The Greater Impact of Mergers on the Growth of Massive Galaxies: Implications for Mass Assembly and Evolution Since z~1
Bibliographic record
Abstract
Using deep infrared observations conducted with the MOIRCS on the Subaru Telescope in GOODS-N combined with public surveys in GOODS-S, we investigate the dependence on stellar mass, M_*, and galaxy type of the close pair fraction (5 kpc < r < 20 kpc) and implied merger rate. In common with some recent studies we find that the fraction of paired systems that could result in major mergers is low (~4%) and does not increase significantly with redshift to z~1.2, with (1+z)^{1.6 \pm 1.6}. Our key finding is that massive galaxies with M_* > 1E11 Msun are more likely to host merging companions than less massive systems (M_* ~ 1E10 Msun). We find evidence for a higher pair fraction for red, spheroidal hosts compared to blue, late-type systems, in line with expectations based on clustering at small scales. So-called "dry" mergers between early-type galaxies represent nearly 50% of close pairs with M_* > 3E10 Msun at z~0.5, but less than 30% at z~1. This result can be explained by the increasing abundance of red, early-type galaxies at these masses. We compare the volumetric merger rate of galaxies with different masses to mass-dependent trends in galaxy evolution, finding that major mergers cannot fully account for the formation of spheroidal galaxies since z~1. In terms of mass assembly, major mergers contribute little to galaxy growth below M_* ~ 3E10 Msun but are more significant among galaxies with M_* > 1E11 Msun, 30% of which have undergone mostly dry mergers over the observed redshift range. Overall, the relatively more rapid coalescence of high mass galaxies mirrors the expected hierarchical growth of halos and is consistent with recent model predictions, even if the downsizing of star formation and morphological evolution involves additional physical processes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".