Interaction networks for the identification of boosted $H\ensuremath{\rightarrow}b\overline{b}$ decays

Open Access

Interaction networks for the identification of boosted $H \to b \bar{b}$ decays

Eric A. Moreno, Thong Q. Nguyen, Jean-Roch Vlimant, Olmo Cerri, Harvey B. Newman, Avikar Periwal, Maria Spiropulu, Javier M. Duarte, and Maurizio Pierini

Phys. Rev. D 102, 012010 – Published 28 July 2020

Abstract

We develop an algorithm based on an interaction network to identify high-transverse-momentum Higgs bosons decaying to bottom quark-antiquark pairs and distinguish them from ordinary jets that reflect the configurations of quarks and gluons at short distances. The algorithm’s inputs are features of the reconstructed charged particles in a jet and the secondary vertices associated with them. Describing the jet shower as a combination of particle-to-particle and particle-to-vertex interactions, the model is trained to learn a jet representation on which the classification problem is optimized. The algorithm is trained on simulated samples of realistic LHC collisions, released by the CMS Collaboration on the CERN Open Data Portal. The interaction network achieves a drastic improvement in the identification performance with respect to state-of-the-art algorithms.

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Received 10 December 2019
Accepted 13 June 2020

DOI:https://doi.org/10.1103/PhysRevD.102.012010

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.

Published by the American Physical Society