Sensor operating point calibration and monitoring of the ALICE Inner Tracking System during LHC Run 3

TL;DR

This paper details the calibration and monitoring strategies for the ALICE ITS2 detector during LHC Run 3, ensuring optimal performance of a large-scale MAPS-based silicon tracking system.

Contribution

It introduces novel calibration methods and operational strategies for the first large-scale MAPS detector at the LHC, enhancing stability and performance.

Findings

Successful calibration of over 24,000 sensors and 12.6 billion pixels.

Implementation of dynamic adjustment strategies for detector parameters.

Enhanced stability and data quality during LHC Run 3.

Abstract

The new Inner Tracking System (ITS2) of the ALICE experiment began operation in 2021 with the start of LHC Run 3. Compared to its predecessor, ITS2 offers substantial improvements in pointing resolution, tracking efficiency at low transverse momenta, and readout-rate capabilities. The detector employs silicon Monolithic Active Pixel Sensors (MAPS) featuring a pixel size of 26.88$\times$29.24 $\mu$m$^2$ and an intrinsic spatial resolution of approximately 5 $\mu$m. With a remarkably low material budget of 0.36% of radiation length ($X_{0}$) per layer in the three innermost layers and a total sensitive area of about 10 m$^2$, the ITS2 constitutes the largest-scale application of MAPS technology in a high-energy physics experiment and the first of its kind operated at the LHC. For stable data taking, it is crucial to calibrate different parameters of the detector, such as in-pixel charge thresholds and the masking of noisy pixels. The calibration of 24120 monolithic sensors, comprising a total of 12.6$\times$10$^{9}$ pixels, represents a major operational challenge. This paper presents the methods developed for the calibration of the ITS2 and outlines the strategies for monitoring and dynamically adjusting the detector's key performance parameters over time.