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arXiv · 2208.03165

Discover the GellMann-Okubo formula with machine learning

Zhenyu Zhang·Rui Ma·Jifeng Hu·Qian Wang
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Abstract

Machine learning is a novel and powerful technology and has been widely used in various science topics. We demonstrate a machine-learning based approach built by a set of general metrics and rules inspired by physics. Taking advantages of physical constraints, such as dimension identity, symmetry and generalization, we succeed to rediscover the GellMann Okubo formula using a technique of symbolic regression. This approach can effectively find explicit solutions among user-defined observable, and easily extend to study on exotic hadron spectrum.

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Zhenyu Zhang, Rui Ma, Jifeng Hu, Qian Wang. 2022-08-05. Discover the GellMann-Okubo formula with machine learning. https://doi.org/10.1088/0256-307x%2F39%2F11%2F111201

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