Solving Conformal Field Theories with Artificial Intelligence
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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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