Ising formulations of some graph-theoretic problems in psychological research: Models and methods

Abstract

It has been established in the fields of computer science and physics that many NP-hard and NP-complete graph-theoretic problems can be formulated and solved as Ising spin models. We discuss several problems that have a history in mathematical psychology, most notably max-cut clustering, graph coloring, a linear ordering problem related to paired comparison ranking and directed acyclic graphs, and the problem of finding a minimum subset of points necessary to contain another point within a convex hull. New Ising spin models are presented for the latter two problems. Additionally, we provide MATLAB software programs for obtaining solutions via enumeration of all spin ensembles (when computationally feasible) and simulated annealing. We are not claiming that the Ising spin model should be the preferred approach for formulating and solving graph-theoretic problems on conventional digital computers but it does provide a unifying framework for these problems, which may lead to future computational improvements. Recent progress in the development of quantum computing architecture has shown that Ising spin models can afford enormous improvements in algorithm efficiency when implemented on these platforms, potentially leading to widespread use of the methodology in the future.