Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
167 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A novel weighting scheme for random $k$-SAT (1310.4303v1)

Published 16 Oct 2013 in cs.DM

Abstract: Consider a random $k$-CNF formula $F_{k}(n, rn)$ with $n$ variables and $rn$ clauses. For every truth assignment $\sigma\in {0, 1}{n}$ and every clause $c=\ell_{1}\vee\cdots\vee\ell_{k}$, let $d=d(\sigma, c)$ be the number of satisfied literal occurrences in $c$ under $\sigma$. For fixed $\beta>-1$ and $\lambda>0$, we take $\omega(\sigma, c)=0$, if $d=0$; $\omega(\sigma, c)=\lambda(1+\beta)$, if $d=1$ and $\omega(\sigma, c)=\lambda{d}$, if $d>1$. Applying the above weighting scheme, we get that if $F_{k}(n, rn)$ is unsatisfiable with probability tending to one as $n\rightarrow\infty$, then $r\geq2.83, 8.09, 18.91, 40.81, 84.87$ for $k=3, 4, 5, 6$ and $7,$ respectively.

Summary

We haven't generated a summary for this paper yet.