Quantum Annealing for Constrained Optimization
Itay Hen, Federico M. Spedalieri · Physical Review Applied · 2016
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.