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Stochastic Numerical Methods - An Introduction for Students and Scientists (Paperback)
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Stochastic Numerical Methods - An Introduction for Students and Scientists (Paperback)
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Stochastic Numerical Methods introduces at Master level the
numerical methods that use probability or stochastic concepts to
analyze random processes. The book aims at being rather general and
is addressed at students of natural sciences (Physics, Chemistry,
Mathematics, Biology, etc.) and Engineering, but also social
sciences (Economy, Sociology, etc.) where some of the techniques
have been used recently to numerically simulate different
agent-based models. Examples included in the book range from
phase-transitions and critical phenomena, including details of data
analysis (extraction of critical exponents, finite-size effects,
etc.), to population dynamics, interfacial growth, chemical
reactions, etc. Program listings are integrated in the discussion
of numerical algorithms to facilitate their understanding. From the
contents: * Review of Probability Concepts * Monte Carlo
Integration * Generation of Uniform and Non-uniform * Random
Numbers: Non-correlated Values * Dynamical Methods * Applications
to Statistical Mechanics * Introduction to Stochastic Processes *
Numerical Simulation of Ordinary and * Partial Stochastic
Differential Equations * Introduction to Master Equations *
Numerical Simulations of Master Equations * Hybrid Monte Carlo *
Generation of n-Dimensional Correlated * Gaussian Variables *
Collective Algorithms for Spin Systems * Histogram Extrapolation *
Multicanonical Simulations
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