3 ms·
Notes for such efforts: From https://news.ycombinator.com/item?id=44043518#44053779 https://news.ycombinator.com/item?id=44043518#44053779 re: deep learning po
by westurner 1y ago
Notes for such efforts:
From https://news.ycombinator.com/item?id=44043518#44053779 https://news.ycombinator.com/item?id=44043518#44053779 re: deep learning poised:
> jax-cfd mentions phiflow
> PhiFlow: https://github.com/tum-pbs/PhiFlow/ https://github.com/tum-pbs/PhiFlow/
>> A differentiable PDE solving framework for machine learning
SymPy can solve ODEs and some PDEs.
sympy.solvers.pde: https://docs.sympy.org/latest/modules/solvers/pde.html https://docs.sympy.org/latest/modules/solvers/pde.html
SymPy's sympy.utilities.lambdify.lambdify() compiles things to faster solvers like CPython math module, mpmath, NumPy, SciPy, CuPy, JAX, TensorFlow, SymPy, numexpr, and PyTorch. https://docs.sympy.org/latest/modules/utilities/lambdify.html https://docs.sympy.org/latest/modules/utilities/lambdify.htm...
dynamicslab/pysindy; https://github.com/dynamicslab/pysindy https://github.com/dynamicslab/pysindy :
> A package for the sparse identification of nonlinear dynamical systems from data
A question about fundamental Anosov flows and CFD in pysindy; due to "Flow Proof Helps Mathematicians Find Stability in Chaos" (2023)
https://www.quantamagazine.org/flow-proof-helps-mathematicians-find-stability-in-chaos-20230615/ https://www.quantamagazine.org/flow-proof-helps-mathematicia... ..
https://github.com/dynamicslab/pysindy/issues/383 https://github.com/dynamicslab/pysindy/issues/383 :
/? site:github.com anosov
https://www.google.com/search?q=site%3Agithub.com+anosov https://www.google.com/search?q=site%3Agithub.com+anosov
> GitHub topic: quantum-fluids: https://github.com/topics/quantum-fluids https://github.com/topics/quantum-fluids
GitHub topic: Gross-Pitaevskii: https://github.com/topics/gross-pitaevskii https://github.com/topics/gross-pitaevskii
OSIRIS-code can simulate laser emissions in plasma, nonlinear optics in plasma,; and supports Checkpointing and thus probably parallelization; https://news.ycombinator.com/context?id=44371059 https://news.ycombinator.com/context?id=44371059
For simulations of gravity-assisted spacecraft trajectories, in n-body (vortical fluidic) gravity:
> JPL SPICE toolkit: https://naif.jpl.nasa.gov/naif/toolkit.html https://naif.jpl.nasa.gov/naif/toolkit.html
> SpiceyPy: https://github.com/AndrewAnnex/SpiceyPy https://github.com/AndrewAnnex/SpiceyPy
"Gravity as a fluid dynamic phenomenon in a superfluid quantum space. Fluid quantum gravity and relativity." (2017) https://hal.science/hal-01248015/ https://hal.science/hal-01248015/ :
> [ Bernoulli, Navier-Stokes, Gross-Pitaevskii vortices in a field with curl ]
Shouldn't solving NS also solve for n-body gravity?
Anosov diffeomorphism; hyperbolicity of complex nonlinear dynamic fluid systems, Lyapunov exponents :
https://en.wikipedia.org/wiki/Anosov_diffeomorphism https://en.wikipedia.org/wiki/Anosov_diffeomorphism
Curl: https://en.wikipedia.org/wiki/Curl_(mathematics) https://en.wikipedia.org/wiki/Curl_(mathematics)
Vorticity: https://en.wikipedia.org/wiki/Vorticity https://en.wikipedia.org/wiki/Vorticity
Bernoulli's principle: https://en.wikipedia.org/wiki/Bernoulli%27s_principle https://en.wikipedia.org/wiki/Bernoulli%27s_principle
Gross-Pitaevskii equation:
https://en.wikipedia.org/wiki/Gross%E2%80%93Pitaevskii_equation https://en.wikipedia.org/wiki/Gross%E2%80%93Pitaevskii_equat...
Navier-Stokes equations:
https://en.wikipedia.org/wiki/Navier%E2%80%93Stokes_equations https://en.wikipedia.org/wiki/Navier%E2%80%93Stokes_equation...
- markstock 1y agoUm, no? This is a fine collection of links - much to learn! - but the connection between flow and gravitation is (in my understanding) limited to both being Green's function solutions of a Poisson problem. https://en.wikipedia.org/wiki/Green%27s_function https://en.wikipedia.org/wiki/Green%27s_function There are n-body methods for both (gravitation and Lagrangian vortex particle methods), and I find the similarities and differences of those algorithms quite interesting. But the Fedi paper misses that key connection: they're simply describing a source/sink in potential flow, not some newly discovered link.