Recent research has demonstrated that Machine Learning (ML) is very good at detecting patterns and automatically understanding the relationship between covariates. In many ways, these tasks appear in some steps of the scientific method and therefore in physics. In fact, recently ML has been applied to both symbolic regression (i.e., discovering new equations), experimental data analysis (i.e. highlighting patterns) and in simulations. In this seminar, I will cover the basics of ML, some applications of ML in physics, and an overview of how we plan to exploit ML in the LEGEND200 experiment.
Meeting ID: 860 6301 6721