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REVIEW 4 major objections 6 minor 66 references

Unveiling Galaxy Structures: Systematic Analysis of Bulge+Disk Decomposition Using Simulated JWST/NIRCam Observations

T0 review · 4 major / 6 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read Under CEERS-like JWST/NIRCam conditions, single and double Sérsic fits recover galaxy magnitudes within about 0.5 mag and sizes within about 0.2 dex, down to 27 mag for total light and 26 mag for individual bulge/disk components.

desk verdict Useful JWST/NIRCam bulge+disk error-budget paper, but the single-Sérsic size claim rests on a flux-weighted radius comparison that does not measure half-light radius; the double-component decomposition results are the solid part. read the letter →

arxiv 2506.18351 v1 pith:HIXW4423 submitted 2025-06-23 astro-ph.GA

Zhengxin Tang , Xuheng Ding , Boris S. Kalita , Lilan Yang This is my paper · ORCID
classification astro-ph.GA
keywords galaxystructurebulge+diskdecompositionSérsicprofileJWSTNIRCamhigh-redshiftgalaxiesBayesianInformationCriterionsignal-to-noiseratio
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 JWST/NIRCam images can be trusted to separate a galaxy's light into a bulge and a disk. The authors generate 5,000 two-component galaxies with realistic CEERS noise and point-spread functions, then fit them with a single Sérsic model and a double Sérsic model. They find that the single model recovers total magnitudes within about 0.5 mag and effective radii within 0.2 dex down to 27 mag, and the double model recovers each component within 0.5 mag and 0.2 dex for components brighter than 26 mag. They also set a signal-to-noise threshold of 10 and give BIC-based brightness limits for when the two-component fit is preferred, providing a practical error budget for high-redshift morphology studies.

What carries the argument

The central object is the Sérsic profile, $I(R)=I_e\exp[-k((R/R_{\rm eff})^{1/n}-1)]$, with $n=4$ for the bulge and $n=1$ for the disk, convolved with real point-spread functions chosen from CEERS F150W and F356W images and embedded in real CEERS sky background with Poisson noise. The argument is carried by a controlled comparison: 5,000 simulated bulge+disk galaxies of known parameters are fit with single and double Sérsic models by a two-dimensional image-fitting pipeline, and recovery accuracy is measured against the known inputs. Two auxiliary tools do key work: the Bayesian Information Criterion decides when the extra component is justified, and the total signal-to-noise ratio is used to make the error budgets portable to other NIRCam surveys.

What would settle it

Take a sample of galaxies with independently known bulge and disk parameters, for example from kinematic decomposition or higher-resolution imaging, degrade them to CEERS-like JWST depth and PSF, and check whether the double Sérsic fits recover those known values within 0.5 mag and 0.2 dex; a simpler version is to rerun the same mock pipeline with pseudo-bulges or barred light and watch whether the recovery error and the BIC separation worsen substantially.

Watch

Extended reading notes

Core claim

Under CEERS-like NIRCam observing conditions, single Sérsic fits recover the total magnitude of a bulge-plus-disk galaxy within 0.5 mag and its effective radius within 0.2 dex for galaxies as faint as 27 mag, while double Sérsic fits recover the bulge and disk magnitudes within 0.5 mag and effective radii within 0.2 dex for components brighter than 26 mag. The recovered parameters are unbiased and the scatter shrinks as signal to noise increases, with SNR>10 quoted as the threshold for reliable recovery. The fitted single-Sérsic index rises monotonically with the true bulge-to-total flux ratio, so n can serve as a B/T proxy, though the relation scatters heavily near n=1 and n=4 and at magnitudes fainter than 26. For model selection, the Bayesian Information Criterion prefers the double model in 90% of systems brighter than 24.9 mag in F150W or 26.2 mag in F356W, and in 90% of comparable-flux systems with B/T between 30% and 70%.

Load-bearing premise

The load-bearing premise is that the mock galaxies are generated from the same Sérsic model family used in the fits, with the bulge index fixed at 4 and the disk index at 1, and that the fits are initialized with the true parameter values; if real high-redshift galaxies contain pseudo-bulges, bars, clumps, or Sérsic indices outside those fixed values, the quoted recovery accuracies and BIC thresholds will not transfer.

