Papers › Polarization Fraction Measurement in same sign WW scattering using Deep Learning
Polarization Fraction Measurement in same sign WW scattering using Deep Learning
Junho Lee, Nicolas Chanon, Andrew Levin, Jing Li, Meng Lu, Qiang Li, Yajun Mao
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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
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