Artificial Intelligence and Machine Learning in Physics

Morten Hjorth-Jensen
Data e ora: 
Martedì, 17 Ottobre, 2023 - 14:45
Sala Conferenze

In this talk I will attempt at giving an overview, through selected examples, on how Machine Learning (and AI based approaches) can aid in analysing problems in physics, from the classification of events in experiments to the solution of quantum mechanical many-body problems, where deep learning methods provide a promising strategy for studying complicated interacting systems. In particular,  since this talk is also meant to honor and celebrate Professor Marcello Baldo, I will also discuss some recent studies of strong pairing correlations related to the BCS-BEC crossover region near unitarity using deep learning methods.

This Colloquium is part of the Festschrift Celebrating Dr Marcello Baldo's 8oth Birthday, organized by INFN Sez. Catania.

Professor Morten Hjorth-Jensen is a theoretical physicist with a strong interest in computational physics and many-body theory in general, and the nuclear many-body problem and nuclear structure problems in particular. He studies various methods for solving either Schrödinger's equation or Dirac's equation for many interacting particles, spanning from algorithmic aspects to the mathematical properties of such methods. The latter also leads to a strong interest in computational physics as well as computational aspects of quantum mechanical methods ranging from traditional many-body methods to quantum computing and machine learning.