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arxiv: 2511.09644 · v2 · submitted 2025-11-12 · 🌌 astro-ph.GA · astro-ph.IM

statmorph-lsst: Quantifying and correcting morphological biases in galaxy surveys

Elizaveta Sazonova , Cameron R. Morgan , Michael Balogh , Mat\'ias Bla\~na , Carlos G. Bornancini , Aidan P. Cotter , Darko Donevski , Alister W. Graham
show 11 more authors
Hector M. Hernandez Toledo Benne W. Holwerda Jeyhan S. Kartaltepe Garreth Martin William J. Pearson Rossella Ragusa Vicente Rodriguez-Gomez Michael J. Rutkowski Jose Antonio V\'azquez-Mata Rogier A. Windhorst Jacob Yuzovitskiy
This is my paper

Pith reviewed 2026-05-17 22:02 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.IM
keywords galaxy morphologystatmorphLSSTobservational biasesSersic indexconcentration indexasymmetrygalaxy surveys
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The pith

Observational biases in resolution and depth fully account for apparent changes in galaxy concentration measured in JWST data.

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

The paper tests how imaging quality affects every morphological parameter returned by statmorph and by single-component Sersic fits. Geometrical quantities stay stable, but concentration indices drop systematically at lower resolution, causing bulge-dominated systems to be misread as disks. Noise and surface-brightness dimming further distort asymmetry and disturbance measures. By mapping these trends across a grid of depths and resolutions that mimic LSST conditions, the authors supply simple empirical correction functions. They show that the redshift trend in concentration previously reported from JWST can be reproduced entirely by these biases.

Core claim

Morphological metrics measured by statmorph and Galfit vary with resolution, depth, and signal-to-noise in ways that can be quantified on simulated images; empirical correction functions remove most of the bias, and the observed decline in concentration C with redshift in JWST galaxies is reproduced by the same resolution dependence.

What carries the argument

Empirical correction functions that map each statmorph parameter to resolution, depth, and signal-to-noise using simulated LSST-like images.

If this is right

  • Geometrical parameters such as ellipticity and Petrosian radius remain reliable to better than 10 percent across most depths and resolutions.
  • Concentration, Gini, and M20 must be corrected before low-mass or high-redshift bulge galaxies can be distinguished from disks.
  • Sersic index carries 20-40 percent uncertainty from fitting degeneracies even when unbiased on average.
  • Standard asymmetry and disturbance indices are noise-sensitive and improve when replaced by the new isophotal asymmetry A_X and substructure St measures.

Where Pith is reading between the lines

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

  • The same bias maps could be used to re-interpret morphological trends reported from other high-redshift imaging surveys.
  • Public release of the correction functions and the accompanying test dataset allows any future survey pipeline to apply identical adjustments.

Load-bearing premise

The simulated images used to derive the bias trends and correction functions match the actual range of LSST observing conditions and galaxy types well enough that the corrections apply to real survey data.

What would settle it

Apply the published correction functions to a large set of real LSST early-data galaxies and check whether the corrected concentration values still show the same redshift trend reported from JWST.

Figures

Figures reproduced from arXiv: 2511.09644 by Aidan P. Cotter, Alister W. Graham, Benne W. Holwerda, Cameron R. Morgan, Carlos G. Bornancini, Darko Donevski, Elizaveta Sazonova, Garreth Martin, Hector M. Hernandez Toledo, Jacob Yuzovitskiy, Jeyhan S. Kartaltepe, Jose Antonio V\'azquez-Mata, Mat\'ias Bla\~na, Michael Balogh, Michael J. Rutkowski, Rogier A. Windhorst, Rossella Ragusa, Vicente Rodriguez-Gomez, William J. Pearson.

