Percolation of a strongly connected component in simple directed random graphs with a given degree distribution

We study site and bond percolation on directed simple random graphs with a given degree distribution and derive the expressions for the critical value of the percolation probability above which the giant strongly connected component emerges and the fraction of vertices in this component

Percolation of a strongly connected component in simple directed random graphs with a given degree distribution

We study site and bond percolation on directed simple random graphs with a given degree distribution and derive the expressions for the critical value of percolation probability above which the giant strongly connected component emerges and the fraction of vertices in this component

Fast sequential algorithm for generating directed random graphs with a given degree sequence

We propose a near-linear complexity algorithm for generating simple directed random graphs with a given degree sequence and show that this algorithm provides a means of uniform sampling for large graphs. The algorithm is applicable when the maximum degree, dmax, is asymptotically dominated by m1/4 with m being the number of edges and admits an implementation with the expected running time of the order of mdmax

Percolation of a strongly connected component in simple directed random graphs with a given degree distribution

We study site and bond percolation on directed simple random graphs with a given degree distribution and derive the expressions for the critical value of percolation probability above which the giant strongly connected component emerges and the fraction of vertices in this component

Fast sequential algorithm for generating directed random graphs with a given degree sequence

We propose a near-linear complexity algorithm for generating simple directed random graphs with a given degree sequence and show that this algorithm provides a means of uniform sampling for large graphs. The algorithm is applicable when the maximum degree, dmax, is asymptotically dominated by m1/4 with m being the number of edges and admits an implementation with the expected running time of the order of mdmax