Article Dans Une Revue Physical Review D Année : 2019

Polarization fraction measurement in same-sign WW scattering using deep learning

Junho Lee
  • Fonction : Auteur
Andrew Levin
  • Fonction : Auteur
Jing Li
  • Fonction : Auteur
Meng Lu
  • Fonction : Auteur
Qiang Li
  • Fonction : Auteur
Yajun Mao
  • Fonction : Auteur

Résumé

Studying the longitudinally polarized fraction of W±W± scattering at the LHC is crucial to examine the unitarization mechanism of the vector boson scattering amplitude through Higgs and possible new physics. We apply here for the first time a deep neural network classification to extract the longitudinal fraction. Based on fast simulation implemented with the Delphes framework, significant improvement from a deep neural network is found to be achievable and robust over all dijet mass region. A conservative estimation shows that a high significance of four standard deviations can be reached with the High-Luminosity LHC designed luminosity of 3000  fb-1.

Dates et versions

hal-01975187 , version 1 (09-01-2019)

Identifiants

Citer

Junho Lee, Nicolas Chanon, Andrew Levin, Jing Li, Meng Lu, et al.. Polarization fraction measurement in same-sign WW scattering using deep learning. Physical Review D, 2019, 99 (3), pp.033004. ⟨10.1103/PhysRevD.99.033004⟩. ⟨hal-01975187⟩
90 Consultations
0 Téléchargements

Altmetric

Partager

  • More