Science of glasses, phase transitions, and applications from inference to learning.

by Chiara Cammarota (King's College London)

Monday 1 Apr 2019, 16:00 → 18:00 Europe/Rome

Aula Conversi (Dipartimento di Fisica - Ed. G.Marconi)

The realm of statistical mechanics has been recently enlarged to be able to describe systems, such as glass forming materials, where structural disorder plays the predominant role. As a result of this effort, new phase transitions and new static and dynamic universality classes have been revealed. Interestingly the spectrum of applications of these new physical concepts goes much beyond the wide scope of condensed matter and extends, among others, to the currently booming field of data science. In this colloquium I will focus on the challenge of signal-reconstruction from noisy background, ubiquitous in the fields of inference and learning. By leveraging tools and ideas from glass physics, I will show how we can describe, predict, and enhance the performances of algorithms introduced to tackle it.