Rigorous results on the threshold network model
Norio Konno, Naoki Masuda, Rahul Roy, Anish Sarkar
Abstract
We analyze the threshold network model in which a pair of vertices with random weights are connected by an edge when the summation of the weights exceeds a threshold. We prove some convergence theorems and central limit theorems on the vertex degree, degree correlation, and the number of prescribed subgraphs. We also generalize some results in the spatially extended cases.
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