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

Lenz, Alexander and Spannowsky, Michael and Tetlalmatzi-Xolocotzi, Gilberto (2018) 'Double-charming Higgs boson identification using machine-learning assisted jet shapes.', Physical review D., 97 (1). 016001.


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.

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Publisher statement:Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.
Date accepted:12 October 2017
Date deposited:25 January 2018
Date of first online publication:09 January 2018
Date first made open access:25 January 2018

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