Performance and design validation of CMS Phase-2 pixel modules
Bibliographic record
Abstract
Abstract In view of the High Luminosity LHC, the current CMS tracking detector will have to be replaced during Long Shutdown 3 to cope with the higher radiation environment and to withstand an increased data rate. To prepare for the so-called CMS Phase-2 upgrade, multiple studies were carried out to characterize the pixel module design and its performance with a particular focus on the Quality Control (QC) and Assurance. For this purpose, different aspects were put together to establish a module full-performance test procedure, and novel techniques became part of the module design validation process for the full-size readout chip (CROCv1). Based on the results collected on CROCv1 prototype modules and according to the module selection criteria the community agreed on, some changes were introduced in the module design to improve the performance. This resulted in multiple prototype versions, including the production of the definitive chip (CROCv2). This study presents the quality control test flow performed, both for the dual and quad-chip module designs, on a big sample of CROCv1 prototypes and on several Kick-off and CROCv2 pre-production modules. In particular, the validation process includes measurements of the readout chip powering, sensor IV bias and open bump bonds identification. Thermal stress tests in extended temperature ranges were performed only on a subset of pixel modules to ensure the integrity of the sensor and to provide quick feedback on the quality of the bump bond connectivity after harsh temperature cycles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".