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ATLAS Collaboration(Aad, G. et al), Aikiot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2024). Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network. Mach. Learn.-Sci. Technol., 5(3), 035051–37pp.
Abstract: The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the specificities of the calibration problem, special loss functions and training procedures are employed, and a complex network architecture, which includes feature annotation and residual connection layers, is used. The DNN-based calibration is compared to the standard numerical approach in an extensive series of tests. The DNN approach is found to perform significantly better in almost all of the tests and over most of the relevant kinematic phase space. In particular, it consistently improves the energy and mass resolutions, with a 30% better energy resolution obtained for transverse momenta p(T) > 500 GeV.
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Perkowski, J. et al, Babiano-Suarez, V., Balibrea Correa, J., Domingo-Pardo, C., Ladarescu, I., & Lerendegui-Marco, J. (2024). Multi-section fission ionization chamber for measurement of 239Pu(n, γ) reaction in fission tagging method. Nucl. Instrum. Methods Phys. Res. A, 1067, 169649–8pp.
Abstract: The Pu-239(n, gamma) reaction cross section is very important for operation of both thermal and fast reactors, when loaded with MOX fuels. According to the NEA/OECD High Priority Request List the precision of cross section data for this reaction should be improved. The cross section of (n, f) reaction is much higher compared to (n, gamma) for this isotope. In such conditions the fission tagging technique could be applied to identify the fission background. In the past, this technique was successfully used for capture measurements at the nTOF facility at CERN. The multi-section fission ionization chamber was constructed and used in the combination with Total Absorption Calorimeter (TAC) for detecting gamma rays for the precise measurement of Pu-239(n, gamma) reaction cross section at the nTOF facility.
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Pilsl, B., Bergauer, T., Casanova, R., Handerkas, H., Irmler, C., Kraemer, U., et al. (2025). Enhancing radiation hardness and granularity in HV-CMOS: The RD50-MPW4 sensor. Nucl. Instrum. Methods Phys. Res. A, 1080, 170752–5pp.
Abstract: The latest HV-CMOS pixel sensor developed by the former CERN-RD50-CMOS group, known as the RD50-MPW4, demonstrates competitive radiation tolerance, spatial granularity, and timing resolution – requirements for future high-energy physics experiments such as the HL-LHC and FCC. Fabricated using 150 nm CMOS process by LFoundry, it introduces several improvements over its predecessor, the RD50-MPW3, including separated power domains for reduced noise, a new backside biasing scheme, and an enhanced guard ring structure, enabling operation at bias voltages up to 800 V. Tests with non-irradiated samples achieved hit detection efficiencies exceeding 99.9 % and a spatial resolution around 16 μm. Neutron-irradiated sensors were characterized using IV measurements and beam campaigns, confirming the sensor's robustness in high-radiation environments. The results highlight ability of HV-CMOS technology to restore hit detection efficiency post-irradiation by increasing the applied bias voltage. Details of these measurements and timing performance are presented in this paper.
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