Variational optimization with infinite projected entangled-pair states

TL;DR

This paper introduces an iterative variational optimization scheme for infinite projected entangled-pair states (iPEPS) to accurately compute ground states of 2D quantum systems, outperforming previous methods in accuracy and convergence speed.

Contribution

The authors develop a new variational optimization method for iPEPS using the corner transfer-matrix approach, achieving higher accuracy and faster convergence than existing algorithms.

Findings

Outperforms previous imaginary time evolution algorithms in accuracy.

Achieves faster convergence to ground states in benchmark models.

Applicable to complex 2D quantum systems like the Heisenberg and t-J models.

Abstract

We present a scheme to perform an iterative variational optimization with infinite projected entangled-pair states (iPEPS), a tensor network ansatz for a two-dimensional wave function in the thermodynamic limit, to compute the ground state of a local Hamiltonian. The method is based on a systematic summation of Hamiltonian contributions using the corner transfer-matrix method. Benchmark results for challenging problems are presented, including the 2D Heisenberg model, the Shastry-Sutherland model, and the t-J model, which show that the variational scheme yields considerably more accurate results than the previously best imaginary time evolution algorithm, with a similar computational cost and with a faster convergence towards the ground state.