Published 2020-07-28T02:04:00.001Z by Physics Derivation Graph

There are three subsets of Physics: computational, theoretical, and experimental.

In Math there are many subsets, one of which is Applied Math.

At the intersection of computational physics and computer science and Applied math is the use of computers for large-scale numerical analysis.

Each of these subspecializations has a different perspective and different jargon for the same task.

I've been using the phrase "documenting mathematical physics" to describe the intent and scope of the Physics Derivation Graph. In conversation with a mathematician, he suggested a few alternative key phrases that might help me find new audiences:

- applied math
- scientific computation
- computational science

This topic came up because I mentioned that I my searches have been repeatedly ending up in pure math due to my focus on semantics of expressions. I think of "pure math" as establishing foundations using axioms, theorems, and proofs.

I have an undergraduate degree in Applied Math, but I've never considered the Physics Derivation Graph as an "applied math" issue. In my experience, applied math is about solving PDEs for specific scenarios and applying combinators to narrow situations.

My PhD is in computational Physics, so my experience with "scientific computation" is using large computers to solve numerical math problems.

I wouldn't consider the Physics Derivation Graph to be "theoretical Physics." However, both feature heavy reliance on math.

Applied Math does have Physics as a domain of use, but there are other domains in which Applied Math is used: engineering, industrial planning, economics, biology.

See https://www.reddit.com/r/math/comments/ec6r0/whats_the_difference_between_applied_math_and/

See https://www.reddit.com/r/math/comments/ec6r0/whats_the_difference_between_applied_math_and/

Looking around the Internet, there are degrees in Applied Math and in Scientific Computation and Computation Science. Many of these focus on numerical computation and big data. I suspect these degree programs have been displaced by the hotter "data science" programs.

- https://www.cs.cornell.edu/research/scientif - in the Computer Science department
- https://www.ucdavis.edu/majors/mathematical-and-scientific-computation/ - Math oriented undergrad
- https://nps.edu/web/math/scientific-computation - computational focus
- https://gradadm.seas.upenn.edu/masters/scientific-computing/
- https://apam.columbia.edu/