Loopholes in Z′ searches at the LHC: exploring supersymmetric and leptophobic scenarios
Bibliographic record
Abstract
Searching for heavy vector bosons Z′, predicted in models inspired by Grand Unification Theories, is among the challenging objectives of the LHC. The ATLAS and CMS collaborations have looked for Z′ bosons assuming that they can decay only into Standard Model channels, and have set exclusion limits by investigating dilepton, dijet and, to a smaller extent, top-antitop final states. In this work we explore possible loopholes in these Z′ searches, by studying supersymmetric as well as leptophobic scenarios. We demonstrate the existence of realizations in which the Z′ boson automatically evades the typical bounds derived from the analyses of the Drell-Yan invariant-mass spectrum. Dileptonic final states can in contrast only originate from supersymmetric Z′ decays and are thus accompanied by additional effects. This feature is analyzed in the context of judiciously chosen bench-mark configurations, for which visible signals could be expected in future LHC data with a 4σ − 7σ significance. Our results should hence motivate an extension of the current Z′ search program to account for supersymmetric and leptophobic models.
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 | 0.002 | 0.004 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".