Editorial extensions

If this is right

  • Surveys can treat single-Sérsic total magnitudes and sizes as reliable down to 27 mag in F150W and F356W, which extends size evolution studies to the faint high-redshift populations JWST actually detects.
  • Bulge and disk magnitudes can be compared at the 0.5 mag level for components brighter than 26 mag, making B/T-based tests of bulge growth versus disk accretion feasible at high redshift.
  • The BIC thresholds, with 90% confidence for mag<24.9 in F150W and mag<26.2 in F356W, give a simple pre-analysis rule for deciding when to attempt two-component decomposition.
  • The SNR>10 criterion lets other NIRCam programs compute, before fitting, which of their galaxies will yield reliable structural parameters.
  • Agreement between two independent fitting codes within 0.1 mag/0.1 dex for single models and 0.5 mag/0.2 dex for double models suggests these error budgets are not quirks of one implementation.

Reading between the lines

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

  • These error budgets are likely optimistic for real high-redshift galaxies because the mocks use exactly the same Sérsic family as the fits, with a classical n=4 bulge and exponential n=1 disk and no bars, clumps, or asymmetric features; adding such substructure would probably degrade the recovery and weaken the BIC separation.
  • Because the nominal fits start from the true parameter values, with a footnote reporting that default initialization gave consistent results, a fully blind search over a larger survey would be a useful additional stress test of the quoted accuracies.
  • A direct extension would be to repeat the calibration with bulge and disk Sérsic indices left free, or with pseudo-bulges at n~2, to map how much of the 0.5 mag budget is absorbed by index flexibility.
  • The BIC magnitude limits translate into a redshift-dependent mass limit: at z~6 only the most luminous galaxies will be bright enough in F356W to support double-component decomposition, so B/T measurements there will be biased toward massive systems.
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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

4 major / 6 minor

Summary. The paper presents controlled simulations of bulge+disk galaxies observed under CEERS/NIRCam conditions (F150W and F356W), fits them with single and double Sérsic models using the galight and galfit codes, and quantifies recovery accuracy for total and component magnitudes, effective radii, bulge-to-total ratios, model selection via the Bayesian Information Criterion, and signal-to-noise thresholds. The central numerical claims are that single Sérsic fits recover total magnitudes within about 0.5 mag and sizes within about 0.2 dex down to 27 mag, and double Sérsic fits recover component magnitudes and effective radii within 0.5 mag and 0.2 dex down to 26 mag, with SNR > 10 as a general reliability threshold.

Significance. If the headline results hold, the paper provides a practical reference for JWST/NIRCam morphological studies, including error budgets and BIC-based selection thresholds. The study's strengths are its large sample of 5,000 simulated galaxies, the use of realistic CEERS PSFs and background noise, explicit PSF-mismatch tests, an independent cross-check with galfit, and the SNR-based parameterization of uncertainties. However, the validation is a closed-box test: the generative model and the fitting model share the same Sérsic family with fixed bulge and disk indices, and the single-Sérsic size comparison is made against a flux-weighted radius that is not the true half-light radius of the composite system. These issues mean that the quoted accuracies are ideal-case, same-model errors unless the analysis is revised or the claims are reframed.

