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arxiv: 2604.13408 · v1 · submitted 2026-04-15 · 🌌 astro-ph.GA

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ALESS--JWST: Dust-driven Morphologies and Hidden Stellar Mass in zsim3 Sub-millimeter Galaxies

J. Li , E. da Cunha , J. A. Hodge , I. Smail , S. Kendrew , A. battisti , M. Cracraft , L. A. Boogaard
show 12 more authors
W. N. Brandt C.-C. Chen P. Cox K. K. Knudsen C.-L. Liao G. Calistro Rivera M. Rybak A. M. Swinbank P. van der Werf F. Walter A. Weiss B. A. Westoby
Authors on Pith no claims yet

Pith reviewed 2026-05-10 13:22 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords submillimeter galaxiesdust attenuationstellar mass biasJWST observationsgalaxy morphologySED fittinghigh-redshift galaxiesALMA imaging
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The pith

Spatially varying dust attenuation in z~3 submillimeter galaxies creates a dust-obscuration bias that misses stellar mass in integrated fits.

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

The paper combines JWST NIRCam and MIRI imaging with high-resolution ALMA 870 micron data for twelve submillimeter galaxies at redshift around 3 to enable spatially resolved SED fitting on kiloparsec scales. It finds that integrated stellar mass estimates remain biased low even with rest-frame 2 micron coverage because dust attenuation varies spatially across each galaxy, hiding obscured stellar populations. This dust-obscuration bias, distinct from classical outshining by young stars, produces wavelength-dependent morphologies where rest-frame optical light shows central offsets and inflated sizes while longer wavelengths reveal compact structures aligned with the dust continuum. The analysis shows centrally concentrated dust drives these effects and that stellar and dust sizes are intrinsically consistent, implying compact obscured star formation builds dense cores en route to quiescent galaxies. The results indicate these biases likely affect many massive star-forming systems at redshifts above 1.

Core claim

Resolved SED fitting reveals a systematic stellar mass bias in integrated fits even with rest-frame ~2um MIRI imaging. Rather than classical outshining, this bias is driven by spatially varying dust attenuation, creating a dust-obscuration bias that misses obscured stellar mass. Morphologies are wavelength-dependent: central obscuration at rest-frame optical wavelengths produces stellar-dust offsets and inflated sizes, while these effects diminish at longer wavelengths. Rest-frame ~1.5-3um MIRI imaging reveals compact stellar structures matching the 870um dust continuum. Centrally concentrated dust attenuation drives both offsets and size variations, and intrinsic stellar mass and dust sizes

What carries the argument

Spatially resolved SED fitting on ~kpc scales using JWST NIRCam/MIRI combined with high-resolution ALMA 870um imaging to isolate effects of spatially varying dust attenuation.

If this is right

  • Star formation remains tightly coupled to local stellar mass distribution, forming a resolved star-forming main sequence even in these obscured systems.
  • Galaxy morphologies measured at rest-frame wavelengths less than or equal to 1.6um can be significantly biased without longer-wavelength constraints.
  • The consistent sizes between stellar mass and dust continuum support a picture of compact obscured star formation building dense stellar cores that evolve into massive quiescent galaxies.
  • Obscured structures and associated biases may be common among massive star-forming galaxies at redshifts greater than or equal to 1.

Where Pith is reading between the lines

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

  • Similar dust-obscuration effects could systematically underestimate stellar masses in other high-redshift galaxy populations observed with limited mid-infrared coverage.
  • Surveys aiming for accurate high-z mass functions should include mid-infrared data to reduce biases in both mass and size measurements.
  • The tight stellar-dust size match points to a co-evolution process where dust both traces and conceals the sites of active mass assembly.
  • Accounting for this bias may help reconcile observed stellar mass densities with predictions from galaxy formation models at early times.

Load-bearing premise

The spatially resolved SED fitting on kpc scales with the chosen models and wavelength coverage accurately isolates the effects of spatially varying dust attenuation from other variables such as star-formation history or resolution limits.

