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        <identifier>oai:drops-oai.dagstuhl.de:24414</identifier>
        <datestamp>2025-12-12T15:01:38Z</datestamp>
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          <dc:title>Sharp Thresholds for the Overlap Gap Property: Ising p-Spin Glass and Random k-SAT</dc:title>
          <dc:creator>Kızıldağ, Eren C.</dc:creator>
          <dc:subject>spin glasses</dc:subject>
          <dc:subject>p-spin model</dc:subject>
          <dc:subject>random constraint satisfaction problems</dc:subject>
          <dc:subject>overlap gap property</dc:subject>
          <dc:subject>phase transitions</dc:subject>
          <dc:subject>computational complexity</dc:subject>
          <dc:description>The Ising p-spin glass and random k-SAT are two canonical examples of disordered systems that play a central role in understanding the link between geometric features of optimization landscapes and computational tractability. Both models exhibit hard regimes where all known polynomial-time algorithms fail and possess the multi Overlap Gap Property (m-OGP), an intricate geometrical property that rigorously rules out a broad class of algorithms exhibiting input stability. &#13;
We establish that, in both models, the symmetric m-OGP undergoes a sharp phase transition, and we pinpoint its exact threshold. For the Ising p-spin glass, our results hold for all sufficiently large p; for the random k-SAT, they apply to all k growing mildly with the number of Boolean variables. Notably, our findings yield qualitative insights into the power of OGP-based arguments. A particular consequence for the Ising p-spin glass is that the strength of the m-OGP in establishing algorithmic hardness grows without bound as m increases. &#13;
These are the first sharp threshold results for the m-OGP. Our analysis hinges on a judicious application of the second moment method, enhanced by concentration. While a direct second moment calculation fails, we overcome this via a refined approach that leverages an argument of Frieze [Frieze, 1990] and exploiting concentration properties of carefully constructed random variables.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Eren C. Kızıldağ</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2025.48</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-244147</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.48</dc:identifier>
          <dc:language>eng</dc:language>
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