Rediscovery of Numerical L\"uscher's Formula from the Neural Network

arXiv:2210.02184v2 Announce Type: replace-cross
Abstract: We present that by predicting the spectrum in discrete space from the phase shift in continuous space, the neural network can remarkably reproduce the numerical L\"uscher's formula to a high precision. The model-independent property of the L\"uscher's formula is naturally realized by the generalizability of the neural network. This exhibits the great potential of the neural network to extract model-independent relation between model-dependent quantities, and this data-driven approach could greatly facilitate the discovery of the …

abstract arxiv continuous cs.lg hep-lat hep-ph hep-th independent network neural network numerical precision property shift space spectrum type