Bounds on Cross-sections and Lifetimes for Dark Matter Annihilation and Decay into Charged Leptons from Gamma-ray Observations of Dwarf Galaxies
Bibliographic record
Abstract
We provide conservative bounds on the dark matter cross-section and lifetime from final state radiation produced by annihilation or decay into charged leptons, either directly or via an intermediate particle $ϕ$. Our analysis utilizes the experimental gamma-ray flux upper limits from four Milky Way dwarf satellites: HESS observations of Sagittarius and VERITAS observations of Draco, Ursa Minor, and Willman 1. Using 90% confidence level lower limits on the integrals over the dark matter distributions, we find that these constraints are largely unable to rule out dark matter annihilations or decays as an explanation of the PAMELA and ATIC/PPB-BETS excesses. However, if there is an additional Sommerfeld enhancement in dwarfs, which have a velocity dispersion ~10 to 20 times lower than that of the local Galactic halo, then the cross-sections for dark matter annihilating through $ϕ$'s required to explain the excesses are very close to the cross-section upper bounds from Willman 1. Dark matter annihilation directly into $τ$'s is also marginally ruled out by Willman 1 as an explanation of the excesses, and the required cross-section is only a factor of a few below the upper bound from Draco. Finally, we make predictions for the gamma-ray flux expected from the dwarf galaxy Segue 1 for the Fermi Gamma-ray Space Telescope. We find that for a sizeable fraction of the parameter space in which dark matter annihilation into charged leptons explains the PAMELA excess, Fermi has good prospects for detecting a gamma-ray signal from Segue 1 after one year of observation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".