Stochastic Numerics For Mathematical Physics

Stochastic differential equations have many applications in the natural sciences. Besides, the employment of probabilistic representations together with the Monte Carlo technique allows us to reduce solution of multi-dimensional problems for partial differential equations to integration of stochastic equations. This approach leads to powerful computational mathematics that is presented in the treatise.

This monograph is devoted to random walk based stochastic algorithms for solving high-dimensional boundary value problems of mathematical physics and chemistry.

Authors: Stickler, Benjamin A., Schachinger, Ewald
Now with ready to use C++ program code available online
Contains heavily expanded chapters on molecular dynamics, PDEs, random generators, Monte Carlo applications, data analysis and data optimization
Presents deterministic methods are presented on a par with stochastic methods
Mathematically precise, but driven by the needs of physicists
Extensive appendices deepen the knowledge and present the mathematical basis

This new edition is a concise introduction to the basic methods of computational physics. Readers will discover the benefits of numerical methods for solving complex mathematical problems and for the direct simulation of physical processes.