Abstract
Resistive Silicon Detectors (RSD, also known as AC-LGAD) are innovative silicon sensors, based on the LGAD technology, characterized by a continuous gain layer that spreads across the whole sensor active area. RSDs are very promising tracking detectors, thanks to the combination of the built-in signal sharing with the internal charge multiplication, which allows large signals to be seen over multiple read-out channels. This work presents the first experimental results obtained from a 34 array with 200~\mum~pitch, coming from the RSD2 production manufactured by FBK, read out with a 16-ch digitizer. A machine learning model has been trained, with experimental data taken with a precise TCT laser setup, and then used to predict the laser shot positions, finding a spatial resolution of ~5.5~\mum.
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