ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Escobar, C., et al. (2011). Search for contact interactions in dimuon events from pp collisions at sqrt(s)=7 TeV with the ATLAS detector. Phys. Rev. D, 84(1), 011101–18pp.
Abstract: A search for contact interactions has been performed using dimuon events recorded with the ATLAS detector in proton-proton collisions at root s = 7 TeV. The data sample corresponds to an integrated luminosity of 42 pb(-1). No significant deviation from the standard model is observed in the dimuon mass spectrum, allowing the following 95% C. L. limits to be set on the energy scale of contact interactions: Lambda > 4: 9 TeV (4.5 TeV) for constructive (destructive) interference in the left-left isoscalar compositeness model. These limits are the most stringent to date for μμqq contact interactions.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Barranco Navarro, L., Cabrera Urban, S., Castillo Gimenez, V., Cerda Alberich, L., et al. (2016). A measurement of material in the ATLAS tracker using secondary hadronic interactions in 7 TeV p p collisions. J. Instrum., 11, P11020–41pp.
Abstract: Knowledge of the material in the ATLAS inner tracking detector is crucial in under-standing the reconstruction of charged-particle tracks, the performance of algorithms that identify jets containing b-hadrons and is also essential to reduce background in searches for exotic particles that can decay within the inner detector volume. Interactions of primary hadrons produced in pp collisions with the material in the inner detector are used to map the location and amount of this material. The hadronic interactions of primary particles may result in secondary vertices, which in this analysis are reconstructed by an inclusive vertex-finding algorithm. Data were collected using minimum-bias triggers by the ATLAS detector operating at the LHC during 2010 at centre-of-mass energy root s = 7 TeV, and correspond to an integrated luminosity of 19 nb(-1). Kinematic properties of these secondary vertices are used to study the validity of the modelling of hadronic interactions in simulation. Secondary-vertex yields are compared between data and simulation over a volume of about 0.7m(3) around the interaction point, and agreement is found within overall uncertainties.
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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., 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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ATLAS Collaboration(Aad, G. et al), Bernabeu Verdu, J., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fassi, F., et al. (2014). Operation and performance of the ATLAS semiconductor tracker. J. Instrum., 9, P08009–73pp.
Abstract: The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74 +/- 0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, delta-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations.
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