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arXiv 1306.2059math.PRmath.CO
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行列式及其在马尔可夫过程中的应用及基尔霍夫矩阵树定理的随机游动证明

Determinants, their applications to Markov processes, and a random walk proof of Kirchhoff's matrix tree theorem

Michael J. Kozdron, Larissa M. Richards, Daniel W. Stroock

摘要:

基尔霍夫矩阵树定理是一个著名的结果,它给出了一个公式的数量的支撑树在有限的,连通图在图形拉普拉斯矩阵。一个密切相关的结果是威尔逊的算法把均匀分布的集的生成树。我们将表明,当一个遵循格雷格劳勒的战略证明威尔逊的算法,基尔霍夫定理几乎立即适用于一些基本线性代数。我们还表明,同样的想法可以适用于其他有关的一般马尔可夫链和过程的有限状态空间的计算。

英文摘要:

Kirchhoff's matrix tree theorem is a well-known result that gives a formula for the number of spanning trees in a finite, connected graph in terms of the graph Laplacian matrix. A closely related result is Wilson's algorithm for putting the uniform distribution on the set of spanning trees. We will show that when one follows Greg Lawler's strategy for proving Wilson's algorithm, Kirchhoff's theorem follows almost immediately after one applies some elementary linear algebra. We also show that the same ideas can be applied to other computations related to general Markov chains and processes on a finite state space.

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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