major comments (4)
  1. [§4.1.2, Eq. (2)] The single-Sérsic size recovery is validated against R_weighted = (R_bulge f_bulge + R_disk f_disk)/(f_bulge + f_disk), which is not the half-light radius of the two-component model. The true total half-light radius solves the cumulative-flux condition and depends on the full shape of both Sérsic profiles; for typical simulated parameters (e.g., B/T ≈ 0.5, R_disk/R_bulge ≈ 2) the difference can be ~0.1 dex, comparable to the quoted 0.2 dex accuracy. The abstract and §6 claims of single-Sérsic size recovery within 0.2 dex are therefore not established; the comparison should be made against the numerically computed half-light radius of the composite model, or the claim should be reframed. The same R_weighted is used in the galfit comparison in §5.3, so that consistency test does not validate the size accuracy either.
  2. [§4.1.2, Figure 3] The threshold statements 'within 0.5 mag' and 'within 0.2 dex' are based on binned means and standard deviations rather than on quantiles of the residuals. For F150W galaxies fainter than 26 mag the magnitude residual is 0.047 ± 0.323 mag; with a 1σ scatter of 0.32 mag a substantial fraction of objects must exceed 0.5 mag, so the statement in the text that 'the overall residuals remain far below 0.5 magnitudes, even for galaxies as faint as 28 mag' is not supported by the reported statistics. Please report the 68th and 90th percentiles of |Δmag| and |Δlog R_eff| and base all threshold claims on those quantiles.
  3. [§4.2.2 and Abstract] The abstract and §6 state that double-Sérsic effective radii are recovered within 0.2 dex for components brighter than 26 mag, but §4.2.2 reports bulge R_eff uncertainties of 0.17–0.24 dex for bright galaxies in F356W and 0.06–0.19 dex in F150W. The F356W bulge radii therefore exceed the stated 0.2 dex tolerance for part of the bright sample, and no fraction or quantile is given. The claim should be restricted to the band and component combination that actually meets the tolerance, or stated as a percentile-based fraction.
  4. [§3.1.1, §3.2, §5.4] The accuracy test is closed-box: the mocks are generated with the same Sérsic family used in the fits, with n_bulge fixed to 4 and n_disk fixed to 1, and the fitting is initialized at the true parameter values. The footnote in §3.2 asserts that default initialization gives consistent results, but no comparison is shown and should be presented. While §5.4 correctly lists bars, clumps, pseudo-bulges, and variable Sérsic indices as unmodeled, the abstract and summary do not carry the caveat that the quoted accuracies are ideal-case, same-model errors. I recommend adding a scope statement to the abstract and either quantifying the degradation on mocks with different indices or substructures, or explicitly stating that such a test is beyond the present scope.
minor comments (6)
  1. [Abstract and §6] The abstract says single-Sérsic total magnitudes are recovered within 0.5 mag, while §6 says within 0.2 mag for galaxies as faint as 27 mag; these numbers should be reconciled, and 'CEERs' in the abstract should be 'CEERS'.
  2. [Figure 3 caption] The caption states that the color scale for the size panels is limited to 0.1–0.3 arcsec 'to emphasize the correlation,' but this is not the actual range of the plotted sizes and is confusing; please rephrase or use a scale that reflects the data.
  3. [§3.2] The text says that for single Sérsic fits 'the index value is limited to the range of 1–4,' while for double Sérsic fits the indices are fixed to 4 and 1; please clarify whether the single-Sérsic index was restricted to integer values or to the continuous range.
  4. [§5.1] There is a typo in 'the single Sérsic and double Sérsic models models'; also the phrase 'double Sérsic models' is used repeatedly and should be made singular where appropriate.
  5. [§5.2, Eq. (3)] The SNR formula uses integral-like symbols that do not render clearly; please define the integration limits and the noise model explicitly.
  6. [References] The reference to Kelly et al. (2023) is incomplete; it should include the journal volume and article number.

Circularity Check

2 steps flagged · score 5.0 of 10

Partial circularity: the n–B/T proxy is built into the mock construction, and the single-Sérsic size validation uses an input-weighted radius instead of the true half-light radius.

  1. self definitional [§3.1.1 Table 1 and §4.1.3]
    "Bulge Sérsic Index (n_bulge,sim): Fixed (4.0); Disk Sérsic Index (n_disk,sim): Fixed (1.0) ... We collected the Sérsic n values obtained from the single Sérsic fitting and compared them with the truth value of the B/T in the system. The results ... reveal a strong correlation between the fitted n and the true B/T ... When the true B/T increases from 10% to 90%, the fitted n values systematically rise from 1.0 to 4.0."

    The mock 'truth' B/T is defined as the flux ratio of an n=4 bulge and an n=1 disk, both fixed in the generative model. A single-Sérsic fit to the sum of these two fixed-shape profiles can only return n values between 1 and 4, so the monotonic n–B/T relation is a mathematical interpolation between the input indices rather than an independent empirical discovery. The paper itself restricts the proxy to classical bulges (n=4), confirming that the claimed relation is tied to the chosen generative indices. Thus the proxy is self-definitional: the relation is loaded into the simulation before any fitting is performed.

  2. other [§4.1.2, Eq. (2)]
    "Since our simulations use bulge+disk components, there is no single effective radius for direct comparison with the single Sérsic fitting. Instead, we calculate a flux-weighted effective radius for the simulated galaxy properties, denoted as R_weighted, using: R_weighted = (R_bulge,sim f_bulge,sim + R_disk,sim f_disk,sim) / (f_bulge,sim + f_disk,sim)."

    R_weighted is a linear flux-weighted average of the two simulated component radii. It is not the half-light radius of the total two-component Sérsic profile, which depends on the full light distribution including the n=4 bulge wings and the n=1 disk outer flux. The fitted single-Sérsic R_eff is by definition a half-light radius, so the reported 0.2 dex size accuracy in §4.1.2, the abstract, and §6 is scored against an input-derived composite, not against the true size of the generated galaxy. This makes the single-Sérsic size-recovery claim a validation against a quantity defined from the same input radii, rather than against the intrinsic half-light radius it purports to recover.

