Dust and Gas Obscuration in ELAIS Deep X‐Ray Survey Reddened Quasars
Bibliographic record
Abstract
Hard X-ray surveys have uncovered a large population of heavily obscured AGNs. They also reveal a population of quasars with moderate obscuration at both visible and X-ray wavelengths. We use Chandra -selected samples of quasars from the ELAIS Deep X-ray Survey (EDXS) and the Chandra Deep Field-North to investigate the obscuration toward the nuclei of moderately obscured AGNs. We find an inverse correlation between the optical-to-X-ray flux ratio and the X-ray hardness ratio that can be interpreted as being due to obscuration at visible and X-ray wavelengths. We present detailed optical and near-infrared data for a sample of optically faint ( R > 23) quasars from the EDXS. These are used to constrain the amount of rest-frame UV/optical reddening toward these quasars. It is found that optically faint quasars are mostly faint because of obscuration, not because they are intrinsically weak. After correcting for reddening, the optical magnitudes of most of these quasars are similar to the brighter quasars at these X-ray fluxes. Combining with gas column densities inferred from the X-ray observations, we consider the gas-to-dust ratios of the obscuring matter. We find that the quasars generally have higher gas-to-dust absorption than that seen in the Milky Way, similar to what has been found for nearby Seyfert galaxies. We consider the possible existence of a large population of X-ray sources that have optical properties of type 1 (unobscured) quasars but X-ray properties of type 2 (obscured) quasars. However, we find that such sources only contribute about 6% of the 0.5-8 keV X-ray background. Finally, we show that the observed distribution of optical-to-X-ray flux ratios of quasars at z > 1 is skewed to low values compared to the intrinsic distribution as a result of the fact that the observed-frame R -band light is emitted in the UV and is more easily obscured than hard X-rays.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".