Evolution of the electrical characteristics of the ATLAS18 ITk strip sensors with HL-LHC radiation exposure range
Bibliographic record
Abstract
Abstract The objective of the study is to evaluate the evolution of the performance of the new ATLAS Inner-Tracker (ITk) strip sensors as a function of radiation exposure, to ensure the proper operation of the upgraded detector during the lifetime of the High-Luminosity Large Hadron Collider (HL-LHC). Full-size ATLAS ITk Barrel Short-Strip (SS) sensors with final layout design, ATLAS18SS, have been irradiated with neutrons and gammas, to confirm the results obtained with prototypes and miniature sensors during the development phase. The irradiations cover a wide range of fluences and doses that ITk will experience, going from 1×10 13 n eq /cm 2 and 0.49 Mrad, to 1.6×10 15 n eq /cm 2 and 80 Mrad. The split irradiation enables a proper combination of fluence and dose values of the HL-LHC, including a 1.5 safety factor. A complete electrical characterization of the key sensor parameters before and after irradiation is presented, studying the leakage current, bulk capacitance, single-strip and inter-strip characteristics. The results confirm the fulfilment of the ATLAS specifications throughout the whole experiment. The study of a wide range of fluences and doses also allows to obtain detailed results, such as the frequency dependence of the bulk capacitance measurements for highly irradiated sensors, or the evolution of the punch-through protection and inter-strip resistance with radiation.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".