<ul><li>Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles commonly found in space and planetary environments.</li><li>Machine learning models are used to learn the complex forces governing the interactions between particles in a dusty plasma.</li><li>A physics-tailored machine learning approach is demonstrated, accounting for symmetries, non-identical particles, and non-reciprocal forces.</li><li>The model accurately infers particle masses, reveals deviations from theoretical assumptions, and enables the discovery of new physics.</li></ul>

Physics-tailored machine learning reveals unexpected physics in dusty plasmas

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