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Poley, L. et al, Lacasta, C., & Soldevila, U. (2016). Characterisation of strip silicon detectors for the ATLAS Phase-II Upgrade with a micro-focused X-ray beam. J. Instrum., 11, P07023–12pp.
Abstract: The planned HL-LHC (High Luminosity LHC) in 2025 is being designed to maximise the physics potential through a sizable increase in the luminosity up to 6.10(34) cm(-2) s(-1). A consequence of this increased luminosity is the expected radiation damage at 3000 fb(-1) after ten years of operation, requiring the tracking detectors to withstand fluences to over 1.10(16) 1 MeV n(eq)/cm(2) . In order to cope with the consequent increased readout rates, a complete re-design of the current ATLAS Inner Detector (ID) is being developed as the Inner Tracker (ITk). Two proposed detectors for the ATLAS strip tracker region of the ITk were characterized at the Diamond Light Source with a 3 μm FWHM 15 keV micro focused X-ray beam. The devices under test were a 320 μm thick silicon stereo (Barrel) ATLAS12 strip mini sensor wire bonded to a 130 nm CMOS binary readout chip (ABC130) and a 320 μm thick full size radial (end-cap) strip sensor – utilizing bi-metal readout layers – wire bonded to 250 nm CMOS binary readout chips (ABCN-25). A resolution better than the inter strip pitch of the 74.5 μm strips was achieved for both detectors. The effect of the p-stop diffusion layers between strips was investigated in detail for the wire bond pad regions. Inter strip charge collection measurements indicate that the effective width of the strip on the silicon sensors is determined by p-stop regions between the strips rather than the strip pitch.
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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. (2016). A measurement of material in the ATLAS tracker using secondary hadronic interactions in 7 TeV p p collisions. J. Instrum., 11, P11020–41pp.
Abstract: Knowledge of the material in the ATLAS inner tracking detector is crucial in under-standing the reconstruction of charged-particle tracks, the performance of algorithms that identify jets containing b-hadrons and is also essential to reduce background in searches for exotic particles that can decay within the inner detector volume. Interactions of primary hadrons produced in pp collisions with the material in the inner detector are used to map the location and amount of this material. The hadronic interactions of primary particles may result in secondary vertices, which in this analysis are reconstructed by an inclusive vertex-finding algorithm. Data were collected using minimum-bias triggers by the ATLAS detector operating at the LHC during 2010 at centre-of-mass energy root s = 7 TeV, and correspond to an integrated luminosity of 19 nb(-1). Kinematic properties of these secondary vertices are used to study the validity of the modelling of hadronic interactions in simulation. Secondary-vertex yields are compared between data and simulation over a volume of about 0.7m(3) around the interaction point, and agreement is found within overall uncertainties.
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Poley, L. et al, & Lacasta, C. (2017). Investigations into the impact of locally modified sensor architectures on the detection efficiency of silicon micro-strip sensors. J. Instrum., 12, P07006–17pp.
Abstract: The High Luminosity Upgrade of the LHC will require the replacement of the Inner Detector of ATLAS with the Inner Tracker (ITk) in order to cope with higher radiation levels and higher track densities. Prototype silicon strip detector modules are currently developed and their performance is studied in both particle test beams and X-ray beams. In previous test beam measurements of prototype modules, the response of silicon sensors has been studied in detailed scans across individual sensor strips. These scans found instances of sensor strips collecting charge across areas on the sensor deviating from the geometrical width of a sensor strip. The variations have been linked to local features of the sensor architecture. This paper presents results of detailed sensor measurements in both X-ray and particle beams investigating the impact of sensor features (metal pads and p-stops) on the sensor strip response.
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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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Kuehn, S. et al, Bernabeu, J., Lacasta, C., Marco-Hernandez, R., Rodriguez Rodriguez, D., Santoyo, D., et al. (2018). Prototyping of petalets for the Phase-II upgrade of the silicon strip tracking detector of the ATLAS experiment. J. Instrum., 13, T03004–22pp.
Abstract: In the high luminosity era of the Large Hadron Collider, the instantaneous luminosity is expected to reach unprecedented values, resulting in about 200 proton-proton interactions in a typical bunch crossing. To cope with the resultant increase in occupancy, bandwidth and radiation damage, the ATLAS Inner Detector will be replaced by an all-silicon system, the Inner Tracker (ITk). The ITk consists of a silicon pixel and a strip detector and exploits the concept of modularity. Prototyping and testing of various strip detector components has been carried out. This paper presents the developments and results obtained with reduced-size structures equivalent to those foreseen to be used in the forward region of the silicon strip detector. Referred to as petalets, these structures are built around a composite sandwich with embedded cooling pipes and electrical tapes for routing the signals and power. Detector modules built using electronic flex boards and silicon strip sensors are glued on both the front and back side surfaces of the carbon structure. Details are given on the assembly, testing and evaluation of several petalets. Measurement results of both mechanical and electrical quantities are shown. Moreover, an outlook is given for improved prototyping plans for large structures.
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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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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2019). Measurement of the electron reconstruction efficiency at LHCb. J. Instrum., 14, P11023–20pp.
Abstract: The single electron track-reconstruction efficiency is calibrated using a sample corresponding to 1.3 fb(-1) of pp collision data recorded with the LHCb detector in 2017. This measurement exploits B+ -> J/psi (e(+)e(-))K+ decays, where one of the electrons is fully reconstructed and paired with the kaon, while the other electron is reconstructed using only the information of the vertex detector. Despite this partial reconstruction, kinematic and geometric constraints allow the B meson mass to be reconstructed and the signal to be well separated from backgrounds. This in turn allows the electron reconstruction efficiency to be measured by matching the partial track segment found in the vertex detector to tracks found by LHCb's regular reconstruction algorithms. The agreement between data and simulation is evaluated, and corrections are derived for simulated electrons in bins of kinematics. These correction factors allow LHCb to measure branching fractions involving single electrons with a systematic uncertainty below 1%.
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., et al. (2019). Electron and photon performance measurements with the ATLAS detector using the 2015-2017 LHC proton-proton collision data. J. Instrum., 14, P12006–69pp.
Abstract: This paper describes the reconstruction of electrons and photons with the ATLAS detector, employed for measurements and searches exploiting the complete LHC Run 2 dataset. An improved energy clustering algorithm is introduced, and its implications for the measurement and identification of prompt electrons and photons are discussed in detail. Corrections and calibrations that affect performance, including energy calibration, identification and isolation efficiencies, and the measurement of the charge of reconstructed electron candidates are determined using up to 81 fb(-1) of proton-proton collision data collected at root s = 13 TeV between 2015 and 2017.
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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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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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