full rationale

This paper is primarily a simulation-based calibration study. Most of its output—double-Sérsic component magnitude and radius residuals, SNR-dependent scatter, and BIC model-selection thresholds—is obtained by fitting the mocks and is not algebraically identical to the input parameters. The galfit comparison in §5.3 provides an external-code cross-check, and the authors explicitly acknowledge in §5.4 that the idealized fixed-index Sérsic mocks limit transferability to clumpy or barred real galaxies; that acknowledgment is a limitation, not a circularity. However, two internal steps require caveats. First, the claimed n–B/T proxy is self-definitional: the mocks are generated with n_bulge=4 and n_disk=1, so the single-Sérsic n fitted to their sum is constrained to interpolate between these two endpoints as the input flux ratio changes; the correlation is built in by construction. Second, the single-Sérsic size recovery is scored against R_weighted from Eq. (2), a linear flux-weighted average of input radii, rather than against the half-light radius of the total two-component profile; the fitted R_eff is a half-light radius by definition, so the 0.2 dex size claim is validated against an input-derived composite rather than the true size. These issues affect the single-Sérsic proxy and size claims, but the double-Sérsic decomposition accuracy, SNR thresholds, and BIC selection criteria are genuine fitting outputs and keep the paper from being fully circular.

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

The central claim depends on the idealized bulge+disk generative model and the unquantified assumption that truth-initialized fitting does not inflate accuracy. No new physical entities are introduced, and no calibration constants are fitted to external data; the only free parameters are the standard Sérsic parameters that are themselves the object of measurement.

assumptions (5)
  • domain assumption Bulge+disk galaxies are adequately represented by a Sérsic n=4 bulge plus a Sérsic n=1 disk.
    Used to generate all 5,000 mocks (§3.1.1, Table 1) and to set the fitting model (§3.2). Limits transfer to pseudo-bulges, bars, clumps; acknowledged in §5.4.
  • domain assumption Fitting initialized with the true simulation parameters does not bias recovery statistics.
    Footnote 1 in §3.2 states default initialization gives consistent results but no quantitative comparison is shown in the main figures.
  • domain assumption Empirical PSFs from CEERS5 and random empty sky backgrounds reproduce JWST observing conditions.
    Used to build mocks in §2; PSF mismatch between generation and fitting partly tests PSF uncertainty but only within a small set of PSFs.
  • standard math BIC difference ΔBIC < -10 is a reliable indicator of strong model preference.
    Standard BIC practice; used for model selection thresholds in §5.1.
  • standard math Sérsic profiles are a valid description of galaxy surface brightness.
    Background assumption from Eq. 1; standard in the field.

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Cite this review

Pith. "Pith review of Unveiling Galaxy Structures: Systematic Analysis of Bulge+Disk Decomposition Using Simulated JWST/NIRCam Observations." pith.science (2026). https://pith.science/paper/HIXW4423

@misc{pith2026250618351,
  author       = {Pith},
  title        = {Pith review of: Unveiling Galaxy Structures: Systematic Analysis of Bulge+Disk Decomposition Using Simulated JWST/NIRCam Observations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HIXW4423}},
  note         = {Machine review of arXiv:2506.18351}
}
read the original abstract

Characterizing and accurately decomposing galaxies into structural components, such as bulges and disks, is essential for understanding galaxy formation and evolution, particularly at high redshift, where galaxies are compact and faint. Leveraging the unparalleled resolution and sensitivity of JWST and imaging data from CEERs program, we simulate galaxies with bulge+disk components and assess the effectiveness of single and double S\'ersic model fittings, respectively. We first evaluate the performance of single S\'ersic fits, and find it can recover total magnitudes (i.e., within 0.5 mag), and size (i.e., within 0.2 dex), down to 27 mag. The features that emerged in the residual map can properly reflect the underlying two-component structures. We also show that S\'ersic indices can serve as proxies for the bulge-to-total flux ratio (B/T). For double S\'ersic models, we find comparable accuracy in recovering bulge and disk magnitudes (i.e., within 0.5 mag), and effective radius (i.e., within 0.2 dex), down to 26 mag. To quantitatively determine whether a double S\'ersic model better describes our two-component systems compared to a single S\'ersic profile, we evaluate the Bayesian Information Criterion for both model configurations. To extend the applicability of our results to other NIRCam programs, we evaluate the signal-to-noise ratio (SNR) of the simulated galaxies and find that model parameters are reliably reproduced when the SNR exceeds 10. Our work demonstrates the detailed morphological measurement uncertainties using single and double S\'ersic models, which provides an essential reference for future JWST/NIRCam-based morphological studies, especially for high-redshift galaxies.

Figures

Figures reproduced from arXiv: 2506.18351 by the authors.

