All beauty, richness and harmony in the emergent dynamics of a complex system largely
depend on the specific way in which its elementary components interact. The last twenty-five …

Network science has evolved into an indispensable platform for studying complex systems.
But recent research has identified limits of classical networks, where links connect pairs of …

Complex networks have become the main paradigm for modelling the dynamics of
interacting systems. However, networks are intrinsically limited to describing pairwise …

Higher-order networks describe the many-body interactions of a large variety of complex
systems, ranging from the the brain to collaboration networks. Simplicial complexes are …

A deluge of new data on real-world networks suggests that interactions among system units
are not limited to pairs, but often involve a higher number of nodes. To properly encode …

Hypergraphs, encoding structured interactions among any number of system units, have
recently proven a successful tool to describe many real-world biological and social …

Complex networks represent the natural backbone to study epidemic processes in
populations of interacting individuals. Such a modeling framework, however, is naturally …

Previous efforts on data-based reconstruction focused on complex networks with pairwise or
two-body interactions. There is a growing interest in networks with higher-order or many …

The spontaneous emergence of patterns in nature, such as stripes and spots, can be
mathematically explained by reaction-diffusion systems. These patterns are often referred as …

ABSTRACT A potential issue of interest is figuring out how the combination of temporal and
higher-order interactions influences the collective dynamics of the brain, specifically …