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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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Poley, L., Blue, A., Bloch, I., Buttar, C., Fadeyev, V., Fernandez-Tejero, J., et al. (2019). Mapping the depleted area of silicon diodes using a micro-focused X-ray beam. J. Instrum., 14, P03024–14pp.
Abstract: For the Phase-II Upgrade of the ATLAS detector at CERN, the current ATLAS Inner Detector will be replaced with the ATLAS Inner Tracker (ITk). The ITk will be an all-silicon detector, consisting of a pixel tracker and a strip tracker. Sensors for the ITk strip tracker are required to have a low leakage current up to bias voltages of 500V to maintain a low noise and power dissipation. In order to minimise sensor leakage currents, particularly in the high-radiation environment inside the ATLAS detector, sensors are foreseen to be operated at low temperatures and to be manufactured from wafers with a high bulk resistivity of several k Omega.cm. Simulations showed the electric field inside sensors with high bulk resistivity to extend towards the sensor edge, which could lead to increased surface currents for narrow dicing edges. In order to map the electric field inside biased silicon sensors with high bulk resistivity, three diodes from ATLAS silicon strip sensor prototype wafers were studied with a monochromatic, micro-focused X-ray beam at the Diamond Light Source (Didcot, U.K.). For all devices under investigation, the electric field inside the diode was mapped and its dependence on the applied bias voltage was studied.
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., et al. (2019). Resolution of the ATLAS muon spectrometer monitored drift tubes in LHC Run 2. J. Instrum., 14, P09011–35pp.
Abstract: The momentum measurement capability of the ATLAS muon spectrometer relies fundamentally on the intrinsic single-hit spatial resolution of the monitored drift tube precision tracking chambers. Optimal resolution is achieved with a dedicated calibration program that addresses the specific operating conditions of the 354 000 high-pressure drift tubes in the spectrometer. The calibrations consist of a set of timing offsets and drift time to drift distance transfer relations, and result in chamber resolution functions. This paper describes novel algorithms to obtain precision calibrations from data collected by ATLAS in LHC Run 2 and from a gas monitoring chamber, deployed in a dedicated gas facility. The algorithm output consists of a pair of correction constants per chamber which are applied to baseline calibrations, and determined to be valid for the entire ATLAS Run 2. The final single-hit spatial resolution, averaged over 1172 monitored drift tube chambers, is 81.7 +/- 2.2 μm.
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Ahlburg, P. et al, & Marinas, C. (2020). EUDAQ – a data acquisition software framework for common beam telescopes. J. Instrum., 15(1), P01038–30pp.
Abstract: EUDAQ is a generic data acquisition software developed for use in conjunction with common beam telescopes at charged particle beam lines. Providing high-precision reference tracks for performance studies of new sensors, beam telescopes are essential for the research and development towards future detectors for high-energy physics. As beam time is a highly limited resource, EUDAQ has been designed with reliability and ease-of-use in mind. It enables flexible integration of different independent devices under test via their specific data acquisition systems into a top-level framework. EUDAQ controls all components globally, handles the data flow centrally and synchronises and records the data streams. Over the past decade, EUDAQ has been deployed as part of a wide range of successful test beam campaigns and detector development applications.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., et al. (2022). Operation and performance of the ATLAS semiconductor tracker in LHC Run 2. J. Instrum., 17(1), P01013–56pp.
Abstract: The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules. During Run 2 (2015-2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb(-1) to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector. Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2. It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%. Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules. '
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