Authors: G. Kantor, V. Niarchos, C. Papageorgakis
Paper available on the arXiv at 2108.08859. Included as reference [1]
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.
References
- [1] G. Kantor, V. Niarchos, C. Papageorgakis
Solving Conformal Field Theories with Artificial Intelligence,
Phys.Rev.Lett. 128 (2022) 4, 041601, arXiv:2108.08859