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arxiv: 2606.31140 · v1 · pith:ZR5S5N7Mnew · submitted 2026-06-30 · 🌌 astro-ph.GA

Deep Extragalactic VIsible Legacy Survey (DEVILS): Morphologically-selected galaxy merger fractions and their direct comparison to close-pair samples

Melissa F. Fuentealba-Fuentes , Luke J. M. Davies , Aaron S. G. Robotham , Sabine Bellstedt , Claudia D. P. Lagos , Michael J. I. Brown , Malgorzata Siudek This is my paper

Pith reviewed 2026-07-01 05:09 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords galaxy mergersmerger fractionsmorphological classificationclose pairsgalaxy evolutionDEVILS surveyredshift evolutionHST imaging
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The pith

Morphological identification yields consistently higher galaxy merger fractions than close-pair counting from redshift 0.2 to 0.9.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper measures galaxy merger fractions in the DEVILS D10 field using both visual classification and automated non-parametric statistics on HST images, then compares those fractions directly to earlier close-pair results over the same redshift range. Morphological methods return higher fractions at every redshift, with little overlap between the two identification approaches. The authors attribute the difference to the distinct merger stages each technique captures, noting that morphological disturbances appear later than close-pair interactions and persist over different timescales. This direct comparison highlights systematic offsets between methods that affect how merger rates are inferred across cosmic time.

Core claim

Galaxy merger fractions derived from morphological disturbances are consistently higher than those from close-pair counts at all redshifts. This potentially reflects how each method probes different stages of the merger process, with distinct observability timescales, as well as the fact that morphologically disturbed galaxies, at a given redshift, are typically the later-stage descendants of close-pairs from earlier epochs.

What carries the argument

Direct comparison of merger fractions from visual and CAS/Gini-M20 morphological classification (including unsharp-masked asymmetry) versus close-pair samples in the same DEVILS volume.

If this is right

  • Morphologically selected merger fractions exceed close-pair fractions at every redshift from 0.2 to 0.9.
  • Visually and automatically identified morphological samples show relatively little overlap.
  • Morphologically disturbed galaxies at a given redshift are later-stage descendants of close-pairs observed at earlier epochs.
  • Different identification techniques carry distinct sensitivities that must be accounted for when tracing merger evolution.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Merger rate calculations that rely on a single technique may systematically under- or over-estimate the true frequency depending on the redshift range.
  • Combining morphological and close-pair indicators could provide a more complete census by covering both early and late merger phases.
  • Future surveys with higher-resolution imaging might reduce contamination in morphological samples and tighten the comparison.

Load-bearing premise

That the observed morphological disturbances are produced by galaxy mergers rather than other processes and that the two samples can be compared without large corrections for selection or completeness.

What would settle it

A measurement demonstrating that the average observability timescale for morphological disturbances is equal to or shorter than the timescale for close-pair visibility would remove the proposed explanation for the higher morphological fractions.

Figures

Figures reproduced from arXiv: 2606.31140 by Aaron S. G. Robotham, Claudia D. P. Lagos, Luke J. M. Davies, Malgorzata Siudek, Melissa F. Fuentealba-Fuentes, Michael J. I. Brown, Sabine Bellstedt.

