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2022

Does Lorentz-symmetric design boost network performance in jet physics?

Li, Congqiao, Qu, Huilin, Qian, Sitian et al.

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In the deep learning era, improving the neural network performance in jet physics is a rewarding task as it directly contributes to more accurate physics measurements at the LHC.

Recent research has proposed various network designs in consideration of the full Lorentz symmetry, but its benefit is still not systematically asserted, given that there remain many successful networks without taking it into account.
We conduct a detailed study on the Lorentz-symmetric design.
We propose two generalized approaches for modifying a network - these methods are experimented on Particle Flow Network, ParticleNet, and LorentzNet, and exhibit a general performance gain.

Does Lorentz-symmetric design boost network performance in jet physics? · Around

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