6533b827fe1ef96bd1286529

RESEARCH PRODUCT

Tensor Network Annealing Algorithm for Two-Dimensional Thermal States

Augustine KshetrimayumAugustine KshetrimayumMatteo RizziRoman OrusRoman OrusRoman OrusJens Eisert

subject

PhysicsOptical latticeQuantum PhysicsStrongly Correlated Electrons (cond-mat.str-el)General Physics and AstronomyQuantum simulatortensor network methodsFOS: Physical sciences01 natural sciencesSquare latticequantum statistical mechanicsCondensed Matter - Strongly Correlated ElectronsExact solutions in general relativityquantum information0103 physical sciencesThermodynamic limit539strongly correlated systemsIsing modelQuantum information010306 general physicsQuantum statistical mechanicsQuantum Physics (quant-ph)Algorithmquantum simulation

description

Tensor network methods have become a powerful class of tools to capture strongly correlated matter, but methods to capture the experimentally ubiquitous family of models at finite temperature beyond one spatial dimension are largely lacking. We introduce a tensor network algorithm able to simulate thermal states of two-dimensional quantum lattice systems in the thermodynamic limit. The method develops instances of projected entangled pair states and projected entangled pair operators for this purpose. It is the key feature of this algorithm to resemble the cooling down of the system from an infinite temperature state until it reaches the desired finite-temperature regime. As a benchmark we study the finite-temperature phase transition of the Ising model on an infinite square lattice, for which we obtain remarkable agreement with the exact solution. We then turn to study the finite-temperature Bose-Hubbard model in the limits of two (hard-core) and three bosonic modes per site. Our technique can be used to support the experimental study of actual effectively two-dimensional materials in the laboratory, as well as to benchmark optical lattice quantum simulators with ultra-cold atoms.

10.1103/physrevlett.122.070502http://dx.doi.org/10.1103/physrevlett.122.070502