Quiescent luminous red galaxies as cosmic chronometers: on the significance of mass and environmental dependence
Bibliographic record
Abstract
Context. Massive luminous red galaxies (LRGs) are believed to be evolving passively and can be used as cosmic chronometers to estimate the Hubble constant (the differential age method). However, different LRGs may be located in different environments. The environmental effects, if any, on the mean ages of LRGs, and the ages of the oldest LRGs at different redshift, may limit the use of the LRGs as cosmic chronometers. Aims. We aim to investigate the environmental and mass dependence of the formation of “quiescent” LRGs, selected from the Sloan Digital Sky Survey (SDSS) data release 8, and to pave the way for using LRGs as cosmic chronometers. Methods. Using the population synthesis software STARLIGHT, we derive the stellar populations in each LRG through the full spectrum fitting and obtain the mean age distribution and the mean star formation history (SFH) of those LRGs. Results. We find that there is no apparent dependence of the mean age and the SFH of quiescent LRGs on their environment, while the ages of those quiescent LRGs depend weakly on their mass. We compare the SFHs of the SDSS LRGs with those obtained from a semi-analytical galaxy formation model and find that they are roughly consistent with each other if we consider the errors in the STARLIGHT-derived ages. We find that a small fraction of later star formation in LRGs leads to a systematical overestimation (~28%) of the Hubble constant by the differential age method, and the systematical errors in the STARLIGHT-derived ages may lead to an underestimation (~ 16%) of the Hubble constant. However, these errors can be corrected by a detailed study of the mean SFH of those LRGs and by calibrating the STARLIGHT-derived ages with those obtained independently by other methods. Conclusions. The environmental effects do not play a significant role in the age estimates of quiescent LRGs; and the quiescent LRGs as a population can be used securely as cosmic chronometers, and the Hubble constant can be measured with high precision by using the differential age method.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".