Probing the Structure of a Perfect Liquid Using Jets and Machine Learning

Aaron Angerami | 20-ERD-041

Executive Summary

To improve our understanding of quark-gluon plasma ("the perfect liquid"), we will develop a new particle reconstruction method that employs artificial intelligence and use it to analyze jet quenching data from relativistic heavy ion collisions. This research addresses Department of Energy goals in nuclear science and will expand our knowledge of the fundamental forces in nature and the properties of the early universe.

Publications, Presentations, and Patents

Angerami, A. and P. Karande. 2020. "Deep Learning for Pion Identification and Energy Calibration with the ATLAS Detector." CERN Document Server. LLNL-JRNL-813169