What would settle it

A direct comparison showing that the total stellar mass summed from resolved fits equals the integrated fit mass for the full sample even when using only shorter-wavelength data, or independent dust maps showing no spatial correlation with the mass discrepancies.

Figures

Figures reproduced from arXiv: 2604.13408 by A. battisti, A. M. Swinbank, A. Weiss, B. A. Westoby, C.-C. Chen, C.-L. Liao, E. da Cunha, F. Walter, G. Calistro Rivera, I. Smail, J. A. Hodge, J. Li, K. K. Knudsen, L. A. Boogaard, M. Cracraft, M. Rybak, P. Cox, P. van der Werf, S. Kendrew, W. N. Brandt.

Figure 1
Figure 1. Figure 1: The stellar masses and SFRs of our targets, de￾rived from magphys SED modeling, color-coded by redshift (red squares indicate targets with photometric redshifts). The blue and green lines and filled regions show the star– forming main sequence at z = 3.5 and its ±0.3 dex region, from J. S. Speagle et al. 2014 and P. Popesso et al. 2023 re￾spectively. and ALMA 870µm data. We adopt the updated spec￾troscopic… view at source ↗
Figure 2
Figure 2. Figure 2: For each galaxy, we show the best-fit magphys SEDs for all spatial bins (grey), their sum (black), and the best-fit integrated SED (green). Red and green points denote integrated JWST/ALMA and unresolved Spitzer, Herschel, and ALMA photometry, respectively. Grey arrows indicate 3σ upper limits from ground-based optical/near-IR data (J. M. Simpson et al. 2014), supplemented by deeper limits from the VIDEO s… view at source ↗
Figure 3
Figure 3. Figure 3: For each source, the left-hand panel shows an RGB composite using JWST F770W, F444W, and F200W, respectively, with superimposed ALMA 870µm contours (2 − 24σ). The middle and right-hand panels show maps of stellar mass, SFR, and dust attenuation (AV) from our spatially-resolved SED fitting. The 850µm flux peak location is marked with white cross in the right panels, where the median AV within one MIRI PSF-s… view at source ↗
Figure 3
Figure 3. Figure 3: Continued [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Resolved star-forming main sequence (rSFMS) for each target. Colored points show independent 0.24′′ (∼ 2 kpc) bins, color-coded by their 870µm flux. The black dashed line shows the best-fit power-law relation for each galaxy, with the slope α given in the legend. neighboring bins). In most galaxies we find a clear pos￾itive correlation between these quantities. For each galaxy we fit a power law, ΣSFR ∝ ΣM… view at source ↗
Figure 5
Figure 5. Figure 5: Comparisons between the total stellar masses of our galaxies obtained from the integrated SED fitting (x-axes) with resolved SED fitting (y-axes). Left: All filters included in the resolved SED fit. Right: Only NIRCam filters used in the resolved SED fits. In both cases, the sum of stellar masses from the resolved SED fits exceed the stellar mass obtained from fitting the integrated photometry. spatially-r… view at source ↗
Figure 6
Figure 6. Figure 6: Comparison between the total stellar masses ob￾tained by summing the spatially resolved SED fits using all available filters (NIRCam+MIRI+ALMA; x-axis) and using only NIRCam bands (y-axis). The solid line shows the one– to-one relation. The dashed line indicates the best-fitting linear relation to the data, with a slope of 1.24 ± 0.05, indi￾cating a superlinear relation between the two estimates. 4.3. Wave… view at source ↗
Figure 7
Figure 7. Figure 7: Spatial offsets relative to the ALMA 870µm peak. We show the peak positions in the four JWST bands (left-hand panel), as a function of rest-frame wavelength, and in the stellar mass (center) and SFR map (right-hand panel), measured relative to the 870µm peak. The dotted lines mark the half-width at half-maximum of the F770W PSF. In all panels, points are colored by central AV inferred from integrated SED f… view at source ↗
Figure 8
