Parameter tuning patterns for random graph coloring with quantum annealing.
Quantum annealing is a combinatorial optimization technique inspired by quantum mechanics. Here we show that a spin model for the k-coloring of large dense random graphs can be field tuned so that its acceptance ratio diverges during Monte Carlo quantum annealing, until a ground state is reached. We...
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Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3498173?pdf=render |
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doaj-5a78b5bb75a44807b65fe3398e7b0b8c2020-11-25T01:35:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-01711e5006010.1371/journal.pone.0050060Parameter tuning patterns for random graph coloring with quantum annealing.Olawale TitiloyeAlan CrispinQuantum annealing is a combinatorial optimization technique inspired by quantum mechanics. Here we show that a spin model for the k-coloring of large dense random graphs can be field tuned so that its acceptance ratio diverges during Monte Carlo quantum annealing, until a ground state is reached. We also find that simulations exhibiting such a diverging acceptance ratio are generally more effective than those tuned to the more conventional pattern of a declining and/or stagnating acceptance ratio. This observation facilitates the discovery of solutions to several well-known benchmark k-coloring instances, some of which have been open for almost two decades.http://europepmc.org/articles/PMC3498173?pdf=render |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Olawale Titiloye Alan Crispin |
| spellingShingle |
Olawale Titiloye Alan Crispin Parameter tuning patterns for random graph coloring with quantum annealing. PLoS ONE |
| author_facet |
Olawale Titiloye Alan Crispin |
| author_sort |
Olawale Titiloye |
| title |
Parameter tuning patterns for random graph coloring with quantum annealing. |
| title_short |
Parameter tuning patterns for random graph coloring with quantum annealing. |
| title_full |
Parameter tuning patterns for random graph coloring with quantum annealing. |
| title_fullStr |
Parameter tuning patterns for random graph coloring with quantum annealing. |
| title_full_unstemmed |
Parameter tuning patterns for random graph coloring with quantum annealing. |
| title_sort |
parameter tuning patterns for random graph coloring with quantum annealing. |
| publisher |
Public Library of Science (PLoS) |
| series |
PLoS ONE |
| issn |
1932-6203 |
| publishDate |
2012-01-01 |
| description |
Quantum annealing is a combinatorial optimization technique inspired by quantum mechanics. Here we show that a spin model for the k-coloring of large dense random graphs can be field tuned so that its acceptance ratio diverges during Monte Carlo quantum annealing, until a ground state is reached. We also find that simulations exhibiting such a diverging acceptance ratio are generally more effective than those tuned to the more conventional pattern of a declining and/or stagnating acceptance ratio. This observation facilitates the discovery of solutions to several well-known benchmark k-coloring instances, some of which have been open for almost two decades. |
| url |
http://europepmc.org/articles/PMC3498173?pdf=render |
| work_keys_str_mv |
AT olawaletitiloye parametertuningpatternsforrandomgraphcoloringwithquantumannealing AT alancrispin parametertuningpatternsforrandomgraphcoloringwithquantumannealing |
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