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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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fassi, F., Ferrer, A., et al. (2014). Monitoring and data quality assessment of the ATLAS liquid argon calorimeter. J. Instrum., 9, P07024–55pp.
Abstract: The liquid argon calorimeter is a key component of the ATLAS detector installed at the CERN Large Hadron Collider. The primary purpose of this calorimeter is the measurement of electron and photon kinematic properties. It also provides a crucial input for measuring jets and missing transverse momentum. An advanced data monitoring procedure was designed to quickly identify issues that would affect detector performance and ensure that only the best quality data are used for physics analysis. This article presents the validation procedure developed during the 2011 and 2012 LHC data-taking periods, in which more than 98% of the proton-proton luminosity recorded by ATLAS at a centre-of-mass energy of 7-8 TeV had calorimeter data quality suitable for physics analysis.
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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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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2015). Identification of beauty and charm quark jets at LHCb. J. Instrum., 10, P06013–29pp.
Abstract: Identification of jets originating from beauty and charm quarks is important for measuring Standard Model processes and for searching for new physics. The performance of algorithms developed to select b- and c-quark jets is measured using data recorded by LHCb from proton-proton collisions at root s = 7TeV in 2011 and at root s = 8TeV in 2012. The efficiency for identifying a b (c) jet is about 65%(25%) with a probability for misidentifying a light-parton jet of 0.3% for jets with transverse momentum pT > 20GeV and pseudorapidity 2 : 2 < eta < 4.2. The dependence of the performance on the pT and eta of the jet is also measured.
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Garonna, A., Amaldi, U., Bonomi, R., Campo, D., Degiovanni, A., Garlasche, M., et al. (2010). Cyclinac medical accelerators using pulsed C6+/H-2(+) ion sources. J. Instrum., 5, C09004–19pp.
Abstract: Charged particle therapy, or so-called hadrontherapy, is developing very rapidly. There is large pressure on the scientific community to deliver dedicated accelerators, providing the best possible treatment modalities at the lowest cost. In this context, the Italian research Foundation TERA is developing fast-cycling accelerators, dubbed 'cyclinacs'. These are a combination of a cyclotron (accelerating ions to a fixed initial energy) followed by a high gradient linac boosting the ions energy up to the maximum needed for medical therapy. The linac is powered by many independently controlled klystrons to vary the beam energy from one pulse to the next. This accelerator is best suited to treat moving organs with a 4D multipainting spot scanning technique. A dual proton/carbon ion cyclinac is here presented. It consists of an Electron Beam Ion Source, a superconducting isochronous cyclotron and a high-gradient linac. All these machines are pulsed at high repetition rate (100-400 Hz). The source should deliver both C6+ and H-2(+) ions in short pulses (1.5 μs flat-top) and with sufficient intensity (at least 10(8) fully stripped carbon ions per pulse at 300 Hz). The cyclotron accelerates the ions to 120 MeV/u. It features a compact design (with superconducting coils) and a low power consumption. The linac has a novel C-band high-gradient structure and accelerates the ions to variable energies up to 400 MeV/u. High RF frequencies lead to power consumptions which are much lower than the ones of synchrotrons for the same ion extraction energy. This work is part of a collaboration with the CLIC group, which is working at CERN on high-gradient electron-positron colliders.
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