Exploring Monte Carlo Methods

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 problem" provides a unifying theme as it is repeatedly used to illustrate many features of Monte Carlo methods. This book provides the basic detail necessary to learn how to apply Monte Carlo methods and thus should be useful as a text book for undergraduate or graduate courses in numerical methods. It is written so that interested readers with only an understanding of calculus and differential equations can learn Monte Carlo on their own. Coverage of topics such as variance reduction, pseudo-random number generation, Markov chain Monte Carlo, inverse Monte Carlo, and linear operator equations will make the book useful even to experienced Monte Carlo practitioners. Provides a concise treatment of generic Monte Carlo methods Proofs for each chapter Appendixes include Certain mathematical functions; Bose Einstein functions, Fermi Dirac functions, Watson functions

Produk Detail:

  • Author : William L. Dunn
  • Publisher : Elsevier
  • Pages : 398 pages
  • ISBN : 9780080930619
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKExploring Monte Carlo Methods

Exploring Monte Carlo Methods

Exploring Monte Carlo Methods
  • Author : William L. Dunn,J. Kenneth Shultis
  • Publisher : Elsevier
  • Release : 24 May 2011
GET THIS BOOKExploring Monte Carlo Methods

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

An Introduction to Quantum Monte Carlo Methods

An Introduction to Quantum Monte Carlo Methods
  • Author : Tao Pang
  • Publisher : Morgan & Claypool Publishers
  • Release : 07 December 2016
GET THIS BOOKAn Introduction to Quantum Monte Carlo Methods

Monte Carlo methods have been very prominent in computer simulation of various systems in physics, chemistry, biology, and materials science. This book focuses on the discussion and path-integral quantum Monte Carlo methods in many-body physics and provides a concise but complete introduction to the Metropolis algorithm and its applications in these two techniques. To explore the schemes in clarity, several quantum many-body systems are analysed and studied in detail. The book includes exercises to help digest the materials covered. It

Handbook of Monte Carlo Methods

Handbook of Monte Carlo Methods
  • Author : Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev
  • Publisher : John Wiley & Sons
  • Release : 06 June 2013
GET THIS BOOKHandbook of Monte Carlo Methods

A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging

Simulation and the Monte Carlo Method

Simulation and the Monte Carlo Method
  • Author : Reuven Y. Rubinstein,Dirk P. Kroese
  • Publisher : John Wiley & Sons
  • Release : 20 October 2016
GET THIS BOOKSimulation and the Monte Carlo Method

This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving 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 state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century

Advanced Lectures on Machine Learning

Advanced Lectures on Machine Learning
  • Author : Olivier Bousquet,Ulrike von Luxburg,Gunnar Rätsch
  • Publisher : Springer
  • Release : 22 March 2011
GET THIS BOOKAdvanced Lectures on Machine Learning

Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in

Markov Chain Monte Carlo Methods in Quantum Field Theories

Markov Chain Monte Carlo Methods in Quantum Field Theories
  • Author : Anosh Joseph
  • Publisher : Springer Nature
  • Release : 16 April 2020
GET THIS BOOKMarkov Chain Monte Carlo Methods in Quantum Field Theories

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

Monte Carlo Simulation and Finance

Monte Carlo Simulation and Finance
  • Author : Don L. McLeish
  • Publisher : John Wiley & Sons
  • Release : 13 September 2011
GET THIS BOOKMonte Carlo Simulation and Finance

Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte

Monte Carlo Simulation and Resampling Methods for Social Science

Monte Carlo Simulation and Resampling Methods for Social Science
  • Author : Thomas M. Carsey,Jeffrey J. Harden
  • Publisher : SAGE Publications
  • Release : 05 August 2013
GET THIS BOOKMonte Carlo Simulation and Resampling Methods for Social Science

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, 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

Should We Risk It?

Should We Risk It?
  • Author : Daniel M. Kammen,David M. Hassenzahl
  • Publisher : Princeton University Press
  • Release : 15 April 2001
GET THIS BOOKShould We Risk It?

The authors draw together, organize, and seek to unify previously disparate theories and methodologies connected with risk analysis for health, environmental, and technological problems. They also provide a rich variety of case studies and worked problems, meeting the growing need for an up-to-date book suitable for teaching and individual learning. The specific problems addressed in the book include order-of-magnitude estimation, dose-response calculations, exposure assessment, extrapolations and forecasts based on experimental or natural data, modeling and the problems of complexity in

Accelerating Monte Carlo methods for Bayesian inference in dynamical models

Accelerating Monte Carlo methods for Bayesian inference in dynamical models
  • Author : Johan Dahlin
  • Publisher : Linköping University Electronic Press
  • Release : 22 March 2016
GET THIS BOOKAccelerating Monte Carlo methods for Bayesian inference in dynamical models

Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are recommendation systems for online shopping and streaming services, connecting genes with certain diseases and modelling climate change. In this thesis, we make use of Bayesian statistics to construct probabilistic models given prior information and historical data, which can be used for decision support and predictions. The main obstacle with this approach is that it often results in

Computational Materials Science

Computational Materials Science
  • Author : Kaoru Ohno,Keivan Esfarjani,Yoshiyuki Kawazoe
  • Publisher : Springer
  • Release : 14 April 2018
GET THIS BOOKComputational Materials Science

This textbook introduces modern techniques based on computer simulation to study materials science. It starts from first principles calculations enabling to calculate the physical and chemical properties by solving a many-body Schroedinger equation with Coulomb forces. For the exchange-correlation term, the local density approximation is usually applied. After the introduction of the first principles treatment, tight-binding and classical potential methods are briefly introduced to indicate how one can increase the number of atoms in the system. In the second half

Diffusion in Crystalline Solids

Diffusion in Crystalline Solids
  • Author : G E Murch
  • Publisher : Academic Press
  • Release : 02 December 2012
GET THIS BOOKDiffusion in Crystalline Solids

Diffusion in Crystalline Solids addresses some of the most active areas of research on diffusion in crystalline solids. Topics covered include measurement of tracer diffusion coefficients in solids, diffusion in silicon and germanium, atom transport in oxides of the fluorite structure, tracer diffusion in concentrated alloys, diffusion in dislocations, grain boundary diffusion mechanisms in metals, and the use of the Monte Carlo Method to simulate diffusion kinetics. This book is made up of eight chapters and begins with an introduction