Solving Conformal Field Theories with Artificial Intelligence

被引:20
|
作者
Kantor, Gergely [1 ]
Papageorgakis, Constantinos [1 ]
Niarchos, Vasilis [2 ,3 ]
机构
[1] Queen Mary Univ London, Ctr Theoret Phys, Dept Phys & Astron, London E1 4NS, England
[2] Univ Crete, Dept Phys, CCTP, Iraklion 71303, Greece
[3] Univ Crete, Dept Phys, ITCP, Iraklion 71303, Greece
关键词
All Open Access; Hybrid Gold; Green;
D O I
10.1103/PhysRevLett.128.041601
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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 (CFI's). 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.
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页数:6
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