Networks and graphs are the most general mathematical description of a set of elements connected pairwise by a relation. Therefore, it is not surprising that graph theory has been successfully
applied to a wide range of very different disciplines, from physics to biology, to social science, computing, psychology, economy and chemistry.
In recent times, physicists have been mainly interested in networks as models of complex
systems and they have used them to describe condensed matter structures such as disordered materials, glasses, polymers, biomolecules. More recently, Networks have become the main language for the description of communication networks, webs, social and economic systems, power grids, statistical models of algorithms, and many others interdisciplinary frameworks.
The function of networks in physics, however, is not purely descriptive. Geometry and
topology have a deep influence on the physical properties of complex systems. The Network structure can indeed affect the dynamical and thermodynamical behaviour of the system it describes, and can give rise to surprising collective effects.
In Parma, we are studying at the moment dynamical models for synchronization on neural networks in collaboration with the University of Granada and models for the evolution of social networks and for epidemics spreading, in collaboration with the MoBS Labs at Boston Northeastern University, with the Institute for Scientific Interchange in Torino, and with several theoretical and experimental groups in Italy, Europe and the United States.