The thermal and non-thermal components within and between galaxy clusters Abell 399 and Abell 401
Bibliographic record
Abstract
ABSTRACT We measure the local correlation between radio emission and Compton-y signal across two galaxy clusters, Abell 399 and Abell 401, using maps from the Low Frequency Array and the Atacama Cosmology Telescope + Planck. These data sets allow us to make the first measurement of this kind at ∼arcmin resolution. We find that the radio brightness scales as Fradio ∝ y1.5 for Abell 401 and Fradio ∝ y2.8 for Abell 399. Furthermore, using XMM–Newton data, we derive a sublinear correlation between radio and X-ray brightness for both the clusters ($F_{\mathrm{radio}} \propto F_{\rm X}^{0.7}$). Finally, we correlate the Compton-y and X-ray data, finding that an isothermal model is consistent with the cluster profiles, $y \propto F_{\rm X}^{0.5}$. By adopting an isothermal–β model, we are able, for the first time, to jointly use radio, X-ray, and Compton-y data to estimate the scaling index for the magnetic field profile, B(r) ∝ ne(r)η in the injection and re-acceleration scenarios. Applying this model, we find that the combined radio and Compton-y signal exhibits a significantly tighter correlation with the X-ray across the clusters than when the data sets are independently correlated. We find η ∼ 0.6–0.8. These results are consistent with the upper limit we derive for the scaling index of the magnetic field using rotation measure values for two radio galaxies in Abell 401. We also measure the radio, Compton-y, and X-ray correlations in the filament between the clusters but conclude that deeper data are required for a convincing determination of the correlations in the filament.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".