Search for new physics in trilepton events and limits on the associated chargino-neutralino production at CDF
Bibliographic record
Abstract
We perform a search for new physics using final states consisting of three leptons and a large imbalance in transverse momentum resulting from proton-antiproton collisions at 1.96 TeV center-of-mass energy. We use data corresponding to $5.8\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of integrated luminosity recorded by the CDF II detector at the Tevatron collider. Our main objective is to investigate possible new low-momentum (down to $5\text{ }\text{ }\mathrm{GeV}/c$) multileptonic final states not investigated by LHC experiments. Relative to previous CDF analyses, we expand the geometric and kinematic coverage of electrons and muons and utilize tau leptons that decay hadronically. Inclusion of tau leptons is particularly important for supersymmetry (SUSY) searches. The results are consistent with standard-model predictions within $1.85\ensuremath{\sigma}$. By optimizing our event selection to increase sensitivity to the minimal supergravity (mSUGRA) SUSY model, we set limits on the associated production of chargino and next-to-lightest neutralino, the SUSY partners of the electroweak gauge bosons. We exclude cross sections up to 0.1 pb and chargino masses up to $168\text{ }\text{ }\mathrm{GeV}/{c}^{2}$ at 95% C.L., for a suitable set of mSUGRA parameters. We also exclude a region of the two-dimensional space of the masses of the neutralino and the supersymmetric partner of the tau lepton, not previously excluded at the Tevatron.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".