Prospects of future MeV telescopes in probing weak-scale dark matter
Bibliographic record
Abstract
Galactic weak-scale Dark Matter (DM) particles annihilating into lepton-rich channels not only produce gamma-rays via prompt radiation but also generate abundant energetic electrons and positrons, which subsequently emit through bremsstrahlung or inverse Compton scattering (collectively called “secondary-radiation photons”). While the prompt gamma-rays concentrate at high-energy, the secondary emission falls in the MeV range, which a number of upcoming experiments (AMEGO, E-ASTROGAM, MAST…) will probe. We investigate the sensitivity of these future telescopes for weak-scale DM, focusing for definiteness on observations of the galactic center. We find that they have the potential of probing a wide region of the DM parameter space which is currently unconstrained. Namely, in rather optimistic configurations, future MeV telescopes could probe thermally-produced DM with a mass up to the TeV range, or GeV DM with an annihilation cross section 2 to 3 orders of magnitude smaller than the current bounds, precisely thanks to the significant leverage provided by their sensitivity to secondary emissions. We comment on astrophysical and methodological uncertainties, and compare with the reach of high-energy gamma ray experiments.
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".