E6 motivated UMSSM confronts experimental data
Bibliographic record
Abstract
Abstract We test E 6 realisations of a generic U(1)′ extended Minimal Supersymmetric Standard Model (UMSSM), parametrised in terms of the mixing angle pertaining to the new U(1)′ sector, $$ {\theta}_{E_6} $$ θ E 6 , against all currently available data, from space to ground experiments, from low to high energies. We find that experimental constraints are very restrictive and indicate that large gauge kinetic mixing and $$ {\theta}_{E_6} $$ θ E 6 ≈ −π/3 are required within this theoretical construct to achieve compliance with current data. The consequences are twofold. On the one hand, large gauge kinetic mixing implies that the Z′ boson emerging from the breaking of the additional U(1)′ symmetry is rather wide since it decays mainly into WW pairs. On the other hand, the preferred $$ {\theta}_{E_6} $$ θ E 6 value calls for a rather specific E 6 breaking pattern different from those commonly studied. We finally delineate potential signatures of the emerging UMSSM scenario in both Large Hadron Collider (LHC) and in Dark Matter (DM) experiments.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".