SpinGlassPEPS.jl: Tensor-network package for Ising-like optimization on quasi-two-dimensional graphs

TL;DR

SpinGlassPEPS.jl is a Julia-based tensor network software package that efficiently finds low-energy configurations of Ising-like models on quasi-2D graphs, aiding optimization problems relevant to quantum annealing.

Contribution

It introduces a modular tensor network approach using PEPS for Ising and QUBO problems on quasi-2D graphs, optimized for modern hardware.

Findings

Enables low-energy configuration discovery on quasi-2D graphs.

Supports various contraction schemes and hardware acceleration.

Facilitates optimization for quantum annealing problems.

Abstract

This work introduces SpinGlassPEPS$.$jl, a software package implemented in Julia, designed to find low-energy configurations of generalized Potts models, including Ising and QUBO problems, utilizing heuristic tensor network contraction algorithms on quasi-2D geometries. In particular, the package employs the Projected Entangled-Pairs States to approximate the Boltzmann distribution corresponding to the model's cost function. This enables an efficient branch-and-bound search (within the probability space) that exploits the locality of the underlying problem's topology. As a result, our software enables the discovery of low-energy configurations for problems on quasi-2D graphs, particularly those relevant to modern quantum annealing devices. The modular architecture of SpinGlassPEPS$.$jl supports various contraction schemes and hardware acceleration.