Deep Learning for Higgs Boson Identification and Searches for New Physics at the Large Hadron Collider

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Mark Neubauer from the University of Illinois

In this video from the Blue Waters Symposium, Mark Neubauer from the University of Illinois presents: Deep Learning for Higgs Boson Identification and Searches for New Physics at the Large Hadron Collider.

The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. As the world’s most powerful particle collider, the Large Hadron Collider (LHC) represents a huge step forward in this quest. The 2012 discovery of the Higgs boson demonstrates the great scientific value of the LHC and the Higgs particle itself represents a new tool for discovery. In this talk, we present our work using deep learning techniques on the Blue Waters supercomputing to develop and optimize a novel method of identifying the decays of highly-boosted Higgs bosons produced at the LHC a signature of new particles and/or phenomena at the energy frontier of particle physics. We also discuss our ongoing work using Blue Waters to develop scalable cyberinfrastructure for sustainable and reproducible data analysis workflows through the NSF-funded IRIS-HEP Institute and SCAILFIN project.

Professor Mark Neubauer received his Ph.D from the University of Pennsylvania (2001). After receiving his Ph.D, he worked as a postdoctoral research associate at the Massachusetts Institute of Technology (2001-2004) and the University of California, San Diego (2004-2007). Professor Neubauer joined the faculty at the University of Illinois in Fall 2007.

Professor Neubauer is an experimental physicist whose research has spanned a diverse set of topics in the study of elementary particles and their interactions. The ultimate goal of this pursuit is to gain a deeper understanding of Nature at its most fundamental level and to elucidate the physics that lies beyond the standard model.

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