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Local geometry of NAE-SAT solutions in the condensation regime

Author(s)
Sly, Allan; Sohn, Youngtak
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Abstract
The local behavior of typical solutions of random constraint satisfaction problems (csp) describes many important phenomena including clustering thresholds, decay of correlations, and the behavior of message passing algorithms. When the constraint density is low, studying the planted model is a powerful technique for determining this local behavior which in many examples has a simple Markovian structure. The work of Coja-Oghlan, Kapetanopoulos, Müller (Comb Prob Comput 29:346-422, 2020) showed that for a wide class of models, this description applies up to the so-called condensation threshold. Understanding the local behavior after the condensation threshold is more complex due to long-range correlations. In this work, we revisit the random regular nae-sat model in the condensation regime and determine the local weak limit which describes a random solution around a typical variable. This limit exhibits a complicated non-Markovian structure arising from the space of solutions being dominated by a small number of large clusters. This is the first description of the local weak limit in the condensation regime for any sparse random csps in the one-step replica symmetry breaking (1rsb) class. Our result is non-asymptotic and characterizes the tight fluctuation O ( n - 1 / 2 ) around the limit. Our proof is based on coupling the local neighborhoods of an infinite spin system, which encodes the structure of the clusters, to a broadcast model on trees whose channel is given by the 1rsb belief-propagation fixed point. We believe that our proof technique has broad applicability to random csps in the 1rsb class.
Date issued
2024-11-14
URI
https://hdl.handle.net/1721.1/157559
Department
Massachusetts Institute of Technology. Department of Mathematics
Journal
Probability Theory and Related Fields
Publisher
Springer Berlin Heidelberg
Citation
Sly, A., Sohn, Y. Local geometry of NAE-SAT solutions in the condensation regime. Probab. Theory Relat. Fields (2024).
Version: Final published version

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