Figure 1
Figure 1. This three-panel figure illustrates a systematic workflow for generating our mock galaxy images. Panel (a) shows a high-resolution, noise-free simulated galaxy, clearly displaying its structural morphology. Panel (b) introduces Poisson noise into the simulation, replicating realistic observational conditions encountered in astronomical imaging. Panel (c) presents a section of a CEERS image, into which we embed the s… view at source ↗
Figure 2
Figure 2. Single Sérsic model fitting results for two example simulated galaxies with B/T of 20% (ID = 75) and 50% (ID = 26), respectively. The panels from left to right are: (1) the simulated galaxy image, (2) the best-fitting Single Sérsic model, (3) the residuals normalized by the variance, and (4) the one-dimensional surface brightness profiles (top) with the corresponding residuals (bottom). In panel (4), the open circle… view at source ↗
Figure 3
Figure 3. Parameter recovery results for single Sérsic fits. The left column shows the results for the F150W band, while the right column corresponds to the F356W band. The color bars represent the B/T (top panels) and the simulated galaxy radius 𝑅sim (bottom panels, as defined in Equation 2). For simulated galaxies brighter than magnitude 26 (𝑚total,sim < 26), fitting accuracies are high, with magnitude errors consistently w… view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: Relation between Sérsic index (fitting) and simulated B/T (truth) for galaxies in the F150W and F356W. Scatter points represent individual galaxies, with colors indicating their total magnitudes. The red line represents the median B/T value at each Sérsic index, and th…
Figure 5
Figure 5. Figure 5: Double Sérsic model fitting results for the simulated galaxy ID = 26. The blue and orange lines in panel (4) represent the bulge and disk contributions, respectively, while the black line represents the total model profile. See the caption of [PITH_FULL_IMAGE:figures/…
Figure 6
Figure 6. Figure 6: Comparison of simulated and inferred galaxy parameters: differences in magnitude and effective radius as functions of simulated bulge and disk magnitudes in the F150W and F356W filters. The color scale represents the B/T for both bulge and disk panels. The red points w…
Figure 7
Figure 7. Figure 7: Comparison of simulated and inferred parameters for single Sérsic fitting as a function of SNR. See the caption of [PITH_FULL_IMAGE:figures/full_fig_p011_7.png]
Figure 8
Figure 8. Figure 8: Comparison of simulated and inferred parameters for galaxy components as a function of SNR. See the caption of [PITH_FULL_IMAGE:figures/full_fig_p012_8.png]
Figure 9
Figure 9. Figure 9: Comparison between galfit and galight for magnitude and effective radius of single Sérsic model fitting . See captions of [PITH_FULL_IMAGE:figures/full_fig_p013_9.png]
Figure 10
Figure 10. Figure 10: Comparison between galfit and galight for magnitude and effective radius of double Sérsic model fitting. See caption of [PITH_FULL_IMAGE:figures/full_fig_p014_10.png]

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Works this paper leans on

66 extracted references · 20 canonical work pages

  1. [1]

    Athanassoula E., 2005, @doi [ ] 10.1111/j.1365-2966.2005.08872.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.358.1477A 358, 1477

    arXiv 2005

  2. [2]

    K., 2014, @doi [ ] 10.1093/mnras/stu1106 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443..874B 443, 874

    Bernardi M., Meert A., Vikram V., Huertas-Company M., Mei S., Shankar F., Sheth R. K., 2014, @doi [ ] 10.1093/mnras/stu1106 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443..874B 443, 874

    doi:10.1093/mnras/stu1106 2014

  3. [3]

    Bi D., Shlosman I., Romano-D \' az E., 2022a, @doi [ ] 10.1093/mnras/stac363 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.513..693B 513, 693

    doi:10.1093/mnras/stac363

  4. [4]

    Bi D., Shlosman I., Romano-D \' az E., 2022b, @doi [ ] 10.3847/1538-4357/ac779b , https://ui.adsabs.harvard.edu/abs/2022ApJ...934...52B 934, 52

    doi:10.3847/1538-4357/ac779b

  5. [5]

    Birrer S., Amara A., 2018, @doi [Physics of the Dark Universe] 10.1016/j.dark.2018.11.002 , https://ui.adsabs.harvard.edu/abs/2018PDU....22..189B 22, 189

    doi:10.1016/j.dark.2018.11.002 2018

  6. [6]

    Birrer S., et al., 2021, @doi [The Journal of Open Source Software] 10.21105/joss.03283 , https://ui.adsabs.harvard.edu/abs/2021JOSS....6.3283B 6, 3283

    doi:10.21105/joss.03283 2021

  7. [7]

    K., et al., 2024, Nature Astronomy, 8, 774

    Blanchard P. K., et al., 2024, Nature Astronomy, 8, 774

    work page 2024

  8. [8]

    M., Amarantidis S., 2019, @doi [ ] 10.1051/0004-6361/201935144 , https://ui.adsabs.harvard.edu/abs/2019A&A...632A.128B 632, A128

