An INTEGRAL/SPI view of reticulum II: particle dark matter and primordial black holes limits in the MeV range
Bibliographic record
Abstract
ABSTRACT Reticulum II (Ret II) is a satellite galaxy of the Milky Way (MW) and presents a prime target to investigate the nature of dark matter (DM) because of its high mass-to-light ratio. We evaluate a dedicated INTEGRAL observation campaign data set to obtain γ-ray fluxes from Ret II and compare those with expectations from DM. Ret II is not detected in the γ-ray band 25–8000 keV, and we derive a flux limit of ${\lesssim}10^{-8}\, \mathrm{erg\, cm^{-2}\, s^{-1}}$. The previously reported 511 keV line is not seen, and we find a flux limit of ${\lesssim}1.7 \times 10^{-4}\, \mathrm{ph\, cm^{-2}\, s^{-1}}$. We construct spectral models for primordial black hole (PBH) evaporation and annihilation/decay of particle DM, and subsequent annihilation of e+s produced in these processes. We exclude that the totality of DM in Ret II is made of a monochromatic distribution of PBHs of masses ${\lesssim}8 \times 10^{15}\, \mathrm{g}$. Our limits on the velocity-averaged DM annihilation cross section into e+e− are $\langle \sigma v \rangle \lesssim 5 \times 10^{-28} \left(m_{\rm DM} / \mathrm{MeV} \right)^{2.5}\, \mathrm{cm^3\, s^{-1}}$. We conclude that analysing isolated targets in the MeV γ-ray band can set strong bounds on DM properties without multi-year data sets of the entire MW, and encourage follow-up observations of Ret II and other dwarf galaxies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".