Signal mixture estimation for degenerate heavy Higgses using a deep neural network

If a new signal is established in future LHC data, a next question will be to determine the signal composition, in particular whether the signal is due to multiple near-degenerate states. We investigate the performance of a deep learning approach to signal mixture estimation for the challenging scen...

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Bibliographic Details
Published in:	The European physical journal. C, Particles and fields Vol. 78; no. 12; pp. 1 - 11
Main Authors:	Kvellestad, Anders, Maeland, Steffen, Strümke, Inga
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2018 Springer Springer Nature B.V SpringerOpen
Subjects:	Artificial neural networks Astronomy Astrophysics and Cosmology Bosons Elementary Particles Hadrons Heavy Ions Higgs bosons Machine learning Measurement Science and Instrumentation Neural networks Nuclear Energy Nuclear Physics Parameter estimation Physics Physics and Astronomy Quantum Field Theories Quantum Field Theory Regular Article - Experimental Physics String Theory
ISSN:	1434-6044, 1434-6052
Online Access:	Get full text
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