Search for dark matter lines at the Galactic Center with 14 years of Fermi data
Bibliographic record
Abstract
Dark matter (DM) in the Milky Way halo may annihilate or decay to photons, producing monochromatic gamma rays. We search for DM-induced spectral lines using 14 years of data from the Large Area Telescope onboard the Fermi Gamma-ray Space Telescope (Fermi-LAT) between 10 GeV and 2 TeV in the inner Milky Way leveraging both the spatial and spectral morphology of an expected signal. We present new constraints as strong as $⟨\ensuremath{\sigma}v⟩\ensuremath{\lesssim}6\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}30}\text{ }\text{ }{\mathrm{cm}}^{3}/\mathrm{s}$ for the two-to-two annihilations and $\ensuremath{\tau}\ensuremath{\gtrsim}{10}^{30}\text{ }\text{ }\mathrm{s}$ for one-to-two decays, representing leading sensitivity between 10 GeV and $\ensuremath{\sim}500\text{ }\text{ }\mathrm{GeV}$. We consider the implications of our line-constraints on the Galactic Center excess (GCE), which is a previously-observed excess of continuum $\ensuremath{\sim}\mathrm{GeV}$ gamma-rays that may be explained by DM annihilation. The Higgs portal and neutralinolike DM scenarios, which have been extensively discussed as possible origins of the GCE, are constrained by our work because of the lack of observed one-loop decays to two photons. More generally, we interpret our null results in a variety of annihilating and decaying DM models, such as neutralinos, gravitinos, and glueballs, showing that in many cases the line search is more powerful than the continuum, despite the continuum annihilation being at tree level.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".