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arXiv:1508.04212 · Physical Review Applied

Quantum Annealing for Constrained Optimization

Itay Hen, Federico M. Spedalieri

Published Mar 11, 2016• 114 citations
arXivHTMLPDF

Abstract

Quantum computers can perform certain tasks much faster than classical computers. An example is $q\phantom{\rule{0}{0ex}}u\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}t\phantom{\rule{0}{0ex}}u\phantom{\rule{0}{0ex}}m$ $a\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}e\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}l\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}g$, an operation that permits the exploration of energy landscapes to find global minima $i.e.$, optimal solutions) for problems that are classically intractable. This permits simultaneous exploration of enormous computational spaces, as is necessary for complex problems in economics, network design, and nonlinear control. The authors show how suitably engineered quantum annealers can efficiently guide and focus the quantum wave function towards the solutions of constrained optimization problems.

DOI
10.1103/physrevapplied.5.034007

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