Leading QCD corrections for indirect dark matter searches: A fresh look
Bibliographic record
Abstract
The annihilation of nonrelativistic dark matter particles at tree level can be strongly enhanced by the radiation of an additional gauge boson. This is particularly true for the helicity-suppressed annihilation of Majorana particles, like neutralinos, into fermion pairs. Surprisingly, and despite the potentially large effect due to the strong coupling, this has so far been studied in much less detail for the internal bremsstrahlung of gluons than for photons or electroweak gauge bosons. Here, we aim at bridging that gap by presenting a general analysis of neutralino annihilation into quark anti-quark pairs and a gluon, allowing e.g. for arbitrary neutralino compositions and keeping the leading quark mass dependence at all stages in the calculation. We find in some cases largely enhanced annihilation rates, especially for scenarios with squarks being close to degenerate in mass with the lightest neutralino, but also notable distortions in the associated antiproton and gamma-ray spectra. Both effects significantly impact limits from indirect searches for dark matter and are thus important to be taken into account in, e.g., global scans. For extensive scans, on the other hand, full calculations of QCD corrections are numerically typically too expensive to perform for each point in parameter space. We present here for the first time an efficient, numerically fast implementation of QCD corrections, extendable in a straightforward way to nonsupersymmetric models, which avoids computationally demanding full one-loop calculations or event generator runs and yet fully captures the leading effects relevant for indirect dark matter searches. In this context, we also present updated constraints on dark matter annihilation from cosmic-ray antiproton data. Finally, we comment on the impact of our results on relic density calculations.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".