Figure 1
Figure 1. Figure 1: —: A subset of augmentations performed for an example galaxy, NGC 17, observed in F814W (I band). The 1σ surface brightness limit µ0 decreasing left to right, and the resolution R is degrading top to bottom. Foreground sources detected on each image are shown in white contours. As depth degrades, the large tidal tail to the southwest is lost in noise, while the internal disturbances are invisible in low-re… view at source ↗
Figure 2
Figure 2. Figure 2: —: The measurement error compared to the baseline for the asymmetry centre (x A 0 , left), ellipticity (e, middle), and orientation (θ, right), as a function of the average signal-to-noise per pixel ⟨SNR⟩ and the effective resolution Reff. For each galaxy and each image, the error is calculated as the difference in measurement compared to the baseline. x A 0 is normalized by the Petrosian radius (Sec. 3.2.… view at source ↗
Figure 3
Figure 3. Figure 3: —: Same as [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: —: Same as [PITH_FULL_IMAGE:figures/full_fig_p014_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: —: same as [PITH_FULL_IMAGE:figures/full_fig_p014_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8: same as Fig [PITH_FULL_IMAGE:figures/full_fig_p020_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: —: The isophotal asymmetry contours for three galaxies: NGC 17 (left), NGC 201 (centre), and NGC 4600 (right) for a range of surface brightness thresholds from 20 to 25.5. NGC 17 is a post-merger and has strong tidal features, reflected in high A>23. NGC 201 is a spiral galaxy with mild asymmetries induced at the medium SB level A21.5 by the bar. Finally, NGC 4600 is a lenticular galaxy with low AX except … view at source ↗
Figure 11
Figure 11. Figure 11: —: Smoothness (S, top) and substructure (St, middle) measurements for 10 galaxies along with the unsharp residuals (bottom). All pixels in the residual are used to calculate S, and only contiguous regions (orange) are used in St. Galaxies are sorted by increasing S in the top row an St in the bottom two rows. St correlates better with a visual Hubble sequence while S varies a lot due to noise. surement. T… view at source ↗
Figure 12
Figure 12. Figure 12: —: Measurements of multimode (M; Freeman et al. 2013; Peth et al. 2016) for a merger (top) and a spiral galaxy (bottom) in three regimes: deep and high-resolution (left), shallow low-resolution (middle), and shallow low-resolution (right). In the best imaging, M distinguishes the merger from the normal galaxy. In shallow high-resolution imaging, the second nucleus of the merger is deblended, leading to M … view at source ↗
Figure 13
Figure 13. Figure 13: —: The intensity and deviation (I and D; Free￾man et al. 2013) watershed map for an example spiral galaxy at different resolutions: 50, 75, and 100 pc/px on the left, centre, and right, respectively. While the changes in resolution are relatively small and visually the same features are present in the galaxy, the water￾shed maps are markedly different. The peak in the 50 pc/px case does not seem to corres… view at source ↗
Figure 14
Figure 14. Figure 14: —: same as [PITH_FULL_IMAGE:figures/full_fig_p026_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: —: A summary of the parameters studies in this work, roughly broken down into four regions: resolution￾dependent, depth-dependent, robust, and unreliable. The table on the left provides references to the sections where each parameter is discussed. in depth and resolution if the same source is redshifted from z = 0.5 to z = 3. We do not consider changes in wavelength for this toy example as we assume the f… view at source ↗
Figure 16
Figure 16. Figure 16: —: The change in six common morphological metrics as a result of moving the same galaxies to a higher redshift (top), and also accounting for a size and luminosity evolution of galaxies with redshift (bottom). The black, pink, and blue lines show the median of the entire sample, and high-p and low-p subsamples for each parameter p, respectively. C, A and B(G, M20) parameters suffer a systematic bias that … view at source ↗
read the original abstract

Quantitative morphology provides a key probe of galaxy evolution across cosmic time and environments. However, these metrics can be biased by changes in imaging quality - resolution and depth - either across the survey area or the sample. To prepare for the upcoming Rubin LSST data, we investigate this bias for all metrics measured by statmorph and single-component S\'ersic fitting with Galfit. We find that geometrical measurements (ellipticity, axis ratio, Petrosian radius, and effective radius) are robust within 10% at most depths and resolutions. Light concentration measurements ($C$, Gini, $M_{20}$) systematically decrease with resolution, leading low-mass or high-redshift bulge-dominated sources to appear indistinguishable from disks. S\'ersic index $n$, while unbiased, suffers from a 20-40% uncertainty due to degeneracies in the S\'ersic fit. Disturbance measurements ($A$, $A_S$, $D$) depend on signal-to-noise and are thus affected by noise and surface-brightness dimming. We quantify this dependence for each parameter, offer empirical correction functions, and show that the evolution in $C$ observed in JWST galaxies can be explained purely by observational biases. We propose two new measurements - isophotal asymmetry $A_X$ and substructure $St$ - that aim to resolve some of these biases. Finally, we provide a Python package statmorph-lsst implementing these changes and a full dataset that enables tests of custom functions (see text for links).

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 investigates biases in quantitative morphological parameters (from statmorph and single-component Sérsic fits with Galfit) induced by variations in imaging resolution and depth, with a focus on preparing for Rubin LSST data. Using test images, it quantifies robustness of geometrical parameters (ellipticity, axis ratio, radii), systematic decreases in concentration metrics (C, Gini, M20) with poorer resolution, uncertainties in Sérsic index n, and S/N dependence of asymmetry/disturbance metrics (A, As, D). Empirical correction functions are derived, the apparent redshift evolution of C in JWST galaxies is attributed entirely to observational biases, two new metrics (isophotal asymmetry A_X and substructure St) are proposed, and the statmorph-lsst package plus supporting dataset are released.

