Vacancies in graphene: an application of adiabatic quantum optimization

TL;DR

This paper demonstrates how quantum annealing can be used to study the stability and arrangements of vacancy defects in graphene, showing potential for physical-chemical problem solving.

Contribution

It introduces a method to map graphene vacancy interactions onto a quadratic unconstrained binary optimization problem suitable for current quantum annealers.

Findings

Successfully reproduces known defect stability results

Extracts multiple defect arrangements and energies

Shows feasibility of quantum annealing for physical-chemical problems

Abstract

Quantum annealers have grown in complexity to the point that quantum computations involving few thousands of qubits are now possible. In this paper, \textcolor{black}{with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study} the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits \textcolor{black}{the ground state as well the excited states found by} the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. This approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical-chemical interest.