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Planting Colourings Silently

Part of: Graph theory

Published online by Cambridge University Press:  07 December 2016

VICTOR BAPST ,
AMIN COJA-OGHLAN  and
CHARILAOS EFTHYMIOU
VICTOR BAPST
Affiliation:
Mathematics Institute, Goethe University, 10 Robert Mayer St, Frankfurt 60325, Germany (e-mail: bapst@math.uni-frankfurt.de, acoghlan@math.uni-frankfurt.de, efthymiou@math.uni-frankfurt.de)
AMIN COJA-OGHLAN
Affiliation:
Mathematics Institute, Goethe University, 10 Robert Mayer St, Frankfurt 60325, Germany (e-mail: bapst@math.uni-frankfurt.de, acoghlan@math.uni-frankfurt.de, efthymiou@math.uni-frankfurt.de)
CHARILAOS EFTHYMIOU
Affiliation:
Mathematics Institute, Goethe University, 10 Robert Mayer St, Frankfurt 60325, Germany (e-mail: bapst@math.uni-frankfurt.de, acoghlan@math.uni-frankfurt.de, efthymiou@math.uni-frankfurt.de)
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Abstract

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Let k ⩾ 3 be a fixed integer and let Zk (G) be the number of k-colourings of the graph G. For certain values of the average degree, the random variable Zk (G(n, m)) is known to be concentrated in the sense that $\tfrac{1}{n}(\ln Z_k(G(n,m))-\ln\Erw[Z_k(G(n,m))])$ converges to 0 in probability (Achlioptas and Coja-Oghlan, Proc. FOCS 2008). In the present paper we prove a significantly stronger concentration result. Namely, we show that for a wide range of average degrees, $\tfrac{1}{\omega}(\ln Z_k(G(n,m))-\ln\Erw[Z_k(G(n,m))])$ converges to 0 in probability for any diverging function $\omega=\omega(n)\ra\infty$ . For k exceeding a certain constant k 0 this result covers all average degrees up to the so-called condensation phase transitiond k,con , and this is best possible. As an application, we show that the experiment of choosing a k-colouring of the random graph G(n,m) uniformly at random is contiguous with respect to the so-called ‘planted model’.

MSC classification

Primary: 05C80: Random graphs
Secondary: 05C15: Coloring of graphs and hypergraphs

Information

Type
Paper
Information
Combinatorics, Probability and Computing , Volume 26 , Issue 3 , May 2017 , pp. 338 - 366
Copyright
Copyright © Cambridge University Press 2016 

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