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AGATA Collaboration(Akkoyun, S. et al), Algora, A., Barrientos, D., Domingo-Pardo, C., Egea, F. J., Gadea, A., et al. (2012). AGATA-Advanced GAmma Tracking Array. Nucl. Instrum. Methods Phys. Res. A, 668, 26–58.
Abstract: The Advanced GAmma Tracking Array (AGATA) is a European project to develop and operate the next generation gamma-ray spectrometer. AGATA is based on the technique of gamma-ray energy tracking in electrically segmented high-purity germanium crystals. This technique requires the accurate determination of the energy, time and position of every interaction as a gamma ray deposits its energy within the detector volume. Reconstruction of the full interaction path results in a detector with very high efficiency and excellent spectral response. The realisation of gamma-ray tracking and AGATA is a result of many technical advances. These include the development of encapsulated highly segmented germanium detectors assembled in a triple cluster detector cryostat, an electronics system with fast digital sampling and a data acquisition system to process the data at a high rate. The full characterisation of the crystals was measured and compared with detector-response simulations. This enabled pulse-shape analysis algorithms, to extract energy, time and position, to be employed. In addition, tracking algorithms for event reconstruction were developed. The first phase of AGATA is now complete and operational in its first physics campaign. In the future AGATA will be moved between laboratories in Europe and operated in a series of campaigns to take advantage of the different beams and facilities available to maximise its science output. The paper reviews all the achievements made in the AGATA project including all the necessary infrastructure to operate and support the spectrometer.
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AGATA Collaboration(Crespi, F. C. L. et al), & Gadea, A. (2013). Response of AGATA segmented HPGe detectors to gamma rays up to 15.1 MeV. Nucl. Instrum. Methods Phys. Res. A, 705, 47–54.
Abstract: The response of AGATA segmented HPGe detectors to gamma rays in the energy range 2-15 MeV was measured. The 15.1 MeV gamma rays were produced using the reaction d(B-11,n gamma)C-12 at E-beam=19.1 MeV, while gamma rays between 2 and 9 MeV were produced using an Am-Be-Fe radioactive source. The energy resolution and linearity were studied and the energy-to-pulse-height conversion resulted to be linear within 0.05%.Experimental interaction multiplicity distributions are discussed and compared with the results of Geant4 simulations. It is shown that the application of gamma-ray tracking allows a suppression of background radiation caused by n-capture in Ge nuclei. Finally the Doppler correction for the 15.1 MeV gamma line, performed using the position information extracted with Pulse-shape analysis is discussed.
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LHCb Collaboration(Aaij, R. et al), Jaimes Elles, S. J., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Rebollo De Miguel, M., et al. (2024). Curvature-bias corrections using a pseudomass method. J. Instrum., 19(3), P03010–22pp.
Abstract: Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy root s = 13 TeV during 2016, 2017 and 2018. The biases are determined using Z -> mu(+)mu(-) decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10(-4) GeV-1 level, improves the Z -> mu(+)mu(-) mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass.
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Identification of charm jets at LHCb. J. Instrum., 17(2), P02028–23pp.
Abstract: The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement.
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Barranco Navarro, L., Cabrera Urban, S., Castillo Gimenez, V., Cerda Alberich, L., et al. (2016). Beam-induced and cosmic-ray backgrounds observed in the ATLAS detector during the LHC 2012 proton-proton running period. J. Instrum., 11, P05013–78pp.
Abstract: This paper discusses various observations on beam-induced and cosmic-ray backgrounds in the ATLAS detector during the LHC 2012 proton-proton run. Building on published results based on 2011 data, the correlations between background and residual pressure of the beam vacuum are revisited. Ghost charge evolution over 2012 and its role for backgrounds are evaluated. New methods to monitor ghost charge with beam-gas rates are presented and observations of LHC abort gap population by ghost charge are discussed in detail. Fake jets from colliding bunches and from ghost charge are analysed with improved methods, showing that ghost charge in individual radio-frequency buckets of the LHC can be resolved. Some results of two short periods of dedicated cosmic-ray background data-taking are shown; in particular cosmic-ray muon induced fake jet rates are compared to Monte Carlo simulations and to the fake jet rates from beam background. A thorough analysis of a particular LHC fill, where abnormally high background was observed, is presented. Correlations between backgrounds and beam intensity losses in special fills with very high beta* are studied.
