LHC phenomenology of a two-Higgs-doublet neutrino mass model
Bibliographic record
Abstract
We study the LHC search prospects for a model in which the neutrinos obtain Dirac masses from couplings to a second Higgs doublet with tiny vacuum expectation value. The model contains a charged Higgs boson that decays to $\ensuremath{\ell}\ensuremath{\nu}$ with branching fractions controlled by the neutrino masses and mixing angles as measured in neutrino oscillation experiments. The most promising signal is electroweak production of ${H}^{+}{H}^{\ensuremath{-}}$ pairs with decays to $\ensuremath{\ell}{\ensuremath{\ell}}^{\ensuremath{'}}{p}_{T}^{\mathrm{miss}}$, where $\ensuremath{\ell}{\ensuremath{\ell}}^{\ensuremath{'}}={e}^{+}{e}^{\ensuremath{-}}$, ${\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}}$, and ${e}^{\ifmmode\pm\else\textpm\fi{}}{\ensuremath{\mu}}^{\ensuremath{\mp}}$. We find that a cut on the kinematic variable ${M}_{T2}$ eliminates most of the $t\overline{t}$ and $W$-pair background. Depending on the neutrino mass spectrum and mixing angles, a 100 (300) GeV charged Higgs could be discovered at the LHC with as little as $8\text{ }(24)\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of integrated luminosity at 14 TeV $pp$ center-of-mass energy.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".