Pursuing forbidden beauty: Search for the lepton-flavour violating decays B0 → e± μ∓ and Bs0 → e± μ∓ and study of electron-reconstruction performance at LHCb
Bibliographic record
Abstract
Physicists have developed a successful theory, called the Standard Model, describing all known fundamental particles and interactions, except gravity, up to high energies and small length scales. Despite its success, it is when extrapolating to astronomical length and time scales that the theory fails. To alleviate these issues, physicists search for more fundamental laws of physics by exploring higher energies. One such approach is the study of heavy and therefore energetic particles called beauty mesons. Since interactions of higher energies mediating decays of particles are relatively suppressed, decays of particles that are rare or forbidden according to the Standard Model are of particular interest, as such interactions can have a relatively large effect. At the particle accelerator LHC at CERN, beauty mesons are produced by the trillions a year. Hence, rare and forbidden beauty decays can be searched for and studied to great precision. This dissertation covers the search for the in the Standard Model forbidden decays of neutral beauty mesons to an electron and muon (a heavier sibling of the electron) with the data collected in 2011 and 2012 by the LHCb detector operating at the LHC. No such decays were found, but its increased precision of the upper limit of its probability is used to constrain new models. In addition, a study of the performance of the reconstruction of electrons at the LHCb experiment is presented, which will allow to determine and reduce systematic uncertainties in future analyses of beauty decays with electrons in the final state.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".