The new LUCID-2 detector for luminosity measurement and monitoring in ATLAS
Bibliographic record
Abstract
The ATLAS luminosity monitor, LUCID ( LU minosity C herenkov I ntegrating D etector), had to be upgraded for the second run of the LHC accelerator that started in spring 2015. The increased energy of the proton beams and the higher luminosity required a redesign of LUCID to cope with the more demanding conditions. The novelty of the LUCID-2 detector is that it uses the thin quartz windows of photomultipliers as Cherenkov medium and a small amounts of radioactive 207 Bi sources deposited on to these windows to monitor the gain stability of the photomultipliers. The result is a fast and accurate luminosity determination that can be kept stable during many months of data taking. LUCID-2 can also measure the luminosity accurately online for each of the up to 2808 colliding bunch pairs in the LHC . These bunch pairs are separated by only 25 ns and new electronics has been built that can count not only the number of pulses above threshold but also integrate the pulses.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".