Evidence of a Supermassive Black Hole in the Galaxy NGC 1023 from the Nuclear Stellar Dynamics
Bibliographic record
Abstract
We analyze the nuclear stellar dynamics of the SB0 galaxy NGC 1023, utilizing observational data both from the Space Telescope Imaging Spectrograph aboard the Hubble Space Telescope and from the ground. The stellar kinematics measured from these long-slit spectra show rapid rotation ( V ≈ 70 km s -1 at a distance of 0 1 = 4.9 pc from the nucleus) and increasing velocity dispersion toward the nucleus (where σ = 295 ± 30 km s -1 ). We model the observed stellar kinematics assuming an axisymmetric mass distribution with both two and three integrals of motion. Both modeling techniques point to the presence of a central dark compact mass (which presumably is a supermassive black hole) with confidence greater than 99%. The isotropic two-integral models yield a best-fitting black hole mass of (6.0 ± 1.4) × 10 7 M ☉ and mass-to-light ratio ( M / L V ) of 5.38 ± 0.08, and the goodness of fit (χ 2 ) is insensitive to reasonable values for the galaxy's inclination. The three-integral models, which nonparametrically fit the observed line-of-sight velocity distribution as a function of position in the galaxy, suggest a black hole mass of (3.9 ± 0.4) × 10 7 M ☉ and M / L V of 5.56 ± 0.02 (internal errors), and the edge-on models are vastly superior fits over models at other inclinations. The internal dynamics in NGC 1023 as suggested by our best-fit three-integral model shows that the velocity distribution function at the nucleus is tangentially anisotropic, suggesting the presence of a nuclear stellar disk. The nuclear line-of-sight velocity distribution has enhanced wings at velocities ≥600 km s -1 from systemic, suggesting that perhaps we have detected a group of stars very close to the central dark mass.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".