Steep-spectrum AGN in eROSITA Final Equatorial-Depth Survey (eFEDS): Their host galaxies and multi-wavelength properties
Bibliographic record
Abstract
We selected sources with a steep soft-X-ray-band spectrum with a photon index of Γ > 2.5 – measured by eROSITA on board the Spectrum-Röntgen-Gamma (SRG) – from the eFEDS AGN catalogue as candidates of highly accreting supermassive black holes, and investigated their multi-wavelength properties. Among 601 bright AGN with 0.2−5 keV counts of greater than 100, 83 sources (≈14%) are classified as steep-spectrum sources. These sources have typical 0.5−2 keV luminosities of LSX ≈ 1044 erg s−1 and the majority of them are found at redshifts below z = 1. In comparison with sources with flatter spectra, these sources have, on average, a UV (or optical) to 2 keV luminosity ratio that is larger by ∼0.3 dex and bluer optical-to-UV continuum emission. They also appear to be radio quiet based on the detection rate in the FIRST and VLASS surveys. Their host galaxies – at least in the redshift range of z = 0.2 − 0.8, where the AGN–galaxy decomposition results from the Subaru Hyper Suprime-Cam imaging are available – tend to be late-type and have smaller stellar masses (M⋆ ∼ 1010.5 M⊙) than those of sources with flatter spectra. These properties are similar to those found in nearby narrow-line Seyfert 1 galaxies, in agreement with the picture that they are AGN with elevated accretion rates and are in the early growth phase of black hole and galaxy co-evolution. However, the steep-spectrum sources are not exclusively narrow-line Seyfert 1 galaxies; indeed many are broad-line Seyfert 1 galaxies, as found by a catalogue search. This suggests that these steep-spectrum sources may be black holes generally with high accretion rates but of a wide mass range, including a few objects emitting at LSX ≥ 1045 erg s−1, of which black hole masses can be close to 109 M⊙.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".