Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2008-10-08
J. Stat. Mech. (2008) P12004
Physics
Condensed Matter
Disordered Systems and Neural Networks
19 pages, 12 figures
Scientific paper
10.1088/1742-5468/2008/12/P12004
We study the phase diagram and the algorithmic hardness of the random `locked' constraint satisfaction problems, and compare them to the commonly studied 'non-locked' problems like satisfiability of boolean formulas or graph coloring. The special property of the locked problems is that clusters of solutions are isolated points. This simplifies significantly the determination of the phase diagram, which makes the locked problems particularly appealing from the mathematical point of view. On the other hand we show empirically that the clustered phase of these problems is extremely hard from the algorithmic point of view: the best known algorithms all fail to find solutions. Our results suggest that the easy/hard transition (for currently known algorithms) in the locked problems coincides with the clustering transition. These should thus be regarded as new benchmarks of really hard constraint satisfaction problems.
Mezard Marc
Zdeborová Lenka
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