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 …

Over the past two decades, complex network theory provided the ideal framework for
investigating the intimate relationships between the topological properties characterizing the …

Higher-order networks have emerged as a powerful framework to model complex systems
and their collective behavior. Going beyond pairwise interactions, they encode structured …

Gathering events, eg, going to gyms and meetings, are ubiquitous and crucial in the
spreading phenomena, which induce higher-order interactions, and thus can be described …

Real-world networks often consist of millions of heterogenous elements that interact at
multiple timescales and length scales. The fields of statistical physics and control theory both …

Simplicial complexes capture the underlying network topology and geometry of complex
systems ranging from the brain to social networks. Here we show that algebraic topology is a …

Percolation establishes the connectivity of complex networks and is one of the most
fundamental critical phenomena for the study of complex systems. On simple networks …

Understanding how the interplay between higher-order and multilayer structures of
interconnections influences the synchronization behaviors of dynamical systems is a …