Poster
in
Workshop: NeurIPS 2024 Workshop: Machine Learning and the Physical Sciences
Learning Conformal Field Theory with Symbolic Regression: Recovering the Symbolic Expressions for the Energy Spectrum
Haotian Cao · Garrett Merz · Kyle Cranmer · Gary Shiu
Abstract:
In this paper, we employ the pySR Symbolic Regression (SR) package to recover symbolic formulae for the primary conformal weights and central charges of two-dimensional rational conformal field theories (2D-RCFTs) given only limited information about the energy spectra of these theories. We find symbolic expressions for these quantities in two well-understood classes of 2D-RCFT, minimal models and Wess-Zumino-Witten (WZW) $\hat{su}(2)_k$ models, and discuss future applications to theories about which less is known.
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