This project is devoted to the study of causal influences in time-signals from model systems that could be useful in physics, systems biology and the study of social behaviours.
It is based on the application of methods from Stochastic Thermodynamics to the study of irreversibility and causality in signals emerging from complex systems, within the general scheme of Information Thermodynamics.
Objective of the project is the study of measures of causal influence associated to data-driven modelling, effective Langevin equations, fluctuation-dissipation relations, entropy production and information fluxes.
Modelling the non-equilibrium behaviour of complex systems in terms of information flows is a recent, innovative trend of theoretical physics, which has a great potential of unifying methods from the study of mesoscopic systems with the theory of information processing. The theoretical work we propose here could also critically contribute to the comprehension of several methods in contemporary bayesian data analysis and artificial intelligence, that are nowadays massively used, often with the assumption that (in the Big Data era) there is no need for models.
The proponents of this project have deep, methodological and critical interests both in non equilibrium statistical mechanics and complex and biological systems. Moreover, they had and have, customarily, friendly intellectual and professional exchanges of ideas and concepts.
AC has a long experience on the study of disordered and non equilibrium systems, such as glasses, spin glasses and system with a small number of degrees of freedom. At the present the main topics of research in this field are the extension of Fluctuation Theorems to aging systems and an information theory approach to Gene Regulatory Networks.
AG teaches computational biophysics and data analysis (genetics and molecular biology) and is actually active in the computational biology of genomic information (codon bias), bioinformatics and stochastic thermodynamics.
AV teaches non equilibrium statistical mechanics and mathematical methods for physics and had a long and militant career in equilibrium and non-equilibrium statistical physics, dynamical systems, stochastic processes and transport phenomena in complex systems, always with a deep attention to the foundational and methodological aspects.
There are then good premises that this project would emerge in a successful one.