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Non-parametric Morphologies of Galaxies in the EAGLE Simulation

T0 review · 3 major / 6 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read Simulated EAGLE galaxies reproduce observed optical morphologies, except their asymmetry values are systematically too high.

desk verdict Solid validation of EAGLE optical morphologies with one honest but untested caveat: the asymmetry excess may be a mock-image smoothing artifact. read the letter →

arxiv 1908.10936 v2 pith:BXGL3SJL submitted 2019-08-28 astro-ph.GA

Lucas A. Bignone , Susana E. Pedrosa , James W. Trayford , Patricia B. Tissera , Leonardo J. Pellizza This is my paper · ORCID
classification astro-ph.GA
keywords galaxymorphologynon-parametricstatisticsGinicoefficientM20asymmetryEAGLEsimulationmockimagesGAMAsurvey
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper asks whether the optical shapes of galaxies produced by the EAGLE cosmological simulation look like real galaxies when rendered as realistic telescope images. Using non-parametric statistics (Gini, M20, Concentration, and Asymmetry) on g-band light distributions, the authors find that simulated galaxies occupy nearly the same Gini-M20 and Concentration regions as GAMA galaxies at z~0.05, but have systematically larger Asymmetry values. The paper also establishes that lowering image spatial resolution systematically reduces Gini and Asymmetry, with the Gini of low-mass galaxies most affected. It argues that the asymmetry excess is likely an artifact of how young star-forming regions are rendered as point-like photon sources, rather than evidence that EAGLE produces an overabundance of genuinely disturbed galaxies.

What carries the argument

The argument runs through four non-parametric statistics computed from the light distribution of each galaxy image: Gini (how unevenly light is distributed among pixels), M20 (the logarithm of the ratio of the second-order moment of the brightest 20 per cent of light to the total second-order moment), Concentration (five times the base-10 logarithm of the ratio of radii containing 80 and 20 per cent of the light), and Asymmetry (the fractional difference between an image and its 180-degree rotation, with background asymmetry subtracted). The mock images are produced by a three-dimensional Monte Carlo radiative-transfer code that models absorption and scattering by dust, with young star-forming regions rendered as smoothed point sources, then convolved with a Gaussian point-spread function and rebinned to SDSS-like pixel scale with signal-to-noise ratio 25; the same measurement routine is applied to SDSS images of GAMA galaxies. Together with the bulge-strength statistic F, defined as five times the signed distance of a galaxy's (G, M20) point from the early/late-type separation line, these statistics carry the comparison: they translate particle data into quantities a survey would actually measure.

What would settle it

Regenerate the EAGLE mock images with a larger smoothing length for young stellar photon sources (for example, using the 128th nearest neighbours) and remeasure the Asymmetry statistic: if the high-$A$ tail disappears while $G$-$M_{20}$ and Concentration remain in agreement with GAMA, the discrepancy is an image-generation artifact; if it persists, EAGLE galaxies are intrinsically more asymmetric than observed.

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Extended reading notes

Core claim

The paper's central claim is that the optical morphologies of EAGLE galaxies, once rendered as realistic g-band images, reproduce the observed morphologies of low-redshift galaxies in the GAMA survey, with one systematic exception: simulated galaxies are more asymmetric. On those terms, the Gini and M20 distributions of EAGLE galaxies at z=0.1 with stellar masses above $10^{10}$ solar masses nearly overlap those of GAMA galaxies with matched mass selection at z~0.05, and the Concentration distribution is also a close match. The Asymmetry distribution, however, develops a large tail of highly asymmetric galaxies with no observed counterpart, which the paper attributes to the point-like spatial distribution of young stellar photon sources in the mock-image generation rather than an intrinsic excess of disturbed galaxies. The paper also establishes that lowering image spatial resolution systematically reduces Gini and Asymmetry values, with the Gini of low-mass galaxies most affected, and that optical morphology correlates with kinematic morphology more strongly for central than for satellite galaxies.

Load-bearing premise

The load-bearing premise is that the mock-image pipeline faithfully represents the true light distribution of simulated galaxies, so the excess asymmetry is caused by how young star-forming regions are rendered rather than by an intrinsic overabundance of disturbed galaxies in EAGLE.

