Searches for lepton-flavour-violating decays of the Higgs boson into $e\tau$ and $\mu\tau$ in $\sqrt{s}=13$ TeV $pp$ collisions with the ATLAS detector
Bibliographic record
Abstract
This paper presents direct searches for lepton flavour violation in Higgs boson decays, $H\rightarrow eτ$ and $H\rightarrowμτ$, performed using data collected with the ATLAS detector at the LHC. The searches are based on a data sample of proton-proton collisions at a centre-of-mass energy $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. Leptonic ($τ\rightarrow \ell ν_\ell ν_τ$) and hadronic ($τ\rightarrow $ hadrons $ ν_τ$) decays of the $τ$-lepton are considered. Two background estimation techniques are employed: the MC-template method, based on data-corrected simulation samples, and the Symmetry method, based on exploiting the symmetry between electrons and muons in the Standard Model backgrounds. No significant excess of events is observed and the results are interpreted as upper limits on lepton-flavour-violating branching ratios of the Higgs boson. The observed (expected) upper limits set on the branching ratios at 95% confidence level, $\mathcal{B}(H\rightarrow eτ)<0.20\%$ (0.12%) and $\mathcal{B}(H\rightarrow μτ)<0.18\%$ (0.09%), are obtained with the MC-template method from a simultaneous measurement of potential $H \rightarrow eτ$ and $H \rightarrowμτ$ signals. The best-fit branching ratio difference, $\mathcal{B}(H\rightarrow μτ)- \mathcal{B}(H\rightarrow eτ)$, measured with the Symmetry method in the channel where the $τ$-lepton decays to leptons, is (0.25 $\pm$ 0.10)%, compatible with a value of zero within 2.5$σ$.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".