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Counting Independent Sets in Hypergraphs

Published online by Cambridge University Press:  08 April 2014

JEFF COOPER ,
KUNAL DUTTA  and
DHRUV MUBAYI
JEFF COOPER
Affiliation:
Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, IL 60607, USA (e-mail: [email protected], [email protected])
KUNAL DUTTA
Affiliation:
Algorithms and Complexity Department, Max Planck Institute for Informatics, Saarbrücken, Germany (e-mail: [email protected])
DHRUV MUBAYI
Affiliation:
Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, IL 60607, USA (e-mail: [email protected], [email protected])
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Abstract

Let G be a triangle-free graph with n vertices and average degree t. We show that G contains at least

${\exp\biggl({1-n^{-1/12})\frac{1}{2}\frac{n}{t}\ln t} \biggl(\frac{1}{2}\ln t-1\biggr)\biggr)}$
independent sets. This improves a recent result of the first and third authors [8]. In particular, it implies that as n → ∞, every triangle-free graph on n vertices has at least ${e^{(c_1-o(1)) \sqrt{n} \ln n}}$ independent sets, where $c_1 = \sqrt{\ln 2}/4 = 0.208138 \ldots$. Further, we show that for all n, there exists a triangle-free graph with n vertices which has at most ${e^{(c_2+o(1))\sqrt{n}\ln n}}$ independent sets, where $c_2 = 2\sqrt{\ln 2} = 1.665109 \ldots$. This disproves a conjecture from [8].

Let H be a (k+1)-uniform linear hypergraph with n vertices and average degree t. We also show that there exists a constant ck such that the number of independent sets in H is at least

${\exp\biggl({c_{k} \frac{n}{t^{1/k}}\ln^{1+1/k}{t}\biggr})}.$
This is tight apart from the constant ck and generalizes a result of Duke, Lefmann and Rödl [9], which guarantees the existence of an independent set of size
$\Omega\biggl(\frac{n}{t^{1/k}} \ln^{1/k}t\biggr).$
 Both of our lower bounds follow from a more general statement, which applies to hereditary properties of hypergraphs.

Keywords

Primary 05D40Secondary 05C6505D05
Type
Paper
Information
Combinatorics, Probability and Computing , Volume 23 , Issue 4 , July 2014 , pp. 539 - 550
Copyright
Copyright © Cambridge University Press 2014 

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