Dresden 2020 – scientific programme

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DY: Fachverband Dynamik und Statistische Physik

DY 58: Poster: Nonlinear Dynamics; Pattern Formation; Networks; Delay Systems; Synchronization

DY 58.14: Poster

Thursday, March 19, 2020, 15:00–18:00, P1C

An MCMC method to determine Complex Network properties — •Oskar Pfeffer — Potsdam Institute for Climate Impact Research

We apply the Markov Chain Monte Carlo (MCMC) algorithm Metropolis Hastings to sample graphs with specific properties. The generated networks are analysed using the measures of clustering and characteristic length that are used in literature to detect small world graphs. We show that optimizing these measures in a graph do not produce typical small world graphs.