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ATLAS Collaboration(Aaboud, M. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Barranco Navarro, L., Cabrera Urban, S., et al. (2019). Electron and photon energy calibration with the ATLAS detector using 2015-2016 LHC proton-proton collision data. J. Instrum., 14, P03017–60pp.
Abstract: This paper presents the electron and photon energy calibration obtained with the ATLAS detector using about 36 fb(-1) of LHC proton-proton collision data recorded at root s = 13 TeV in 2015 and 2016. The different calibration steps applied to the data and the optimization of the reconstruction of electron and photon energies are discussed. The absolute energy scale is set using a large sample of Z boson decays into electron-positron pairs. The systematic uncertainty in the energy scale calibration varies between 0.03% to 0.2% in most of the detector acceptance for electrons with transverse momentum close to 45 GeV. For electrons with transverse momentum of 10 GeV the typical uncertainty is 0.3% to 0.8% and it varies between 0.25% and 1% for photons with transverse momentum around 60 GeV. Validations of the energy calibration with J/psi -> e(+)e(-) decays and radiative Z boson decays are also presented.
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ATLAS Collaboration(Aad, G. et al), Aikot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2024). Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data. J. Instrum., 19(2), P02009–58pp.
Abstract: This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton -proton collision data recorded at -Js = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z -boson decays into electron -positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z -boson decays, 0.4% at ET – 10 GeV, and 0.3% at ET – 1 TeV; for photons at ET <^>' 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using .11tfr -, ee and radiative Z -boson decays.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). Event reconstruction for KM3NeT/ORCA using convolutional neural networks. J. Instrum., 15(10), P10005–39pp.
Abstract: The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.
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ATLAS Tile Calorimeter System(Abdallah, J. et al), Ferrer, A., Fiorini, L., Hernandez Jimenez, Y., Higon-Rodriguez, E., Ruiz-Martinez, A., et al. (2016). The Laser calibration of the ATLAS Tile Calorimeter during the LHC run 1. J. Instrum., 11, T10005–29pp.
Abstract: This article describes the Laser calibration system of the ATLAS hadronic Tile Calorimeter that has been used during the run 1 of the LHC. First, the stability of the system associated readout electronics is studied. It is found to be stable with variations smaller than 0.6 %. Then, the method developed to compute the calibration constants, to correct for the variations of the gain of the calorimeter photomultipliers, is described. These constants were determined with a statistical uncertainty of 0.3 % and a systematic uncertainty of 0.2 % for the central part of the calorimeter and 0.5 % for the end-caps. Finally, the detection and correction of timing mis-configuration of the Tile Calorimeter using the Laser system are also presented.
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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. (2017). Study of the material of the ATLAS inner detector for Run 2 of the LHC. J. Instrum., 12, P12009–59pp.
Abstract: The ATLAS inner detector comprises three different sub-detectors: the pixel detector, the silicon strip tracker, and the transition-radiation drift-tube tracker. The Insertable B-Layer, a new innermost pixel layer, was installed during the shutdown period in 2014, together with modifications to the layout of the cables and support structures of the existing pixel detector. The material in the inner detector is studied with several methods, using a low-luminosity root s = 13 TeV pp collision sample corresponding to around 2.0 nb(-1) collected in 2015 with the ATLAS experiment at the LHC. In this paper, the material within the innermost barrel region is studied using reconstructed hadronic interaction and photon conversion vertices. For the forward rapidity region, the material is probed by a measurement of the efficiency with which single tracks reconstructed from pixel detector hits alone can be extended with hits on the track in the strip layers. The results of these studies have been taken into account in an improved description of the material in the ATLAS inner detector simulation, resulting in a reduction in the uncertainties associated with the charged-particle reconstruction efficiency determined from simulation.
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