Figure 1
Figure 1. Figure 1: The stellar mass/redshift bin used to estimate the galaxy merger fractions in the D10 (COSMOS) field. The grey region shows the bin adopted in Fuentealba-Fuentes et al. (2025), which ensures stellar mass and colour completeness. The pink region indicates the bin used in this work, defined to enclose the resulting stellar masses (green squares and circles), assuming that all the close-pairs identified in Fu… view at source ↗
Figure 2
Figure 2. Figure 2: Examples of cutouts from the HST/ACS mosaic. Panels are cat￾egorized by merger classification: both visual and automated, visual only, automated only, and non-mergers. Here, "Visual" indicates galaxies identi￾fied as mergers by all four classifiers, while no visual confirmation indicates galaxies classified as non-mergers by all. 2 for examples). These cutouts were used for both the visual and automated cl… view at source ↗
Figure 3
Figure 3. Figure 3: Examples of galaxies visually classified as mergers. Each row represents the consensus of 2, 3, or all 4 classifiers. Galaxies were randomly selected within each category, with their redshifts shown in the corner of each image. 4 VISUAL CLASSIFICATION We first identified mergers by visually selecting galaxies that show evidence of an ongoing or recent major interaction (stellar mass ratio ≥ 1 : 3), specifi… view at source ↗
Figure 4
Figure 4. Figure 4: Galaxy merger fractions using the D10 (COSMOS) sample. Top-left: Galaxy merger fractions estimated from close-pair selections, as presented in Fuentealba-Fuentes et al. (2025) are shown in different colours. Predictions from the Eagle and IllustrisTNG simulations are also shown. Works from the literature based on close-pair samples are shown in grey. Top-right: Galaxy merger fractions estimated from visual… view at source ↗
Figure 5
Figure 5. Figure 5 [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Concentration and asymmetry parameters measured from original and unsharp-masked images for 0.55 < 𝑧 < 0.73 galaxies, illustrating the impact of software and images on measured parameters. The concentration index is derived using statmorph in all panels. In the top row, the asymmetry index is calculated using statmorph, while in the bottom row it is measured using ProFound. The left column shows the asymme… view at source ↗
Figure 7
Figure 7. Figure 7: Examples of unsharp-masked images obtained using profoundImDiff. Panels are categorized by merger classification: both vi￾sual and automated, visual only, automated only, and non-mergers. Here, "Visual" indicates galaxies identified as mergers by all four classifiers, while no visual confirmation indicates galaxies classified as non-mergers by all. Red squares indicate galaxies classified as mergers by the… view at source ↗
Figure 8
Figure 8. Figure 8: Non-parametric merger selection. The top row shows the asymmetry using the unsharp-masked images produced using profoundImDiff vs. the concentration from statmorph. The bottom row shows the Gini vs. 𝑀20 space, both from statmorph. Grey points represent the full galaxy sample within the full redshift range. Galaxies visually classified as mergers are shown as blue points, with light to dark shades indicatin… view at source ↗
Figure 9
Figure 9. Figure 9: Non-parametric merger selection. The first two columns on the left show the asymmetry vs. concentration and Gini vs. 𝑀20 spaces, respectively, using the unsharp-masked images produced using profoundImDiff. The two rightmost columns show the same parameter spaces measured on images that were first downgraded in physical resolution and then unsharp-masked using profoundImBlur and profoundImDiff, respectively… view at source ↗
Figure 11
Figure 11. Figure 11: Examples of physical resolution matched images derived from profoundImblur. Panels are categorized by merger classification: both vi￾sual and automated, visual only, automated only, and non-mergers. Here, "Visual" indicates galaxies identified as mergers by all four classifiers, while no visual confirmation indicates galaxies classified as non-mergers by all. (JWST) could mitigate these effects by probing… view at source ↗
Figure 10
Figure 10. Figure 10: Galaxy merger fractions using the D10 (COSMOS) sample. galaxy merger fractions estimated from close-pair selections, as presented in Fuentealba-Fuentes et al. (2025), are shown as grey circles and filled and unfilled grey diamonds. Top: Galaxy merger fractions estimated from auto￾mated classifications using asymmetry from ProFound, and concentration, Gini, and 𝑀20 from statmorph. Filled red stars correspo… view at source ↗
Figure 12
Figure 12. Figure 12: Venn diagrams showing the overlap between the automated sample and our broader visual sample (defined as galaxies with two or more visual merger flags) for each redshift bin. by high-confidence morphological disturbances rather than noise or contamination. However, the overlap between this automated sample and our broader visual sample, which includes galaxies with two or more visual merger flags (all blu… view at source ↗
Figure 13
Figure 13. Figure 13: Examples of galaxies classified as mergers by automated methods only, but considered morphologically ambiguous by the classifiers after visual re-inspection. The original number of classifiers identifying each system as a merger is shown in each panel, along with the source redshift. without spectroscopic follow-up, whereas close-pair identification requires high spectroscopic completeness, which is obser… view at source ↗
read the original abstract

Galaxy mergers are a central driver of galaxy evolution across cosmic time, and thus, quantifying their frequency is critical for constraining hierarchical models of galaxy formation. Motivated by the need to robustly quantify these fractions and their evolution, we build on our previous close-pair analysis by exploring morphological identification techniques within the Deep Extragalactic VIsible Legacy Survey (DEVILS), using the D10 (COSMOS) field, which covers an area of $1.47$ deg$^2$. While close-pairs trace the early stages of galaxy interactions, morphological methods probe more advanced phases of the merging process, including systems with disturbed structures and post-merger remnants. We present galaxy merger fractions over the redshift range $0.2 < z < 0.9$ using visual classification and automated identification based on non-parametric statistics: concentration ($C$), asymmetry ($A$), smoothness ($S$), Gini ($G$), and $M_{20}$, applied to HST/ACS imaging. To enhance the detection of subtle structural perturbations, we measure asymmetry on unsharp-masked images. We find relatively little overlap between visually and automatically identified samples, which highlights their distinct sensitivities and limitations. Moreover, galaxy merger fractions derived from morphological disturbances are consistently higher than those from close-pair counts at all redshifts. This potentially reflects how each method probes different stages of the merger process, with distinct observability timescales, as well as the fact that morphologically disturbed galaxies, at a given redshift, are typically the later-stage descendants of close-pairs from earlier epochs. This comparison allows us to examine systematic differences between identification techniques and assess how they impact the observed evolution of the galaxy merger fraction.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper analyzes galaxy merger fractions in the DEVILS D10 (COSMOS) 1.47 deg² field over 0.2 < z < 0.9 using visual classification and automated non-parametric statistics (C, A, S, G, M20 with unsharp-masked asymmetry) on HST/ACS imaging. It reports consistently higher merger fractions from morphological disturbances than from prior close-pair counts at all redshifts, with little overlap between visual and automated morphological samples, and interprets this as evidence that the methods probe different merger stages with distinct observability timescales.

