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High Energy Physics - Theory

arXiv:2108.08859 (hep-th)
[Submitted on 19 Aug 2021 (v1), last revised 1 Sep 2021 (this version, v2)]

Title:Solving Conformal Field Theories with Artificial Intelligence

Authors: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.
Comments: 6 pages; v2: references added
Subjects: High Energy Physics - Theory (hep-th)
Cite as: arXiv:2108.08859 [hep-th]
  (or arXiv:2108.08859v2 [hep-th] for this version)
  https://doi.org/10.48550/arXiv.2108.08859
Related DOI: https://doi.org/10.1103/PhysRevLett.128.041601

Submission history

From: Constantinos Papageorgakis [view email]
[v1] Thu, 19 Aug 2021 18:00:57 UTC (14 KB)
[v2] Wed, 1 Sep 2021 13:46:47 UTC (14 KB)
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