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arXiv · 1812.07591

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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Abstract

Studying the longitudinally polarized fraction of $W^\pm W^\pm$ 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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Junho Lee, Nicolas Chanon, Andrew Levin, Jing Li, Meng Lu, Qiang Li, Yajun Mao. 2018-12-18. Polarization fraction measurement in same-sign WW scattering using deep learning. https://doi.org/10.1103/physrevd.99.033004

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