Jet substructure techniques study the internal dynamics of a jet and play an important role in the broad physics programme at the LHC. This talk will focus on jet substructure techniques applied to the tagging of boosted objects. As an introduction, we will motivate the use of such an approach and discuss a few applications. We will describe the first generation of taggers based on basic principles in QCD. We will then compare those with more modern tools based on Deep Learning techniques. Finally, we will discuss how dedicated jet substructure measurements connect with boosted jet tagging applications. Each aspect will be covered from both the experimental and theoretical viewpoints.
Chris Delitzsch recently started an Emmy Noether Young Independent Research Group at the TU Dortmund University working on the ATLAS experiment. Her research focusses on jet substructure measurements and improvements to jet reconstruction. She obtained her PhD working on the (in)famous 2 TeV diboson excess in Run 1 and then joined the University of Arizona as a post-doc where she continued to work on jet reconstruction and coordinated the Jet Substructure and Tagging Group between 2017 and 2019 and the Jet/Etmiss group from 2019 - 2021.
Clemens Lange is a scientist at Paul Scherrer Institute (PSI), Switzerland working on the CMS experiment. He has performed several analyses using jet substructure techniques with a focus on searches for heavy resonances in diboson final states. He led one of the CMS new physics search groups from 2019-2021 and has previously also contributed to the development and calibration of jet substructure algorithms. Currently, Clemens is deputy coordinator of the CMS Data Preservation and Open Access group and also convener of the newly created CMS Common Analysis Tools group.
Gregory Soyez is a theoretical physicist working on perturbative QCD. His main topics of interest include jet physics and parton showers. He is working at the IPhT (CEA Saclay) since 2010 and currently visiting CERN until the end of August 2023.