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• W3106899423 abstract "In a broad class of sparse random constraint satisfaction problems (CSP), deep heuristics from statistical physics predict that there is a condensation phase transition before the satisfiability threshold, governed by one-step replica symmetry breaking (1RSB). In fact, in random regular k-NAE-SAT, which is one of such random CSPS, it was verified [1] that its free energy is well-defined and the explicit value follows the 1RSB prediction. However, for any model of sparse random CSP, it has been unknown whether the solution space indeed condensates on O(1) clusters according to the 1RSB prediction. In this paper, we give an affirmative answer to this question for the random regular k-NAE-SAT model. Namely, we prove that with probability close to one, most of the solutions lie inside a bounded number of solution clusters whose sizes are comparable to the scale of the free energy. Furthermore, we establish that the overlap between two independently drawn solutions concentrates precisely at two values. This is the defining property of the one-step replica symmetry breaking class which we establish for the first time in a sparse random CSP, Our proof is based on a detailed moment analysis of a spin system, which has an infinite spin space that encodes the structure of solution clusters. We develop new techniques to study the partition function as well as enhance previous approaches which were only applicable to spin systems with finitely many spins. We believe that our method is applicable to a broad range of random CSPS in the 1RSB universality class." @default.
• W3106899423 created "2020-12-07" @default.
• W3106899423 creator A5044363834 @default.
• W3106899423 creator A5056469270 @default.
• W3106899423 creator A5076570918 @default.
• W3106899423 date "2022-02-01" @default.
• W3106899423 modified "2023-09-26" @default.
• W3106899423 title "One-step replica symmetry breaking of random regular NAE-SAT" @default.
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• W3106899423 doi "https://doi.org/10.1109/focs52979.2021.00039" @default.
• W3106899423 hasPublicationYear "2022" @default.
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