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Sharpness of the Satisfiability Threshold for Non-uniform Random k-SAT

  • Tobias Friedrich
  • Ralf RothenbergerEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10929)

Abstract

We study non-uniform random k-SAT on n variables with an arbitrary probability distribution \(\varvec{p}\) on the variable occurrences. The number \(t=t(n)\) of randomly drawn clauses at which random formulas go from asymptotically almost surely (a. a. s.) satisfiable to a. a. s. unsatisfiable is called the satisfiability threshold. Such a threshold is called sharp if it approaches a step function as n increases. We show that a threshold t(n) for random k-SAT with an ensemble \((\varvec{p}_n)_{n\in \mathbb {N}}\) of arbitrary probability distributions on the variable occurrences is sharp if \(\Vert \varvec{p}_n\Vert _2^2=\mathcal {O}_n\left( {t}^{-\frac{2}{k}}\right) \) and \(\Vert \varvec{p}_n\Vert _{\infty }=o_n\left( {t}^{-\frac{k}{2k-1}}\cdot \log ^{-\frac{k-1}{2k-1}}{t}\right) \).

This result generalizes Friedgut’s sharpness result from uniform to non-uniform random k-SAT and implies sharpness for thresholds of a wide range of random k-SAT models with heterogeneous probability distributions, for example such models where the variable probabilities follow a power-law distribution.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Hasso Plattner InstitutePotsdamGermany

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