Quantum Optimization

dc.creatorHogg, Tad
dc.creatorPortnov, Dmitriy
dc.date2000-06-20
dc.date.accessioned2026-07-07T06:00:15Z
dc.date.available2026-07-07T06:00:15Z
dc.descriptionWe present a quantum algorithm for combinatorial optimization using the cost structure of the search states. Its behavior is illustrated for overconstrained satisfiability and asymmetric traveling salesman problems. Simulations with randomly generated problem instances show each step of the algorithm shifts amplitude preferentially towards lower cost states, thereby concentrating amplitudes into low-cost states, on average. These results are compared with conventional heuristics for these problems.
dc.description11 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/quant-ph/0006090
dc.identifierhttp://arxiv.org/abs/quant-ph/0006090
dc.identifierInformation Sciences 128, 181-197 (2000)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/88937
dc.subjectQuantum Physics
dc.titleQuantum Optimization
dc.typetext

Files

Collections