Year: 2019
Type: article
Abstract: Measuring longitudinally polarized vector boson scattering in the ZZ channel is a promising way to investigate unitarity restoration with the Higgs mechanism and to search for possible new physics. We investigated several deep neural network structures and compared their ability to improve the measurement of the longitudinal fraction ${\mathrm{Z}}_{\mathrm{L}}{\mathrm{Z}}_{\mathrm{L}}$. Using fast simulation with the Delphes framework, a clear improvement is found using a previously investigated ``particle-based'' deep neural network on a preprocessed dataset and applying principle component analysis to the outputs. A significance of around 1.7 standard deviations can be achieved with the integrated luminosity of $3000\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ that will be recorded at the High-Luminosity LHC. The technique developed in this article is also useful to other LHC analyses involving helicity fraction measurement.
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Awards: G2591070845, G6756483702, G8567866377
OpenAlex ID: W2969005229