Basic Concepts in Computational Physics

"Basic Concepts in Computational Physics" is a concise introduction to the fundamental methods of computational physics. This new edition offers readers the opportunity to explore the advantages of numerical methods for solving complex mathematical problems and for directly simulating physical processes. The book is divided into two main parts: deterministic methods and stochastic methods in computational physics. The first part covers numerical differentiation and integration, as well as the treatment of ordinary differential equations, and provides a brief introduction to the numerics of partial differential equations. The second part focuses on random number generation, the basics of stochastic processes, and introduces Monte Carlo methods, with a particular emphasis on Markov chain Monte Carlo algorithms. The last two chapters deal with data analysis and stochastic optimization, supported by applications from physics. Numerous exercises with detailed solutions, chapter introductions, and summaries, along with a clear, application-oriented style, enhance readers' understanding. Online provided C++ codes enable practical application of the concepts.