Locked constraint satisfaction problems

dc.creatorZdeborová, Lenka
dc.creatorMézard, Marc
dc.date2008-03-20
dc.date2008-09-05
dc.date.accessioned2026-07-07T10:00:32Z
dc.date.available2026-07-07T10:00:32Z
dc.descriptionWe introduce and study the random "locked" constraint satisfaction problems. When increasing the density of constraints, they display a broad "clustered" phase in which the space of solutions is divided into many isolated points. While the phase diagram can be found easily, these problems, in their clustered phase, are extremely hard from the algorithmic point of view: the best known algorithms all fail to find solutions. We thus propose new benchmarks of really hard optimization problems and provide insight into the origin of their typical hardness.
dc.description4 pages, 2 figures
dc.identifierhttps://arxiv.org/abs/0803.2955
dc.identifierhttp://arxiv.org/abs/0803.2955
dc.identifierPhys. Rev. Lett. 101, 078702 (2008)
dc.identifierdoi:10.1103/PhysRevLett.101.078702
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/168345
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.subjectComputational Complexity
dc.titleLocked constraint satisfaction problems
dc.typetext

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