Ricerc@Sapienza

Understanding the statistical properties of complex systems and of their predominant out-of-equilibrium dynamics is central to a large set of disparate fields, including statistical and high-energy physics, computer science, economy and finance, biology and ecology.
Spin-glasses and glass physics offer a prototypical example of complex systems where slow dynamics is originated by a complicated non-convex structure of the energy landscape. Their investigation led to a plethora of studies carrying multiple solid results about the intimate connection between the structure of the energy landscape and main traits of dynamical phenomenology, which can nowadays be applied to different systems characterized by slow dynamics and rough cost landscapes.
In recent years due to the emergence of new questions and applications, research on this topic has boomed showing the extent of the potentialities of theoretical physics approaches in the corresponding fields.
This project aims at making further steps in this direction in the different fields ranging from the prototypical example of spin glasses to modern applications in ecology, statistical models of learning and artificial neural networks, dynamics in quantum systems.