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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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