Gonzalez-Sevilla, S. et al, Bernabeu Verdú, J., Civera, J. V., Garcia, C., Lacasta, C., Marco, R., et al. (2014). A double-sided silicon micro-strip Super-Module for the ATLAS Inner Detector upgrade in the High-Luminosity LHC. J. Instrum., 9, P02003–37pp.
Abstract: The ATLAS experiment is a general purpose detector aiming to fully exploit the discovery potential of the Large Hadron Collider (LHC) at CERN. It is foreseen that after several years of successful data-taking, the LHC physics programme will be extended in the so-called High-Luminosity LHC, where the instantaneous luminosity will be increased up to 5 x 10(34) cm(-2) s(-1). For ATLAS, an upgrade scenario will imply the complete replacement of its internal tracker, as the existing detector will not provide the required performance due to the cumulated radiation damage and the increase in the detector occupancy. The current baseline layout for the new ATLAS tracker is an all-silicon-based detector, with pixel sensors in the inner layers and silicon micro-strip detectors at intermediate and outer radii. The super-module is an integration concept proposed for the strip region of the future ATLAS tracker, where double-sided stereo silicon micro-strip modules are assembled into a low-mass local support structure. An electrical super-module prototype for eight double-sided strip modules has been constructed. The aim is to exercise the multi-module readout chain and to investigate the noise performance of such a system. In this paper, the main components of the current super-module prototype are described and its electrical performance is presented in detail.
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Diez, S. et al, Bernabeu Verdú, J., Civera, J. V., Garcia, C., Garcia-Argos, C., Lacasta, C., et al. (2014). A double-sided, shield-less stave prototype for the ATLAS Upgrade strip tracker for the High Luminosity LHC. J. Instrum., 9, P03012–16pp.
Abstract: A detailed description of the integration structures for the barrel region of the silicon strips tracker of the ATLAS Phase-II upgrade for the upgrade of the Large Hadron Collider, the so-called High Luminosity LHC (HL-LHC), is presented. This paper focuses on one of the latest demonstrator prototypes recently assembled, with numerous unique features. It consists of a shortened, shield-less, and double sided stave, with two candidate power distributions implemented. Thermal and electrical performances of the prototype are presented, as well as a description of the assembly procedures and tools.
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Brown, J. M. C., Dimmock, M. R., Gillam, J. E., & Paganin, D. M. (2014). A low energy bound atomic electron Compton scattering model for Geant4. Nucl. Instrum. Methods Phys. Res. B, 338, 77–88.
Abstract: A two-body fully relativistic three-dimensional scattering framework has been utilised to develop an alternative Compton scattering computational model to those adapted from Ribberfors' work for Monte Carlo modelling of Compton scattering. Using a theoretical foundation that ensures the conservation of energy and momentum in the relativistic impulse approximation, this new model, the Monash University Compton scattering model, develops energy and directional algorithms for both the scattered photon and ejected Compton electron from first principles. The Monash University Compton scattering model was developed to address the limitation of the Compton electron directionality algorithms of other computational models adapted from Ribberfors' work. Here the development of the Monash University Compton scattering model, including its implementation in a Geant4 low energy electromagnetic physics class, G4LowEPComptonModel, is outlined. Assessment of the performance of G4LowEPComptonModel was undertaken in two steps: (1) comparison with respect to the two standard Compton scattering classes of Geant4 version 9.5, G4LivermoreComptonModel and G4PenelopeComptonModel, and (2) experimental comparison with respect to Compton electron kinetic energy spectra obtained from the Compton scattering of 662 key photons off the K-shell of gold. Both studies illustrate that the Monash University Compton scattering model, and in turn G4LowEPComptonModel, is a viable replacement for the majority of computational models that have been adapted from Ribberfors' work. It was also shown that the Monash University Compton scattering model is able to reproduce the Compton scattering triply differential cross-section Compton electron kinetic energy spectra of 662 keV photons K-shell scattering off of gold to within experimental uncertainty.
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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 measurement of the ratio of the production cross sections for W and Z bosons in association with jets with the ATLAS detector. Eur. Phys. J. C, 74(12), 3168–31pp.
Abstract: The ratio of the production cross sections for W and Z bosons in association with jets has been measured in proton-proton collisions at root s = 7 TeV with the ATLAS experiment at the Large Hadron Collider. The measurement is based on the entire 2011 dataset, corresponding to an integrated luminosity of 4.6 fb(-1). Inclusive and differential cross-section ratios for massive vector bosons decaying to electrons and muons are measured in association with jets with transverse momentum p(T) > 30 GeV and jet rapidity vertical bar y vertical bar < 4.4. The measurements are compared to next-to-leading-order perturbative QCD calculations and to predictions from different Monte Carlo generators implementing leading-order matrix elements supplemented by parton showers.
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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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