Symmetric cluster expansions with tensor networks

Abstract

Cluster expansions for the exponential of local operators are constructed using tensor networks. In contrast to other approaches, the cluster expansion does not break any spatial or internal symmetries and exhibits a very favourable prefactor to the error scaling versus bond dimension. This is illustrated by time evolving a matrix product state using very large time steps, and by constructing a novel robust algorithm for finding ground states of 2-dimensional Hamiltonians using projected entangled pair states as fixed points of 2-dimensional transfer matrices.

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Cited by in corpus (9)

• The ITensor Software Library for Tensor Network Calculations
• A scaling hypothesis for projected entangled-pair states
• Computing time-periodic steady-state currents via the time evolution of tensor network states
• Momentum-resolved time evolution with matrix product states
• Variational Tensor Network Operator
• Single-layer tensor network approach for three-dimensional quantum systems
• Quantum Gauge Networks: A New Kind of Tensor Network
• Tensor Network for Supervised Learning at Finite Temperature
• Locally accurate tensor networks for thermal states and time evolution