Significance. If the central comparison holds after accounting for selection effects, the result would clarify systematic differences between merger identification techniques and their impact on inferred merger evolution, aiding constraints on hierarchical galaxy formation models. The multi-technique approach within a single large-area field is a positive aspect for internal consistency checks.

major comments (2)
  1. [Results (comparison to close-pairs)] Results section (comparison to close-pairs): The claim that morphological fractions exceed close-pair fractions at all redshifts is load-bearing on the assumption that both samples have been corrected for their respective selection functions and completeness within the identical 1.47 deg² volume; this correction and its impact on the numerical comparison are not demonstrated.
  2. [Methods (sample identification)] Methods (sample identification): The interpretation that elevated morphological fractions reflect later-stage mergers requires quantitative estimates of contamination from non-merger processes (internal instabilities, minor interactions, projection); the reported low overlap between visual and automated (CAS + unsharp-masked) samples indicates differing sensitivities that could admit such contaminants, directly affecting the central claim.
minor comments (2)
  1. [Abstract] Abstract and results: Provide quantitative overlap fractions (e.g., percentages or Venn diagram statistics) between visual and automated samples rather than the qualitative statement 'relatively little overlap'.
  2. [Figures and results text] Figure captions and text: Ensure error bars, sample sizes, and statistical significance of the reported difference in fractions are explicitly stated when comparing morphological and close-pair results.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thorough review and valuable comments on our manuscript. We address each of the major comments in turn below, providing clarifications and indicating where revisions will be made to strengthen the paper.

read point-by-point responses

  1. Referee: Results section (comparison to close-pairs): The claim that morphological fractions exceed close-pair fractions at all redshifts is load-bearing on the assumption that both samples have been corrected for their respective selection functions and completeness within the identical 1.47 deg² volume; this correction and its impact on the numerical comparison are not demonstrated.

    Authors: The referee correctly identifies that the direct numerical comparison relies on consistent application of selection corrections. The close-pair sample from our prior work was selected and corrected within the same D10 field and redshift range, and the morphological sample uses identical volume limits. However, the manuscript does not include an explicit side-by-side demonstration of the corrected values. We will revise the results section to include a table presenting the merger fractions before and after corrections for both methods, ensuring the comparison is transparent and the impact is quantified. revision: yes

  2. Referee: Methods (sample identification): The interpretation that elevated morphological fractions reflect later-stage mergers requires quantitative estimates of contamination from non-merger processes (internal instabilities, minor interactions, projection); the reported low overlap between visual and automated (CAS + unsharp-masked) samples indicates differing sensitivities that could admit such contaminants, directly affecting the central claim.

    Authors: We agree that quantitative estimates of contamination would provide a more robust foundation for the interpretation. The low overlap is discussed in the paper as indicating complementary sensitivities to different merger phases rather than a source of contamination. While we cannot provide new quantitative contamination fractions without additional simulations or data, we will expand the methods and discussion sections to include a more detailed assessment of potential non-merger contaminants based on the criteria used (e.g., visual inspection thresholds and CAS parameter cuts), and reference relevant literature on contamination rates in similar studies. This will be a partial revision as full quantification is beyond the scope of the current analysis. revision: partial

Circularity Check

0 steps flagged

Minor self-citation to prior close-pair analysis; purely observational comparison with no derivation reducing to inputs

full rationale

The paper reports direct observational measurements of merger fractions via visual classification and non-parametric CAS/GM20 statistics on HST imaging, then compares the resulting fractions to close-pair counts from earlier work by overlapping authors. No equations, fitted parameters, or derivations are presented that reduce by construction to the inputs; the central result is a numerical contrast between two independent selection techniques. The reference to 'our previous close-pair analysis' constitutes a self-citation but is not load-bearing for any claimed derivation or uniqueness result. The study remains self-contained against external benchmarks as an empirical comparison.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard assumptions that morphological disturbances trace mergers and that the two identification methods have different but quantifiable observability windows; no free parameters or invented entities are visible in the abstract.

axioms (2)
  • domain assumption Morphological disturbances (asymmetry, low smoothness, high M20) are produced by galaxy mergers rather than other dynamical processes.
    Invoked when interpreting higher morphological fractions as later-stage mergers.
  • domain assumption The DEVILS D10 field is representative for merger statistics at 0.2 < z < 0.9.
    Required to generalize the measured fractions beyond the single 1.47 deg^{2} field.

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Reference graph

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