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arXiv · 2011.04698

AI Poincaré: Machine Learning Conservation Laws from Trajectories

Ziming Liu·Max Tegmark
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Abstract

We present AI Poincaré, a machine learning algorithm for auto-discovering conserved quantities using trajectory data from unknown dynamical systems. We test it on five Hamiltonian systems, including the gravitational 3-body problem, and find that it discovers not only all exactly conserved quantities, but also periodic orbits, phase transitions and breakdown timescales for approximate conservation laws.

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Ziming Liu, Max Tegmark. 2021-04-26. AI Poincaré: Machine Learning Conservation Laws from Trajectories. https://doi.org/10.1103/physrevlett.126.180604

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