Thermal two-point functions of scalar CFT operators at zero spatial separation are reconstructed from their discontinuities via Hurwitz zeta kernels, with OPE coefficients as the only dynamical input.
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Simple neural networks trained on crossing symmetry and one anchor point reproduce conformal correlators to within a few percent across many CFTs.
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The analytic bootstrap at finite temperature
Thermal two-point functions of scalar CFT operators at zero spatial separation are reconstructed from their discontinuities via Hurwitz zeta kernels, with OPE coefficients as the only dynamical input.
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Neural Networks Reveal a Universal Bias in Conformal Correlators
Simple neural networks trained on crossing symmetry and one anchor point reproduce conformal correlators to within a few percent across many CFTs.