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Network science meets circuit theory: Kirchhoff index of a graph and the power of node-to-datum resistance matrix

机译:网络科学与电路理论相遇:图的基尔霍夫指数和节点对基准电阻矩阵的功效

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The emerging area of network science studies the properties of networks and dynamic processes on networks (such as spread of epidemics) that arises in a variety of applications including electrical, communication, internet, biological, ecological networks etc. Treating each element of a graph as a resistance, Kirchhoff index defined by the chemistry community is the sum of the effective resistances across all pairs of nodes of the graph. This index has been studied using the graph Laplacian (same as the indefinite admittance matrix). In this paper we present a simpler formula for Kirchhoff index based on the properties of the node-to-datum resistance matrix, considerably reducing the computational effort. A byproduct of this formula is a new invariant property of node-to-conductance matrix that does not depend on the choice of the datum node, extending the currently available knowledge on the determinant of the node-to-conductance matrix. Furthermore it can be shown that link congestion (if random-walk routing is used) can be estimated using the elements of the node-to-datum resistance matrix.
机译:网络科学的新兴领域研究网络的特性和网络上的动态过程(例如流行病的传播),这些过程在包括电气,通信,互联网,生物,生态网络等各种应用中产生。电阻,化学界定义的基尔霍夫指数是图上所有节点对的有效电阻之和。使用图拉普拉斯算子(与不定导纳矩阵相同)研究了该指数。在本文中,我们基于节点到基准电阻矩阵的特性,提出了一个更简单的Kirchhoff指数公式,大大减少了计算量。该公式的副产品是节点到电导矩阵的新不变性,它不依赖于基准节点的选择,从而扩展了关于节点到电导矩阵的行列式的现有知识。此外,可以证明,可以使用节点到基准电阻矩阵的元素来估计链路拥塞(如果使用随机行走路由)。

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