Machine learning for precise hit position reconstruction in Resistive Silicon Detectors
F. Siviero,
R. Arcidiacono,
N. Cartiglia
et al.
Abstract:RSDs are LGAD silicon sensors with 100% fill factor, based on the principle of AC-coupled resistive read-out. Signal sharing and internal charge multiplication are the RSD key features to achieve picosecond-level time resolution and micron-level spatial resolution, thus making these sensors promising candidates as 4D-trackers for future experiments. This paper describes the use of a neural network to reconstruct the hit position of ionizing particles, an approach that can boost the performance of the RSD with … Show more
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