Computational physics problems that involve nontrivial CS concepts?

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A third-year physics major and a computer science major are seeking a collaborative project that combines their skills, specifically in computational physics. They express concern that many computational physics problems are too simplistic from a computer science perspective, focusing primarily on repetitive calculations rather than complex algorithms or data structures. Suggestions include exploring non-trivial programming challenges like polygon triangulation and applying them to physics, or creating a simulator for the n-body problem, which emphasizes optimization of calculations. Additionally, integrating machine learning with sensor data is proposed as an innovative approach, exemplified by a project that learns text input patterns from keyboard sounds. The overall goal is to find engaging projects that are interesting from both physics and computer science viewpoints, without the need for groundbreaking results.
Ragnord
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I'm a 3rd year physics major and my friend is a 3rd year computer science major, and for a bit of fun we want to do some sort of project that will utilize both of our skills. Some sort of computational physics problem seems appropriate, but with my limited knowledge, it seems that a lot of them are somewhat trivial from a CS point of view. That is, they seem to involve very simple algorithms for doing a bunch of repetitive calculations, and don't have much to do with data structures and the sorts of things that computer scientists like. So can I have some examples of computational physics problems, or of ways of approaching them that involve concepts which are "interesting" from both a physics and computer science point of view? It doesn't have to be anything groundbreaking or new, even just trying to recreate some well known result would be alright, we're just doing this for fun. Thanks.

Edit: Oops, could I get this moved to Programming and Comp Sci?
 
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Ragnord said:
I'm a 3rd year physics major and my friend is a 3rd year computer science major, and for a bit of fun we want to do some sort of project that will utilize both of our skills. Some sort of computational physics problem seems appropriate, but with my limited knowledge, it seems that a lot of them are somewhat trivial from a CS point of view. That is, they seem to involve very simple algorithms for doing a bunch of repetitive calculations, and don't have much to do with data structures and the sorts of things that computer scientists like. So can I have some examples of computational physics problems, or of ways of approaching them that involve concepts which are "interesting" from both a physics and computer science point of view? It doesn't have to be anything groundbreaking or new, even just trying to recreate some well known result would be alright, we're just doing this for fun. Thanks.

Edit: Oops, could I get this moved to Programming and Comp Sci?
Try to reverse your steps then. Look up some non-simplistic programming issues, like triangulation of a polygon, and apply them to physics.

Or you could just try to implement the O(n) time polygon triangulation algorithm into actual code. I don't think anyone will notice (or care) there was no physics if you do that.

Also are you trying to break new ground, or just do something? You can always try to make a simulator for the n-body problem. Even just doing a lot of simple calculations is impressive programming when you optimize it. Actually, optimized simplistic calculations is the more preferred code when compared to complex arcane programming to solve the same problem.
 
lawtonfogle said:
Even just doing a lot of simple calculations is impressive programming when you optimize it. Actually, optimized simplistic calculations is the more preferred code when compared to complex arcane programming to solve the same problem.

Agreed.
 
Some kind of machine learning combined with sensors. For example, people listened to the keys being typed on a keyboard and were able to learn the text begin typed after a while using frequencies of letters and the distinctive key sounds learned dynamically from each keyboard.
 
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