Hubble space telescope imaging of the CFRS and LDSS redshift surveys - IV. Influence of mergers in the evolution of faint field galaxies from z ∼ 1
Bibliographic record
Abstract
Hubble Space Telescope images of a sample of 285 galaxies with measured redshifts from the Canada-France Redshift Survey (CFRS) and Autofib-Low Dispersion Spectrograph Survey (LDSS) redshift surveys are analysed to derive the evolution of the merger fraction out to redshifts z ∼ 1. We have performed visual and machine-based merger identifications, as well as counts of bright pairs of galaxies with magnitude differences δm ≤ 1.5 mag. We find that the pair fraction increases with redshift, with up to ∼ 20 per cent of the galaxies being in physical pairs at z ∼ 0.75-1. We derive a merger fraction varying with redshift as ∝ (1 + z)3.2±0.6, after correction for line-of-sight contamination, in excellent agreement with the merger fraction derived from the visual classification of mergers for which m = 3.4 ± 0.6. After correcting for seeing effects on the ground-based selection of survey galaxies, we conclude that the pair fraction evolves as ∝ (1 + z)2.7±0.6. This implies that an average L* galaxy will have undergone 0.8-1.8 merger events from z = 1 to z = 0, with 0.5 to 1.2 merger events occuring in a 2-Gyr time-span at around z ∼ 0.9. This result is consistent with predictions from semi-analytical models of galaxy formation. From the simple coaddition of the observed luminosities of the galaxies in pairs, physical mergers are computed to lead to a brightening of 0.5 mag for each pair on average, and a boost in star formation rate of a factor of 2, as derived from the average [O II] equivalent widths. Mergers of galaxies are therefore contributing significantly to the evolution of both the luminosity function and luminosity density of the Universe out to z ∼ 1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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 teacher head, 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".