Searching for new physics with Bs0→K(⁎)0K¯(⁎)0 — A reappraisal
Bibliographic record
Abstract
Abstract The effective phase 2 β s eff can be extracted from the indirect CP-violating asymmetry in B s 0 → K ( ⁎ ) 0 K ¯ ( ⁎ ) 0 . In the standard model, 2 β s eff is expected to vanish, and so its measurement can potentially reveal the presence of new physics. However, there is a theoretical error if the second amplitude, V u b ⁎ V u s P u c ′ , is non-negligible. Ciuchini, Pierini and Silvestrini (CPS) have suggested measuring P u c in B d 0 → K ( ⁎ ) 0 K ¯ ( ⁎ ) 0 , and relating it to P u c ′ using SU(3). For their choice of C d and S d , the direct and indirect CP asymmetries in B d 0 → K ( ⁎ ) 0 K ¯ ( ⁎ ) 0 , they find that the error on 2 β s eff is very small, even allowing for 100% SU(3) breaking. In this Letter, we re-examine the CPS method, allowing for a large range of the B d , s 0 → K ( ⁎ ) 0 K ¯ ( ⁎ ) 0 observables. We find that, if C d 2 + S d 2 is measured to be ≲ 0.4 – 0.5 , the theoretical error on 2 β s eff is indeed small, 2–3°. However, for other values of these observables, this error can be quite large, up to 14.9°. This problem can be ameliorated if the values of SU(3) breaking were known, and we discuss different experimental ways of determining this quantity.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".