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Quantum Optimization
Calculating Nash Equilibrium on Quantum Annealers
arXiv
Authors: Olga Okrut, Keith Cannon, Kareem H. El-Safty, Nada Elsokkary, Faisal Shah Khan
Year
2021
Paper ID
40424
Status
Preprint
Abstract Read
~2 min
Abstract Words
139
Citations
N/A
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.
Why This Paper Matters
- This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
- It adds a 2021 reference point for readers tracking recent quantum research.
- Adiabatic quantum computing is implemented on specialized hardware using the heuristics of the quantum annealing algorithm.
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