Abstract
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)] flows of partition functions. We benchmark the method against theoretically known results for the square-lattice -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 Ising model and find good agreement.
- Received 20 March 2019
- Revised 20 August 2019
DOI:https://doi.org/10.1103/PhysRevB.100.094430
©2019 American Physical Society