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    Wyświetlanie 1-6 z 6
    Tytuł:
    Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC
    Autorzy:
    Richter-Wąs, Elżbieta
    Pałka, Marek
    Topolnicki, Kacper
    Gil, Damian
    Współwytwórcy:
    Współautorami artykułu są członkowie ATLAS Collaboration w liczbie 2930
    Opis:
    Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to `fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
    Tytuł:
    Accuracy versus precision in boosted top tagging with the ATLAS detector
    Autorzy:
    Volkotrub, Yuriy
    Richter-Wąs, Elżbieta
    Gil, Damian
    Przygoda, Witold
    Topolnicki, Kacper
    Współwytwórcy:
    Współautorami artykułu są członkowie ATLAS Collaboration w liczbie 2906
    Opis:
    The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at $\sqrt{s}$ = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
    Tytuł:
    Modelling $Z \rightarrow \tau \tau$ processes in ATLAS with $\tau$-embedded $Z \rightarrow \mu \mu$ data
    Autorzy:
    Pałka, Marek
    Richter-Wąs, Elżbieta
    Współwytwórcy:
    Współautorami artykułu są członkowie ATLAS Collaboration w liczbie powyżej 2 tyś.
    Opis:
    This paper describes the concept, technical realisation and validation of a largely data-driven method to model events with $Z \to \tau\tau$ decays. In $Z \to \mu\mu$ events selected from proton-proton collision data recorded at $\sqrt{s}$ = 8 TeV with the ATLAS experiment at the LHC in 2012, the Z decay muons are replaced by $\tau$ leptons from simulated $Z \to \tau\tau$ decays at the level of reconstructed tracks and calorimeter cells. The $\tau$ lepton kinematics are derived from the kinematics of the original muons. Thus, only the well-understood decays of the Z boson and $\tau$ leptons as well as the detector response to the $\tau$ decay products are obtained from simulation. All other aspects of the event, such as the Z boson and jet kinematics as well as effects from multiple interactions, are given by the actual data. This so-called $\tau$-embedding method is particularly relevant for Higgs boson searches and analyses in $\tau\tau$ final states, where $Z \to \tau\tau$ decays constitute a large irreducible background that cannot be obtained directly from data control samples. In this paper, the relevant concepts are discussed based on the implementation used in the ATLAS Standard Model $H \to \tau\tau$ analysis of the full datataset recorded during 2011 and 2012.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
    Tytuł:
    Characterisation and mitigation of beam-induced backgrounds observed in the ATLAS detector during the 2011 proton-proton run
    Autorzy:
    Richter-Wąs, Elżbieta
    Współwytwórcy:
    Współautorami artykułu są członkowie ATLAS Collaboration w liczbie 2308
    Opis:
    This paper presents a summary of beam-induced backgrounds observed in the ATLAS detector and discusses methods to tag and remove background contaminated events in data. Trigger-rate based monitoring of beam-related backgrounds is presented. The correlations of backgrounds with machine conditions, such as residual pressure in the beam-pipe, are discussed. Results from dedicated beam-background simulations are shown, and their qualitative agreement with data is evaluated. Data taken during the passage of unpaired, i.e. non-colliding, proton bunches is used to obtain background-enriched data samples. These are used to identify characteristic features of beam-induced backgrounds, which then are exploited to develop dedicated background tagging tools. These tools, based on observables in the Pixel detector, the muon spectrometer and the calorimeters, are described in detail and their efficiencies are evaluated. Finally an example of an application of these techniques to a monojet analysis is given, which demonstrates the importance of such event cleaning techniques for some new physics searches.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
      Wyświetlanie 1-6 z 6

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