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Advances in Quantum Monte Carlo confronts the challenges in quantum mechanics that have become progressively more prevalent in the last five years. This book will cover the needed advances in Quantum Monte Carlo methods including improvements and a complete range of applications. Advances in Quantum Monte Carlo will also include a complete spectrum of applications.
Monte Carlo methods are a class of computational algorithms for
simulating the behavior of a wide range of various physical and
mathematical systems (with many variables). Their utility has
increased with general availability of fast computers, and new
applications are continually forthcoming. The basic concepts of
Monte Carlo are both simple and straightforward and rooted in
statistics and probability theory, their defining characteristic
being that the methodology relies on random or pseudo-random
sequences of numbers. It is a technique of numerical analysis based
on the approximate solution of a problem using repeated sampling
experiments and observing the proportion of times a given property
is satisfied.
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