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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., Fiorini, L., et al. (2012). Measurement of the b-hadron production cross section using decays to D*(+)mu X- final states in pp collisions at root s=7 TeV with the ATLAS detector. Nucl. Phys. B, 864(3), 341–381.
Abstract: The b-hadron production cross section is measured with the ATLAS detector in pp collisions at root s = 7 TeV, using 3.3 pb(-1) of integrated luminosity, collected during the 2010 LHC run. The b-hadrons are selected by partially reconstructing D*(+)mu X- final states. Differential cross sections are measured as functions of the transverse momentum and pseudorapidity. The measured production cross section for a b-hadron with p(T) > 9 GeV and vertical bar eta vertical bar < 2.5 is 32.7 +/- 0.8(stat.)(-6.8)(+4.5)(syst.) μb, higher than the next-to-leading-order QCD predictions but consistent within the experimental and theoretical uncertainties.
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ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Escobar, C., et al. (2011). Measurement of the inclusive isolated prompt photon cross-section in pp collisions at sqrt(s)=7 TeV using 35 pb(-1) of ATLAS data. Phys. Lett. B, 706(2-3), 150–167.
Abstract: A measurement of the differential cross-section for the inclusive production of isolated prompt photons in pp collisions at a center-of-mass energy sqrt(s) = 7 TeV is presented. The measurement covers the pseudorapidity ranges vertical bar eta vertical bar < 1.37 and 1.52 <= vertical bar eta vertical bar < 2.37 in the transverse energy range 45 <= E(T) < 400 GeV. The results are based on an integrated luminosity of 35 pb(-1), collected with the ATLAS detector at the LHC. The yields of the signal photons are measured using a data-driven technique, based on the observed distribution of the hadronic energy in a narrow cone around the photon candidate and the photon selection criteria. The results are compared with next-to-leading order perturbative QCD calculations and found to be in good agreement over four orders of magnitude in cross-section.
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fernandez Martinez, P., et al. (2015). Modelling Z -> ττ processes in ATLAS with τ-embedded Z -> μμ data. J. Instrum., 10, P09018–41pp.
Abstract: This paper describes the concept, technical realisation and validation of a largely data-driven method to model events with Z -> tau tau decays. In Z -> μμevents selected from proton-proton collision data recorded at root s = 8 TeV with the ATLAS experiment at the LHC in 2012, the Z decay muons are replaced by tau leptons from simulated Z -> 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 -> 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 -> tau tau analysis of the full datataset recorded during 2011 and 2012.
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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fassi, F., Ferrer, A., et al. (2013). Characterisation and mitigation of beam-induced backgrounds observed in the ATLAS detector during the 2011 proton-proton run. J. Instrum., 8, P07004–72pp.
Abstract: 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.
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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., Fiorini, L., et al. (2014). A neural network clustering algorithm for the ATLAS silicon pixel detector. J. Instrum., 9, P09009–34pp.
Abstract: A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.
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