Solving Conformal Field Theories with Artificial Intelligence
| Autor: | Kántor, Gergely, Niarchos, Vasilis, Papageorgakis, Constantinos |
|---|---|
| Rok vydání: | 2021 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1103/PhysRevLett.128.041601 |
| Popis: | 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. Comment: 6 pages; v2: references added |
| Databáze: | arXiv |
| Externí odkaz: |
|