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Certifying solution geometry in random CSPs: counts, clusters and balance
[article]
2021
arXiv
pre-print
An active topic in the study of random constraint satisfaction problems (CSPs) is the geometry of the space of satisfying or almost satisfying assignments as the function of the density, for which a precise landscape of predictions has been made via statistical physics-based heuristics. In parallel, there has been a recent flurry of work on refuting random constraint satisfaction problems, via nailing refutation thresholds for spectral and semidefinite programming-based algorithms, and also on
arXiv:2106.12710v1
fatcat:54qtuux4yrcm5kenh5nbvstyfa