SUPERMASSIVE BLACK HOLES AND THEIR HOST GALAXIES. II. THE CORRELATION WITH NEAR-INFRARED LUMINOSITY REVISITED
Bibliographic record
Abstract
We present an investigation of the scaling relations between supermassive black hole (SMBH) masses, M • , and their host galaxies' K -band bulge ( L bul ) and total ( L tot ) luminosities. The wide-field WIRCam imager at the Canada–France–Hawaii–Telescope was used to obtain the deepest and highest resolution near-infrared images available for a sample of 35 galaxies with securely measured M • , selected irrespective of Hubble type. For each galaxy, we derive bulge and total magnitudes using a two-dimensional image decomposition code that allows us to account, if necessary, for large- and small-scale disks, cores, bars, nuclei, rings, envelopes, and spiral arms. We find that the present-day M • – L bul and M • – L tot relations have consistent intrinsic scatter, suggesting that M • correlates equally well with bulge and total luminosity of the host. Our analysis provides only mild evidence of a decreased scatter if the fit is restricted to elliptical galaxies. The log-slopes of the M • – L bul and M • – L tot relations are 0.75 ± 0.10 and 0.92 ± 0.14, respectively. However, while the slope of the M • – L bul relation depends on the detail of the image decomposition, the characterization of M • – L tot does not. Given the difficulties and ambiguities of decomposing galaxy images into separate components, our results indicate that L tot is more suitable as a tracer of SMBH mass than L bul , and that the M • – L tot relation should be used when studying the co-evolution of SMBHs and galaxies.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".