Literature DB >> 14524921

Polynomial iterative algorithms for coloring and analyzing random graphs.

A Braunstein1, R Mulet, A Pagnani, M Weigt, R Zecchina.   

Abstract

We study the graph coloring problem over random graphs of finite average connectivity c. Given a number q of available colors, we find that graphs with low connectivity admit almost always a proper coloring whereas graphs with high connectivity are uncolorable. Depending on q, we find with a one-step replica-symmetry breaking approximation the precise value of the critical average connectivity c(q). Moreover, we show that below c(q) there exists a clustering phase c in [c(d),c(q)] in which ground states spontaneously divide into an exponential number of clusters. Furthermore, we extended our considerations to the case of single instances showing consistent results. This leads us to propose a different algorithm that is able to color in polynomial time random graphs in the hard but colorable region, i.e., when c in [c(d),c(q)].

Year:  2003        PMID: 14524921     DOI: 10.1103/PhysRevE.68.036702

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  2 in total

1.  Efficient supervised learning in networks with binary synapses.

Authors:  Carlo Baldassi; Alfredo Braunstein; Nicolas Brunel; Riccardo Zecchina
Journal:  Proc Natl Acad Sci U S A       Date:  2007-06-20       Impact factor: 11.205

2.  Perturbation biology: inferring signaling networks in cellular systems.

Authors:  Evan J Molinelli; Anil Korkut; Weiqing Wang; Martin L Miller; Nicholas P Gauthier; Xiaohong Jing; Poorvi Kaushik; Qin He; Gordon Mills; David B Solit; Christine A Pratilas; Martin Weigt; Alfredo Braunstein; Andrea Pagnani; Riccardo Zecchina; Chris Sander
Journal:  PLoS Comput Biol       Date:  2013-12-19       Impact factor: 4.475

  2 in total

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