Computational Physics

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The work shows, by means of examples coming from different corners of physics, how physical and mathematical questions can be answered using a computer. Starting with maps and neural networks, applications from Newton's mechanics described by ordinary differential equations come into the focus, like the computation of planetary orbits or classical molecular dynamics. A large part of the textbook is dedicated to deterministic chaos normally encountered in systems with sufficiently many degrees of freedom. Partial differential equations are studied considering (nonlinear) field theories like quantum mechanics, thermodynamics or fluid mechanics. In the second edition, a new chapter gives a detailed survey on delay or memory systems with a direct application to epidemic and road traffic models. Most of the algorithms are realized in FORTRAN, a language most suitable for effectively solving the discussed problems. On the other hand, the codes given and presented on the book’s homepage can be easily translated into other languages. Moreover, several MATLAB examples are presented, mainly for didactic reasons. The book is addressed to advanced Bachelor or Master students of physics, applied mathematics and mechanical engineering.

Author(s): Michael Bestehorn
Series: De Gruyter Textbook
Edition: 2
Publisher: De Gruyter
Year: 2023

Language: English
Pages: 396
Tags: Computational Physics

Contents
1 Introduction
2 Nonlinear maps
3 Dynamical systems
4 Ordinary differential equations I, initial value problems
5 Ordinary differential equations II, boundary value problems
6 Ordinary differential equations III, memory, delay and noise
7 Partial differential equations I, basics
8 Partial differential equations II, applications
9 Monte Carlo methods
A Matrices and systems of linear equations
B Program library
C Solutions of the problems
D README and a short guide to FE-tools
Index