Neural networks optimized solely on crossing symmetry reconstruct CFT correlators from minimal input data to few-percent accuracy across generalized free fields, minimal models, Ising, N=4 SYM, and AdS diagrams.
Superconformal symmetry, correlation functions and the operator product expansion
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Dynamical data in E=2 mixed correlators of half-maximally supersymmetric CFTs is encoded in reduced correlator functions admitting block expansions with shifted kinematics.
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Neural Spectral Bias and Conformal Correlators I: Introduction and Applications
Neural networks optimized solely on crossing symmetry reconstruct CFT correlators from minimal input data to few-percent accuracy across generalized free fields, minimal models, Ising, N=4 SYM, and AdS diagrams.
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Reduced superblocks at next-to-next-to-extremality for all half-maximally supersymmetric CFTs
Dynamical data in E=2 mixed correlators of half-maximally supersymmetric CFTs is encoded in reduced correlator functions admitting block expansions with shifted kinematics.