Search for a high-mass dimuon resonance produced in association with b quark jets at $$ \sqrt{s} $$ = 13 TeV
Bibliographic record
Abstract
A bstract A search for high-mass dimuon resonance production in association with one or more b quark jets is presented. The study uses proton-proton collision data collected with the CMS detector at the LHC corresponding to an integrated luminosity of 138 fb − 1 at a center-of-mass energy of 13 TeV. Model-independent limits are derived on the number of signal events with exactly one or more than one b quark jet. Results are also interpreted in a lepton-flavor-universal model with Z′ boson couplings to a bb quark pair ( g b ), an sb quark pair ( g b δ bs ), and any same-flavor charged lepton ( g ℓ ) or neutrino pair ( g ν ), with |g ν | = |g ℓ | . For a Z′ boson with a mass $$ {m}_{{\textrm{Z}}^{\prime }} $$ m Z ′ = 350 GeV (2 TeV) and |δ bs | < 0.25, the majority of the parameter space with 0.0057 < |g ℓ | < 0.35 (0.25 < |g ℓ | < 0.43) and 0.0079 < | g b | < 0.46 (0.34 < | g b | < 0.57) is excluded at 95% confidence level. Finally, constraints are set on a Z′ model with parameters consistent with low-energy b → s ℓℓ measurements. In this scenario, most of the allowed parameter space is excluded for a Z′ boson with 350 < $$ {m}_{{\textrm{Z}}^{\prime }} $$ m Z ′ < 500 GeV, while the constraints are less stringent for higher $$ {m}_{{\textrm{Z}}^{\prime }} $$ m Z ′ hypotheses. This is the first dedicated search at the LHC for a high-mass dimuon resonance produced in association with multiple b quark jets, and the constraints obtained on models with this signature are the most stringent to date.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".