The performance of the New Small Wheel of the ATLAS detector in the heart of LHC Run-3
Bibliographic record
Abstract
During the second long shutdown of the Large Hadron Collider (LHC) at CERN, the most important upgrade within the ATLAS experiment was the replacement of the two inner endcap stations of the Muon Spectrometer (MS), with the New Small Wheel (NSW). Consisting of two novel detector technologies, the small-strip Thin Gap Chambers (sTGC) and the resistive strips Micromegas (MM), the NSW is targeting the rejection of fake muons at the endcap region between pseudorapidity 1 . 3 < | η | < 2 . 4 . Furthermore, thanks to the excellent muon tracking and the improved triggering capability NSW contributes to the identification of muons coming from the interaction point with high precision. Following an extensive effort to finalise the commissioning of the new detectors, both technologies were integrated successfully into the ATLAS data acquisition, reconstruction and simulation, and in 2024 they were also fully integrated into the ATLAS trigger, offering a significant reduction of the ATLAS Level-1 trigger rate and further reducing the readout dead-time. Despite the demanding challenges and increased luminosity delivered by LHC, the ATLAS NSW completed important milestones and now demonstrates its readiness towards the end of the Run-3 data-taking period of LHC. These proceedings will present an overview of the advances made within 2024, followed by a brief report of the NSW performance in terms of tracking and triggering, using data recorded from proton–proton collisions at 13.6 TeV .
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".