In the past 15 years, statistical physics has been successful as a framework for modelling
complex networks. On the theoretical side, this approach has unveiled a variety of physical …

In the past years, network theory has successfully characterized the interaction among the
constituents of a variety of complex systems, ranging from biological to technological, and …

A modern introduction to synchronization phenomena, this text presents recent discoveries
and the current state of research in the field, from low-dimensional systems to complex …

Homophily can put minority groups at a disadvantage by restricting their ability to establish
links with a majority group or to access novel information. Here, we show how this …

Simplicial complexes are generalized network structures able to encode interactions
occurring between more than two nodes. Simplicial complexes describe a large variety of …

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 …

Our ability to control complex systems is a fundamental challenge of contemporary science.
Recently introduced tools to identify the driver nodes, nodes through which we can achieve …

Sampling random graphs with given properties is a key step in the analysis of networks, as
random ensembles represent basic null models required to identify patterns such as …

In estimating the complexity of objects, in particular, of graphs, it is common practice to rely
on graph-and information-theoretic measures. Here, using integer sequences with …

Many natural and man-made complex dynamical systems can be represented by networks
with vertices representing system units and edges the coupling between vertices. If edges of …