Early-type galaxy distances from the Fundamental Plane and surface brightness fluctuations
Bibliographic record
Abstract
We compare two of the most popular methods for deriving distances to early-type galaxies: the Fundamental Plane (FP) and surface brightness fluctuations (SBF). Distances for 170 galaxies are compared. A third set of distances is provided by predictions derived from the density field of the IRAS redshift survey. Overall there is good agreement between the different distance indicators. We investigate systematic trends in the residuals of the three sets of distance comparisons. First, we find that several nearby, low-luminosity, mainly S0 galaxies have systematically low FP distances. Because these galaxies also have Mg2 indices among the lowest in the sample, we conclude that they deviate from the FP partly because of recent star formation and consequently low mass-to-light ratios; differences in their internal velocity structures may also play a role. Secondly, we find some evidence that the ground-based I-band SBF survey distances (Tonry et al. 2001) begin to show a bias near the survey limit at cz≳3500 km s−1, which is expected for this sort of distance-limited survey, but had not previously been demonstrated. Although SBF and FP distances are affected in opposite senses by errors in the Galactic extinction estimates, we find no evidence for biases in the distances due to Galactic extinction. The tie between the Cepheid-calibrated SBF distances (Mpc) and the far-field calibrated FP distances (km s−1) yields a Hubble constant H0=68±3 km s−1 Mpc−1, while the comparison between SBF and the IRAS-reconstructed distances yields H0=74±2 km s−1 Mpc−1 (independent errors only). Thus there is a marginal inconsistency in the direct and IRAS-reconstructed ties to the Hubble flow (this can be seen independently of the SBF distances). Possible explanations include systematic errors in the redshift survey completeness estimates or in the FP aperture corrections, but at this point the best estimate of H0 may come from a simple average of the above two estimates. After revising the SBF distances downward by 2.8 per cent to be in agreement with the final set of Key Project Cepheid distances (Freedman et al.), we conclude that H0=73±4±11 km s−1 Mpc−1 from early-type galaxies, where the second error bar represents the total systematic uncertainty in the distance zero-point. We also discuss the ‘fluctuation star count’N¯≡m¯− mtot, recently introduced by Tonry et al. (2001) as a less demanding alternative to (V−I) for calibrating SBF distances. The N¯-calibrated SBF method is akin to a hybrid SBF—FP distance indicator, and we find that the use of N¯ actually improves the SBF distances. Further study of the behaviour of this quantity may provide an important new test for models of elliptical galaxy formation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".