Editorial extensions

If this is right

  • Because galaxy morphology was not used to calibrate EAGLE, the agreement in Gini-M20 and Concentration counts as an independent prediction of the simulation rather than a retuning of parameters.
  • The asymmetry excess should be treated as a known bias when using mock EAGLE images to train or test morphological classifiers, merger identifications, or neural networks.
  • Resolution corrections derived from the simulated sample could be applied to observed surveys with different seeing, though only after checking that the simulated light profiles are realistic at sub-kiloparsec scales.
  • The correspondence of the kinematic threshold $\kappa_{co} = 0.4$ means kinematic morphology can serve as a proxy for optical morphology in EAGLE, even though the two criteria select different galaxy populations.
  • The weaker optical-kinematic correlation in satellites indicates environmental quenching changes a galaxy's light distribution less than its internal dynamics, motivating separate evolutionary tracks for central and satellite galaxies.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A direct test the paper implies but does not run: regenerate the mock images with a larger smoothing length for young stellar particles and check whether the asymmetry tail disappears while Gini-M20 and Concentration stay matched; if it does, the A excess is an image-rendering artifact.
  • The resolution effects documented here could be converted into a practical calibration: apply the simulated mass- and FWHM-dependent shifts to observed Gini and Asymmetry measurements before comparing surveys with different seeing. The paper stops at reporting the effect.
  • The excess of actively star-forming EAGLE galaxies above about $10^{11}$ solar masses, if it reflects weak feedback in the simulation, implies that morphology statistics could serve as an indirect constraint on feedback physics, an extension the paper does not make.
  • The same mock-image pipeline could be extended to higher redshift or to LSST-like resolution to predict how observed morphology distributions evolve, testing whether the agreement holds beyond the z~0.05 comparison presented here.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper presents non-parametric optical morphologies (Gini, M20, Concentration, Asymmetry) for galaxies in the EAGLE Ref-100 simulation at z=0.1, computed from SKIRT mock images that are post-processed to approximate SDSS imaging. These are compared with morphologies measured from SDSS images of GAMA galaxies at z~0.05 with M*>10^10 M_sun, and with published morphologies for Illustris and IllustrisTNG. The authors report that the Gini-M20 distribution of EAGLE galaxies agrees well with GAMA observations, while the asymmetry statistic A is systematically larger in the simulations. They also study the effect of spatial resolution, finding that Gini and Asymmetry decrease with decreasing resolution, and examine trends between optical morphology and star formation rate, galaxy size, and kinematic morphology indicators. The paper concludes that EAGLE reproduces observed optical morphologies except for the asymmetry excess, which they tentatively attribute to the treatment of young stellar photon sources in the mock-image generation.

Significance. If the conclusions hold, this is a valuable benchmark for hydrodynamic simulations: it provides a like-for-like comparison of simulated and observed non-parametric morphologies using the same measurement code, and it demonstrates that EAGLE and IllustrisTNG produce broadly similar optical morphologies that match GAMA in G-M20 space. The paper also gives useful quantitative results on how non-parametric statistics depend on spatial resolution and viewing angle, which are relevant for future surveys such as LSST. Strengths include the use of publicly available EAGLE mock images, the consistent application of statmorph to both simulated and observed images, the explicit use of external GAMA/SDSS data as a validation target, and the inclusion of convergence and orientation tests in the appendices. The main weakness is that the central exception to the reproduction of observations, the asymmetry excess, is not conclusively separated from a plausible imaging artifact, and the paper itself flags but does not execute the decisive test.

major comments (3)
  1. [Sections 4.2 and 5(v)]
  2. [Section 5(i) and Figure 2]
  3. [Sections 3.3.4 and 4.2, Figure 5]
minor comments (6)
  1. [Section 3.3.4]
  2. [Section 3.3.2]
  3. [Section 4.2]
  4. [Section 4.3]
  5. [Section 3.1.3]
  6. [Section 5(v)]

Circularity Check

0 steps flagged · score 2.0 of 10

No load-bearing circularity: the morphology comparison is independent of EAGLE calibration, and the self-citations are methodological inputs, not definitional replacements.

full rationale

The paper's central validation target, optical morphology, was not used in calibrating EAGLE. The paper states this explicitly: "The morphologies of galaxies have not been taken into consideration on the calibration procedure and can therefore be contrasted fairly with GAMA, or other similar galaxy samples." The observational benchmark is external (GAMA/SDSS, with T-types from Dominguez Sanchez et al. 2018), and both simulated and observed images are processed with the same statmorph code. The self-citations (Trayford et al. 2017 for the mock images; Bignone et al. 2017 for an asymmetry-implementation detail) supply data and methodology, not the conclusion that EAGLE morphologies match observations. The one place where the analysis depends on a prior modeling choice, the 64th-neighbor smoothing of young stellar photon sources, is flagged by the authors as a likely cause of the A excess rather than hidden: Section 3.1.1 notes that the smoothing-length choice "can have an impact on non-parametric morphologies," and Section 5(v) proposes the mitigation experiment without claiming it was run. An unrun mitigation test is a limitation or correctness risk, not a circular reduction. No equation in the paper defines a predicted statistic in terms of a fitted parameter, and the modified A0 background procedure is applied symmetrically to simulated and observed samples, so it does not construct the simulated-versus-observed asymmetry offset. The score of 2 reflects only minor, non-load-bearing self-citations in the methods; the main comparison is externally benchmarked and independent.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

