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Solving Conformal Field Theories with Artificial Intelligence

Gergely Kántor, Constantinos Papageorgakis, and Vasilis Niarchos
Phys. Rev. Lett. 128, 041601 – Published 24 January 2022

Abstract

In this Letter, we deploy for the first time reinforcement-learning algorithms in the context of the conformal-bootstrap program 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 nonunitary) CFTs in any spacetime dimension.

  • Received 3 September 2021
  • Revised 15 October 2021
  • Accepted 8 November 2021

DOI:https://doi.org/10.1103/PhysRevLett.128.041601

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Particles & FieldsInterdisciplinary Physics

Authors & Affiliations

Gergely Kántor* and Constantinos Papageorgakis

  • Centre for Theoretical Physics, Department of Physics and Astronomy Queen Mary University of London, London E1 4NS, United Kingdom

Vasilis Niarchos

  • CCTP and ITCP, Department of Physics, University of Crete, Heraklion 71303, Greece

  • *Corresponding author. g.kantor@qmul.ac.uk
  • Corresponding author. c.papageorgakis@qmul.ac.uk
  • Corresponding author. niarchos@physics.uoc.gr

See Also

Conformal bootstrap with reinforcement learning

Gergely Kántor, Vasilis Niarchos, and Constantinos Papageorgakis
Phys. Rev. D 105, 025018 (2022)

Article Text

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Issue

Vol. 128, Iss. 4 — 28 January 2022

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