Brightest x-ray clusters of galaxies in the CFHTLS wide fields: catalog and optical mass estimator
Bibliographic record
Abstract
The Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) presents a unique data set for weak-lensing studies, having high-quality imaging and deep multiband photometry. We have initiated an XMM-CFHTLS project to provide X-ray observations of the brightest X-ray-selected clusters within the wide CFHTLS area. Performance of these observations and the high quality of CFHTLS data allow us to revisit the identification of X-ray sources, introducing automated reproducible algorithms, based on the multicolor red sequence finder. We have also introduced a new optical mass proxy. We provide the calibration of the red sequence observed in the Canada–France–Hawaii filters and compare the results with the traditional single-color red sequence and photo-z. We test the identification algorithm on the subset of highly significant XMM clusters and identify 100% of the sample. We find that the integrated z-band luminosity of the red sequence galaxies correlates well with the X-ray luminosity, with a surprisingly small scatter of 0.20 dex. We further use the multicolor red sequence to reduce spurious detections in the full XMM and ROSAT All-Sky Survey (RASS) data sets, resulting in catalogs of 196 and 32 clusters, respectively. We made spectroscopic follow-up observations of some of these systems with HECTOSPEC and in combination with BOSS DR9 data. We also describe the modifications needed to the source detection algorithm in order to maintain high purity of extended sources in the shallow X-ray data. We also present the scaling relation between X-ray luminosity and velocity dispersion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".