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We investigate geometrical properties of the random K-satisfiability problem using the notion of x-satisfiability: a formula is x-satisfiable if there exist two SAT assignments differing in Nx variables. We show the existence of a sharp…

Disordered Systems and Neural Networks · Physics 2008-03-20 Hervé Daudé , Marc Mezard , Thierry Mora , Riccardo Zecchina

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…

Probability · Mathematics 2025-02-25 Allan Sly , Youngtak Sohn

In this note we study the convergence of the survey decimation algorithm. An analytic formula for the reduction of the complexity during the decimation is derived. The limit of the converge of the algorithm are estimated in the random case:…

Computational Complexity · Computer Science 2007-05-23 Giorgio Parisi

As a natural variant of the $k$-SAT problem, NAE-$k$-SAT additionally requires the literals in each clause to take not-all-equal (NAE) truth values. In this paper, we study the worst-case time complexities of solving NAE-$k$-SAT and…

Computational Complexity · Computer Science 2019-06-27 S. Cliff Liu

We study the performance of stochastic local search algorithms for random instances of the $K$-satisfiability ($K$-SAT) problem. We introduce a new stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a…

Data Structures and Algorithms · Computer Science 2009-11-13 Mikko Alava , John Ardelius , Erik Aurell , Petteri Kaski , Supriya Krishnamurthy , Pekka Orponen , Sakari Seitz

In this short paper we present a survey of some results concerning the random SAT problems. To elaborate, the Boolean Satisfiability (SAT) Problem refers to the problem of determining whether a given set of $m$ Boolean constraints over $n$…

Probability · Mathematics 2023-11-07 Andreas Basse-O'Connor , Tobias Lindhardt Overgaard , Mette Skjøtt

Several algorithms for solving constraint satisfaction problems are based on survey propagation, a variational inference scheme used to obtain approximate marginal probability estimates for variable assignments. These marginals correspond…

Artificial Intelligence · Computer Science 2020-01-29 Aditya Grover , Tudor Achim , Stefano Ermon

We introduce an efficient message passing scheme for solving Constraint Satisfaction Problems (CSPs), which uses stochastic perturbation of Belief Propagation (BP) and Survey Propagation (SP) messages to bypass decimation and directly…

Artificial Intelligence · Computer Science 2016-01-05 Siamak Ravanbakhsh , Russell Greiner

The Random K-Satisfiability Problem, consisting in verifying the existence of an assignment of N Boolean variables that satisfy a set of M=alpha N random logical clauses containing K variables each, is studied using the replica symmetric…

Disordered Systems and Neural Networks · Physics 2009-10-28 R. Monasson , R. Zecchina

Constraint satisfaction problems (CSPs) models many important intractable NP-hard problems such as propositional satisfiability problem (SAT). Algorithms with non-trivial upper bounds on running time for restricted SAT with bounded clause…

Data Structures and Algorithms · Computer Science 2008-01-22 Liang Li , Xin Li , Tian Liu , Ke Xu

The survey propagation (SP) algorithm has been shown to work well on large instances of the random 3-SAT problem near its phase transition. It was shown that SP estimates marginals over covers that represent clusters of solutions. The SP-y…

Artificial Intelligence · Computer Science 2014-01-16 Hai Leong Chieu , Wee Sun Sun Lee

The evaluation of incomplete satisfiability solvers depends critically on the availability of hard satisfiable instances. A plausible source of such instances consists of random k-SAT formulas whose clauses are chosen uniformly from among…

Artificial Intelligence · Computer Science 2007-05-23 Dimitris Achlioptas , Haixia Jia , Cristopher Moore

Here we study the NP-complete $K$-SAT problem. Although the worst-case complexity of NP-complete problems is conjectured to be exponential, there exist parametrized random ensembles of problems where solutions can typically be found in…

Disordered Systems and Neural Networks · Physics 2019-07-11 Hendrik Schawe , Roman Bleim , Alexander K. Hartmann

We report a cluster of results regarding the difficulty of finding approximate ground states to typical instances of the quantum satisfiability problem $k$-QSAT on large random graphs. As an approximation strategy, we optimize the solution…

Statistical Mechanics · Physics 2013-06-27 B. Hsu , C. R. Laumann , A. Laeuchli , R. Moessner , S. L. Sondhi

Many natural optimization problems are NP-hard, which implies that they are probably hard to solve exactly in the worst-case. However, it suffices to get reasonably good solutions for all (or even most) instances in practice. This paper…

Artificial Intelligence · Computer Science 2022-09-13 Raffaele Marino

The constraint satisfaction problems k-SAT and Quantum k-SAT (k-QSAT) are canonical NP-complete and QMA_1-complete problems (for k>=3), respectively, where QMA_1 is a quantum generalization of NP with one-sided error. Whereas k-SAT has been…

Quantum Physics · Physics 2021-04-01 Marco Aldi , Niel de Beaudrap , Sevag Gharibian , Seyran Saeedi

We study and solve some variations of the random K-satisfiability problem - balanced K-SAT and biased random K-SAT - on a regular tree, using techniques we have developed earlier(arXiv:1110.2065). In both these problems, as well as…

Statistical Mechanics · Physics 2013-05-01 Sumedha , Supriya Krishnamurthy , Sharmistha Sahoo

The basic random $k$-SAT problem is: Given a set of $n$ Boolean variables, and $m$ clauses of size $k$ picked uniformly at random from the set of all such clauses on our variables, is the conjunction of these clauses satisfiable? Here we…

Combinatorics · Mathematics 2019-06-13 Joel Larsson , Klas Markström

Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with…

Discrete Mathematics · Computer Science 2009-11-13 Amin Coja-Oghlan

The best current estimates of the thresholds for the existence of solutions in random constraint satisfaction problems ('CSPs') mostly derive from the first and the second moment method. Yet apart from a very few exceptional cases these…

Discrete Mathematics · Computer Science 2017-11-17 Amin Coja-Oghlan , Konstantinos Panagiotou