Dark matter with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>t</mml:mi></mml:math>-channel mediator: A simple step beyond contact interaction
Bibliographic record
Abstract
Effective contact operators provide the simplest parametrization of dark matter searches at colliders. However, light mediators can significantly change the sensitivity and search strategies. Considering simple models of mediators is an important next step for collider searches. In this paper, we consider the case of a $t$-channel mediator. Its presence opens up new contributions to the $\text{monojet}+{\overline{)\mathrm{E}}}_{T}$ searches and can change the reach significantly. We also study the complementarity between searches for processes of $\text{monojet}+{\overline{)\mathrm{E}}}_{T}$ and direct pair production of the mediators. Mediator pair production also gives an important contribution to a CMS-like $\text{monojet}+{\overline{)\mathrm{E}}}_{T}$ search, where a second hard jet is allowed. There is a large region of parameter space in which the $\text{monojet}+{\overline{)\mathrm{E}}}_{T}$ search provides the stronger limit. Assuming the relic abundance of the dark matter is thermally produced within the framework of this model, we find that in the Dirac fermion dark matter case, there is no region in the parameter space that satisfies the combined constraint of $\text{monojet}+{\overline{)\mathrm{E}}}_{T}$ search and direct detection; whereas in the Majorana fermion dark matter case, the mass of dark matter must be larger than about 100 GeV. If the relic abundance requirement is not assumed, the discovery of the $t$-channel mediator predicts additional new physics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".