Exploring corner transfer matrices and corner tensors for the classical simulation of quantum lattice systems
Roman Orus

TL;DR
This paper develops tensor network algorithms using corner transfer matrices and tensors for classical simulation of infinite quantum lattice systems in 1d and 2d, offering an alternative to existing methods.
Contribution
It introduces new algorithms based on corner transfer matrices and tensors that preserve symmetries and provide a viable alternative to established tensor network techniques.
Findings
Algorithms successfully approximate ground state properties.
Preliminary benchmarks on the quantum Ising model show promising results.
Differences in computational complexity are observed depending on the scheme.
Abstract
In this paper we explore the practical use of the corner transfer matrix and its higher-dimensional generalization, the corner tensor, to develop tensor network algorithms for the classical simulation of quantum lattice systems of infinite size. This exploration is done mainly in one and two spatial dimensions (1d and 2d). We describe a number of numerical algorithms based on corner matri- ces and tensors to approximate different ground state properties of these systems. The proposed methods make also use of matrix product operators and projected entangled pair operators, and naturally preserve spatial symmetries of the system such as translation invariance. In order to assess the validity of our algorithms, we provide preliminary benchmarking calculations for the spin-1/2 quantum Ising model in a transverse field in both 1d and 2d. Our methods are a plausible alternative to other…
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