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A Guide to Monte Carlo and Quantum Monte Carlo methods: Quantum Monte Carlo: Variational and Diffusion; MC in general; Markov Chain; Statistics; Rando

De (autor): Aleksandar Ciric

A Guide to Monte Carlo and Quantum Monte Carlo methods: Quantum Monte Carlo: Variational and Diffusion; MC in general; Markov Chain; Statistics; Rando - Aleksandar Ciric

A Guide to Monte Carlo and Quantum Monte Carlo methods: Quantum Monte Carlo: Variational and Diffusion; MC in general; Markov Chain; Statistics; Rando

De (autor): Aleksandar Ciric


This books intention is to cover in detail everything needed for Monte Carlo and Quantum Monte Carlo methods. It does not contain the applications to the complex systems investigated today, but it comes right at their doorstep. Thus, it may be considered as beginners and intermediate level guide. This book started as a guide for postgraduate students, and it continued in that fashion - to be clear and understandable, while covering all the material. It is the union of all the important parts from all of those books listed in bibliography, with additional code, images and explanations. The book starts with a short introduction to random number generators and statistics, progresses to the Monte Carlo method in general, Markov Chain, Markov Chain Monte Carlo, and finally - Quantum Monte Carlo section. It touches on the subject of the Hidden Monte Carlo. As for the Quantum Monte Carlo, Variational Monte Carlo and Diffusion Monte Carlo methods are described in detail, including problems like fixed-node approximation, importance sampling, Metropolis algorithm, etc. Program code is in C++, however, the algorithms are clearly presented and the code is understandable and commented so it can be ported to other programming languages.
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This books intention is to cover in detail everything needed for Monte Carlo and Quantum Monte Carlo methods. It does not contain the applications to the complex systems investigated today, but it comes right at their doorstep. Thus, it may be considered as beginners and intermediate level guide. This book started as a guide for postgraduate students, and it continued in that fashion - to be clear and understandable, while covering all the material. It is the union of all the important parts from all of those books listed in bibliography, with additional code, images and explanations. The book starts with a short introduction to random number generators and statistics, progresses to the Monte Carlo method in general, Markov Chain, Markov Chain Monte Carlo, and finally - Quantum Monte Carlo section. It touches on the subject of the Hidden Monte Carlo. As for the Quantum Monte Carlo, Variational Monte Carlo and Diffusion Monte Carlo methods are described in detail, including problems like fixed-node approximation, importance sampling, Metropolis algorithm, etc. Program code is in C++, however, the algorithms are clearly presented and the code is understandable and commented so it can be ported to other programming languages.
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