Computational Physics

by Mark Newman

A complete introduction to the field of computational physics, with examples and exercises in the Python programming language. Computers play a central role in virtually every major physics discovery today, from astrophysics and particle physics to biophysics and condensed matter. This book explains the fundamentals of computational physics and describes in simple terms the techniques that every physicist should know, such as finite difference methods, numerical quadrature, and the fast Fourier transform. The book offers a complete introduction to the topic at the undergraduate level, and is also suitable for the advanced student or researcher who wants to learn the foundational elements of this important field.

Genres: Physics, Textbooks, Computer Science, Science, Reference

561 pages, Paperback

First published November 7, 2012

About the author

Librarian Note: There is more than one author with this name on GR. This profile might contain books by multiple authors with this name.

Reviews

[Bernardo Blue]

This book made me cry, made me smile. It was the calm during a storm, the storm during the calm. May cause trauma.

[Amy · Rating 5 out of 5]

Fantastic. This is the perfect book for bridging software development knowledge with a domain area - in this case, physics! It does assume physics knowledge, but it's nothing an undergrad in physics can't tackle. The methods you learn are definitely transferable to other areas (like finance) as well!

The book provides clear descriptions and explanation for various computational methods (applied to physics, but again, it's definitely knowledge that's transferable to other domains), ample code recipes, and helpful exercises to really help you practice and hone the skills learned.

Solid book all around to help you gain the confidence to apply computational methods to solve a ton of problems in physics. I actually think it's the best intro book I've come across so far applying these computational methods in any field.

Some specifics:
- The book uses Python 3 and Numpy
- Topics include (all programming focused): numerically calculating integrals & derivatives, solving linear & nonlinear equations, Fourier transforms, solving ODEs/PDEs, random processes & Monte Carlo methods

[James · Rating 4 out of 5]

Pretty good, I thought most chapters were comprehensive and fairly easily understood, and felt comfortable that the book was covering all the essential topics, thanks to Newman's consistent explanations of where the topics fit within the wider context of physics. The biggest weakness I found was the chapter on Fourier Analysis, but maybe that's in-part a failure of my own conceptual understanding. It's the first textbook I've ever had to read cover-to-cover, and hopefully it will be the last time that my professor is too lazy to write their own notes, though I'm not getting my hopes up.

[Khazam · Rating 1 out of 5]

I was expecting way more than what it delivered,
The book contains general knowledge on numerical analysis & python implementation for basic and fundamental equations,
The programming level it introduced is 101
I would prefer buying a numerical book instead, physics does not take much chunk of the book's content.

[Nate Pierce · Rating 5 out of 5]

A fantastic undergraduate-suitable introduction to computational physics.

[Gabi · Rating 3 out of 5]

socorro

[Grant Eastland · Rating 5 out of 5]

This is an excellent introduction to computational physics utilizing a powerful scripting language such as Python. There are several examples from various areas of physics that are able to be performed by a student who may not have any specific knowledge of the physics. The problems and examples provide a good way to discover the underlying physics. The author additionally provides background information about the particular numerical methods being employed, with their limitations.

[lucaslol · Rating 4 out of 5]

Quando chega aos processos de Monte Carlo fica hype