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This sounds interesting! Could you talk a bit more about what sources you used to find problems and learn from that translated well to this approach?


The Applications chapter in the "Introduction to High Performance Scientific Computing" book [0] (it's freely available as a PDF) has some chapters dedicated to relevant computational physics problems, i.e., Molecular Dynamics, N-body problems, and Monte Carlo methods (e.g., for approximating integrals).

The book has been posted on HN in the past [1]

[0] http://pages.tacc.utexas.edu/~eijkhout/Articles/EijkhoutIntr...

[1] https://news.ycombinator.com/item?id=19827993


Math for Game Programmers - Jorge Rodriguez. There is a playlist on youtube.

Game programming is an underrated/underused tool to teach math, physics and programming.


Game engine implements only a tiny slice of physics science, and even that in very distorted smoke-and-mirrors way in order to make it run in realtime. You learn more about computational optimizations, numerical methods and linear algebra, while physics is mostly elementary level. For example, all of optics is stuffed into highly optimized and simplified rendering pipeline and "physically based rendering" is anything but.




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