Figure 8. Figure 8: Half-light radii as a function of wavelength. Left: distributions of the half-light radii for all ALESS SMGs measured in each JWST band, the ALMA 870µm map, and the stellar mass and SFR maps. Black points show independent measurements from J. A. Hodge et al. (2025). Right: half-light radius versus rest-frame wavelength for the same galaxies. Points connected by dashed lines correspond to individual galaxie… view at source ↗
Figure 9
Figure 9. Figure 9: Comparison between the intrinsic stellar effective radii, Re,∗, with those measured from F444W (left), F770W (middle), and 870µm (right) images. The x-axis in all panels shows the stellar-mass effective radii from S´ersic fits to the ΣM∗ maps using IMFIT at 240 mas pixel scale (including a 25% error floor). The y-axes show the effective radii from S´ersic modelling of each observed image with statmorph at … view at source ↗
Figure 10
Figure 10. Figure 10: Distribution of half-light radius, CAS parameters, and Gini–M20 values as a function of rest-frame wavelength (see Section 4.3.4). Points are colored by central AV (red: AV > 4.5; blue: AV ≤ 4.5), with locally-weighted smoothing curves for each group. Grey symbols show comparable measurements for z ∼ 2 SMGs from S. Gillman et al. (2023); S. Gillman et al. (2024) at similar rest-frame wavelengths. Black po… view at source ↗
Figure 11
Figure 11. Figure 11: Observed, dust-corrected model images, and resolved Aλ maps for ALESS 3.1. Top row: observed JWST images (each convolved to the MIRI/F770W resolution), plus an RGB composite using F770W, F444W, and F200W. Middle row: corresponding dust-corrected model images produced from the best-fit resolved SEDs, shown in identical format. All images are displayed with a logarithmic stretch. Bottom row: wavelength-depe… view at source ↗
Figure 12
Figure 12. Figure 12: Comparison of stellar mass effective radii (left) and stellar mass surface densities within Re,∗ (right). Red points show results from this work based on SED-derived stellar mass maps. Grey points are z ∼ 0 quiescent galaxies from ATLAS-3D (M. Cappellari et al. 2011, 2013), and pink points are z ≃ 1.5 quiescent galaxies from M. Longhetti et al. (2007). Blue squares and green circles indicate F444W-based S… view at source ↗
Figure 13
Figure 13. Figure 13: Non-parametric classifications of the ALESS SMGs. Left: Gini-M20 plane with J. M. Lotz et al. (2008) boundaries. Middle: Clumpiness-Concentration (S-C) plane showing regions for disks and ellipticals (C. J. Conselice et al. 2003; C. J. Conselice 2014). Right: Concentration-Asymmetry (C-A) plane with Hubble sequence regions and merger thresholds (M. A. Bershady et al. 2000; C. J. Conselice et al. 2003). Bl… view at source ↗
Figure 14
Figure 14. Figure 14: JWST images of our SMGs (including the ALESS 3.1 companion). For each galaxy, columns show F200W, F356W, F444W, F770W, and an RGB composite (B: F200W, G: F444W, R: F770W; linear stretch). Redshifts are indicated in the RGB panel, with ‘zp’ marking photometric values. Red contours show ALMA 870µm continuum emission, starting at 3σ and increasing by factors of two up to 24σ [PITH_FULL_IMAGE:figures/full_fi… view at source ↗
Figure 14
Figure 14. Figure 14: Continued [PITH_FULL_IMAGE:figures/full_fig_p030_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: Comparison of S´rsic parameters measured from the 870µm continuum and NIRCam/F444W imaging, before (top row) and after (bottom row) dust correction. Panels show ellipticity (e), S´ersic index (n), and position angle (PA). Points are color-coded by central AV (blue to red; see Figures 7 and 8). Median parameter ratios and their scatter are indicated in each panel [PITH_FULL_IMAGE:figures/full_fig_p031_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: Same as [PITH_FULL_IMAGE:figures/full_fig_p032_16.png] view at source ↗
read the original abstract

