Luigi MARANGIO : "Rigorous computational methods for understanding the statistical behavior of random dynamical systems"

PhD works of Luigi MARANGIO : "Rigorous computational methods for understanding the statistical behavior of random dynamical systems"

Abstract : In 2019 it has been estimated that the amount of digital data in the world is 40 zettabytes, 40 times the number of observable stars in the universe. Obviously providing an accurate estimate of this amount is impossible, but looking at our society, it is not difficult to imagine that it is so. Managing this amount of data and digital devices is a huge challenge for mankind, involving virtually every area of knowledge, from metallurgy to ethics. It arises spontaneously then, to wonder if, despite their intrinsic complexity, it is possible to understand, in some sense, the evolution of this type of complex systems. This question is naturally placed in the mathematical field, and one of the techniques currently used to model an observable phenomenon is to describe the evolution of a system through the evolution of a certain stochastic process, a random dynamical system. The purpose of this thesis is to try to answer the following question: given a random dynamical system, are we able to predict (not just simulate) its behavior in the long term?

Jury Composition : 

Christophe GUYEUX, PR1, Université Bourgogne Franche-Comté, PhD Director

Sandro VAIENTI, Full professor, Centre de Physique Theorique, UMR 7332 CNRS, Universite d’Aix- Marseille, Reporter

Wael BAHSOUN, Full professor, Loughborough University, Reporter

Stefano GALATOLO, Full professor, Università di Pisa, PhD co-director

Isaia NISOLI, Professeur, Universidad Federal do Rio de Janeiro, Examinateur

Localization :  IUT Belfort-Montbéliard 19, avenue du Maréchal Juin 90016 BELFORT - Room Amphithéâtre 4