Calculating Nash Equilibrium on Quantum Annealers
arXiv:2112.12583 · doi:10.1007/s10479-023-05700-z
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.
8 pages, 5 figures
References in corpus (7)
- Quantum Annealing for Industry Applications: Introduction and Review
- Coherent quantum annealing in a programmable 2000-qubit Ising chain
- Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems
- Adiabatic Quantum Linear Regression
- Bayesian estimation of one-parameter qubit gates
- Quantum Optimization for the Graph Coloring Problem with Space-Efficient Embedding
- Community Detection in Electrical Grids Using Quantum Annealing