Coupled biological and chemical systems, neural networks, social interacting species, the
Internet and the World Wide Web, are only a few examples of systems composed by a large …

The availability of large data sets has allowed researchers to uncover complex properties
such as large-scale fluctuations and heterogeneities in many networks, leading to the …

Sparse non-Hermitian random matrices arise in the study of disordered physical systems
with asymmetric local interactions, and have applications ranging from neural networks to …

Many complex networks display strong heterogeneity in the degree (connectivity)
distribution. Heterogeneity in the degree distribution often reduces the average distance …

Dynamical organization of connection weights is studied in scale-free networks of chaotic
oscillators, where the coupling strength of a node from its neighbors develops adaptively …

What can we learn from the collective dynamics of a complex network about its interaction
topology? Taking the perspective from nonlinear dynamics, we briefly review recent …

In this work, we study the synchronization of coupled phase oscillators on the underlying
topology of scale-free networks. In particular, we assume that each network's component is …

While abrupt regime shifts between different metastable states have occurred in natural
systems from many areas including ecology, biology, and climate, evidence for this …

Revealing physical interactions in complex systems from observed collective dynamics
constitutes a fundamental inverse problem in science. Current reconstruction methods …

Limit cycle oscillators that are coupled in a pulsatile manner are referred to as pulse coupled
oscillators. In these oscillators, the interactions take the form of brief pulses such that the …