Adil A. GangatYING-JER KAO2021-07-282021-07-28201924699950https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072804318&doi=10.1103%2fPhysRevB.100.094430&partnerID=40&md5=cd6239d02dfb19538bb91a729a5eae8ehttps://scholars.lib.ntu.edu.tw/handle/123456789/575269We 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.Crystal lattices; Entropy; Ising model; Potts model; Statistical mechanics; Tensors; Continuous phase transitions; Lattice models; Monte Carlo results; Network methods; Partition functions; Q-state Potts model; Square lattices; Tensor renormalization; Information theoryjournal article10.1103/PhysRevB.100.0944302-s2.0-85072804318