A central goal of our research has been to understand how spatially
distributed systems can exhibit behavioral homogeneity even though the
systems themselves are spatially heterogeneous. Think of heart cells
beating together, a power grid operating in sync, agents trying to
reach consensus, and so on. It is widely held that individual entities
in such systems are more likely to exhibit the same behavior if they
are equal or similar. Yet, recent research by our group and others
shows that this assumption is generally false when the entities
interact with each other through a network, and this counterintuitive
result can be rigorously established in the rapidly developing area of
network synchronization.

In this presentation, I will discuss the role of different forms of
disorder in inhibiting and promoting synchronization, where the latter
is a line of research that is now flourishing. In particular, I will
comment on scenarios in which interacting entities can keep pace with
each other only when they are suitably different, and thus the
observed behavior is homogeneous only when the system itself is
not. This reveals situations in which consensus, coherence, or
synchronization is observed because of (not despite)
differences. Examples will be given of theoretical predictions and
experimental observations of this effect for networks of
optoelectronic, electromechanical, and electrochemical entities as
well as power generators and chaotic circuits, among others. Since
individual differences are ubiquitous and often unavoidable in real
systems, such parameter mismatches can serve as an unexpected (and
still essentially unexplored) source of behavioral homogeneity.