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CALICE Collaboration(Lai, S. et al), & Irles, A. (2024). Software compensation for highly granular calorimeters using machine learning. J. Instrum., 19(4), P04037–28pp.
Abstract: A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.
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T2K Collaboration(Abe, K. et al), Antonova, M., Cervera-Villanueva, A., Molina Bueno, L., & Novella, P. (2022). Scintillator ageing of the T2K near detectors fro 2010 to 2021. J. Instrum., 17(10), P10028–36pp.
Abstract: The T2K experiment widely uses plastic scintillator as a target for neutrino interactions and an active medium for the measurement of charged particles produced in neutrino interactions at its near detector complex. Over 10 years of operation the measured light yield recorded by the scintillator based subsystems has been observed to degrade by 0.9-2.2% per year. Extrapolation of the degradation rate through to 2040 indicates the recorded light yield should remain above the lower threshold used by the current reconstruction algorithms for all subsystems. This will allow the near detectors to continue contributing to important physics measurements during the T2K-II and Hyper-Kamiokande eras. Additionally, work to disentangle the degradation of the plastic scintillator and wavelength shifting fibres shows that the reduction in light yield can be attributed to the ageing of the plastic scintillator. The long component of the attenuation length of the wavelength shifting fibres was observed to degrade by 1.3-5.4% per year, while the short component of the attenuation length did not show any conclusive degradation.
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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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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(Aad, G. et al), Alvarez Piqueras, D., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fernandez Martinez, P., et al. (2016). Performance of b-jet identification in the ATLAS experiment. J. Instrum., 11, P04008–126pp.
Abstract: The identification of jets containing b hadrons is important for the physics programme of the ATLAS experiment at the Large Hadron Collider. Several algorithms to identify jets containing b hadrons are described, ranging from those based on the reconstruction of an inclusive secondary vertex or the presence of tracks with large impact parameters to combined tagging algorithms making use of multi-variate discriminants. An independent b-tagging algorithm based on the reconstruction of muons inside jets as well as the b-tagging algorithm used in the online trigger are also presented. The b-jet tagging efficiency, the c-jet tagging efficiency and the mistag rate for light flavour jets in data have been measured with a number of complementary methods. The calibration results are presented as scale factors defined as the ratio of the efficiency (or mistag rate) in data to that in simulation. In the case of b jets, where more than one calibration method exists, the results from the various analyses have been combined taking into account the statistical correlation as well as the correlation of the sources of systematic uncertainty.
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