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arXiv 0804.2343cs.DM
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具有常数颜色数的稀疏随机图着色的随机抽样

Random sampling of colourings of sparse random graphs with a constant number of colours

Charilaos Efthymiou, Paul G. Spirakis

摘要:

在这项工作中,我们提出了一个简单而有效的算法,它以很高的概率,提供了一个几乎均匀的样本,从一个稀疏随机图G(n,d/n),其中k=k(d)是一个足够大的常数适当的k-着色的集合。我们的算法不是基于马尔可夫链蒙特卡罗方法(M.C.M.C.)。相反,我们提供了一个新的证明我们的算法是基于有趣的“空间混合”性质的G(n,d/n)的着色的正确性。我们的结果改进了以前的结果(基于M.C.M.C.)这就要求颜色的数量随着n无限增长。

英文摘要:

In this work we present a simple and efficient algorithm which, with high probability, provides an almost uniform sample from the set of proper k-colourings on an instance of a sparse random graph G(n,d/n), where k=k(d) is a sufficiently large constant. Our algorithm is not based on the Markov Chain Monte Carlo method (M.C.M.C.). Instead, we provide a novel proof of correctness of our Algorithm that is based on interesting "spatial mixing" properties of colourings of G(n,d/n). Our result improves upon previous results (based on M.C.M.C.) that required a number of colours growing unboundedly with n.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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