Test of light-lepton universality in τ decays with the Belle II experiment
Bibliographic record
Abstract
A bstract We present a measurement of the ratio $$ {R}_{\mu }=\mathcal{B}\left({\tau}^{-}\to {\mu}^{-}{\overline{\nu}}_{\mu }{\nu}_{\tau}\right)/\mathcal{B}\left({\tau}^{-}\to {e}^{-}{\overline{\nu}}_e{\nu}_{\tau}\right) $$ R μ = B τ − → μ − ν ¯ μ ν τ / B τ − → e − ν ¯ e ν τ of branching fractions $$ \mathcal{B} $$ B of the τ lepton decaying to muons or electrons using data collected with the Belle II detector at the SuperKEKB e + e − collider. The sample has an integrated luminosity of 362 ± 2 fb − 1 at a centre-of-mass energy of 10.58 GeV. Using an optimised event selection, a binned maximum likelihood fit is performed using the momentum spectra of the electron and muon candidates. The result, R μ = 0.9675 ± 0.0007 ± 0.0036, where the first uncertainty is statistical and the second is systematic, is the most precise to date. It provides a stringent test of the light-lepton universality, translating to a ratio of the couplings of the muon and electron to the W boson in τ decays of 0.9974 ± 0.0019, in agreement with the standard model expectation of unity.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".