Constraining the Little Higgs model of Schmaltz, Stolarski, and Thaler with recent results from the LHC
Bibliographic record
Abstract
In this paper, we use the latest Higgs measurements from ATLAS and CMS to constrain the parameter space of the model of Schmaltz, Stolarski, and Thaler, a little Higgs model with two Higgs doublets, which we will refer to as the BLH model. We account for all production and decay modes explored at ATLAS and CMS in two scenarios: a general case, which assumes the ${h}_{0}$ state is light (${m}_{{h}_{0}}\ensuremath{\approx}125\text{ }\text{ }\mathrm{GeV}$) and the masses of the other neutral scalars (${H}_{0}$ and ${A}_{0}$) are allowed to vary, and a case with a near-degeneracy between the masses of the ${h}_{0}$ and ${A}_{0}$ and, for some choices of parameters, the ${H}_{0}$ states. The near-degeneracy scenario can result in an enhanced diphoton rate, as measured by ATLAS, but is largely ruled out by a combination of the ${h}_{0}\ensuremath{\rightarrow}{\ensuremath{\tau}}^{+}{\ensuremath{\tau}}^{\ensuremath{-}}$ and the heavy ${H}_{0}\ensuremath{\rightarrow}{W}^{+}{W}^{\ensuremath{-}}$ measurements. In the general case, we find large regions of parameter space that are in better agreement with either the ATLAS or CMS results than is the SM. However, a significantly enhanced diphoton rate is only possible through large contributions to the ${h}_{0}\ensuremath{\gamma}\ensuremath{\gamma}$ effective coupling from charged Higgs bosons in a region of parameter space that borders on violation of perturbativity in the scalar sector.
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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 | 0.003 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".