A single-layer variational tensor network method reduces computational cost by three orders of magnitude in bond dimension for 2D quantum models and confirms an intermediate empty-plaquette valence bond solid phase in the Shastry-Sutherland model.
Vidal, Phys
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cond-mat.str-el 2years
2025 2verdicts
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TTNR combines global-optimization TNR with a new thermal density-matrix construction to extract high-accuracy CFT data at 2D quantum thermal transitions.
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Single-layer framework of variational tensor network states
A single-layer variational tensor network method reduces computational cost by three orders of magnitude in bond dimension for 2D quantum models and confirms an intermediate empty-plaquette valence bond solid phase in the Shastry-Sutherland model.
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Global Tensor Network Renormalization for 2D Quantum systems: A new window to probe universal data from thermal transitions
TTNR combines global-optimization TNR with a new thermal density-matrix construction to extract high-accuracy CFT data at 2D quantum thermal transitions.