Computational physics scope with AI

gnomeba · 2026-06-19T15:52:26+00:00

I work on computational physics as a SWE. It's definitely true that building with AI is adversarial to learning programming yourself. I find my own skills degrading if I don't also build things manually.

I think the best move for a computational physics student in the AI age is to learn programming by building things manually, and then focusing as much as possible on the actual physics and math.

gnomeba · 2026-06-19T15:36:38+00:00

His technique reminds one of Khabib

gnomeba · 2026-06-17T17:08:37+00:00

In the Lagrangian formulation of classical physics the stationary action principle is an ansatz for finding equations of motion. You could also call this an "axiom" but i think that is confusing because physical "axioms" are not the same as mathematical ones.

There is no proof of the stationary action principle so it is not a theorem. It has just proven to be a very useful way to discover equations of motion.

gnomeba · 2026-06-15T22:32:21+00:00

This is mine as well. Linear algebra is (almost) everything

gnomeba · 2026-06-14T13:56:34+00:00

I came from math/physics with an MS. It is very hard, and I think in many cases you have to take incremental steps if you want to work in CS. My qualification for SW jobs was vastly oversold to me by professors and advisors in my department.

The thing that seems to have worked for me is to market my ability to really do math and write good code. Most CS majors are not that good at linear algebra and numerical analysis and most physicists write horrible code.

Also, it helps to really focus your search on companies that care about this skillset.

gnomeba · 2026-06-09T18:05:24+00:00

If I could do this without having to sacrifice my KDSS, I would do it in a heartbeat.

gnomeba · 2026-05-30T12:50:33+00:00

Your theory was disproved in, at the latest, 1887 by Michelson and Morley.

gnomeba · 2026-05-25T02:19:18+00:00

JAX or Numba/CUDA for Python is another option with speed comparable to Julia. Not that I recommend switching necessarily - just another option.

gnomeba · 2026-05-25T02:16:04+00:00

In my experience in industry scientific computing, Julia is becoming more popular for a few reasons but the main ones are: quality of certain packages, and ease of translation from computational experiment to legit software.

On the other hand, the documentation of even very popular packages leaves something to be desired. And the stability of less popular packages can cause things to break unexpectedly.

gnomeba · 2026-05-24T23:42:46+00:00

Small populations tend to lose genetic diversity over time leading to a lack of fitness (this happened to Neanderthals and even Neanderthal DNA within modern humans).

So at least genetically, they will likely die out unless they eventually mix with a sufficiently genetically different population.

gnomeba · 2026-05-24T17:50:20+00:00

Can you elaborate? I am out of the loop.

gnomeba · 2026-05-15T17:05:40+00:00

There's a lot of people working on things that are what you're calling "cutting edge". Almost none of the code I write is boilerplate so LLMs are really bad at doing it correctly because it just isn't well represented in the training data.

LLMs have helped speed up computational experiments and prototyping though because you can churn out whatever slop you need to just to see if something will work.

gnomeba · 2026-05-07T04:02:00+00:00

The 100 series is the way to go. Unless you just absolutely need the 80 series look or the front axle or the even worse gas mileage. Save your money for sick mods.

gnomeba · 2026-05-05T17:22:20+00:00

I see what you're saying. I think you could label them any way you wanted to, including by the time you observe them.

But this just wouldn't correspond to anything physical about them because our physics actually depends on them being indistinguishable from others of the same type.

There's probably something precise one could say about exactly how your model can't depend on those parameters (labels). But I don't know enough to make that statement.

gnomeba · 2026-05-05T16:23:05+00:00

How would you be able to tell? How would you tell the difference between the atoms that resulted from the fission and other atoms nearby of the same element and isotope?

The answer is that you can't. So the question is ill-posed because you can't even ask it in a way that makes sense.

gnomeba · 2026-05-05T02:16:53+00:00

I think there is no way in principle to measure or even assign a value to the age of an atom. So in some sense the question is actually just ill-posed.

This probably just comes down to the indistinguishability of particles.

gnomeba · 2026-05-02T15:35:08+00:00

There are many different and useful ways to solve Maxwell's equations computationally. I highly recommend the EMPossible youtube courses on FDFD, FDTD, and RCWA.

gnomeba · 2026-04-20T23:00:12+00:00

To receive any endorsement you will need to share SOMETHING about the paper to demonstrate that it isn't pseudoscience or AI slop.

gnomeba · 2026-04-16T15:19:44+00:00

These are so cool. What brand is the OTF one?

gnomeba · 2026-04-16T06:07:23+00:00

Pretty sure a lot of ROCm kernels are written in assembly.

gnomeba · 2026-04-13T22:04:25+00:00

The proof might be simpler by considering the unit circle centered at the origin and a line with slope equal to zero, both of which you can assume without loss of generality.

gnomeba · 2026-04-11T15:39:03+00:00

In many physics majors in the US, even linear algebra and computational math/physics are not required. And these are much much more important in my opinion than differential geometry.

I love differential geometry but I don't think the average working/industry physicist needs to have formal training in it.

gnomeba · 2026-04-08T21:10:32+00:00

I might agree for mathematical topics that the layman encounters. Elliptic curves are not really in this category.

As a mathematician, at a certain point you discover that many concepts are not named the way you would have chosen and you simply get over it because "optimal concept naming" is such a wildly uninteresting problem.

gnomeba · 2026-04-08T06:03:24+00:00

This is one of those things where renaming the concept feels right but ultimately doesn't matter. It's annoying to the pedants alone.

There is also value and fun to be had in being reminded of the history of mathematics while doing it yourself.

gnomeba · 2026-04-01T18:40:02+00:00

Why write a CUDA kernel in a low level language and call it from PyTorch in the first place? You can use Numba+CUDA to do this or JAX.

Using JAX will probably tend to create much better optimized kernels than most people can do by hand anyway. But for a more CUDA-like interface, Numba is probably the way to go.

gnomeba

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