Mixed stops and the ATLAS on-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>Z</mml:mi></mml:math>excess
Bibliographic record
Abstract
The ATLAS experiment has recently observed a $3\ensuremath{\sigma}$ excess in a channel with a leptonically decaying $Z$, jets, and ${E}_{T}^{\text{miss}}$. It is tantalizing to interpret the signal as the first sign of a natural supersymmetric spectrum. We study such a possibility in a minimal model containing light stops and a neutralino lightest supersymmetric particle. The signal is characterized by a novel topology (compared to previous attempts) where the $Z$ is emitted from a colored particle in the first step of a decay chain, namely ${\stackrel{\texttildelow{}}{t}}_{2}\ensuremath{\rightarrow}{\stackrel{\texttildelow{}}{t}}_{1}Z$, which is characteristic of mixed stops. We show that the excess is compatible with a compressed stop spectrum and is not excluded by any other relevant search, finding some regions of parameter space with signal strength within $1\ensuremath{\sigma}$ of that measured by the ATLAS Collaboration. In addition, we notice that the corresponding CMS search could be prone to background contamination in unexpected topologies of this kind.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".