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Electronic Colloquium on Computational Complexity

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Reports tagged with SAT:
TR03-054 | 2nd July 2003
Daniel Rolf

3-SAT in RTIME(O(1.32793^n)) - Improving Randomized Local Search by Initializing Strings of 3-Clauses

This paper establishes a randomized algorithm that finds a satisfying assignment for a satisfiable formula $F$ in 3-CNF in $O(1.32793^n)$ expected running time. The algorithms is based on the analysis of so-called strings, which are sequences of 3-clauses where non-succeeding clauses do not share a variable and succeeding clauses share ... more >>>

TR04-016 | 3rd March 2004
Michael Alekhnovich, Eli Ben-Sasson

Linear Upper Bounds for Random Walk on Small Density Random 3CNFs

We analyze the efficiency of the random walk algorithm on random 3CNF instances, and prove em linear upper bounds on the running time
of this algorithm for small clause density, less than 1.63. Our upper bound matches the observed running time to within a multiplicative factor. This is the ... more >>>

TR04-041 | 18th May 2004
Michael Alekhnovich, Edward Hirsch, Dmitry Itsykson

Exponential lower bounds for the running time of DPLL algorithms on satisfiable formulas

DPLL (for Davis, Putnam, Logemann, and Loveland) algorithms form the largest family of contemporary algorithms for SAT (the propositional satisfiability problem) and are widely used in applications. The recursion trees of DPLL algorithm executions on unsatisfiable formulas are equivalent to tree-like resolution proofs. Therefore, lower bounds for tree-like resolution (which ... more >>>

TR05-154 | 11th December 2005
Albert Atserias

Non-Uniform Hardness for NP via Black-Box Adversaries

We may believe SAT does not have small Boolean circuits.
But is it possible that some language with small circuits
looks indistiguishable from SAT to every polynomial-time
bounded adversary? We rule out this possibility. More
precisely, assuming SAT does not have small circuits, we
show that ... more >>>

TR06-094 | 29th July 2006
Parikshit Gopalan, Phokion G. Kolaitis, Elitza Maneva, Christos H. Papadimitriou

The Connectivity of Boolean Satisfiability: Computational and Structural Dichotomies

Revisions: 1

Boolean satisfiability problems are an important benchmark for questions about complexity, algorithms, heuristics and threshold phenomena. Recent work on heuristics, and the satisfiability threshold has centered around the structure and connectivity of the solution space. Motivated by this work, we study structural and connectivity-related properties of the space of solutions ... more >>>

TR12-027 | 29th March 2012
Eric Allender, Shiteng Chen, Tiancheng Lou, Periklis Papakonstantinou, Bangsheng Tang

Time-space tradeoffs for width-parameterized SAT:Algorithms and lower bounds

Revisions: 2

A decade has passed since Alekhnovich and Razborov presented an algorithm that solves SAT on instances $\phi$ of size $n$ having tree-width $TW(\phi)$, using time (and space) bounded by $2^{O(TW(\phi))}n^{O(1)}$. Although there have been several papers over the ensuing years building on the work of Alekhnovich and Razborov there has ... more >>>

TR13-097 | 25th June 2013
Mikolas Janota, Joao Marques-Silva

On Propositional QBF Expansions and Q-Resolution

Over the years, proof systems for propositional satisfiability (SAT)
have been extensively studied. Recently, proof systems for
quantified Boolean formulas (QBFs) have also been gaining attention.
Q-resolution is a calculus enabling producing proofs from
DPLL-based QBF solvers. While DPLL has become a dominating technique
for SAT, QBF has been tackled ... more >>>

TR14-031 | 16th February 2014
Joao Marques-Silva, Mikolas Janota

On the Query Complexity of Selecting Few Minimal Sets

Propositional Satisfiability (SAT) solvers are routinely used for
solving many function problems.

A natural question that has seldom been addressed is: what is the
best worst-case number of calls to a SAT solver for solving some
target function problem?

This paper develops tighter upper bounds on the query complexity of
more >>>

TR14-036 | 8th March 2014
Mikolas Janota, Leroy Chew, Olaf Beyersdorff

On Unification of QBF Resolution-Based Calculi

Revisions: 1

Several calculi for quantified Boolean formulas (QBFs) exist, but
relations between them are not yet fully understood.
This paper defines a novel calculus, which is resolution-based and
enables unification of the principal existing resolution-based QBF
calculi, namely Q-resolution, long-distance Q-resolution and the expansion-based
calculus ... more >>>

TR14-143 | 3rd November 2014
Ronald de Haan, Stefan Szeider

Compendium of Parameterized Problems at Higher Levels of the Polynomial Hierarchy

We present a list of parameterized problems together with a complexity classification of whether they allow a fixed-parameter tractable reduction to SAT or not. These parameterized problems are based on problems whose complexity lies at the second level of the Polynomial Hierarchy or higher. The list will be updated as ... more >>>

TR17-117 | 20th July 2017
Dmitry Itsykson, Alexander Knop

Hard satisfiable formulas for splittings by linear combinations

Itsykson and Sokolov in 2014 introduced the class of DPLL($\oplus$) algorithms that solve Boolean satisfiability problem using the splitting by linear combinations of variables modulo 2. This class extends the class of DPLL algorithms that split by variables. DPLL($\oplus$) algorithms solve in polynomial time systems of linear equations modulo two ... more >>>

TR18-115 | 11th June 2018
Valentine Kabanets, Zhenjian Lu

Satisfiability and Derandomization for Small Polynomial Threshold Circuits

A polynomial threshold function (PTF) is defined as the sign of a polynomial $p\colon\bool^n\to\mathbb{R}$. A PTF circuit is a Boolean circuit whose gates are PTFs. We study the problems of exact and (promise) approximate counting for PTF circuits of constant depth.

Satisfiability (#SAT). We give the first zero-error randomized algorithm ... more >>>

TR21-044 | 14th February 2021
Alexander Kulikov, Nikita Slezkin

SAT-based Circuit Local Improvement

Finding exact circuit size is a notorious optimization problem in practice. Whereas modern computers and algorithmic techniques allow to find a circuit of size seven in blink of an eye, it may take more than a week to search for a circuit of size thirteen. One of the reasons of ... more >>>

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