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Solving Conformal Field Theories with Artificial Intelligence
Gergely Kántor1, Constantinos Papageorgakis1, Vasilis Niarchos2
1Centre for Theoretical Physics, Department of Physics and Astronomy Queen Mary University of London, London E1 4NS, United Kingdom.
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.
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