MPP Colloquium

Machine Learning Precision High Energy Physics

by Prof. Stefano Forte (Dipartimento di Fisica, Universita' di Milano, Italy)

MPI Meeting rooms

MPI Meeting rooms

The search for new physics at the shortest distance scales is currently moving from the energy frontier to the accuracy frontier. The need for ever more accurate theory prediction has led to the development of new theoretical, computational and modeling tools, many of which are exploiting methods and ideas from artificial intelligence. I will discuss specifically how, thanks to the use of these techniques, the determination of the structure of the proton has been turned from crude phenomenology into a statistically reliable methodology. I will give some examples of methods which have been used to produce results crucially used for the discovery of the Higgs boson, and discuss current frontier challenges and how they might be overcome thanks to machine learning techniques.