Calculating Nash Equilibrium on Quantum Annealers

TL;DR

This paper presents a novel QUBO formulation for computing Nash equilibria using quantum annealers, demonstrating significant speedups in solving two-player game problems compared to classical methods.

Contribution

The authors develop a penalty-based QUBO formulation for Nash equilibrium, enabling its computation on quantum annealers, which was not previously possible.

Findings

Achieved 7-10x speedup in solving Nash equilibrium problems on D-Wave quantum annealers.

Successfully formulated Nash equilibrium as a QUBO problem suitable for quantum annealing.

Validated the approach with three example problems, demonstrating effectiveness.

Abstract

Adiabatic quantum computing is implemented on specialized hardware using the heuristics of the quantum annealing algorithm. This setup requires the addressed problems to be formatted as discrete quadratic functions without constraints and the variables to take binary values only. The problem of finding Nash equilibrium in two-player, non-cooperative games is a two-fold quadratic optimization problem with constraints. This problem was formatted as a single, constrained quadratic optimization in 1964 by Mangasarian and Stone. Here, we show that adding penalty terms to the quadratic function formulation of Nash equilibrium gives a quadratic unconstrained binary optimization (QUBO) formulation of this problem that can be executed on quantum annealers. Three examples are discussed to highlight the success of the formulation, and an overall, time-to-solution (hardware + software processing) speed up of seven to ten times is reported on quantum annealers developed by D-Wave System.