The paper introduces no new physical entities. Its central comparison rests on inherited simulation calibration (GSMF and size-mass, not morphology), mock-image modeling choices, and the reliability of GAMA/CNN-derived labels. The smoothing length and dust-to-metal ratio are particularly load-bearing for the asymmetry result.

free parameters (5)
  • Dust-to-metal ratio fdust = 0.3
    Assumed constant in Equation 1 (Section 3.1.2), following Camps et al. (2016). It sets the dust opacity in mock images and thereby affects G, M20, C, and A, but it is not fitted in this work.
  • Photon source smoothing length = 64th nearest-neighbor distance
    Adopted for re-sampling stellar sources in SKIRT images (Section 3.1.1). The paper identifies the point-like distribution of young stellar sources as the likely cause of the excess asymmetry, so this choice is load-bearing for the A comparison.
  • Reference PSF FWHM = 1.0 kpc
    Chosen to approximate SDSS seeing at z=0.05 (Section 3.1.3); varied to 0.7 and 1.5 kpc to study resolution effects. The reference value affects every statistic in the main comparison.
  • Signal-to-noise ratio per pixel = 25
    Injected into mock images (Section 3.1.3) to mimic SDSS; the paper states this simulates only strongly detected galaxies, so it is a regime choice that affects the computed statistics.
  • Galaxy aperture radius = 30 pkpc
    Used to define the light considered in mock images and integrated properties (Section 3.1); the paper notes it omits outer light of the most extended galaxies, which can bias morphology statistics.
assumptions (5)
  • domain assumption EAGLE subgrid parameters were calibrated only to the z~0 GSMF and size-mass relation, not to galaxy morphology, so the morphology comparison is a genuine prediction.
    Section 2.1 states the calibration targets. This premise justifies interpreting the G-M20 match as a success of the simulation rather than a fitted result.
  • domain assumption The SKIRT mock-image pipeline, including dust, PSF convolution, rebinning, and noise, produces images equivalent to SDSS for morphology measurements.
    Section 3.1.3 describes the procedure. The validity of every comparison with GAMA depends on this equivalence; the paper itself questions it for the asymmetry statistic.
  • domain assumption GAMA photometric stellar masses (Taylor et al. 2011) rescaled to the EAGLE cosmology are accurate enough that the 10^10 Msun mass thresholds define comparable samples.
    Section 2.3. The paper notes ~0.3 dex uncertainties and a mass-distribution mismatch at the low-mass end, yet uses the samples as comparable.
  • domain assumption T-Type classifications from the CNN of Dominguez Sanchez et al. (2018) are reliable labels for testing the G-M20 separation.
    Section 2.3 and Section 4.1.1; >97% GZ2 accuracy is quoted, but T-Type/S0 ambiguities are acknowledged.
  • domain assumption The Lotz et al. (2008b) demarcation lines in G-M20 and C-A space, derived from observed galaxies at 0.2<z<1.2, apply to z~0.05 GAMA and z=0.1 simulated galaxies.
    The lines define the merger/early/late sectors and the F statistic (Section 4.1). Slight shifts in these lines could alter the fraction of galaxies classified as bulge-dominated.

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Cite this review

Pith. "Pith review of Non-parametric Morphologies of Galaxies in the EAGLE Simulation." pith.science (2026). https://pith.science/paper/BXGL3SJL

@misc{pith2026190810936,
  author       = {Pith},
  title        = {Pith review of: Non-parametric Morphologies of Galaxies in the EAGLE Simulation},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BXGL3SJL}},
  note         = {Machine review of arXiv:1908.10936}
}
abstract

