New Techniques for Relating Dynamically Close Galaxy Pairs to Merger and Accretion Rates: Application to the Second Southern Sky Redshift Survey
Bibliographic record
Abstract
The galaxy merger and accretion rates, and their evolution with time, provide important tests for models of galaxy formation and evolution. Close pairs of galaxies are the best available means of measuring redshift evolution in these quantities. In this study, we introduce two new pair statistics, which relate close pairs to the merger and accretion rates. We demonstrate the importance of correcting these (and other) pair statistics for selection effects related to sample depth and completeness. In particular, we highlight the severe bias that can result from the use of a flux-limited survey. The first statistic, N c , gives the number of companions per galaxy within a specified range in absolute magnitude. N c is directly related to the galaxy merger rate. The second statistic, L c , gives the total luminosity in companions, per galaxy. This quantity can be used to investigate the mass accretion rate. Both N c and L c are related to the galaxy correlation function ξ and luminosity function ϕ( M ) in a straightforward manner. Both statistics have been designed with selection effects in mind. We outline techniques that account for various selection effects and demonstrate the success of this approach using Monte Carlo simulations. If one assumes that clustering is independent of luminosity (which is appropriate for reasonable ranges in luminosity), then these statistics may be applied to flux-limited surveys. These techniques are applied to a sample of 5426 galaxies in the Second Southern Sky Redshift Survey (SSRS2). This is the first large, well-defined low- z survey to be used for pair statistics. Using close (5 h -1 kpc ≤ r p ≤ 20 h -1 kpc) dynamical (Δ v ≤ 500 km s -1 ) pairs, we find N c (-21 ≤ M B ≤ -18) = 0.0226 ± 0.0052 and L c (-21 ≤ M B ≤ -18) = 0.0216 ± 0.0055 × 10 10 h 2 L ☉ at z = 0.015. These are the first secure estimates of low-redshift pair statistics, and they will provide local benchmarks for ongoing and future pair studies. If N c remains fixed with redshift, simple assumptions imply that ~6.6% of present day galaxies with -21 ≤ M B ≤ -18 have undergone mergers since z = 1. When applied to redshift surveys of more distant galaxies, these techniques will yield the first robust estimates of evolution in the galaxy merger and accretion rates.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".