arXiv subjects

I. Farkas

Publications and source records attributed to I. Farkas.

3 recordsLinked to original sources

arXiv2004

A Tractable Complex Network Model based on the Stochastic Mean-field Model of Distance

Much recent research activity has been devoted to empirical study and theoretical models of complex networks (random graphs) with three qualitative features: power-law degree distribution, local clustering of edges, and small diameter. We point out a new (in this context) platform for such models -- the stochastic mean-field model of distance -- and within this platform study a simple two-parameter proportional attachment model. The model is mathematicallly natural, permits a wide variety of explicit calculations, has the desired three qualitative features, and fits the complete range of degree scaling exponents and clustering parameters; in these respects it compares favorably to existing models.

cond-mat.dis-nn↗

arXiv2003

Networks in life: Scaling properties and eigenvalue spectra

We analyse growing networks ranging from collaboration graphs of scientists to the network of similarities defined among the various transcriptional profiles of living cells. For the explicit demonstration of the scale-free nature and hierarchical organization of these graphs, a deterministic construction is also used. We demonstrate the use of determining the eigenvalue spectra of sparse random graph models for the categorization of small measured networks.

cond-mat.stat-mech↗

arXiv2002

Critical Discussion of "Synchronized Flow", Simulation of Pedestrian Evacuation, and Optimization of Production Processes

We critically discuss the concept of ``synchronized flow'' from a historical, empirical, and theoretical perspective. Problems related to the measurement of vehicle data are highlighted, and questionable interpretations are identified. Moreover, we propose a quantitative and consistent theory of the empirical findings based on a phase diagram of congested traffic states, which is universal for all conventional traffic models having the same instability diagram and a fundamental diagram. New empirical and simulation data supporting this approach are presented as well. We also give a short overview of the various phenomena observed in panicking pedestrian crowds relevant from the point of evacuation of buildings, ships, and stadia. Some of these can be applied to the optimization of production processes, e.g. the ``slower-is-faster effect''.

cond-mat.stat-mech↗