    Breda I., Papaderos P., Gomes J. M., Amarantidis S., 2019, @doi [ ] 10.1051/0004-6361/201935144 , https://ui.adsabs.harvard.edu/abs/2019A&A...632A.128B 632, A128

    doi:10.1051/0004-6361/201935144 2019

Show all 66 references
  1. [9]

    A., et al., 2014, @doi [ ] 10.1093/mnras/stu1478 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.1001B 444, 1001

    Bruce V. A., et al., 2014, @doi [ ] 10.1093/mnras/stu1478 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.1001B 444, 1001

    2014 doi

  2. [10]

    Casura S., et al., 2022, Monthly Notices of the Royal Astronomical Society, 516, 942

    2022

  3. [11]

    J., 2014, @doi [ ] 10.1146/annurev-astro-081913-040037 , https://ui.adsabs.harvard.edu/abs/2014ARA&A..52..291C 52, 291

    Conselice C. J., 2014, @doi [ ] 10.1146/annurev-astro-081913-040037 , https://ui.adsabs.harvard.edu/abs/2014ARA&A..52..291C 52, 291

    2014 doi

  4. [12]

    Ding X., et al., 2020, @doi [The Astrophysical Journal] 10.3847/1538-4357/ab5b90 , 888, 37

    2020 doi

  5. [13]

    D., Onoue M., 2022, @doi [ ] 10.3847/2041-8213/ac9c02 , https://ui.adsabs.harvard.edu/abs/2022ApJ...939L..28D 939, L28

    Ding X., Silverman J. D., Onoue M., 2022, @doi [ ] 10.3847/2041-8213/ac9c02 , https://ui.adsabs.harvard.edu/abs/2022ApJ...939L..28D 939, L28

    2022 doi

  6. [14]

    Ding X., et al., 2023, @doi [ ] 10.1038/s41586-023-06345-5 , https://ui.adsabs.harvard.edu/abs/2023Natur.621...51D 621, 51

    2023 doi

  7. [15]

    C., Debattista V

    Du M., Ho L. C., Debattista V. P., Pillepich A., Nelson D., Hernquist L., Weinberger R., 2021, The Astrophysical Journal, 919, 135

    2021

  8. [16]

    Ferreira L., et al., 2022, @doi [ ] 10.3847/2041-8213/ac947c , https://ui.adsabs.harvard.edu/abs/2022ApJ...938L...2F 938, L2

    2022 doi

  9. [17]

    L., Pirzkal N., Malhotra S., Rhoads J

    Finkelstein S. L., Pirzkal N., Malhotra S., Rhoads J. E., 2017, @doi [The Astrophysical Journal] 10.3847/1538-4357/aa6c80 , 839, 99

    2017 doi

  10. [18]

    L., Bagley M., Ferguson H

    Finkelstein S. L., Bagley M., Ferguson H. C., et al., 2022, @doi [The Astrophysical Journal] 10.3847/1538-4357/ac84b1 , 936, 80

    2022 doi

  11. [19]

    B., Drory N., 2008, @doi [ ] 10.1088/0004-6256/136/2/773 , https://ui.adsabs.harvard.edu/abs/2008AJ....136..773F 136, 773

    Fisher D. B., Drory N., 2008, @doi [ ] 10.1088/0004-6256/136/2/773 , https://ui.adsabs.harvard.edu/abs/2008AJ....136..773F 136, 773

    2008 doi

  12. [20]

    C., 1970, @doi [ ] 10.1086/150474 , https://ui.adsabs.harvard.edu/abs/1970ApJ...160..811F 160, 811

    Freeman K. C., 1970, @doi [ ] 10.1086/150474 , https://ui.adsabs.harvard.edu/abs/1970ApJ...160..811F 160, 811

    1970 doi

  13. [21]

    A., 2009a, @doi [ ] 10.1111/j.1365-2966.2008.14257.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.393.1531G 393, 1531

    Gadotti D. A., 2009a, @doi [ ] 10.1111/j.1365-2966.2008.14257.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.393.1531G 393, 1531

    2008

  14. [22]

    A., 2009b, Monthly Notices of the Royal Astronomical Society, 393, 1531

    Gadotti D. A., 2009b, Monthly Notices of the Royal Astronomical Society, 393, 1531

  15. [23]

    Genel S., et al., 2018, @doi [ ] 10.1093/mnras/stx3078 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.3976G 474, 3976

    2018 doi

  16. [24]

    C., Macchetto F

    Giavalisco M., Steidel C. C., Macchetto F. D., 1996, @doi [ ] 10.1086/177859 , https://ui.adsabs.harvard.edu/abs/1996ApJ...470..189G 470, 189

