1,943 research outputs found

    Probing Higgs in Type III Seesaw at the LHC

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    We show that the type III seesaw mechanism opens up a promising possibility of searching the Higgs boson in the bbΛ‰b \bar b channel through the Higgs production associated with a charged lepton coming from the decay of the triplet seesaw particle. In particular we look for the 2b2b signals with trileptons or same-sign dileptons to construct the Higgs and the triplet fermion mass and calculate the reach with the integrated luminosity of 10 fbβˆ’1^{-1} at the 14 TeV LHC.Comment: 4 pages and 8 figure

    Infrared Safety of a Neural-Net Top Tagging Algorithm

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    Neural network-based algorithms provide a promising approach to jet classification problems, such as boosted top jet tagging. To date, NN-based top taggers demonstrated excellent performance in Monte Carlo studies. In this paper, we construct a top-jet tagger based on a Convolutional Neural Network (CNN), and apply it to parton-level boosted top samples, with and without an additional gluon in the final state. We show that the jet observable defined by the CNN obeys the canonical definition of infrared safety: it is unaffected by the presence of the extra gluon, as long as it is soft or collinear with one of the quarks. Our results indicate that the CNN tagger is robust with respect to possible mis-modeling of soft and collinear final-state radiation by Monte Carlo generators.Comment: 7 pages, 8 figures, final version to be published in JHE
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