Phase boundary location with information-theoretic entropy in tensor renormalization group flows

We present a simple and efficient tensor network method to accurately locate phase boundaries of two-dimensional classical lattice models. The method utilizes only the information-theoretic (von Neumann) entropy of quantities that automatically arise along tensor renormalization group [Phys. Rev. Lett. 99, 120601 (2007)PRLTAO0031-900710.1103/PhysRevLett.99.120601] flows of partition functions. We benchmark the method against theoretically known results for the square-lattice q-state Potts models, which includes first-order, weakly first-order, and continuous phase transitions, and find good agreement in all cases. We also compare against previous Monte Carlo results for the frustrated square lattice J1-J2 Ising model and find good agreement. ? 2019 American Physical Society.