Neutralino annihilation beyond leading order
Bibliographic record
Abstract
High-precision measurements of the relic dark matter density and the calculation of dark matter annihilation branching fractions in the sun or the galactic halo today motivate the computation of the neutralino annihilation cross section beyond leading order. We consider neutralino annihilation via squark exchange and parameterize the effective annihilation vertex as a dimension-six operator suppressed by two powers of the squark mass and related to the divergence of the axial vector current of the final-state quarks. Since the axial vector current is conserved at tree level in the limit of massless quarks, this dimension-six operator contains a suppression by the quark mass. The quark mass suppression can be lifted in two ways: (1) by corrections to the dimension-six operator involving the anomalous triangle diagram, and (2) by going to dimension-eight. We address the first of these possibilities by evaluating the anomalous triangle diagram, which contributes to neutralino annihilation to gluon pairs. We relate the triangle diagram via the anomaly equation to the decay of a pseudoscalar into two gluons and use the Adler–Bardeen theorem to extract the next-to-leading order (NLO) QCD corrections to χ χ → g g from the known corrections to pseudoscalar decay. The strong dependence of the dominant χ χ → q q ¯ cross section on the relative velocity of the neutralinos makes these NLO corrections unimportant at χ decoupling but significant today.
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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 | 0.003 |
| 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 | 0.002 | 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".