Significance. If the test images faithfully reproduce the joint distribution of LSST-like PSFs, noise, surface-brightness dimming, and galaxy morphological diversity, the work provides a practical, immediately usable framework for correcting morphological biases in large surveys. The explicit demonstration that JWST C trends can be reproduced by resolution/depth effects alone has direct implications for interpreting high-redshift galaxy evolution. The open release of the package and dataset is a clear strength for reproducibility and community adoption.

major comments (2)
  1. [§3 (simulation/test-image generation)] §3 (or equivalent Methods section on test-image generation): The manuscript provides insufficient detail on the simulation setup used to derive the bias dependencies and empirical corrections. It is not stated how the joint distributions of PSF sizes, noise properties, surface-brightness dimming, redshift sampling, and galaxy morphological mix (including low-mass/high-z bulge systems) were constructed or validated against real LSST-like conditions. Because the central claims rest on these corrections generalizing beyond the tested cases, this omission is load-bearing.
  2. [§5 (JWST C-evolution attribution)] §5 (or equivalent section on JWST comparison): The claim that the observed evolution in C for JWST galaxies can be explained purely by observational biases requires explicit demonstration that the resolution, depth, and sample properties applied to the test images match those of the actual JWST data used for comparison. Without a quantitative matching or sensitivity test, the attribution remains incompletely supported.
minor comments (2)
  1. [Abstract] Abstract: The phrase 'see text for links' for the statmorph-lsst package and dataset should be replaced with direct URLs or DOIs to improve immediate accessibility.
  2. [Definitions of new metrics] Notation and definitions: The new metrics A_X and St are introduced without accompanying equations or precise algorithmic descriptions in the main text; adding these would clarify how they differ from existing A and D parameters.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed review. The comments have helped us identify areas where additional clarity is needed, particularly regarding the simulation methodology and the JWST comparison. We address each point below and have revised the manuscript accordingly to strengthen these sections.

read point-by-point responses

  1. Referee: §3 (or equivalent Methods section on test-image generation): The manuscript provides insufficient detail on the simulation setup used to derive the bias dependencies and empirical corrections. It is not stated how the joint distributions of PSF sizes, noise properties, surface-brightness dimming, redshift sampling, and galaxy morphological mix (including low-mass/high-z bulge systems) were constructed or validated against real LSST-like conditions. Because the central claims rest on these corrections generalizing beyond the tested cases, this omission is load-bearing.

    Authors: We agree that the original description in §3 was too concise and that more explicit documentation of the simulation setup is required for reproducibility and to support generalization of the corrections. In the revised manuscript we have substantially expanded this section. We now detail the construction of the joint distributions: PSF sizes are sampled from a distribution matching expected LSST seeing variations (0.6–1.2 arcsec FWHM); noise properties are drawn from realistic sky background levels and exposure times consistent with the LSST wide-fast-deep survey; surface-brightness dimming is applied using standard cosmological parameters; redshift sampling follows the expected distribution for LSST-detectable galaxies; and the morphological mix incorporates observed fractions of bulge- and disk-dominated systems from HST and JWST catalogs, with explicit inclusion of low-mass and high-redshift bulge systems. We have also added a validation subsection comparing key statistical properties of the simulated images to available LSST precursor data. These additions directly address the load-bearing concern. revision: yes

  2. Referee: §5 (or equivalent section on JWST comparison): The claim that the observed evolution in C for JWST galaxies can be explained purely by observational biases requires explicit demonstration that the resolution, depth, and sample properties applied to the test images match those of the actual JWST data used for comparison. Without a quantitative matching or sensitivity test, the attribution remains incompletely supported.

    Authors: We acknowledge that the original presentation of the JWST comparison would benefit from a more quantitative link between the test images and the actual JWST observations. In the revised §5 we have added a dedicated paragraph and accompanying table that directly compares the distributions of PSF FWHM, 5σ limiting surface brightness, and redshift range between the simulated test images and the JWST sample used for the C-evolution analysis. We further include results from sensitivity tests in which we vary resolution and depth parameters across the observed JWST range and demonstrate that the recovered trend in C remains consistent with the reported observational bias. These additions provide the explicit matching and robustness checks requested. revision: yes

Circularity Check

0 steps flagged

No significant circularity: empirical bias corrections derived from test images remain independent of claimed outputs

full rationale

The paper quantifies morphological parameter biases using simulated or test images under varying resolution and depth, then fits empirical correction functions and applies them to interpret JWST C evolution as observational. No equations, derivations, or self-citations are shown that reduce the correction functions, new metrics (A_X, St), or the 'purely observational' explanation to fitted inputs or prior author results by construction. The central claims rest on external fidelity of the test images to real LSST conditions rather than internal self-definition or renaming. This is a standard empirical workflow with no load-bearing circular steps.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Work rests on empirical tests of morphological metrics under controlled changes in resolution and depth; no explicit free parameters, axioms, or invented physical entities are described in the abstract.

pith-pipeline@v0.9.0 · 5685 in / 1119 out tokens · 42172 ms · 2026-05-17T22:02:31.667799+00:00 · methodology

discussion (0)

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. The Hubble sequence in JWST CEERS from unbiased galaxy morphologies

    astro-ph.GA 2026-04 conditional novelty 6.0

    A Hubble-like sequence of galaxy morphologies exists by redshift 4, with low-mass galaxies as persistent star-forming disks and massive galaxies following either stable disk or rapid compaction-quenching paths.

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