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Computational Physics (2nd Edition) (2025)
- vectorcrumb 7mo agoCould somebody provide some opinion on the book and/or accompanying course?
- braedonwatkins 7mo agoI read most of the 1st edition (busy), I'm sure it hasn't changed much to the 2nd. I would say it's rather good at an introductory level to the subject! It definitely targets physics undergrads who have never programmed so if that's not you then you may feel friction during some chapters. If, like me, you are much more developed in programming than physics you might just want to do the exercises in the first few chapters to check your knowledge and move on to the good bits. If you're looking for something more rigorous I would bet [Numerical Recipes](https://numerical.recipes/ https://numerical.recipes/) is better (I haven't read it but I want to; see "busy").
- redbluered 7mo agoNo, Numerical Recipes isn't better. Or worse. It's a different book on a different topic, with there topic very clearly advertised in the title. It's a series of... numerical recipes. Nice descriptions of many numerical algorithms sufficient to use them. It's not focused on physics. It's also not rigorous. The Sussman / Wisdom reference is rigorous. Why would you post about a book you haven't read?
- braedonwatkins 6mo agolol. lmao even.
- HexDecOctBin 7mo agoWhat physics do I need to know to follow this book?
- mapt 7mo ago> Exercises by chapter Click on a chapter to download: Chapter 2: Python programming for physicists Chapter 3: Graphics and visualization Chapter 4: Accuracy and speed Chapter 5: Integrals and derivatives Chapter 6: Solution of linear and nonlinear equations Chapter 7: Fourier transforms Chapter 8: Ordinary differential equations Chapter 9: Partial differential equations Chapter 10: Random processes and Monte Carlo methods Chapter 11: Data science
- griffzhowl 7mo agoLooks like not much. The book is about using Python to implement numerical methods, mainly about teaching the Python part, and that's all explained. You might be missing motivation if you don't know any physics, but even so, basic mechanics using differential equations seems to be enough to give context, at least for the earlier parts
- kordlessagain 7mo agoWeber's Electrodynamics.
- elteto 7mo agoOnly after working through Rudin’s Analysis first.
- analog31 7mo agoJust to give a bit of flavor, I was a math + physics major in the 80s. The physics curriculum had some oddly named courses such as "theoretical physics" that were not really physics courses but were meant to give you the math and computational background needed for the more advanced courses or for graduate work. The math was stuff that wasn't covered extensively enough in the math major courses, such as vector calculus.
- ktallett 7mo agoI did a few courses across academic years that were based around this book and it's very handy skills to learn. Whilst perhaps not in the moment, it's a good introduction to implementing functions and equations, before you lead on to the next steps of specific functions and methods of analysis alongside hpc with parallelization.
- ninjahawk1 7mo ago[flagged]
- friendlyasparag 7mo agoI took Mark Newman’s course some years ago. It was fantastic! Geared at sophomore/ junior year physics major — someone who had completed the basic intro sequence. I am sure this book is also great.
- lkm0 7mo agoThe matplotlib chapter seems fairly barebones but I remain in awe at this gorgeous latex work
- emil-lp 7mo agoIsn't it a pretty standard book/memoir template? He could have invested in a Python syntax highlighter. I use minted, myself, but I'm sure there are many alternatives.
- lkm0 6mo agoThere's actually a source tex file bundled with exercises with a custom setup.tex which makes me believe the whole thing is bespoke. Might be wrong though https://websites.umich.edu/~mejn/cp2/exercises.html https://websites.umich.edu/~mejn/cp2/exercises.html By the way, I use typst now, so I don't have to worry about highlighting anymore!
- inzlab 7mo agocomputation will revolutionize physics.
- analog31 7mo agoI hope that's sarcastic. Physics is the original computational science.
- Morpheus_Matrix 7mo ago[flagged]
- analog31 7mo agoI was a math + physics major in college, in the 80s. Thankfully, our differential equations course covered both analytical and numerical integration. We also took a course in the math department called "numerical analysis" that got further into it and also dealt with the foibles of floating point arithmetic. For us, it was all in FORTRAN.
- queuebert 7mo agoI think the course by Richard Fitzpatrick is a much better selection of content if you want to actually do computational physics: https://farside.ph.utexas.edu/teaching/329/329.pdf https://farside.ph.utexas.edu/teaching/329/329.pdf
- redbluered 7mo agoShould be modernized to Python or similar. In 2026, I don't want to do numerical programming in C. That was fine 30 years ago, but today, I expect to have garbage collection or to be able to multiply a matrix as A×B.
- queuebert 6mo agoIf that's what you want, use Matlab. High-performance scientific computing is still using C, C++ +/- CUDA, or Fortran, with Rust a growing segment.
- deterministic 6mo agoDifferent strokes for different fokes. In 2026 I don't want to use a slow interpreted non-typed language like Python. C++ (for example) has excellent super fast matrix libraries where you can do AxB.
- dfordp11 7mo ago[dead]
- GeorgeTirebiter 7mo agoA bit surprised Sussman's and Wisdom's book hasn't yet been mentioned: https://mitpress.mit.edu/9780262028967/structure-and-interpretation-of-classical-mechanics/ https://mitpress.mit.edu/9780262028967/structure-and-interpr...