A Transformer predicts the analytic expectation values of 2D lattice Yang-Mills Wilson loops from tokenized loop shapes with over 99% accuracy for loops up to length 16, but does not extrapolate to longer loops.
Learning Feynman integrals from differential equations with neural networks.JHEP, 07:124, 2024
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AI for Pattern Hunter: Application in Wilson Loop of 2D Lattice Yang-Mills Theory
A Transformer predicts the analytic expectation values of 2D lattice Yang-Mills Wilson loops from tokenized loop shapes with over 99% accuracy for loops up to length 16, but does not extrapolate to longer loops.