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Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a digital image of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p_T in the 1100-1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.
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In top quark production, the polarization of top quarks, decided by the chiral structure of couplings, is likely to be modified in the presence of any new physics contribution to the production. Hence the same is a good discriminator for those new physics models wherein the couplings have a chiral structure different than that in the Standard Model (SM). In this note we construct probes of the polarization of a top quark decaying hadronically, using easily accessible kinematic variables such as the energy fraction or angular correlations of the decay products. Tagging the boosted top quark using the usual jet sub structure technique we study robustness of these observables for a benchmark process, $W^{prime} to tb$. We demonstrate that the energy fraction of b-jet in the laboratory frame and a new angular variable, constructed by us in the top rest frame, are both very powerful tools to discriminate between the left and right polarized top quarks. Based on the polarization sensitive angular variables, we construct asymmetries which reflect the polarization. We study the efficiency of these variables for two new physics processes where which give rise to boosted top quarks: (i) decay of the top squark in the context of supersymmetry searches, and (ii) decays of the Kaluza-Klein(KK) graviton and KK gluon, in Randall Sundrum(RS) model. Remarkably, it is found that the asymmetry can vary over a wide range about +20% to -20%. The dependence of asymmetry on top quark couplings of the new particles present in these models beyond the SM (BSM) is also investigated in detail.
We address the potential of measurements with boosted single-top final states at the high-luminosity LHC (HL-LHC) and possible future hadron colliders: the high-energy LHC (HE-LHC), and the future circular collider (FCC). As new physics examples to assess the potential, we consider the search for $tbW$ anomalous couplings and for a weakly-coupled $W$ boson. The FCC would improve by a factor of two the sensitivity to anomalous couplings of the HL-LHC. For $W$ bosons, the FCC is sensitive to $W$ couplings $2-5$ times smaller than the HL-LHC in the mass range 2-4 TeV, and to masses up to 30 TeV in the case of Standard Model-like couplings.
The LHC searches for light compressed stop squarks have resulted in considerable bounds in the case where the stop decays to a neutralino and a charm quark. However, in the case where the stop decays to a neutralino, a bottom quark and two fermions via an off-shell W-boson, there is currently a significant unconstrained region in the stop-neutralino mass plane, still allowing for stop masses in the range 90-140 GeV. In this paper we propose a new monojet-like search for light stops, optimized for the four-body decay mode, in which at least one $b$-tagged jet is required. We show that, already by using the existing 8 TeV LHC data set, such a search would cover the entire unconstrained region. Moreover, in the process of validating our tools against an ATLAS monojet search, we show that the existing limit can be extended to exclude also stop masses below 100 GeV.
Top polarization is an important probe of new physics that couples to the top sector, and which may be discovered at the 14 TeV LHC. Taking the example of the MSSM, we argue that top polarization measurements can put a constraint on the soft supersymmetry breaking parameter A_t. In light of the recent discovery of a Higgs-like boson of mass ~125 GeV, a large A_t is a prediction of many supersymmetric models. To this end, we develop a *detector level* analysis methodology for extracting polarization information from hadronic tops using boosted jet substructure. We show that with 100 fb^(-1) of data, left and right 600 GeV stops can be distinguished to 4sigma, and 800 GeV stops can be distinguished to 3sigma.
We evaluate the phenomenological applicability of the dynamical grooming technique, introduced in [1], to boosted W and top tagging at LHC conditions. An extension of our method intended for multi-prong decays with an internal mass scale, such as the top quark decay, is presented. First, we tackle the reconstruction of the mass distribution of W and top jets quantifying the smearing due to pileup. When compared to state-of-the-art grooming algorithms like SoftDrop and its recursive version, dynamical grooming shows an enhanced resilience to background fluctuations. In addition, we asses the discriminating power of dynamical grooming to distinguish W (top) jets from QCD ones by performing a two-step analysis: introduce a cut on the groomed mass around the W (top) mass peak followed by a restriction on the N-subjettinnes ratio $tau_{21}$ ($tau_{32}$). For W jets, the out-of-the-box version of dynamical grooming, free of ad-hoc parameters, results into a comparable performance to SoftDrop. Regarding the top tagger efficiency, 3-prong dynamical grooming, in spite of its simplicity, presents better performance than SoftDrop and similar results to Recursive SoftDrop.
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