Subcritical percolation on networks
Dane Taylor
Applied Mathematics, University of Colorado Boulder
Date and time:
Thursday, February 17, 2011 - 4:30pm
Abstract:
Percolation on networks has applications ranging from epidemic and information spreading to system robustness. Extending previous results restricted to directed or Markovian networks, we introduce a general theory for predicting the percolation threshold based on an analysis of the network adjacency matrix. In addition to its applicability for networks with non-Markovian statistics, our method is easily implemented when the adjacency matrix is known. We illustrate our theory with various examples.