Search for high-mass resonances in final states with a τ -lepton and missing transverse momentum with the ATLAS detector
Bibliographic record
Abstract
A search for high-mass resonances decaying into a τ-lepton and a neutrino using proton-proton collisions at a center-of-mass energy of s=13 TeV is presented. The full run 2 data sample corresponding to an integrated luminosity of 139 fb−1 recorded by the ATLAS experiment in the years 2015–2018 is analyzed. The τ-lepton is reconstructed in its hadronic decay modes and the total transverse momentum carried out by neutrinos is inferred from the reconstructed missing transverse momentum. The search for new physics is performed on the transverse mass between the τ-lepton and the missing transverse momentum. No excess of events above the Standard Model expectation is observed and upper exclusion limits are set on the W′→τν production cross section. Heavy W′ vector bosons with masses up to 5.0 TeV are excluded at 95% confidence level, assuming that they have the same couplings as the Standard Model W boson. For nonuniversal couplings, W′ bosons are excluded for masses less than 3.5–5.0 TeV, depending on the model parameters. In addition, model-independent limits on the visible cross section times branching ratio are determined as a function of the lower threshold on the transverse mass of the τ-lepton and missing transverse momentum. © 2024 CERN, for the ATLAS Collaboration 2024 CERN
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".