WHERE DO WET, DRY, AND MIXED GALAXY MERGERS OCCUR? A STUDY OF THE ENVIRONMENTS OF CLOSE GALAXY PAIRS IN THE DEEP2 GALAXY REDSHIFT SURVEY
Bibliographic record
Abstract
We study the environments of wet, dry, and mixed galaxy mergers at 0.75 < z < 1.2 using close pairs in the DEEP2 Galaxy Redshift Survey. We find that the typical environment of dry and mixed merger candidates is denser than that of wet mergers, mostly due to the color–density relation. While the galaxy companion rate ( N c ) is observed to increase with overdensity, using N -body simulations, we find that the fraction of pairs that will eventually merge decreases with the local density, predominantly because interlopers are more common in dense environments. After taking into account the merger probability of pairs as a function of local density, we find only marginal environment dependence of the galaxy merger rate for wet mergers. On the other hand, the dry and mixed merger rates increase rapidly with local density due to the increased population of red galaxies in dense environments, implying that the dry and mixed mergers are most effective in overdense regions. We also find that the environment distribution of K+A galaxies is similar to that of wet mergers alone and of wet+mixed mergers, suggesting a possible connection between K+A galaxies and wet and/or wet+mixed mergers. Based on our results, we therefore expect that the properties, including structures and masses, of red-sequence galaxies should be different between those in underdense regions and those in overdense regions since the dry mergers are significantly more important in dense environments. We conclude that, as early as z ∼ 1, high-density regions are the preferred environment in which dry mergers occur, and that present-day red-sequence galaxies in overdense environments have, on average, undergone 1.2 ± 0.3 dry mergers since this time, accounting for (38 ± 10)% of their mass accretion in the last 8 billion years. The main uncertainty in this finding is the conversion from the pair fraction to the galaxy merger rate, which is possibly as large as a factor of 2. Our findings suggest that dry mergers are crucial in the mass assembly of massive red galaxies in dense environments, such as brightest cluster galaxies in galaxy groups and clusters.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".