Identifying boosted objects with N-subjettiness

229

285

Machine learning based on convolutional neural networks can be used to study jet images from the LHC. Top tagging in fat jets offers a well-defined framework to establish our DeepTop approach and compare its performance to QCD-based top taggers. We first optimize a network architecture to identify top quarks in Monte Carlo simulations of the Standard Model production channel. Using standard fat jets we then compare its performance to a multivariate QCD-based top tagger. We find that both approaches lead to comparable performance, establishing convolutional networks as a promising new approach for multivariate hypothesis-based top tagging.

Section: Qcd-based Taggersmentioning

confidence: 99%

Deep-learning top taggers or the end of QCD?

Kasieczka

Plehn²,

Russell

et al. 2017

229

285

“…Since there are many observables associated with jets (angularities [23], broadening [24], jet shape [25], N-subjettiness [26], etc. ), one can generate a very large number of new tests of the NRQCD factorization formalism by applying jet physics techniques to the study of quarkonia produced within jets.…”

Section: Jhep11(2014)003mentioning

confidence: 99%

Probing quarkonium production mechanisms with jet substructure

Baumgart

Leibovich

Mehen

et al. 2014

We use fragmenting jet functions (FJFs) in the context of quarkonia to study the production channels predicted by NRQCD (We choose a set of FJFs that give the probability to find a quarkonium with a given momentum fraction inside a cone-algorithm jet with fixed cone size and energy. This observable gives several lever arms that allow one to distinguish different production channels. In particular, we show that at fixed momentum fraction the individual production mechanisms have distinct behaviors as a function of the the jet energy. As a consequence of this fact, we arrive at the robust prediction that if the depolarizing 1 S (8) 0 matrix element dominates, then the gluon FJF will diminish with increasing energy for fixed momentum fraction, z, and z > 0.5.

“…The produced leptons are indeed unlikely to be isolated, so that they could be captured by a selection involving the ratio of the electromagnetic to hadronic calorimetric deposits. Additionally, we also consider in our multivariate tagging technique the N -subjettiness variable τ 21 = τ 2 /τ 1 that allows one order to resolve the substructure of the ditau jet [74,75], with τ N being defined by…”

Section: Jhep05(2016)100mentioning

confidence: 99%

Investigating light NMSSM pseudoscalar states with boosted ditau tagging

Conte

Fuks

Guo

et al. 2016

We study a class of realizations of the Next-to-Minimal Supersymmetric Standard Model that is motivated by dark matter and Higgs data, and in which the lightest pseudoscalar Higgs boson mass is smaller than twice the bottom quark mass and greater than twice the tau lepton mass. In such scenarios, the lightest pseudoscalar Higgs boson can be copiously produced at the LHC from the decay of heavier superpartners and will dominantly further decay into a pair of tau leptons that is generally boosted. We make use of a boosted object tagging technique designed to tag such a ditau jet, and estimate the sensitivity of the LHC to the considered supersymmetric scenarios with 20 to 50 fb −1 of proton-proton collisions at a center-of-mass energy of 13 TeV.