Meccanica Statistica, Complessità e applicazioni interdisciplinari

Research Meccanica Statistica, Complessità e applicazioni interdisciplinari

In its original meaning, Statistical Mechanics is the science that, starting from the microscopic knowledge of a system, aims at deriving, theoretically (paper and pen) its macroscopic, i.e. thermodynamic, properties, using a probabilistic approach. Nowadays, however, the refined techniques developed in a century in this field are increasingly used to describe systems in different fields, not necessarily pertinent to Physics in a strict sense. Therefore, today Statistical Mechanics deals with problems ranging from cybernetics, to biology, to social sciences, as well as, of course, to many sectors of Physics.

In the Physics Department of the University of Salerno, within the scope of Statistical Mechanics, there are numerous lines of research among which, as an example, we mention the followings:

  • Out of equilibrium systems. Equilibrium is the condition that is usually reached by a system if it is not perturbed from the outside. For the description of this state, Statistical Mechanics – thanks to the founding work mainly due to L. Boltzmann, J.W. Gibbs, and others – is a complete and consistent theory. The same is not true for non-equilibrium systems, although much progress has been made recently. Given the diffusion and importance of out-of-equilibrium systems (the universe itself is a notable example), the study of these systems represents an important research field. (For more information contact prof. F. Corberi, E-mail:
  • Studies on the brain and neural networks. The recent development of neuroscience has shown the similarity between the functioning of the brain and that of some models of physical systems studied by statistical mechanics. This has opened the way on the one hand to the interpretation of cognitive processes occurring in the brain, and on the other hand to the implementation of synthetic neural networks for the development of artificial intelligence. (For more information contact prof. S. Scarpetta, E-mail:
  • Big Data Analysis. In recent years, the possibility of storing large amounts of data (Big Data) has posed the important problem of analyzing this mass of information, from which to extrapolate the characteristics of interest for the problem under consideration. This task can be undertaken using techniques borrowed from Statistical Mechanics. An important example is that of the analysis of health data, which today are collected in large quantities by medical institutions and pharmaceutical companies, in order to optimize patient care and management. (For more information contact prof. P. Cavallo, E-mail:


CAVALLO PierpaoloMember
CORBERI FedericoMember
SCARPETTA SilviaMember