Organized by: Prof. Lu Lu
Finding Neutrinos: Advancing Neutrino Detection, Reconstruction, and Analysis
Date: Monday, February 24th
Time: 4:00 pm - 5:00 pm
Place: 5280 CH &
Speaker: Dr. Jessica Micallef, Institute for Artificial Intelligence and Fundamental Interactions
Abstract: Neutrino oscillation, or flavor changing between the neutral leptons, has indicated that neutrinos do not fit as perfectly into the Standard Model puzzle as they were first predicted. Improving measurements of neutrino oscillation and properties are important to help us better understand the Standard Model, and thus how these fundamental particles influence our universe. To successfully complete their goals, future experiments aiming to make decisive measurements need results from the new technology and methods used by current experiments and prototypes. Machine Learning (ML) is one such tool that particle physics has begun to employ that can tackle new challenges facing neutrino experiments. I will discuss how my work with ML will help the success of one of the largest, future neutrino physics experiments--the Deep Underground Neutrino Experiment.
Host: Sridhara Dasu
Add this event to your calendar