LUCID-3: Upgrade of the ATLAS Luminosity Monitor for the High Luminosity LHC
Bibliographic record
Abstract
LUCID-2 ($\textbf{LU}$minosity $\textbf{C}$herenkov $\textbf{I}$ntegrating $\textbf{D}$etector) has been the main luminometer for the ATLAS experiment during Run-2 (2015-2018) and Run-3 (2022-ongoing). Offline a precision on the $\mathcal{L}$ measurement for the entirety of Run-2 of 0.8% was achieved, and a similar precision is expected at the conclusion of Run-3. LUCID-2 however will not be able to produce competitive measurements of luminosity in the HL-LHC era, particularly due to the increased number of collisions per bunch crossing. Due to this, an upgrade to LUCID-2, LUCID-3, is under development. Multiple technologies and designs have been proposed, of which prototypes have been produced, installed and have been operating alongside LUCID-2. These prototypes and the results obtained with them are discussed in order to evaluate their potential effectiveness in the HL-LHC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".