    1996 doi

  17. [25]

    H \"a u ler B., et al., 2013, @doi [ ] 10.1093/mnras/sts633 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.430..330H 430, 330

    2013 doi

  18. [26]

    F., et al., 2009, @doi [ ] 10.1111/j.1365-2966.2009.14983.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.397..802H 397, 802

    Hopkins P. F., et al., 2009, @doi [ ] 10.1111/j.1365-2966.2009.14983.x , https://ui.adsabs.harvard.edu/abs/2009MNRAS.397..802H 397, 802

    2009

  19. [27]

    Jogee S., et al., 2004, @doi [ ] 10.1086/426138 , https://ui.adsabs.harvard.edu/abs/2004ApJ...615L.105J 615, L105

    2004 doi

  20. [28]

    S., Silverman J

    Kalita B. S., Silverman J. D., Daddi E., Mercier W., Ho L. C., Ding X., 2025, @doi [ ] 10.1093/mnras/staf031 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.537..402K 537, 402

    2025 doi

  21. [29]

    Kelly P., et al., 2023, The Astrophysical Journal

    2023

  22. [30]

    pp 1942--1945

    Kennedy J., Eberhart R., 1995, in Proceedings of the IEEE International Conference on Neural Networks. pp 1942--1945

    1995

  23. [31]

    Kormendy J., 2013, arXiv preprint arXiv:1311.2609

    2013 arXiv

  24. [32]

    Kormendy J., Kennicutt Jr. R. C., 2004, @doi [ ] 10.1146/annurev.astro.42.053102.134024 , https://ui.adsabs.harvard.edu/abs/2004ARA&A..42..603K 42, 603

    2004

  25. [33]

    B., Cornell M

    Kormendy J., Fisher D. B., Cornell M. E., Bender R., 2009, @doi [ ] 10.1088/0067-0049/182/1/216 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..216K 182, 216

    2009 doi

  26. [34]

    D., Bird S., 2025, @doi [The Open Journal of Astrophysics] 10.33232/001c.129991 , 8

    LaChance P., Croft R., Ni Y., Chen N., Matteo T. D., Bird S., 2025, @doi [The Open Journal of Astrophysics] 10.33232/001c.129991 , 8

    2025 doi

  27. [35]

    N., Gunn J

    Lackner C. N., Gunn J. E., 2012, @doi [ ] 10.1111/j.1365-2966.2012.20450.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.421.2277L 421, 2277

    2012

  28. [36]

    G., Maddox S

    Lambas D. G., Maddox S. J., Loveday J., 1992, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/258.2.404 , 258, 404

    1992 doi

  29. [37]

    Lang P., et al., 2014, @doi [ ] 10.1088/0004-637X/788/1/11 , https://ui.adsabs.harvard.edu/abs/2014ApJ...788...11L 788, 11

    2014 doi

  30. [38]

    Le Bail A., et al., 2024, @doi [ ] 10.1051/0004-6361/202347465 , https://ui.adsabs.harvard.edu/abs/2024A&A...688A..53L 688, A53

    2024 doi

  31. [39]

    Meert A., Vikram V., Bernardi M., 2013a, @doi [ ] 10.1093/mnras/stt822 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.433.1344M 433, 1344

    doi

  32. [40]

    Meert A., Vikram V., Bernardi M., 2013b, Monthly Notices of the Royal Astronomical Society, 433, 1344

  33. [41]

    Miller T. B., et al., 2024, JWST UNCOVERs the Optical Size - Stellar Mass Relation at 4<z<8 : Rapid Growth in the Sizes of Low Mass Galaxies in the First Billion Years of the Universe ( @eprint arXiv 2412.06957 ), https://arxiv.org/abs/2412.06957

    2024 arXiv

  34. [42]

    Cambridge University Press

    Mo H., Van den Bosch F., White S., 2010, Galaxy formation and evolution. Cambridge University Press

    2010

  35. [43]

    Montes M., Trujillo I., 2022, The Astrophysical Journal Letters, 940, L51

    2022

  36. [44]

    J., Franx M., 2013, The Astrophysical Journal, 777, 117

    Mosleh M., Williams R. J., Franx M., 2013, The Astrophysical Journal, 777, 117

    2013

  37. [45]

    B., Ellis R

    Newman A. B., Ellis R. S., Bundy K. e. a., 2012, @doi [ApJ] 10.1088/0004-637X/746/2/162 , 746, 162

    2012 doi

  38. [46]

    Y., Ho L

    Peng C. Y., Ho L. C., Impey C. D., Rix H.-W., 2002, @doi [ ] 10.1086/340952 , https://ui.adsabs.harvard.edu/abs/2002AJ....124..266P 124, 266