We present JWST/NIRCam and MIRI observations of twelve $z\sim3$ sub-millimeter galaxies (SMGs) from the ALESS survey, combined with high-resolution ($0.08''-0.16''$) ALMA 870$\mu$m imaging, enabling spatially resolved SED fitting on $\sim$kpc scales. We find a resolved star-forming main sequence linking surface densities of star formation rate and stellar mass, suggesting star formation remains tightly coupled to local mass distribution even in obscured systems. Our resolved SED analysis reveals a systematic stellar mass bias in integrated fits, even including rest-frame $\sim2\mu$m MIRI imaging. Rather than classical `outshining', this is mainly driven by spatially varying dust attenuation, indicating a `dust-obscuration bias' that causes obscured stellar mass to be missed. We show SMG morphologies are wavelength-dependent. At rest-frame optical wavelengths, central obscuration produces stellar-dust offsets and inflated sizes, while at longer wavelengths these effects diminish. The rest-frame $\sim1.5-3\mu$m MIRI imaging is less affected by dust than NIRCam and reveals compact stellar structures matching the 870$\mu$m dust continuum. We find centrally concentrated dust attenuation drives both offsets and size variations, demonstrating dust geometry is the main driver of structural diversity. Consequently, morphologies from rest-frame wavelengths $\lesssim1.6\mu$m can be biased without longer-wavelength constraints. The intrinsic stellar mass and dust continuum sizes are consistent ($R_\mathrm{e,870\mu m}/R_\mathrm{e,\ast}=1.0\pm0.4$), supporting a picture in which SMGs host compact, obscured star formation that builds dense stellar cores, consistent with evolution into massive quiescent galaxies. We suggest such obscured structures and associated biases may also be common among massive star-forming galaxies at $z\gtrsim1$, implying these effects are likely of broad relevance.

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 reports JWST/NIRCam+MIRI observations of 12 z~3 ALESS SMGs combined with high-resolution ALMA 870μm imaging. Spatially resolved SED fitting on ~kpc scales is used to identify a resolved star-forming main sequence, demonstrate that integrated stellar-mass estimates suffer a systematic underestimate even with rest-frame ~2μm MIRI data, attribute this bias primarily to spatially varying dust attenuation ('dust-obscuration bias') rather than classical outshining, and show that dust geometry drives wavelength-dependent morphologies and size offsets. The intrinsic stellar and dust-continuum sizes are found to be consistent, supporting compact obscured star formation that builds dense cores en route to massive quiescent galaxies.

Significance. If the separation of dust-attenuation effects from SFH/metallicity degeneracies holds, the work provides direct evidence for a previously under-appreciated bias in stellar-mass recovery for dusty high-z galaxies and links observed morphological diversity to dust geometry. The resolved main-sequence result and the R_e,870μm / R_e,* ~1 consistency are concrete, testable findings that bear on SMG evolutionary pathways. The inclusion of MIRI photometry to reach rest-frame near-IR is a clear technical strength that improves constraints relative to NIRCam-only studies.

major comments (2)
  1. [Abstract and resolved-SED analysis] Abstract and resolved-SED section: the central claim that the integrated stellar-mass underestimate is driven by spatially varying dust attenuation (rather than outshining) rests on the assumption that kpc-scale SED fits with the adopted SPS models, attenuation curves, and SFH parametrizations correctly isolate attenuation from age and metallicity effects. With only broadband NIRCam+MIRI photometry at z~3, age-dust-metallicity degeneracies remain; no quantitative robustness tests (e.g., varying SFH priors, attenuation-law families, or mock recovery experiments) are described to show that extra mass recovered in high-A_V pixels is not an artifact of model choice.
  2. [Methods and results] Methods and results sections: the manuscript provides no quantitative details on the SED-fitting procedure, including the specific code or templates employed, the treatment of error propagation, the handling of spatially correlated noise, or sample-completeness corrections. These omissions directly limit verification that the reported stellar-mass bias and the dust-obscuration interpretation are robust to reasonable variations in modeling assumptions.
minor comments (2)
  1. [Figures and text] Figure captions and text should explicitly state the rest-frame wavelengths sampled by each NIRCam and MIRI filter at the median redshift of the sample to aid reader interpretation of the wavelength-dependent morphology claims.
  2. [Discussion] The statement that morphologies from rest-frame wavelengths ≲1.6 μm 'can be biased' would benefit from a quantitative comparison (e.g., size or offset statistics) between NIRCam-only and NIRCam+MIRI fits for the same objects.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We are grateful to the referee for their careful reading of our manuscript and for the constructive major comments. We agree that enhancing the description of our methods and providing robustness tests will improve the paper. Below we respond to each comment in turn, indicating the revisions we will make.

