Lund jet plane for Higgs tagging
Charanjit K. Khosa
SciPost Phys. Proc. 10, 011 (2022) · published 10 August 2022
- doi: 10.21468/SciPostPhysProc.10.011
- Submissions/Reports
Proceedings event
50th International Symposium on Multiparticle Dynamics
Abstract
We study the boosted Higgs tagging using the Lund jet plane. The convolutional neural network is used for the Lund images data set to classify hadronically decaying Higgs from the QCD background. We consider $H\to b \bar{b}$ and $H \to gg$ decay for moderate and high Higgs transverse momentum and compare the performance with the cut based approach using the jet color ring observable. The approach using Lund plane images provides good tagging efficiency for all the cases.
Cited by 2
Author / Affiliations: mappings to Contributors and Organizations
See all Organizations.- 1 Università degli Studi di Genova / University of Genoa [UniGe]
- 2 Istituto Nazionale di Fisica Nucleare Sezione di Genova / National Institute of Nuclear Physics Genoa Section [INFN Genova]
Funder for the research work leading to this publication
- Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR) (through Organization: Ministero dell'Istruzione, dell'Università e della Ricerca / Ministry of Education, Universities and Research [MIUR])