192 research outputs found

    The Satisfiability Threshold for k-XORSAT

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    We consider "unconstrained" random kk-XORSAT, which is a uniformly random system of mm linear non-homogeneous equations in F2\mathbb{F}_2 over nn variables, each equation containing k≥3k \geq 3 variables, and also consider a "constrained" model where every variable appears in at least two equations. Dubois and Mandler proved that m/n=1m/n=1 is a sharp threshold for satisfiability of constrained 3-XORSAT, and analyzed the 2-core of a random 3-uniform hypergraph to extend this result to find the threshold for unconstrained 3-XORSAT. We show that m/n=1m/n=1 remains a sharp threshold for satisfiability of constrained kk-XORSAT for every k≥3k\ge 3, and we use standard results on the 2-core of a random kk-uniform hypergraph to extend this result to find the threshold for unconstrained kk-XORSAT. For constrained kk-XORSAT we narrow the phase transition window, showing that m−n→−∞m-n \to -\infty implies almost-sure satisfiability, while m−n→+∞m-n \to +\infty implies almost-sure unsatisfiability.Comment: Version 2 adds sharper phase transition result, new citation in literature survey, and improvements in presentation; removes Appendix treating k=

    Ground-state configuration space heterogeneity of random finite-connectivity spin glasses and random constraint satisfaction problems

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    We demonstrate through two case studies, one on the p-spin interaction model and the other on the random K-satisfiability problem, that a heterogeneity transition occurs to the ground-state configuration space of a random finite-connectivity spin glass system at certain critical value of the constraint density. At the transition point, exponentially many configuration communities emerge from the ground-state configuration space, making the entropy density s(q) of configuration-pairs a non-concave function of configuration-pair overlap q. Each configuration community is a collection of relatively similar configurations and it forms a stable thermodynamic phase in the presence of a suitable external field. We calculate s(q) by the replica-symmetric and the first-step replica-symmetry-broken cavity methods, and show by simulations that the configuration space heterogeneity leads to dynamical heterogeneity of particle diffusion processes because of the entropic trapping effect of configuration communities. This work clarifies the fine structure of the ground-state configuration space of random spin glass models, it also sheds light on the glassy behavior of hard-sphere colloidal systems at relatively high particle volume fraction.Comment: 26 pages, 9 figures, submitted to Journal of Statistical Mechanic

    On the freezing of variables in random constraint satisfaction problems

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    The set of solutions of random constraint satisfaction problems (zero energy groundstates of mean-field diluted spin glasses) undergoes several structural phase transitions as the amount of constraints is increased. This set first breaks down into a large number of well separated clusters. At the freezing transition, which is in general distinct from the clustering one, some variables (spins) take the same value in all solutions of a given cluster. In this paper we study the critical behavior around the freezing transition, which appears in the unfrozen phase as the divergence of the sizes of the rearrangements induced in response to the modification of a variable. The formalism is developed on generic constraint satisfaction problems and applied in particular to the random satisfiability of boolean formulas and to the coloring of random graphs. The computation is first performed in random tree ensembles, for which we underline a connection with percolation models and with the reconstruction problem of information theory. The validity of these results for the original random ensembles is then discussed in the framework of the cavity method.Comment: 32 pages, 7 figure

    The satisfiability threshold for random linear equations

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    Let AA be a random m×nm\times n matrix over the finite field FqF_q with precisely kk non-zero entries per row and let y∈Fqmy\in F_q^m be a random vector chosen independently of AA. We identify the threshold m/nm/n up to which the linear system Ax=yA x=y has a solution with high probability and analyse the geometry of the set of solutions. In the special case q=2q=2, known as the random kk-XORSAT problem, the threshold was determined by [Dubois and Mandler 2002, Dietzfelbinger et al. 2010, Pittel and Sorkin 2016], and the proof technique was subsequently extended to the cases q=3,4q=3,4 [Falke and Goerdt 2012]. But the argument depends on technically demanding second moment calculations that do not generalise to q>3q>3. Here we approach the problem from the viewpoint of a decoding task, which leads to a transparent combinatorial proof

    Geometrical organization of solutions to random linear Boolean equations

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    The random XORSAT problem deals with large random linear systems of Boolean variables. The difficulty of such problems is controlled by the ratio of number of equations to number of variables. It is known that in some range of values of this parameter, the space of solutions breaks into many disconnected clusters. Here we study precisely the corresponding geometrical organization. In particular, the distribution of distances between these clusters is computed by the cavity method. This allows to study the `x-satisfiability' threshold, the critical density of equations where there exist two solutions at a given distance.Comment: 20 page

    On the cavity method for decimated random constraint satisfaction problems and the analysis of belief propagation guided decimation algorithms

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    We introduce a version of the cavity method for diluted mean-field spin models that allows the computation of thermodynamic quantities similar to the Franz-Parisi quenched potential in sparse random graph models. This method is developed in the particular case of partially decimated random constraint satisfaction problems. This allows to develop a theoretical understanding of a class of algorithms for solving constraint satisfaction problems, in which elementary degrees of freedom are sequentially assigned according to the results of a message passing procedure (belief-propagation). We confront this theoretical analysis to the results of extensive numerical simulations.Comment: 32 pages, 24 figure
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