read point-by-point responses

  1. Referee: [Abstract and resolved-SED analysis] Abstract and resolved-SED section: the central claim that the integrated stellar-mass underestimate is driven by spatially varying dust attenuation (rather than outshining) rests on the assumption that kpc-scale SED fits with the adopted SPS models, attenuation curves, and SFH parametrizations correctly isolate attenuation from age and metallicity effects. With only broadband NIRCam+MIRI photometry at z~3, age-dust-metallicity degeneracies remain; no quantitative robustness tests (e.g., varying SFH priors, attenuation-law families, or mock recovery experiments) are described to show that extra mass recovered in high-A_V pixels is not an artifact of model choice.

    Authors: We acknowledge that the submitted manuscript does not present quantitative robustness tests such as mock recovery experiments or systematic variations in SFH priors and attenuation laws. Our analysis relies on standard SPS models and attenuation curves, and the physical consistency with the ALMA 870μm sizes and the resolved main sequence provides supporting evidence for the dust-obscuration interpretation. Nevertheless, to strengthen the claim, we will add a dedicated subsection in the revised manuscript describing mock SED fitting experiments. These will include simulated galaxies with known stellar mass distributions, varying dust geometries, SFHs, and metallicities to demonstrate that the recovered extra mass in high-A_V regions is not driven by model degeneracies. revision: yes

  2. Referee: [Methods and results] Methods and results sections: the manuscript provides no quantitative details on the SED-fitting procedure, including the specific code or templates employed, the treatment of error propagation, the handling of spatially correlated noise, or sample-completeness corrections. These omissions directly limit verification that the reported stellar-mass bias and the dust-obscuration interpretation are robust to reasonable variations in modeling assumptions.

    Authors: We agree that the Methods section in the submitted version lacks sufficient quantitative detail for full reproducibility and verification. We will substantially expand this section in the revision to include: the specific SED-fitting code and version used, the stellar population synthesis templates and libraries, the exact parametrization of SFHs and attenuation curves, details on photometric error propagation (accounting for spatially correlated noise in the JWST and ALMA images), and any sample completeness or selection corrections applied. This will allow readers to assess the robustness to modeling assumptions. revision: yes

Circularity Check

0 steps flagged

No significant circularity; analysis relies on new data and standard methods

full rationale

The paper presents new JWST/NIRCam+MIRI and ALMA observations of z~3 SMGs and applies standard spatially resolved SED fitting on kpc scales to compare integrated versus resolved stellar masses and morphologies. The claimed dust-obscuration bias follows directly from these data-driven comparisons without any self-definitional equations, fitted inputs renamed as predictions, or load-bearing self-citations that reduce the result to its own inputs by construction. The derivation chain is self-contained and externally falsifiable via the provided photometry and imaging.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The abstract invokes standard astrophysical modeling for SED fitting but supplies no explicit free parameters, ad-hoc axioms, or new entities; assessment is limited by lack of full methods section.

axioms (1)
  • domain assumption Standard assumptions in stellar population synthesis and dust attenuation models for high-redshift galaxies
    Implicit in the resolved SED fitting described in the abstract.

pith-pipeline@v0.9.0 · 5768 in / 1291 out tokens · 35058 ms · 2026-05-10T13:22:13.569207+00:00 · methodology

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Works this paper leans on

106 extracted references · 106 canonical work pages · 1 internal anchor

  1. [1]

    2017, MNRAS, 469, 2806, doi: 10.1093/mnras/stx936 Astropy Collaboration, Price-Whelan, A

