X-ray observations of high redshift active galactic nuclei and galaxy clusters
Bibliographic record
Abstract
X-ray surveys of three Canada-France Redshift Survey (CFRS) fields using XMM-Newton are presented, with the aim of studying the Active Galactic Nuclei (AGN) and galaxy cluster populations in these fields. The X-ray sources detected in these surveys resolve 51% of the X-ray background (XRB) in the 0.5 10 keV X-ray band. The relation between the X-ray and sub-mm extra-galactic backgrounds is investigated using a combination of X-ray data and sub-mm data. The X-ray properties of the sub-mm sources and visa versa indicate that the XRB is domi nated by accretion onto super-massive black holes, while the sub-mm background is dominated by dust-obscured star formation. X-ray sources are identified with optical objects using the Canada-France Deep Fields (CFDF) survey, which covers the majority of two fields. The redshift dis tribution of the AGN shows a clear peak at z 0.7. The 2-point angular correlation function, W(6), is calculated for the identified AGN but no significant clustering is detected. However, the results are consis tent with X-ray selected AGN being good tracers of the normal, inactive galaxy population. The environments of moderate luminosity AGN at z 0.5 are investigated, using the clustering amplitude measure Bgq and close pair counts. When compared to a control sample of equivalent inactive galaxies no difference is found between the respective environments. Minor mergers with low mass companions is therefore the most likely mechanism by which these AGN are fuelled. A new method for finding high redshift, optically selected, galaxy clusters is presented and is compared to X-ray selection. It is found that most optically selected clusters may have lower than expected X-ray luminosities suggesting that they are dynamically young compared to X-ray selected clusters.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".