A Kernel Method for Positive 1-in-3-SAT

08/08/2018
by   Valentin Bura, et al.
0

This paper illustrates the power of Gaussian Elimination by adapting it to Positive 1-in-3-SAT. We derive a general kernelization method for this problem and thus obtain an upper bound for the complexity of its counting version of O(2kR 2^(1-k)R) for number of variables R and clauses-to-variables ratio k. Combining this method with previous results gives a time and space complexity for the counting problem of O(4/3|V|2^3|V|/8) and O(4/3|V|2^3|V|/16).

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/08/2018

Positive 1-in-3-SAT admits a non-trivial kernel

This paper illustrates the power of Gaussian Elimination by adapting it ...
research
12/15/2022

A Graphical #SAT Algorithm for Formulae with Small Clause Density

We study the counting version of the Boolean satisfiability problem #SAT...
research
06/08/2010

New worst upper bound for #SAT

The rigorous theoretical analyses of algorithms for #SAT have been propo...
research
03/20/2018

Sub-exponential Upper Bound for #XSAT of some CNF Classes

We derive an upper bound on the number of models for exact satisfiabilit...
research
05/17/2023

Function synthesis for maximizing model counting

Given a boolean formula Φ(X, Y, Z), the Max#SAT problem asks for finding...
research
09/11/2022

Nearly all k-SAT functions are unate

We prove that 1-o(1) fraction of all k-SAT functions on n Boolean variab...
research
05/23/2014

Understanding model counting for β-acyclic CNF-formulas

We extend the knowledge about so-called structural restrictions of #SAT ...

Please sign up or login with your details

Forgot password? Click here to reset