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arXiv · 2108.08859

Solving Conformal Field Theories with Artificial Intelligence

Gergely Kántor·Vasilis Niarchos·Constantinos Papageorgakis
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Abstract

In this paper we deploy for the first time Reinforcement-Learning algorithms in the context of the conformal-bootstrap programme to obtain numerical solutions of conformal field theories (CFTs). As an illustration, we use a soft Actor-Critic algorithm and find approximate solutions to the truncated crossing equations of two-dimensional CFTs, successfully identifying well-known theories like the 2D Ising model and the 2D CFT of a compactified scalar. Our methods can perform efficient high-dimensional searches that can be used to study arbitrary (unitary or non-unitary) CFTs in any spacetime dimension.

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Gergely Kántor, Vasilis Niarchos, Constantinos Papageorgakis. 2021-09-01. Solving Conformal Field Theories with Artificial Intelligence. https://doi.org/10.1103/physrevlett.128.041601

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