Complex and Co-evolving Networks

Focus Session: Complex and Co-evolving Networks

 

During the APS March Meeting

February 27 - March 2

Boston, Massachusetts

 

Traditional statistical mechanics deals with interacting particle systems that can either be described by an ordered interaction topology (crystals) or random interactions embedded in the three dimensional continuum, approachable by differential equations. In these cases the complex behavior arises from nonlinearity and nonlocality of the interactions. There is, however, a large class of systems called complex networks, in which the interactions are mediated not necessarily by a continuum, or a regular structure but by a complex graph, whose structure may evolve as part of the dynamics of the interactions themselves. Accordingly, collective phenomena appearing in complex networks can be fundamentally different from those observed in classical materials and systems. This Focus Session will feature some of the latest advancements in understanding collective phenomena in complex networks including critical phenomena, random processes on networks, stochastic synchronization, flow optimization, routing, load balancing, failure cascades and flow control.

An important aspect that will be explored is the behavior of co-evolving networks. Networks are not static but rather evolve continuously in response to underlying endogenous exogenous forces. Furthermore, networks do not live in isolation as they are interlinked either by sharing edger or through a multitude of interdependencies to transport and store various entities, including materials, energy, information and people across vastly varying spatial and temporal scales. Through this coupling, changes in one network or in a dynamical process cause changes in all interdependent networks. It is vital to consider co-evolution and interdependency on which the processes of interest unfold. In recent years, however, most of the work considered only a single snapshot of the network as the input and paid little attention to the networks’ evolutionary process over time. The objective of this session is to present recent work in the definition of formal models and the appropriate mathematical and statistical tools aimed at understanding and characterizing the properties of information flow, evolution, and co-evolution of networks.

Important Dates:

 

Abstract Submission: Nov. 11, 2011

 

Organizers:

Bruno Goncalves
Indiana University
Nicola Perra
Indiana University

Zoltan Toroczkai
University of Notre Dame