Unified tensor network theory for frustrated classical spin models in two dimensions

Abstract

Frustration is a ubiquitous phenomenon in many-body physics that influences the nature of the system in a profound way with exotic emergent behavior. Despite its long research history, the analytical or numerical investigations on frustrated spin models remain a formidable challenge due to their extensive ground state degeneracy. In this work, we propose a unified tensor network theory to numerically solve the frustrated classical spin models on various two-dimensional (2D) lattice geometry with high efficiency. We show that the appropriate encoding of emergent degrees of freedom in each local tensor is of crucial importance in the construction of the infinite tensor network representation of the partition function. The frustrations are thus relieved through the effective interactions between emergent local degrees of freedom. Then the partition function is written as a product of a one-dimensional (1D) transfer operator, whose eigen-equation can be solved by the standard algorithm of matrix product states rigorously, and various phase transitions can be accurately determined from the singularities of the entanglement entropy of the 1D quantum correspondence. We demonstrated the power of our unified theory by numerically solving 2D fully frustrated XY spin models on the kagome, square and triangular lattices, giving rise to a variety of thermal phase transitions from infinite-order Brezinskii-Kosterlitz-Thouless transitions, second-order transitions, to first-order phase transitions. Our approach holds the potential application to other types of frustrated classical systems like Heisenberg spin antiferromagnets.

arXiv comment20 pages, 19 figures

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• Theory of charge-6e condensed phase in Kagome lattice superconductors
• Phase coherence of charge-$6e$ superconductors via a frustrated Kagome XY antiferromagnet
• Probing phase transitions with correlations in configuration space
• Tensor network renormalization approach to antiferromagnetic 6-state clock model on the Union Jack lattice
• Efficient optimization of variational tensor-network approach to three-dimensional statistical systems
• Emergent Intermediate Phase in the $J_1$-$J_2$ XY model from Tensor Network Approaches
• Variational boundary based tensor network renormalization group
• Equivalence of residual entropy of hexagonal and cubic ices from tensor network methods