Observation of the $\gamma\gamma\to\tau\tau$ process in Pb+Pb collisions and constraints on the $\tau$-lepton anomalous magnetic moment with the ATLAS detector
Bibliographic record
Abstract
This Letter reports the observation of $τ$-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb($γγ→ττ$)Pb and constraints on the $τ$-lepton anomalous magnetic moment $a_τ$. The dataset corresponds to an integrated luminosity of 1.44 nb$^{-1}$ of LHC Pb+Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a $τ$-lepton decay, an electron or charged-particle track(s) from the other $τ$-lepton decay, little additional central-detector activity, and no forward neutrons. The $γγ→ττ$ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of $μττ$=1.03-0.05+0.06 assuming the standard model value for $a_τ$. To measure aτ, a template fit to the muon transverse-momentum distribution from $τ$-lepton candidates is performed, using a dimuon $(γγ→μμ)$ control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for $a_τ$ is -0.057<$a_τ$<0.024.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".