1,509 research outputs found
From one solution of a 3-satisfiability formula to a solution cluster: Frozen variables and entropy
A solution to a 3-satisfiability (3-SAT) formula can be expanded into a
cluster, all other solutions of which are reachable from this one through a
sequence of single-spin flips. Some variables in the solution cluster are
frozen to the same spin values by one of two different mechanisms: frozen-core
formation and long-range frustrations. While frozen cores are identified by a
local whitening algorithm, long-range frustrations are very difficult to trace,
and they make an entropic belief-propagation (BP) algorithm fail to converge.
For BP to reach a fixed point the spin values of a tiny fraction of variables
(chosen according to the whitening algorithm) are externally fixed during the
iteration. From the calculated entropy values, we infer that, for a large
random 3-SAT formula with constraint density close to the satisfiability
threshold, the solutions obtained by the survey-propagation or the walksat
algorithm belong neither to the most dominating clusters of the formula nor to
the most abundant clusters. This work indicates that a single solution cluster
of a random 3-SAT formula may have further community structures.Comment: 13 pages, 6 figures. Final version as published in PR
The decimation process in random k-SAT
Let F be a uniformly distributed random k-SAT formula with n variables and m
clauses. Non-rigorous statistical mechanics ideas have inspired a message
passing algorithm called Belief Propagation Guided Decimation for finding
satisfying assignments of F. This algorithm can be viewed as an attempt at
implementing a certain thought experiment that we call the Decimation Process.
In this paper we identify a variety of phase transitions in the decimation
process and link these phase transitions to the performance of the algorithm
Proving Looping and Non-Looping Non-Termination by Finite Automata
A new technique is presented to prove non-termination of term rewriting. The
basic idea is to find a non-empty regular language of terms that is closed
under rewriting and does not contain normal forms. It is automated by
representing the language by a tree automaton with a fixed number of states,
and expressing the mentioned requirements in a SAT formula. Satisfiability of
this formula implies non-termination. Our approach succeeds for many examples
where all earlier techniques fail, for instance for the S-rule from combinatory
logic
Glassy Behavior and Jamming of a Random Walk Process for Sequentially Satisfying a Constraint Satisfaction Formula
Random -satisfiability (-SAT) is a model system for studying
typical-case complexity of combinatorial optimization. Recent theoretical and
simulation work revealed that the solution space of a random -SAT formula
has very rich structures, including the emergence of solution communities
within single solution clusters. In this paper we investigate the influence of
the solution space landscape to a simple stochastic local search process {\tt
SEQSAT}, which satisfies a -SAT formula in a sequential manner. Before
satisfying each newly added clause, {\tt SEQSAT} walk randomly by single-spin
flips in a solution cluster of the old subformula. This search process is
efficient when the constraint density of the satisfied subformula is
less than certain value ; however it slows down considerably as
and finally reaches a jammed state at . The glassy dynamical behavior of {\tt SEQSAT} for probably is due to the entropic trapping of various communities in
the solution cluster of the satisfied subformula. For random 3-SAT, the jamming
transition point is larger than the solution space clustering
transition point , and its value can be predicted by a long-range
frustration mean-field theory. For random -SAT with , however, our
simulation results indicate that . The relevance of this
work for understanding the dynamic properties of glassy systems is also
discussed.Comment: 10 pages, 6 figures, 1 table, a mistake of numerical simulation
corrected, and new results adde
A quantum-walk-inspired adiabatic algorithm for graph isomorphism
We present a 2-local quantum algorithm for graph isomorphism GI based on an
adiabatic protocol. By exploiting continuous-time quantum-walks, we are able to
avoid a mere diffusion over all possible configurations and to significantly
reduce the dimensionality of the visited space. Within this restricted space,
the graph isomorphism problem can be translated into the search of a satisfying
assignment to a 2-SAT formula without resorting to perturbation gadgets or
projective techniques. We present an analysis of the execution time of the
algorithm on small instances of the graph isomorphism problem and discuss the
issue of an implementation of the proposed adiabatic scheme on current quantum
computing hardware.Comment: 10 pages, 5 figure
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