    Abdurro’uf, & Akiyama, M. 2017, MNRAS, 469, 2806, doi: 10.1093/mnras/stx936 Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, apj, 935, 167, doi: 10.3847/1538-4357/ac7c74

    work page doi:10.1093/mnras/stx936 2017

  2. [2]

    2024, A&A, 683, A182, doi: 10.1051/0004-6361/202348419

    Baes, M., Mosenkov, A., Kelly, R., et al. 2024, A&A, 683, A182, doi: 10.1051/0004-6361/202348419

    work page doi:10.1051/0004-6361/202348419 2024

  3. [3]

    B., Finkelstein , S

    Bagley, M. B., Finkelstein, S. L., Koekemoer, A. M., et al. 2023, ApJL, 946, L12, doi: 10.3847/2041-8213/acbb08

    work page doi:10.3847/2041-8213/acbb08 2023

  4. [4]

    M., Maiolino, R., Bluck, A

    Baker, W. M., Maiolino, R., Bluck, A. F. L., et al. 2022, MNRAS, 510, 3622, doi: 10.1093/mnras/stab3672

    work page doi:10.1093/mnras/stab3672 2022

  5. [5]

    The Journal of Open Source Software , year = 2016, month = oct, volume =

    Barbary, K. 2016, Journal of Open Source Software, 1, 58, doi: 10.21105/joss.00058

    work page doi:10.21105/joss.00058 2016

  6. [6]

    J., Cowie, L

    Barger, A. J., Cowie, L. L., Sanders, D. B., et al. 1998, Nature, 394, 248, doi: 10.1038/28338

    work page doi:10.1038/28338 1998

  7. [7]

    , keywords =

    Barro, G., Faber, S. M., Koo, D. C., et al. 2017, ApJ, 840, 47, doi: 10.3847/1538-4357/aa6b05

    work page doi:10.3847/1538-4357/aa6b05 2017

  8. [8]

    J., Cunha, E

    Battisti, A. J., Cunha, E. d., Shivaei, I., & Calzetti, D. 2020, ApJ, 888, 108, doi: 10.3847/1538-4357/ab5fdd

    work page doi:10.3847/1538-4357/ab5fdd 2020

  9. [9]

    J., da Cunha, E., Grasha, K., et al

    Battisti, A. J., da Cunha, E., Grasha, K., et al. 2019, ApJ, 882, 61, doi: 10.3847/1538-4357/ab345d

    work page doi:10.3847/1538-4357/ab345d 2019

  10. [10]

    A., et al., 2000, @doi [ ] 10.1086/301386 , 119, 2645

    Bershady, M. A., Jangren, A., & Conselice, C. J. 2000, AJ, 119, 2645, doi: 10.1086/301386

    work page doi:10.1086/301386 2000

  11. [11]

    1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    work page doi:10.1051/aas:1996164 1996

  12. [12]

    E., Weiss, A., Wardlow, J

    Birkin, J. E., Weiss, A., Wardlow, J. L., et al. 2021, MNRAS, 501, 3926, doi: 10.1093/mnras/staa3862

    work page doi:10.1093/mnras/staa3862 2021

  13. [13]

    Frayer, D. T. 2002, PhR, 369, 111, doi: 10.1016/S0370-1573(02)00134-5

    work page doi:10.1016/s0370-1573(02)00134-5 2002

  14. [14]

    E., Abdullah, A., et al

    Bodansky, S., Whitaker, K. E., Abdullah, A., et al. 2025, arXiv e-prints, arXiv:2507.19472, doi: 10.48550/arXiv.2507.19472

    work page doi:10.48550/arxiv.2507.19472 2025

  15. [15]

    A., Gillman, S., Melinder, J., et al

    Boogaard, L. A., Gillman, S., Melinder, J., et al. 2024, ApJ, 969, 27, doi: 10.3847/1538-4357/ad43e5

    work page doi:10.3847/1538-4357/ad43e5 2024

  16. [16]

