36 research outputs found
On the random satisfiable process
In this work we suggest a new model for generating random satisfiable k-CNF
formulas. To generate such formulas -- randomly permute all 2^k\binom{n}{k}
possible clauses over the variables x_1, ..., x_n, and starting from the empty
formula, go over the clauses one by one, including each new clause as you go
along if after its addition the formula remains satisfiable. We study the
evolution of this process, namely the distribution over formulas obtained after
scanning through the first m clauses (in the random permutation's order).
Random processes with conditioning on a certain property being respected are
widely studied in the context of graph properties. This study was pioneered by
Ruci\'nski and Wormald in 1992 for graphs with a fixed degree sequence, and
also by Erd\H{o}s, Suen, and Winkler in 1995 for triangle-free and bipartite
graphs. Since then many other graph properties were studied such as planarity
and H-freeness. Thus our model is a natural extension of this approach to the
satisfiability setting.
Our main contribution is as follows. For m \geq cn, c=c(k) a sufficiently
large constant, we are able to characterize the structure of the solution space
of a typical formula in this distribution. Specifically, we show that typically
all satisfying assignments are essentially clustered in one cluster, and all
but e^{-\Omega(m/n)} n of the variables take the same value in all satisfying
assignments. We also describe a polynomial time algorithm that finds with high
probability a satisfying assignment for such formulas
Optimal Testing for Planted Satisfiability Problems
We study the problem of detecting planted solutions in a random
satisfiability formula. Adopting the formalism of hypothesis testing in
statistical analysis, we describe the minimax optimal rates of detection. Our
analysis relies on the study of the number of satisfying assignments, for which
we prove new results. We also address algorithmic issues, and give a
computationally efficient test with optimal statistical performance. This
result is compared to an average-case hypothesis on the hardness of refuting
satisfiability of random formulas
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's
We present an algorithm for recovering planted solutions in two well-known
models, the stochastic block model and planted constraint satisfaction
problems, via a common generalization in terms of random bipartite graphs. Our
algorithm matches up to a constant factor the best-known bounds for the number
of edges (or constraints) needed for perfect recovery and its running time is
linear in the number of edges used. The time complexity is significantly better
than both spectral and SDP-based approaches.
The main contribution of the algorithm is in the case of unequal sizes in the
bipartition (corresponding to odd uniformity in the CSP). Here our algorithm
succeeds at a significantly lower density than the spectral approaches,
surpassing a barrier based on the spectral norm of a random matrix.
Other significant features of the algorithm and analysis include (i) the
critical use of power iteration with subsampling, which might be of independent
interest; its analysis requires keeping track of multiple norms of an evolving
solution (ii) it can be implemented statistically, i.e., with very limited
access to the input distribution (iii) the algorithm is extremely simple to
implement and runs in linear time, and thus is practical even for very large
instances
Strong Refutation Heuristics for Random k-SAT
This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.A simple first moment argument shows that in a randomly chosen -SAT formula with clauses over boolean variables, the fraction of satisfiable clauses is as almost surely. In this paper, we deal with the corresponding algorithmic strong refutation problem: given a random -SAT formula, can we find a certificate that the fraction of satisfiable clauses is in polynomial time? We present heuristics based on spectral techniques that in the case and , and in the case and , find such certificates almost surely. In addition, we present heuristics for bounding the independence number (resp. the chromatic number) of random -uniform hypergraphs from above (resp. from below) for .Peer Reviewe
Random Constraint Satisfaction Problems
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 probability close to one due to non-constructive arguments. However, no
algorithms are known to find solutions efficiently with a non-vanishing
probability at even much lower densities. This fact appears to be related to a
phase transition in the set of all solutions. The goal of this extended
abstract is to provide a perspective on this phenomenon, and on the
computational challenge that it poses