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arXiv 1709.02674math.COcs.DS
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幂律度序列随机图的均匀生成

Uniform generation of random graphs with power-law degree sequences

Pu Gao, Nicholas Wormald

摘要:

我们给出了一个线性时间算法,该算法近似一致地生成一个具有幂律度序列的随机单图,其指数至少为2.8811。虽然对指数至少为3的幂律度序列的图进行采样是相当容易的,并且许多采样器在这种情况下有效地工作,但当指数下降到3以下时,问题变得更加困难;我们是这种情况下第一个可证明可行的采样器。我们还表明,适当的拒绝计划,我们的算法可以调整到一个精确的均匀采样器。精确采样器的运行时间是O(n^{4.081}),在大概率情况下是O(n^{2.107})。

英文摘要:

We give a linear-time algorithm that approximately uniformly generates a random simple graph with a power-law degree sequence whose exponent is at least 2.8811. While sampling graphs with power-law degree sequence of exponent at least 3 is fairly easy, and many samplers work efficiently in this case, the problem becomes dramatically more difficult when the exponent drops below 3; ours is the first provably practicable sampler for this case. We also show that with an appropriate rejection scheme, our algorithm can be tuned into an exact uniform sampler. The running time of the exact sampler is O(n^{2.107}) with high probability, and O(n^{4.081}) in expectation.

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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