Simulating thermal density operators with cluster expansions and tensor networks
Bram Vanhecke, David Devoogdt, Frank Verstraete, Laurens Vanderstraeten
SciPost Phys. 14, 085 (2023) · published 26 April 2023
- doi: 10.21468/SciPostPhys.14.4.085
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Abstract
We provide an efficient approximation for the exponential of a local operator in quantum spin systems using tensor-network representations of a cluster expansion. We benchmark this cluster tensor network operator (cluster TNO) for one-dimensional systems, and show that the approximation works well for large real- or imaginary-time steps. We use this formalism for representing the thermal density operator of a two-dimensional quantum spin system at a certain temperature as a single cluster TNO, which we can then contract by standard contraction methods for two-dimensional tensor networks. We apply this approach to the thermal phase transition of the transverse-field Ising model on the square lattice, and we find through a scaling analysis that the cluster-TNO approximation gives rise to a continuous phase transition in the correct universality class; by increasing the order of the cluster expansion we find good values of the critical point up to surprisingly low temperatures.
Cited by 6
Authors / Affiliations: mappings to Contributors and Organizations
See all Organizations.- 1 2 Bram Vanhecke,
- 2 David Devoogdt,
- 2 Frank Verstraete,
- 2 Laurens Vanderstraeten
- European Research Council [ERC]
- Fonds Wetenschappelijk Onderzoek (FWO) (through Organization: Fonds voor Wetenschappelijk Onderzoek - Vlaanderen / Research Foundation - Flanders [FWO])