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Quantum Optimization for Combinatorial Searches

Carlo A. Trugenberger
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Abstract

I propose a "quantum annealing" heuristic for the problem of combinatorial search among a frustrated set of states characterized by a cost function to be minimized. The algorithm is probabilistic, with postselection of the measurement result. A unique parameter playing the role of an effective temperature governs the computational load and the overall quality of the optimization. Any level of accuracy can be reached with a computational load independent of the dimension {\it N} of the search set by choosing the effective temperature correspondingly low. This is much better than classical search heuristics, which typically involve computation times growing as powers of log({\it N})

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Carlo A. Trugenberger. 2002-04-19. Quantum Optimization for Combinatorial Searches. https://doi.org/10.1088/1367-2630%2F4%2F1%2F326

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