Double-charming Higgs boson identification using machine-learning assisted jet shapes

Lenz, Alexander; Spannowsky, Michael; Tetlalmatzi-Xolocotzi, Gilberto

doi:10.1103/physrevd.97.016001

Double-charming Higgs boson identification using machine-learning assisted jet shapes

Lenz, Alexander; Spannowsky, Michael; Tetlalmatzi-Xolocotzi, Gilberto

Authors

Alexander Lenz

Professor Michael Spannowsky michael.spannowsky@durham.ac.uk
Director

Gilberto Tetlalmatzi-Xolocotzi

Abstract

We study the possibility of identifying a boosted resonance that decays into a charm pair against different sources of background using QCD event shapes, which are promoted to jet shapes. Using a set of jet shapes as input to a boosted decision tree, we find that observables utilizing the simultaneous presence of two charm quarks can access complementary information compared to approaches relying on two independent charm tags. Focusing on Higgs associated production with subsequent H → cc¯ decay and on a CP-odd scalar A with mA ≤ 10 GeV we obtain the limits BrðH → cc¯Þ ≤ 6.48% and BrðH → Að→ cc¯ÞZÞ ≤ 0.01% at 95% C.L.

Citation

Lenz, A., Spannowsky, M., & Tetlalmatzi-Xolocotzi, G. (2018). Double-charming Higgs boson identification using machine-learning assisted jet shapes. Physical Review D, 97(1), Article 016001. https://doi.org/10.1103/physrevd.97.016001

Journal Article Type	Article
Acceptance Date	Oct 12, 2017
Online Publication Date	Jan 9, 2018
Publication Date	Jan 9, 2018
Deposit Date	Jan 25, 2018
Publicly Available Date	Jan 25, 2018
Journal	Physical Review D
Print ISSN	2470-0010
Electronic ISSN	2470-0029
Publisher	American Physical Society
Peer Reviewed	Peer Reviewed
Volume	97
Issue	1
Article Number	016001
DOI	https://doi.org/10.1103/physrevd.97.016001

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