Connecting Galaxy Evolution, Star Formation, and the Cosmic X‐Ray Background
Bibliographic record
Abstract
As a result of deep hard X-ray observations by Chandra and XMM-Newton , a significant fraction of the CXRB has been resolved into individual sources. These objects are almost all AGNs, and optical follow-up observations find that they are mostly obscured type 2 AGNs, have Seyfert-like X-ray luminosities, and peak in redshift at z ~ 0.7. Since this redshift is similar to the peak in the cosmic star formation rate, this paper proposes that the obscuring material required for AGN unification is regulated by star formation within the host galaxy. We test this idea by computing CXRB synthesis models with a ratio of type 2 to type 1 AGNs that is a function of both z and 2-10 keV X-ray luminosity, L X . The evolutionary models are constrained by parameterizing the observed type 1 AGN fractions from the recent work by Barger et al. The parameterization that simultaneously best accounts for Barger's data, the CXRB spectrum, and the X-ray number counts has a local, low- L X type 2/type 1 ratio of 4 and predicts a type 2 AGN fraction that evolves as (1 + z ) 0.3 . This particular evolution predicts a type 2/type 1 ratio of 1-2 for log L X > 44, and thus the deep X-ray surveys are missing about half the obscured AGNs with these luminosities. These objects are likely to be Compton thick. Overall, these calculations show that the current data strongly support a change to the AGN unification scenario in which the obscuration is connected with star formation in the host galaxy rather than a molecular torus alone. The evolution of the obscuration implies a close relationship between star formation and AGN fueling.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".