Searching Ground States of Ising Spin Glasses with Particle Swarms

This paper presents a method for searching ground states of Ising spin glasses. The Ising model is one of the most commonly used because of its simplicity and its accuracy in representing real problems. We tackle the problem of finding ground states with particle swarm optimization (PSO), a population-based stochastic optimization technique inspired by social behavior of bird flocking. The paper is organized as follows: the first section briefly presents Ising spin glasses. Section 2 describes the basic principles of the particle swarm optimization meta-heuristic. Section 3 presents experimental results, followed by some conclusion and future work in Section 4.