PoS - Proceedings of Science
Volume 372 - Artificial Intelligence for Science, Industry and Society (AISIS2019) - Day 1
Portraying Double Higgs at the Large Hadron Collider
M. Kim, J. Kim, K.C. Kong,* K.T. Matchev, M. Park
*corresponding author
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Pre-published on: July 10, 2020
Published on:
Abstract
We examine the discovery potential for double Higgs production at the high luminosity LHC in the final state with two b-tagged jets, two leptons and missing transverse momentum. Although this dilepton final state has been considered a difficult channel due to the large backgrounds, we argue that it is possible to obtain a sizable signal significance, by adopting a deep learning framework making full use of the relevant kinematics along with the jet images from the Higgs decay. The proposed method can be easily generalized to the semi-leptonic channel of double Higgs production, as well as to other processes with similar final states.
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