2022
DOI: 10.1103/physreve.106.045307
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Machine learning conservation laws from differential equations

Abstract: Six months after the author derived a constant of motion for a 1D damped harmonic oscillator [1], a similar result appeared by Liu, Madhavan, and Tegmark [2, 3], without citing the author. However, their derivation contained six serious errors, causing both their method and result to be incorrect. In this Comment, those errors are reviewed.Review of Liu, et al.

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Cited by 24 publications
(10 citation statements)
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References 16 publications
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“…The key here is all: software which will nominally find a single conserved quantity does exist (but does not always perform in a timely manner). A very recent article Liu et al (2022) appeared once the work here was substantially complete and may suggest a solution. Given the problem domain in which we are operating (galaxies), we are able to provide support to any symbolic regression packages trying to find algebraic formulae from trajectory data.…”
Section: Discussionmentioning
confidence: 85%
See 1 more Smart Citation
“…The key here is all: software which will nominally find a single conserved quantity does exist (but does not always perform in a timely manner). A very recent article Liu et al (2022) appeared once the work here was substantially complete and may suggest a solution. Given the problem domain in which we are operating (galaxies), we are able to provide support to any symbolic regression packages trying to find algebraic formulae from trajectory data.…”
Section: Discussionmentioning
confidence: 85%
“…The reason we say "appears to" above is that no robust mechanism yet exists for determining the algebraic formulae for multiple conserved quantities from a single trajectory in a timely manner, though it may be that the investigations of Liu et al (2022) will suggest a viable solution. Addressing this symbolic regression issue needs to be tackled with some urgency, and this or a similar investigation repeated.…”
Section: Discussionmentioning
confidence: 99%
“…In one of these works mentioned, the Schrödinger equation is solved for a particle inside a Pöschl-Teller potential, they obtain the ground state energy and its wavefunction. We would like to highlight the work by Radu and Duque, who presented a treatment based in neural networks for solving the Schrödinger equation for arbitrary potentials [18][19][20][21][22].…”
Section: Discussionmentioning
confidence: 99%
“…For stationary states of ( ) x , y the Schrödinger equation becomes an eigenvalue problem, as seen in (19):…”
Section: About the Variational And Shooting Methodsmentioning
confidence: 99%
“…Thus, N I is at least 3 (in our case), and there is at least one hidden symmetry. Starting from particle trajectory data in the equilibrium electromagnetic fields, future research on this topic could make use of machine learning models to help find the number of invariants or even discover the analytic formula of these invariants (e.g., Liu & Tegmark 2021;Liu et al 2022).…”
Section: Conclusion and Discussionmentioning
confidence: 99%