A Monte Carlo Primer

A Monte Carlo Primer
Author: Stephen A. Dupree
Publisher: Springer Science & Business Media
Total Pages: 236
Release: 2012-12-06
Genre: Science
ISBN: 1441990364

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In Volume 1, A Monte Carlo Primer - A Practical Approach to Radiation Transport (the "Primer"), we attempt to provide a simple, convenient, and step-by-step approach to the development, basic understanding, and use of Monte Carlo methods in radiation transport. Using the PC, the Primer begins by developing basic Monte Carlo codes to solve simple transport problems, then introduces a teaching tool, the Probabilistic Framework Code (PFC), as a standard platform for assembling, testing, and executing the various Monte Carlo techniques that are presented. This second volume attempts to continue this approach by using both custom Monte Carlo codes and PFC to apply the concepts explained in the Primer to obtain solutions to the exercises given at the end of each chapter in the Primer. A relatively modest number of exercises is included in the Primer. Some ambiguity is left in the statement of many of the exercises because the intent is not to have the user write a particular, uniquely correct piece of coding that produces a specific number as a result, but rather to encourage the user to think about the problems and develop further the concepts explained in the text. Because in most cases there is more than one way to solve a Monte Carlo transport problem, we believe that working with the concepts illustrated by the exercises is more important than obtaining anyone particular solution.

A Monte Carlo Primer

A Monte Carlo Primer
Author: Stephen A. Dupree
Publisher: Springer Science & Business Media
Total Pages: 348
Release: 2012-09-07
Genre: Science
ISBN: 1441984917

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The mathematical technique of Monte Carlo, as applied to the transport of sub-atomic particles, has been described in numerous reports and books since its formal development in the 1940s. Most of these instructional efforts have been directed either at the mathematical basis of the technique or at its practical application as embodied in the several large, formal computer codes available for performing Monte Carlo transport calculations. This book attempts to fill what appears to be a gap in this Monte Carlo literature between the mathematics and the software. Thus, while the mathematical basis for Monte Carlo transport is covered in some detail, emphasis is placed on the application of the technique to the solution of practical radiation transport problems. This is done by using the PC as the basic teaching tool. This book assumes the reader has a knowledge of integral calculus, neutron transport theory, and Fortran programming. It also assumes the reader has available a PC with a Fortran compiler. Any PC of reasonable size should be adequate to reproduce the examples or solve the exercises contained herein. The authors believe it is important for the reader to execute these examples and exercises, and by doing so to become accomplished at preparing appropriate software for solving radiation transport problems using Monte Carlo. The step from the software described in this book to the use of production Monte Carlo codes should be straightforward.

A Primer for the Monte Carlo Method

A Primer for the Monte Carlo Method
Author: Ilʹi︠a︡ Meerovich Sobolʹ
Publisher:
Total Pages: 107
Release: 1994
Genre: MATHEMATICS
ISBN: 9781315136448

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A Primer for the Monte Carlo Method

A Primer for the Monte Carlo Method
Author: Ilya M. Sobol
Publisher: CRC Press
Total Pages: 130
Release: 1994-05-19
Genre: Mathematics
ISBN: 9780849386732

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The Monte Carlo method is a numerical method of solving mathematical problems through random sampling. As a universal numerical technique, the method became possible only with the advent of computers, and its application continues to expand with each new computer generation. A Primer for the Monte Carlo Method demonstrates how practical problems in science, industry, and trade can be solved using this method. The book features the main schemes of the Monte Carlo method and presents various examples of its application, including queueing, quality and reliability estimations, neutron transport, astrophysics, and numerical analysis. The only prerequisite to using the book is an understanding of elementary calculus.

A Primer for the Monte Carlo Method

A Primer for the Monte Carlo Method
Author: Ilya M. Sobol
Publisher: CRC Press
Total Pages: 126
Release: 2017-08-29
Genre: Monte Carlo method
ISBN: 9781138469556

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The Monte Carlo method is a numerical method of solving mathematical problems through random sampling. As a universal numerical technique, the method became possible only with the advent of computers, and its application continues to expand with each new computer generation. A Primer for the Monte Carlo Method demonstrates how practical problems in science, industry, and trade can be solved using this method. The book features the main schemes of the Monte Carlo method and presents various examples of its application, including queueing, quality and reliability estimations, neutron transport, astrophysics, and numerical analysis. The only prerequisite to using the book is an understanding of elementary calculus.

An Option Greeks Primer

An Option Greeks Primer
Author: Jawwad Farid
Publisher: Springer
Total Pages: 326
Release: 2015-03-23
Genre: Business & Economics
ISBN: 1137371676

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This book provides a hands-on, practical guide to understanding derivatives pricing. Aimed at the less quantitative practitioner, it provides a balanced account of options, Greeks and hedging techniques avoiding the complicated mathematics inherent to many texts, and with a focus on modelling, market practice and intuition.

Markov Chain Monte Carlo Methods in Quantum Field Theories

Markov Chain Monte Carlo Methods in Quantum Field Theories
Author: Anosh Joseph
Publisher: Springer Nature
Total Pages: 134
Release: 2020-04-16
Genre: Science
ISBN: 3030460444

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This primer is a comprehensive collection of analytical and numerical techniques that can be used to extract the non-perturbative physics of quantum field theories. The intriguing connection between Euclidean Quantum Field Theories (QFTs) and statistical mechanics can be used to apply Markov Chain Monte Carlo (MCMC) methods to investigate strongly coupled QFTs. The overwhelming amount of reliable results coming from the field of lattice quantum chromodynamics stands out as an excellent example of MCMC methods in QFTs in action. MCMC methods have revealed the non-perturbative phase structures, symmetry breaking, and bound states of particles in QFTs. The applications also resulted in new outcomes due to cross-fertilization with research areas such as AdS/CFT correspondence in string theory and condensed matter physics. The book is aimed at advanced undergraduate students and graduate students in physics and applied mathematics, and researchers in MCMC simulations and QFTs. At the end of this book the reader will be able to apply the techniques learned to produce more independent and novel research in the field.

Monte Carlo Simulation and Resampling Methods for Social Science

Monte Carlo Simulation and Resampling Methods for Social Science
Author: Thomas M. Carsey
Publisher: SAGE Publications
Total Pages: 304
Release: 2013-08-05
Genre: Social Science
ISBN: 1483324923

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Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.

Uncertainty in Engineering

Uncertainty in Engineering
Author: Louis J. M. Aslett
Publisher: Springer Nature
Total Pages: 148
Release: 2022
Genre:
ISBN: 3030836401

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This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.