[samloveshummus]

It's true that there are many mathematically equivalent ways to describe physical systems. But the important point is that some are more useful than others. For example, Lagrangian mechanics and Hamiltonian mechanics are equivalent to Newtonian mechanics, but they can give much better intuition for certain problems. Feynman diagrams are equivalent to grinding out the QFT algebra by hand à la Schwinger, but they give a completely different intuition for the underlying Physics.

More importantly, though, they could use this NN on systems that have not yet successfully been modeled, perhaps complex dynamical systems, to discover good parameters and conserved quantities.

[sbf501]

> For example, Lagrangian mechanics and Hamiltonian mechanics are equivalent to Newtonian mechanics, but they can give much better intuition for certain problems. Feynman diagrams are equivalent to grinding out the QFT algebra by hand à la Schwinger, but they give a completely different intuition for the underlying Physics.

I just read about Langrangian and Hamiltonian mechanics. I didn't encounter those at all in my EE physics, and they are fascinating. Great examples! Are you a physics professor, or is this stuff undergrad physics majors learn?

[a9h74j]

Used to be third-year in the major under Classical Mechanics.

There's a good series of videos on YT, with the title Variational Calculus and the Euler-Lagrange equation on channel Structural Dynamics. I have only seen the first few. This first video should give you the full playlist:

https://www.youtube.com/watch?v=VCHFCXgYdvY

[sbf501]

Sounds like Alan Rickman! Thanks!

[theptip]

Lagrangian Dynamics was a 3rd or 4th year elective in my undergrad physics. You need it for string theory (which was masters level IIRC).

[MauranKilom]

> More importantly, though, they could use this NN on systems that have not yet successfully been modeled, perhaps complex dynamical systems, to discover good parameters and conserved quantities.

That would only make sense to try if the model could do this for systems we already understand. By the sound of the article, it can't even do that. Despite many efforts the researchers couldn't even understand the second pair of parameters. That doesn't correspond to my understanding of "good parameters".