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arXiv · 1901.08193

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

Adil A. Gangat·Ying-Jer Kao
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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. \textbf{12}, 120601 (2007)] 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 $J_1-J_2$ Ising model and find good agreement.

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Adil A. Gangat, Ying-Jer Kao. 2019-11-10. Phase boundary location with information-theoretic entropy in tensor renormalization group flows. https://doi.org/10.1103/physrevb.100.094430

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