We study the optical morphology of galaxies in a large-scale hydrodynamic cosmological simulation, the EAGLE simulation. Galaxy morphologies were characterized using non-parametric statistics (Gini, $M_{20}$, Concentration and Asymmetry) derived from mock images computed using a 3D radiative transfer technique and post-processed to approximate observational surveys. The resulting morphologies were contrasted to observational results from a sample of $\log_{10}(M_{*}/M_\odot) > 10$ galaxies at $z \sim 0.05$ in the GAMA survey. We find that the morphologies of EAGLE galaxies reproduce observations, except for asymmetry values which are larger in the simulated galaxies. Additionally, we study the effect of spatial resolution in the computation of non-parametric morphologies, finding that Gini and Asymmetry values are systematically reduced with decreasing spatial resolution. Gini values for lower mass galaxies are especially affected. Comparing against other large scale simulations, the non-parametric statistics of EAGLE galaxies largely agree with those found in IllustrisTNG. Additionally, EAGLE galaxies mostly reproduce observed trends between morphology and star formation rate and galaxy size. Finally, We also find a significant correlation between optical and kinematic estimators of morphologies, although galaxy classification based on an optical or a kinematic criteria results in different galaxy subsets. The correlation between optical and kinematic morphologies is stronger in central galaxies than in satellites, indicating differences in morphological evolution.

Figures

Figures reproduced from arXiv: 1908.10936 by the authors.

Figure 1
Figure 1. Stellar mass distribution of the gama and Ref-100 sam￾ples. The gama sample presents a slightly higher median stellar mass of 1010.45 M compared to the median stellar mass of 1010.36 M in the Ref-100 sample due to the paucity of galaxies below ∼ 1010.5 M . See text for a more complete discussion simulations are those inferred by the Planck Collabora￾tion et al. (2014), the key parameters being Ωm = 0.307, ΩΛ = 0.693… view at source ↗
Figure 2
Figure 2. The central panel shows the G-M20 diagram from galaxies in Ref-100 (blue), Illustris (orange), IllustrisTNG (red) and gama (points). The coloured solid (dotted) lines enclose regions containing 68 (95) percent of galaxies in each respective sample. The gama galaxies are coloured according to their T-Types. The black dashed and dotted lines separate the subspace into regions for mergers, late types and early types ac… view at source ↗
Figure 3
Figure 3. Mock gri-SDSS colour composite images of galaxies in the Ref-100 sample arranged according to their G and M20 values. Solid (dotted) contours represent the region containing 68 (95) percent of objects. The straight lines are as in [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: shows the distribution of F for gama galaxies, differentiating positive and negative T-Type populations. We can appreciate that the F = 0 separation line is located very close to the point where the number of early type galax￾ies starts to dominate. We can also ascerta…
Figure 5
Figure 5. Figure 5: The central panel shows the C-A diagram from galaxies in Ref-100 (blue), Illustris (orange), IllustrisTNG (red) and gama (points). The coloured Solid (dotted) lines enclose regions containing 68 (95) percent of galaxies in each respective sample. The gama galaxies are …
Figure 6
Figure 6. Figure 6: Mock gri-SDSS colour composite images of galaxies in the Ref-100 sample arranged according to their C and A values. Solid (dotted) contours represent the region containing 68 (95) percent of objects. The straight line is as in [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: Boxplots describing the median relative changes in morphological values obtained as a consequence of varying the spatial resolution of images by using different FWHM values in the procedure described in Section 3.1.3. Changes in the statistics are measured from those o…
Figure 8
Figure 8. Figure 8: Top panels: SFR versus stellar mass for galaxies in the Ref-100 (left) and gama samples (right). with colours proportional to the mean bulge strength F in each 2D bin. Solid (dotted) lines enclose regions that contain 68 (95) percent of objects. Bottom panels: the same…
Figure 9
Figure 9. Figure 9: Bulge strength statistic F versus galaxy size parametrized by the semimajor axis of an ellipse containing half of the total flux. The panel on the left shows galaxies in Ref-100, while the panel on the right shows galaxies from gama. The contours indicate the overall d…
Figure 10
Figure 10. Figure 10: The bottom panels show the bulge strength statistic F versus κco (left), D/T (centre) and vrot/σ (right) for Ref-100 galaxies. The solid lines show the binned median and 1σ (16th-84th) percentile scatter of the dependent variables. Overall, the optical morphology show…
Figure 11
Figure 11. Figure 11: Mock gri-SDSS colour composite images of galaxies in the Ref-100 sample arranged according to their F and κco values. The left (right) panel contains central (satellite) galaxies. Solid (dotted) contours represent the region containing 68 (95) percent of objects. The …
Figure 12
Figure 12. Figure 12: As the first panel of [PITH_FULL_IMAGE:figures/full_fig_p016_12.png]

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    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.