Constraints on dark matter annihilation and turbulent reacceleration set by high-frequency observations of the radio halo in the Coma cluster
Bibliographic record
Abstract
ABSTRACT We study the impact of the recent observation of the radio halo in the Coma galaxy cluster at 6.6 GHz with the Sardinia Radio Telescope on models based on turbulent reacceleration of electrons produced in dark matter annihilation processes. Observing at that frequency it is possible to obtain information on the electrons spectrum at energies where the effect of turbulent reacceleration becomes sub-dominant with respect to energy losses, and therefore to obtain information on the properties of seed electrons. Under the assumption that dark matter particles are neutralino-like particles annihilating at a rate close to the maximum allowed by Fermi-Large Area Telescope (LAT) upper limits in dwarf galaxies, we obtain some constraints on the intensity of the reacceleration and on the value of the neutralino mass. In particular, models with mass of the order of 10 GeV are generally disfavoured, because they produce a high-frequency radio spectrum that can not reproduce the possible flattening observed between 5 and 6.6 GHz; on the other hand, models with mass of the order of 500 GeV, in order to reproduce the observed spectrum at frequencies below 100 MHz, require a reacceleration phase longer than $10^9$ yr, which would require more than one event responsible of the generation of turbulence in the cluster. The resulting optimal mass values are in the range 100–200 GeV, with a preference for the quark annihilation channel.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".