Interaction networks for the identification of boosted HbbH \rightarrow b\overline{b} decays

Sep 26, 2019
18 pages
Published in:
  • Phys.Rev.D 102 (2020) 1, 012010
  • Published: Jul 29, 2020
e-Print:
DOI:
Report number:
  • FERMILAB-PUB-19-492-CMS-E

Citations per year

2019202120232025202505101520
Abstract: (APS)
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.
Note:
  • 20 pages, 8 figures, 6 tables, version published in PRD
  • Particle Physics Experiments
  • p p: scattering
  • Higgs particle: hadronic decay
  • showers: jet
  • quark antiquark: pair
  • bottom: pair production
  • bottom: particle identification
  • quark: hadronization
  • vertex: secondary
  • network