Computational Physics

I studied computer science and physics at university, and I'm happy to say this is an excellent text if you're interested in learning about one interesting cross-disciplinary intersection between the two. The book uses Python 3, and most of the sample code uses non-deprecated dependencies (most of the expired packages are in matplotlib).I found it guided me along just well enough so that I could complete most exercises without any high level of hand holding (some of the exercises can be done as mild alterations to the examples). While there are plenty of scientific computing packages out there that will do almost all of the behind-the-scenes heavy lifting for you, this book isn't about using them -- instead, it dives deep into the numerical computing methods often used by those same packages.There's plenty of example programs to step you through the exercises. Also, if you have very little programming experience, the first chapter is committed to getting you caught up to speed, but if I'd have to recommend having at least some experience with programming before tackling this (a single introductory uni course, or some time with self-instruction learning python or some other language should be enough).Topics include Visualization, Accuracy and Speed, Integrals and Derivatives, Solving Linear/Non-Linear Equations, Fourier Transforms, ODEs, PDEs, and Monte Carlo/Random Methods.

This is an incredible book for a first timer. It gives a very good introduction to the Python language and how to apply aspects of it to solving Physics problems.There are a few minor issues with the book (Not worth rating it lower than 5 stars). Dr. Newman will introduce libraries and not explain some of them, such as gaussxw. These are usually libraries and functions on the book website. However, there is no reference to it in the book when introduced. Minor oversite. Another issue is that there are parts of the book where it appears he didn't pay attention to which values he was using.These are types of issues that I am sure will be fixed in later editions. Overall this is an incredible book. I picked up this book to see what it had to say. It has taught me things that I did not know. I love that!

I'm a novice Python programmer, but yet I find this book very accessible, well-structured, clearly written, and comprehensive. I am only about halfway through this book but feel that it has really helped me learn both Python programming and solid numerical analysis skills. My only warning is that without a strong physics background the examples and problems may be a bit opaque, but with a strong physics background this book does an excellent job of connecting the physics with computational techniques.

Good Condition

I am a mathematician with some basic programing experience and I was interested in learning Python mostly for mathematical and educational purposes. I consulted many Python books, but I find myself returning over and over again to Chapters 2 and 3 of this book. If you are new to Python and you are interested in scientific applications this is in my view the best place to start.

As Eric Ayars said, there are a lot of good books about Python, a bunch of good books about computational physics but we gota lack of book about comp. phys. using Python 3. That's the one and it's a real good one. I got only a suggestion: more practical exercises but, you know, if you buy this book you've advanced in this subject a lot of the road probably...

Excelent! After decades using Fortran, accessing this book I wrote my first program in Python. It covers everyday problems in Computational Physics and use them as examples to apply Python programming.

Great Book. I really liked it for python, it's impressive on how many example it provides you in order for your to understand the gist of python and once you get over Chapter 8, you get the heavy loads of python. The quality of the book was NEW, soft cover, non-glossy paper.