First experimental results of the spatial resolution of RSD pad arrays read out with a 16-ch board

TL;DR

This paper reports the first experimental evaluation of the spatial resolution of Resistive Silicon Detectors (RSD) read out with a 16-channel board, demonstrating a spatial resolution of approximately 5.5 micrometers using machine learning predictions.

Contribution

It provides the first experimental results on RSD spatial resolution using a 16-channel readout and machine learning for position prediction.

Findings

Achieved a spatial resolution of ~5.5 micrometers.

Demonstrated effective use of machine learning for position prediction.

Validated RSDs as promising high-precision tracking detectors.

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 3$\times$4 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 $\sim$~5.5~\mum.