A simple algorithm for random colouring G(n, d/n) using (2 + ε)d colours

Approximate random k-colouring of a graph G = (V, E) is a very well studied problem in computer science and statistical physics. It amounts to constructing a k-colouring of G which is distributed close to Gibbs distribution, i.e. the uniform distribution over all the k-colourings of G. Here, we deal with the problem when the underlying graph is an instance of Erdos-Renyi random graph G(n, p), where p = d/n and d is fixed. We propose a novel efficient algorithm for approximate random k-colouring with the following properties: given an instance of G(n, d/n) and for any k ≥ (2 + e)d, it returns a k-colouring distributed within total variation distance n−Ω(1) from the Gibbs distribution, with probability 1 − n−Ω(1). What we propose is neither a MCMC algorithm nor some algorithm inspired by the message passing heuristics that were introduced by statistical physicists. Our algorithm is of combinatorial nature. It is based on a rather simple recursion which reduces the random k-colouring of G(n, d/n) to random k-colouring simpler subgraphs first. The lower bound on the number of colours for our algorithm to run in polynomial time is significantly smaller than the corresponding bounds we have for any previous algorithm.

[1]  Elchanan Mossel,et al.  Gibbs rapidly samples colorings of G(n, d/n) , 2007, 0707.3241.

[2]  Eric Vigoda,et al.  Randomly coloring sparse random graphs with fewer colors than the maximum degree , 2006 .

[3]  Svante Janson,et al.  Random graphs , 2000, ZOR Methods Model. Oper. Res..

[4]  David Gamarnik,et al.  Counting without sampling: new algorithms for enumeration problems using statistical physics , 2006, SODA '06.

[5]  Andrea Montanari,et al.  Reconstruction and Clustering in Random Constraint Satisfaction Problems , 2011, SIAM J. Discret. Math..

[6]  M. Mézard,et al.  Survey propagation: An algorithm for satisfiability , 2005 .

[7]  Amin Coja-Oghlan,et al.  Algorithmic Barriers from Phase Transitions , 2008, 2008 49th Annual IEEE Symposium on Foundations of Computer Science.

[8]  G. Grimmett,et al.  On colouring random graphs , 1975 .

[9]  Brendan J. Frey,et al.  Factor graphs and the sum-product algorithm , 2001, IEEE Trans. Inf. Theory.

[10]  Mark Jerrum,et al.  The Markov chain Monte Carlo method: an approach to approximate counting and integration , 1996 .

[11]  A. Naor,et al.  The two possible values of the chromatic number of a random graph , 2005 .

[12]  Andrea Montanari,et al.  Gibbs states and the set of solutions of random constraint satisfaction problems , 2006, Proceedings of the National Academy of Sciences.

[13]  Paul G. Spirakis,et al.  Random sampling of colourings of sparse random graphs with a constant number of colours , 2008, Theor. Comput. Sci..