    A., Walter, F., Weiß, A., et al

    Boogaard, L. A., Walter, F., Weiß, A., et al. 2026, ApJ, 996, 19, doi: 10.3847/1538-4357/ae14eb

    work page doi:10.3847/1538-4357/ae14eb 2026

  17. [17]

    P., Angeretti L., Leitherer C., Sirianni M., 2008, AJ, 135, 1900 Annibali F., et al., 2017, ApJ, 843, 20 Arnaboldi M., Freeman K

    Bradley, L., Sip˝ ocz, B., Robitaille, T., et al. 2022, astropy/photutils: 1.5.0, 1.5.0 Zenodo, doi: 10.5281/zenodo.6825092

    work page doi:10.5281/zenodo.6825092 2022

  18. [18]

    2019, A&A, 632, A79, doi: 10.1051/0004-6361/201936643

    Buat, V., Ciesla, L., Boquien, M., Ma lek, K., & Burgarella, D. 2019, A&A, 632, A79, doi: 10.1051/0004-6361/201936643

    work page doi:10.1051/0004-6361/201936643 2019

  19. [19]

    2023, JWST Calibration Pipeline, 1.11.3 Zenodo, doi: 10.5281/zenodo.8157276

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2023, JWST Calibration Pipeline, 1.11.3 Zenodo, doi: 10.5281/zenodo.8157276

    work page doi:10.5281/zenodo.8157276 2023

  20. [20]

    2024, JWST Calibration Pipeline, 1.13.4, Zenodo, doi: 10.5281/zenodo.10569856

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2024, JWST Calibration Pipeline, 1.13.4 Zenodo, doi: 10.5281/zenodo.10569856 Calistro Rivera, G., Hodge, J. A., Smail, I., et al. 2018, ApJ, 863, 56, doi: 10.3847/1538-4357/aacffa Cano-D´ ıaz, M., S´ anchez, S. F., Zibetti, S., et al. 2016, ApJL, 821, L26, doi: 10.3847/2041-8205/821/2/L26

    work page doi:10.5281/zenodo.10569856 2024

  21. [21]

    G., Tanaka, M., et al

    Cappellari, M., Emsellem, E., Krajnovi´ c, D., et al. 2011, MNRAS, 413, 813, doi: 10.1111/j.1365-2966.2010.18174.x 25

    work page doi:10.1111/j.1365-2966.2010.18174.x 2011

  22. [22]

    M., Alatalo, K., et al

    Cappellari, M., McDermid, R. M., Alatalo, K., et al. 2013, MNRAS, 432, 1862, doi: 10.1093/mnras/stt644

    work page doi:10.1093/mnras/stt644 2013

  23. [23]

    N., van Dokkum, P

    Cardamone, C. N., van Dokkum, P. G., Urry, C. M., et al. 2010, ApJS, 189, 270, doi: 10.1088/0067-0049/189/2/270

    work page doi:10.1088/0067-0049/189/2/270 2010

  24. [24]

    Dusty Star-Forming Galaxies at High Redshift

    Casey, C. M., Narayanan, D., & Cooray, A. 2014, PhR, 541, 45, doi: 10.1016/j.physrep.2014.02.009

    work page Pith review doi:10.1016/j.physrep.2014.02.009 2014

  25. [25]

    2003, PASP, 115, 763, doi: 10.1086/376392

    Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392

    work page internal anchor Pith review doi:10.1086/376392 2003

  26. [26]

    2025, arXiv e-prints, arXiv:2509.07913, doi: 10.48550/arXiv.2509.07913

    Chan, S.-W., Ao, Y., & Tan, Q. 2025, arXiv e-prints, arXiv:2509.07913, doi: 10.48550/arXiv.2509.07913

    work page doi:10.48550/arxiv.2509.07913 2025

  27. [27]

    M., et al

    Chen, C.-C., Smail, I., Swinbank, A. M., et al. 2015, The Astrophysical Journal, 799, 194, doi: 10.1088/0004-637X/799/2/194

    work page doi:10.1088/0004-637x/799/2/194 2015

  28. [28]

    A., Smail, I., et al

    Chen, C.-C., Hodge, J. A., