Quantified H i morphology - IV. The merger fraction and rate in WHISP
Bibliographic record
Abstract
The morphology of the atomic hydrogen (H i) disc of a spiral galaxy is the first component to be disturbed by a gravitational interaction such as a merger between two galaxies. We use a simple parametrization of the morphology of H i column density maps of the Westerbork observations of neutral Hydrogen in Irregular and SPiral galaxies (WHISP) project to select those galaxies that are likely undergoing a significant interaction. Merging galaxies occupy a particular part of parameter space defined by Asymmetry (A), the relative contribution of the 20 per cent brightest pixels to the second-order moment of the column density map (M20) and the distribution of the second-order moment over all the pixels (GM). Based on their H i morphology, we find that 13 per cent of the WHISP galaxies are in an interaction (Concentration–M20) and only 7 per cent are based on close companions in the data cube. This apparent discrepancy can be attributed to the difference in visibility time-scales: mergers are identifiable as close pairs for 0.5 Gyr but are identifiable for ∼1 Gyr by their disturbed H i morphology. Expressed as volume merger rates, the two estimates agree very well: 7 and 6.8 × 10−3 mergers Gyr−1 Mpc−3 for paired and morphologically disturbed H i discs, respectively. The consistency of our merger fractions with those published for bigger surveys such as the Sloan Digital Sky Survey shows that H i morphology can be a very viable way to identify mergers in large H i surveys. The relatively high value for the volume merger rate may be a bias in the selection or WHISP volume. The expected abundance in high-resolution H i data by the planned South African Karoo Array Telescope (MeerKAT), Australian SKA Pathfinder (ASKAP) and Westerbork Synthesis Radio Telescope/APERture Tile In Focus instrument (WSRT/APERTIF) radio observatories will reveal the importance of mergers in the local Universe and, with the advent of the Square Kilometer Array (SKA), over cosmic times.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".