Solving Conformal Field Theories with Artificial Intelligence
Gergely Kántor, Constantinos Papageorgakis, Vasilis Niarchos
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.
Topics & Concepts
Conformal mapIsing modelContext (archaeology)SpacetimeField (mathematics)Computer scienceConformal field theoryPhysicsTheoretical physicsAlgorithmField theory (psychology)Theoretical computer scienceSpace (punctuation)Artificial intelligenceAlgebra over a fieldSpace timeEfficient algorithmCritical phenomenaField equationQuantum many-body systemsQuantum Chromodynamics and Particle InteractionsBlack Holes and Theoretical Physics