# 5 Highly Recommended Computational Physics Textbooks

Scientific programming is an invaluable tool in the arsenal of a modern physicist. Hence today we will have a loom at 5 highly recommended computational physics textbooks. The books were chosen based on their content, price, programming language, reviews and a pinch of personal taste. So here are the 5 books with the corresponding Amazon links and short reviews.

**Computational Physics by Mark Newman**

This in-depth introduction to the field of computational physics explains the fundamental techniques that every physicist should know. Techniques such as finite difference methods, numerical quadrature, and the fast Fourier transform are of great importance in nearly every branch of physics. Computational Physics by Newman gives a detailed introduction to these techniques in Python along with clear examples. The text starts with an in-depth introduction to the basic principles of Python and then heads on into various numerical methods used for solving differential equations. In addition, Fourier transforms and Markov chain Monte Carlo processes are explored as well.

**Computational Physics by ****Giordano and Nakanishi**

Computational Physics by Giordano and Nakanishi is another often quoted text that covers a wide range of topics in computational physics. The physical situations explored in the text include projectile motion, the movement of the planets in the Solar System, pendulum motion and chaos, problems in statistical physics and others. Additional interdisciplinary topics include neural networks and the brain, real neurons and action potentials and even cellular automata. The examples are written in Basic, which is a language renowned for being easy to pick up.

**Computational Physics by ****Thijssen **

This entry is a more advanced take on the core topics in computational physics. The book covers many different topics such as Monte Carlo and molecular dynamics, various electronic structure methodologies, methods for solving partial differential equations, and lattice gauge theory. Newly added topics in this updated edition include finite element methods and lattice Boltzmann simulation, density functional theory, quantum molecular dynamics and diagonalisation of one-dimensional quantum systems. Recommended for those with a solid foundation in physics and programming.

**A First Course in Computational Physics by DeVries and Hasbun**

Intended for the physics and engineering students who have completed introductory physics courses, this text covers the different types of computational problems using MATLAB. Topics such as root finding, Newton-Cotes integration, and ordinary differential equations are included and presented in the context of physics problems. A decent understanding of MATLAB programming is required.

**Introduction to Numerical Programming by Beu**

This often cited text aims to make numerical programming more accessible to a wider audience of scientists and engineers. Through practical examples in Python and C/C++ a wide variety of relevant topics are introduced, including function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems. Furthermore, Markov chain Monte Carlo methods are employed to solve a variety of physics problems. The text requires only a basic understanding of programming in Python or C/C++, as an introductory section covers the needed topics.

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**Category**: Physics Books

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