Abstract
Feedback-controlled electromigration (FCE) is employed to control metal nanowires with quantized conductance and create atomic junctions. The FCE scheme is commonly implemented using many experimental parameters, and determining the optimal FCE parameters can be regarded as a combinatorial optimization problem. The D-Wave quantum annealer has attracted attention for its hardware implementation of quantum annealing (QA), which is a heuristic algorithm for solving combinatorial optimization problems. This study developed a QA approach for optimizing the FCE parameters and executed it on a quantum annealer. The results and performance were compared with those of a classical solver.
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