High Frequency Cluster Radio Galaxies: Luminosity Functions and Implications for SZE Selected Cluster Samples
Bibliographic record
Abstract
We study the overdensity of point sources in the direction of X-ray-selected galaxy clusters from the meta-catalogue of X-ray-detected clusters of galaxies (MCXC; 〈z〉 = 0.14) at South Pole Telescope (SPT) and Sydney University Molonglo Sky Survey (SUMSS) frequencies. Flux densities at 95, 150 and 220 GHz are extracted from the 2500 deg2 SPT-SZ survey maps at the locations of SUMSS sources, producing a multifrequency catalogue of radio galaxies. In the direction of massive galaxy clusters, the radio galaxy flux densities at 95 and 150 GHz are biased low by the cluster Sunyaev–Zel’dovich Effect (SZE) signal, which is negative at these frequencies. We employ a cluster SZE model to remove the expected flux bias and then study these corrected source catalogues. We find that the high-frequency radio galaxies are centrally concentrated within the clusters and that their luminosity functions (LFs) exhibit amplitudes that are characteristically an order of magnitude lower than the cluster LF at 843 MHz. We use the 150 GHz LF to estimate the impact of cluster radio galaxies on an SPT-SZ like survey. The radio galaxy flux typically produces a small bias on the SZE signal and has negligible impact on the observed scatter in the SZE mass–observable relation. If we assume there is no redshift evolution in the radio galaxy LF then 1.8 ± 0.7 per cent of the clusters with detection significance ξ ≥ 4.5 would be lost from the sample. Allowing for redshift evolution of the form (1 + z)2.5 increases the incompleteness to 5.6 ± 1.0 per cent. Improved constraints on the evolution of the cluster radio galaxy LF require a larger cluster sample extending to higher redshift.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".