    2002 doi

  39. [47]

    Y., Ho L

    Peng C. Y., Ho L. C., Impey C. D., Rix H.-W., 2010, The Astronomical Journal, 139, 2097

    2010

  40. [48]

    J., et al., 2023, @doi [ ] 10.1088/1538-3873/acac53 , https://ui.adsabs.harvard.edu/abs/2023PASP..135b8001R 135, 028001

    Rieke M. J., et al., 2023, @doi [ ] 10.1088/1538-3873/acac53 , https://ui.adsabs.harvard.edu/abs/2023PASP..135b8001R 135, 028001

    2023 doi

  41. [49]

    R., Perrin M

    Rigby J. R., Perrin M. D., McElwain M. W., et al., 2022, @doi [Publications of the Astronomical Society of the Pacific] 10.1088/1538-3873/ac8a3a , 134, 073001

    2022 doi

  42. [50]

    Sandage A., 2005, @doi [ ] 10.1146/annurev.astro.43.112904.104839 , https://ui.adsabs.harvard.edu/abs/2005ARA&A..43..581S 43, 581

    2005

  43. [52]

    R., Ellison S

    Simard L., Trevor Mendel J., Patton D. R., Ellison S. L., McConnachie A. W., 2011b, @doi [The Astrophysical Journal Supplement Series] 10.1088/0067-0049/196/1/11 , 196, 11

    doi

  44. [53]

    C., Zhuang M.-Y., Ma C., Chen C., Li R., 2024, The Astrophysical Journal, 960, 104

    Sun W., Ho L. C., Zhuang M.-Y., Ma C., Chen C., Li R., 2024, The Astrophysical Journal, 960, 104

    2024

  45. [54]

    A., 2016, @doi [MNRAS] 10.1093/mnras/stv2896 , 456, 3378

    Sánchez-Janssen R., Gadotti D. A., 2016, @doi [MNRAS] 10.1093/mnras/stv2896 , 456, 3378

    2016 doi

  46. [55]

    L., 1963, Boletin de la Asociacion Argentina de Astronomia, 6, 41

    Sérsic J. L., 1963, Boletin de la Asociacion Argentina de Astronomia, 6, 41

    1963

  47. [56]

    P., Johnston E., 2017, @doi [ ] 10.1093/mnras/stw3183 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.466.2024T 466, 2024

    Tabor M., Merrifield M., Arag \'o n-Salamanca A., Cappellari M., Bamford S. P., Johnston E., 2017, @doi [ ] 10.1093/mnras/stw3183 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.466.2024T 466, 2024

    2017 doi

  48. [57]

    Treu T., et al., 2023, @doi [ ] 10.3847/2041-8213/ac9283 , https://ui.adsabs.harvard.edu/abs/2023ApJ...942L..28T 942, L28

    2023 doi

  49. [58]

    J., Bundy K., Cooper M

    Trujillo I., Conselice C. J., Bundy K., Cooper M. C., Eisenhardt P., Ellis R. S., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12388.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.382..109T 382, 109

    2007

  50. [59]

    Yang L., et al., 2022, @doi [ ] 10.3847/2041-8213/ac8803 , https://ui.adsabs.harvard.edu/abs/2022ApJ...938L..17Y 938, L17

    2022 doi

  51. [60]

    arXiv:2504.07185

    Yang L., et al., 2025, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2025arXiv250407185Y p. arXiv:2504.07185

    2025 arXiv

  52. [61]

    de Vaucouleurs G., 1948a, Annales d'Astrophysique, https://ui.adsabs.harvard.edu/abs/1948AnAp...11..247D 11, 247

  53. [62]

    de Vaucouleurs G., 1948b, Annales d'Astrophysique, Vol. 11, p. 247, 11, 247

  54. [63]

    van der Kruit P., Freeman K., 2011, @doi [Annual Review of Astronomy and Astrophysics] 10.1146/annurev-astro-083109-153241 , 49, 301–371

    2011 doi

  55. [64]

    van der Wel A., et al., 2012, @doi [ ] 10.1088/0067-0049/203/2/24 , https://ui.adsabs.harvard.edu/abs/2012ApJS..203...24V 203, 24

    2012 doi

  56. [65]

    van der Wel A., Franx M., van Dokkum P. G. e. a., 2014, @doi [ApJ] 10.1088/0004-637X/788/1/28 , 788, 28

    2014 doi

  57. [66]

    van der Wel A., et al., 2023, The Astrophysical Journal, 960, 53

    2023

  58. [67]

    write newline

    " 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 15, 2026 · model on record in the stance chip above.