated at 1800 K from the TI method. The predicted activity of copper in Cu-Zr melts at 1499 K obtained from our thermodynamic optimization was corroborated by experimental data found in the literature. The validity of the amplitude of the entropy of mixing obtained from the in silico procedure presented in this work was analyzed based on the thermodynamic description of hard sphere mixtures.
Use of the Monte Carlo Method for OECD Principles-Guided QSAR Modeling of SIRT1 Inhibitors.
Kumar, Ashwani; Chauhan, Shilpi
2017-01-01
SIRT1 inhibitors offer therapeutic potential for the treatment of a number of diseases including cancer and human immunodeficiency virus infection. A diverse series of 45 compounds with reported SIRT1 inhibitory activity has been employed for the development of quantitative structure-activity relationship (QSAR) models using the Monte Carlo optimization method. This method makes use of simplified molecular input line entry system notation of the molecular structure. The QSAR models were built up according to OECD principles. Three subsets of three splits were examined and validated by respective external sets. All the three described models have good statistical quality. The best model has the following statistical characteristics: R(2) = 0.8350, Q(2)test = 0.7491 for the test set and R(2) = 0.9655, Q(2)ext = 0.9261 for the validation set. In the mechanistic interpretation, structural attributes responsible for the endpoint increase and decrease are defined. Further, the design of some prospective SIRT1 inhibitors is also presented on the basis of these structural attributes.
Lysak, Y. V.; Klimanov, V. A.; Narkevich, B. Ya
2017-01-01
One of the most difficult problems of modern radionuclide therapy (RNT) is control of the absorbed dose in pathological volume. This research presents new approach based on estimation of radiopharmaceutical (RP) accumulated activity value in tumor volume, based on planar scintigraphic images of the patient and calculated radiation transport using Monte Carlo method, including absorption and scattering in biological tissues of the patient, and elements of gamma camera itself. In our research, to obtain the data, we performed modeling scintigraphy of the vial with administered to the patient activity of RP in gamma camera, the vial was placed at the certain distance from the collimator, and the similar study was performed in identical geometry, with the same values of activity of radiopharmaceuticals in the pathological target in the body of the patient. For correct calculation results, adapted Fisher-Snyder human phantom was simulated in MCNP program. In the context of our technique, calculations were performed for different sizes of pathological targets and various tumors deeps inside patient’s body, using radiopharmaceuticals based on a mixed β-γ-radiating (131I, 177Lu), and clear β- emitting (89Sr, 90Y) therapeutic radionuclides. Presented method can be used for adequate implementing in clinical practice estimation of absorbed doses in the regions of interest on the basis of planar scintigraphy of the patient with sufficient accuracy.
Directory of Open Access Journals (Sweden)
Kaarina Matilainen
Full Text Available Estimation of variance components by Monte Carlo (MC expectation maximization (EM restricted maximum likelihood (REML is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR, where the information matrix was generated via sampling; MC average information(AI, where the information was computed as an average of observed and expected information; and MC Broyden's method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden's method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.