The<i>Planck</i>clusters in the LOFAR sky
Bibliographic record
Abstract
Context.The footprint of the recent second data release of the LOFAR Two-metre Sky Survey (LoTSS-DR2) covers 309PlanckSunyaev-Zeldovich (SZ) selected galaxy clusters, 83 of which host a radio halo and 26 host a radio relic(s). It provides an excellent opportunity to statistically study the properties of extended cluster radio sources, especially their connection with merging activities. Aims.We quantify cluster dynamic states to investigate their relation with the occurrence of extended radio sources. We also search for connections between intracluster medium (ICM) turbulence and nonthermal characteristics of radio halos in the LoTSS-DR2. Methods.We analyzedXMM-NewtonandChandraarchival X-ray data of allPlanckSZ clusters in the footprint of LoTSS-DR2. We computed concentration parameters and centroid shifts that indicate the dynamic states of the clusters. We also performed a power spectral analysis of the X-ray surface brightness fluctuations to investigate large-scale density perturbations and estimate the turbulent velocity dispersion. Furthermore, we searched for the relation between radio halo power and the turbulent dissipation flux channeled to particle acceleration. Results.The concentration parameters measured by the two telescopes agree well, but the centroid shift has a larger scatter. The surface brightness power spectral analysis results in a large scatter of the surface brightness and density fluctuation amplitudes. We therefore only found a marginal anticorrelation between density fluctuations and cluster relaxation state, and we did not find a correlation between density fluctuations and radio halo power. Nevertheless, the injected power for particle acceleration calculated from turbulent dissipation is correlated with the radio halo power, where the best-fit unity slope supports the turbulent (re)acceleration scenario. Two different acceleration models, transit-time damping and adiabatic stochastic acceleration, cannot be distinguished due to the large scatter of the estimated turbulent Mach number. We introduced a new quantity [kBT ⋅ YX]rRH, which is proportional to the turbulent acceleration power assuming a constant Mach number. This quantity is strongly correlated with radio halo power, where the slope is also unity.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.001 |
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".