The project "Study of dynamic transitions in complex networks: a functional multilayer approach, models and validation" coordinated with our collaborators at AlephSys (Universitat Rovira i Virgili, Tarragona) has got funding for the next three years.

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

The ClabB participates in 3 new funded networking projects, two at Spanish level and one at European level:

• Red temática: COMplejidad SOcio-TECnológica (COMSOTEC FIS2015-71795-REDT), coordinated by Josep Perelló.
• Red temática: Dinámica y sincronización en redes complejas (IBERSINC FIS2015-71929-REDT), coordinated by Alex Arenas.
• COST Action: Cooperation for Statistics of Network data science (OC-2015-1-19400), coordinated by Ernst Wit.

multiNetX is a python package for the manipulation and visualization of multilayer networks. It is builded on NetworkX (https://networkx.github.io/).

multiNetX allows for:

• Creating networks with weighted or unweighted links (only undirected networks are supported in this version)
• Analysing the spectral properties of adjacency or Laplacian matrices
• Visualizing dynamical processes by coloring the nodes and links accordingly

You  may download or clone the source code with the brief tutorial and examples from https://github.com/nkoub/multinetx

Felipe Montes joins the group for a short stay

Jan focuses his research in complex systems, aiming at describing emergent complexity, e.g. self-organization and bistability, using models inspired by non-equilibrium statistical physics. The goal is to build models that capture the essence of experimental or field-observed data, without resolving all microscopic detail. Systems he is currently interested in are self-organization of the convectively unstable atmosphere and extreme events, as well as ecology and evolution.

Two post-doctoral research associate positions (1+1 years) are available at the University of Barcelona to work on the field of complex networks/network science (read more).

Luce Prignano, former PhD student, joins the group as a postdoc of the EPNet project.

EPNet (Production and Distribution of Food during the Roman Empire: Economic and Political Dynamics) is an ERC Advanced Grant Project and intends to set up an innovative framework to investigate the political and economic mechanisms that characterized the dynamics of the commercial trade system during the Roman Empire.

She is a PhD student from the University of Brasilia. She joined the group to continue her studies urban transport and statistical physics.

Pol Colomer and Oleguer Sagarra joined the group as PhD students