Search for Exotic Higgs Boson Decays to Merged Diphotons

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A Novel CMS Analysis Using End-to-End Deep Learning, Springer Theses

ISBN: 3031250931
ISBN 13: 9783031250934
Autor: Andrews, Michael
Verlag: Springer Verlag GmbH
Umfang: xiii, 188 S., 10 s/w Illustr., 77 farbige Illustr., 188 p. 87 illus., 77 illus. in color.
Erscheinungsdatum: 03.03.2024
Auflage: 1/2024
Produktform: Kartoniert
Einband: Kartoniert
Artikelnummer: 2830091 Kategorie:

Beschreibung

Autorenporträt

Michael Andrews completed his Ph.D. in Physics at Carnegie Mellon University where he was involved with the CMS collaboration at the Large Hadron Collider at CERN. He worked at CERN in Geneva, Switzerland, from 2015 to 2019 where he served as Run Coordinator for the CMS electromagnetic calorimeter group. For his distinguished service to CMS detector operations, he received the CMS Achievement Award in 2018.Michaels physics research focuses on the application advanced deep learning techniques to problems in LHC physics. He played a leading role in the development of deep learning algorithms trained directly on low-level detector data, so-called end-to-end physics reconstruction. His work on end-to-end physics reconstruction led to the first CMS results demonstrating the breakthrough potential of this technique over traditional methods for the reconstruction of boosted decays to highly merged photons. For his contributions, summarized in his Ph.D. thesis, he was awardedthe CMS Ph.D. Thesis Award in 2021.

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Springer Verlag GmbH
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E-Mail: juergen.hartmann@springer.com

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