Sensor operating point calibration and monitoring of the ALICE Inner Tracking System during LHC Run 3
Pith reviewed 2026-05-18 03:03 UTC · model grok-4.3
The pith
Calibration of charge thresholds and noisy pixel masking across 12.6 billion pixels enables stable ALICE ITS2 data taking in LHC Run 3.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The calibration of in-pixel charge thresholds and noisy pixel masking for the 24120 monolithic sensors comprising 12.6×10^9 pixels, together with monitoring and dynamic adjustment of key parameters, enables stable data taking for the ITS2 detector.
What carries the argument
In-pixel charge threshold calibration and noisy pixel masking procedures applied to MAPS sensors, which set operating points to optimize signal detection while suppressing noise across the full detector area.
If this is right
- The procedures allow continuous operation at the high readout rates needed for Run 3 data taking.
- They preserve the intrinsic spatial resolution of approximately 5 μm across all layers.
- Dynamic adjustments counteract gradual changes in sensor response during long periods of operation.
- The low material budget of 0.36% X0 per inner layer remains compatible with high-quality track reconstruction.
Where Pith is reading between the lines
- Similar threshold and masking protocols could be adapted for future MAPS-based trackers at higher luminosities.
- Automated versions of the monitoring loop might reduce the need for periodic manual interventions in long runs.
- The methods highlight practical limits on scaling pixel count while keeping calibration feasible within LHC constraints.
Load-bearing premise
The chosen calibration parameters and monitoring adjustments maintain tracking performance without introducing time-dependent biases or efficiency losses that would affect downstream physics analyses.
What would settle it
A time-dependent measurement of tracking efficiency and spatial resolution over LHC Run 3 that shows degradation correlated with calibration adjustments rather than other factors.
read the original 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.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript describes the calibration and monitoring procedures developed for the ALICE ITS2 detector, which consists of 24120 monolithic active pixel sensors comprising 12.6×10^9 pixels. It focuses on in-pixel charge threshold calibration, noisy pixel masking, and strategies for ongoing monitoring and dynamic adjustment of key performance parameters to support stable data taking in LHC Run 3, building on the detector's low material budget and ~5 µm intrinsic resolution.
Significance. If the operational procedures are shown to maintain the detector's intrinsic performance, the work would be significant for documenting the first large-scale deployment of MAPS technology at the LHC and for providing practical guidance on calibrating and stabilizing such high-granularity systems under high-rate conditions.
major comments (2)
- [Abstract and monitoring strategies section] The central claim that the described calibration and monitoring strategies enable stable data taking without time-dependent efficiency losses or biases is not supported by quantitative evidence in the manuscript. No plots of tracking efficiency, pointing resolution, or run-to-run stability metrics (with error bars) are presented to validate that threshold settings and masking fractions preserve the ~5 µm resolution and low-pT performance required for physics analyses.
- [Strategies for monitoring and dynamically adjusting parameters] The assumption that dynamic adjustments do not introduce undetected variations is load-bearing but untested. The manuscript should include at least one example of before/after monitoring data or a table quantifying masked pixel fractions and threshold distributions over multiple runs to demonstrate that corrections remain within acceptable bounds.
minor comments (2)
- [Introduction] Ensure consistent use of pixel count (12.6×10^9) and sensor count (24120) throughout; cross-check against any tabulated breakdowns of the seven layers.
- [Conclusion] Add a brief reference to the expected impact on downstream tracking algorithms if calibration drifts exceed the stated tolerances.
Simulated Author's Rebuttal
We thank the referee for the careful and constructive review of our manuscript describing the calibration and monitoring procedures for the ALICE ITS2. We address each major comment below and indicate the revisions we will make to the next version of the paper.
read point-by-point responses
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Referee: [Abstract and monitoring strategies section] The central claim that the described calibration and monitoring strategies enable stable data taking without time-dependent efficiency losses or biases is not supported by quantitative evidence in the manuscript. No plots of tracking efficiency, pointing resolution, or run-to-run stability metrics (with error bars) are presented to validate that threshold settings and masking fractions preserve the ~5 µm resolution and low-pT performance required for physics analyses.
Authors: We acknowledge that the manuscript does not contain direct quantitative plots of tracking efficiency, pointing resolution, or run-to-run stability metrics with error bars. This paper is dedicated to the calibration methods, in-pixel threshold setting, noisy-pixel masking, and the operational monitoring framework itself. Performance metrics of the type mentioned are documented in separate ALICE detector-performance and physics publications that use the calibrated ITS2 data. In the revised manuscript we will add explicit references to those works and include a short textual summary of the stability achieved through the monitoring procedures. We cannot add the full set of efficiency and resolution plots requested, as they lie outside the scope of a methods-focused paper. revision: partial
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Referee: [Strategies for monitoring and dynamically adjusting parameters] The assumption that dynamic adjustments do not introduce undetected variations is load-bearing but untested. The manuscript should include at least one example of before/after monitoring data or a table quantifying masked pixel fractions and threshold distributions over multiple runs to demonstrate that corrections remain within acceptable bounds.
Authors: We agree that an illustrative example would strengthen the presentation. In the revised version we will add a table (or figure) that quantifies the masked-pixel fraction and the evolution of threshold distributions across several runs or data-taking periods. This will show that the dynamic corrections remain within the tolerances required for stable operation and do not introduce large undetected variations. revision: yes
- Inclusion of comprehensive plots of tracking efficiency, pointing resolution, and low-pT performance with error bars; these metrics are presented in dedicated performance papers rather than in the present calibration-methods manuscript.
Circularity Check
No circularity: descriptive account of calibration procedures with no derivations or self-referential predictions
full rationale
The paper describes operational methods for threshold calibration, noisy-pixel masking, and monitoring of the ITS2 detector's 12.6×10^9 pixels. No equations, first-principles derivations, or predictions appear in the provided text or abstract. The central claim is that these procedures enable stable data taking; this rests on empirical implementation details rather than any logical reduction of outputs to inputs by construction. No self-citation load-bearing steps, fitted parameters renamed as predictions, or ansatz smuggling are present. The work is self-contained as an experimental methods report.
discussion (0)
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