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.
|
Rebel, B., Hall, C., Bernard, E., Faham, C. H., Ito, T. M., Lundberg, B., et al. (2014). High voltage in noble liquids for high energy physics. J. Instrum., 9, T08004–57pp.
Abstract: A workshop was held at Fermilab November 8-9, 2013 to discuss the challenges of using high voltage in noble liquids. The participants spanned the fields of neutrino, dark matter, and electric dipole moment physics. All presentations at the workshop were made in plenary sessions. This document summarizes the experiences and lessons learned from experiments in these fields at developing high voltage systems in noble liquids.
|
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.
|
NEXT Collaboration(Lorca, D. et al), Martin-Albo, J., Laing, A., Ferrario, P., Gomez-Cadenas, J. J., Alvarez, V., et al. (2014). Characterisation of NEXT-DEMO using xenon K-alpha X-rays. J. Instrum., 9, P10007–20pp.
Abstract: The NEXT experiment aims to observe the neutrinoless double beta decay of Xe-136 in a high-pressure xenon gas TPC using electroluminescence (EL) to amplify the signal from ionization. Understanding the response of the detector is imperative in achieving a consistent and well understood energy measurement. The abundance of xenon K-shell X-ray emission during data taking has been identified as a multitool for the characterisation of the fundamental parameters of the gas as well as the equalisation of the response of the detector. The NEXT-DEMO prototype is a similar to 1.5 kg volume TPC filled with natural xenon. It employs an array of 19 PMTs as an energy plane and of 256 SiPMs as a tracking plane with the TPC light tube and SiPM surfaces being coated with tetraphenyl butadiene (TPB) which acts as a wavelength shifter for the VUV scintillation light produced by xenon. This paper presents the measurement of the properties of the drift of electrons in the TPC, the effects of the EL production region, and the extraction of position dependent correction constants using K-alpha X-ray deposits. These constants were used to equalise the response of the detector to deposits left by gammas from Na-22.
|
Sorel, M. (2014). Expected performance of an ideal liquid argon neutrino detector with enhanced sensitivity to scintillation light. J. Instrum., 9, P10002–25pp.
Abstract: Scintillation light is used in liquid argon (LAr) neutrino detectors to provide a trigger signal, veto information against cosmic rays, and absolute event timing. In this work, we discuss additional opportunities offered by detectors with enhanced sensitivity to scintillation light, that is with light collection efficiencies of about 10(-3). We focus on two key detector performance indicators for neutrino oscillation physics: calorimetric neutrino energy reconstruction and neutrino/antineutrino separation in a non-magnetized detector. Our results are based on detailed simulations, with neutrino interactions modelled according to the GENIE event generator, while the charge and light responses of a large LAr ideal detector are described by the Geant4 and NEST simulation tools. A neutrino energy resolution as good as 3.3% RMS for 4 GeV electron neutrino charged-current interactions can in principle be obtained in a large detector of this type, by using both charge and light information. By exploiting muon capture in argon and scintillation light information to veto muon decay electrons, we also obtain muon neutrino identification efficiencies of about 50%, and muon antineutrino misidentification rates at the few percent level, for few-GeV neutrino interactions that are fully contained. We argue that the construction of large LAr detectors with sufficiently high light collection efficiencies is in principle possible.
|
