Search for minimal supersymmetric standard model Higgs Bosons H / A and for a $$Z^{\prime }$$ Z ′ boson in the $$\tau \tau $$ τ τ final state produced in pp collisions at $$\sqrt{s}= 13$$ s = 13 TeV with the ATLAS detector
Bibliographic record
Abstract
A search for neutral Higgs bosons of the Minimal Supersymmetric Standard Model (MSSM) and for a heavy neutral $Z^{\prime}$ boson is performed using a data sample corresponding to an integrated luminosity of 3.2 fb$^{-1}$ from proton--proton collisions at $\sqrt{s} = 13$ TeV recorded by the ATLAS detector at the LHC. The heavy resonance is assumed to decay to a $\tau^+ \tau^-$ pair with at least one $\tau$ lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2--1.2 TeV for the MSSM neutral Higgs bosons and 0.5--2.5 TeV for the heavy neutral $Z^{\prime}$ boson. The data are in good agreement with the background predicted by the Standard Model and hence results are given as upper limits on the production cross section times branching fraction of the boson decay to $\tau^+\tau^-$ as a function of the boson mass. The results are interpreted in MSSM and $Z^{\prime}$ benchmark scenarios. The most stringent MSSM parameter space constraints for the Higgs boson search exclude at 95\% confidence level (CL) $\tan\beta > 7.6$ for $m_A = 200$ GeV in the $m_{h}^{\textrm{mod+}}$ MSSM scenario. This analysis extends the MSSM limits from previous searches for the mass range $m_A > 500$ GeV. For the Sequential Standard Model, a $Z^{\prime}_\mathrm{SSM}$ mass up to 1.90 TeV is excluded at 95% CL and masses up to 1.82--2.17 TeV are excluded for a $Z^{\prime}_{\mathrm{SFM}}$ of the Strong Flavour Model.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".