Constraining dwarf spheroidal dark matter halos with the Galactic Center excess
Bibliographic record
Abstract
If the gamma-ray excess from the Galactic Center reported by Fermi-LAT is a signal from annihilating dark matter, one must question why a similar excess has not been observed in dwarf spheroidal galaxies. We use this observation to place constraints on the density profile of dwarf spheroidal galaxies under the assumption that the Galactic Center excess is in fact a signal from annihilating dark matter. We place constraints on the generalized Navarro-Frenk-White (NFW) parameter $\ensuremath{\gamma}$ and the Einasto profile parameter $\ensuremath{\alpha}$ which control the logarithmic slope of the inner regions of the halo's density profile. The best-fit halo parameters ${R}_{s}$ and ${\ensuremath{\rho}}_{s}$ are determined using stellar kinematic data for a range of $\ensuremath{\gamma}$ and $\ensuremath{\alpha}$. We determine that under these assumptions the Galactic Center excess is inconsistent with the standard NFW profile (and other ``cuspy'' profiles) for dwarf spheroidal galaxies, but is consistent with observations of cored dwarf galaxy profiles. Specifically, we find that dwarf spheroidal profiles must be less cuspy than that of the Milky Way. Models of dark matter which self-interacts through a light mediator can achieve this.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".