Characterization of a 28 nm ASIC With On-Chip ML for Particle Tracking Detectors
This paper presents the characterization of a 28 nm CMOS ASIC for particle tracking detectors that integrates in-pixel analog signal processing and an on-chip neural network classifier to achieve low noise, high linearity, and effective data reduction with 99.06% agreement between hardware measurements and offline predictions.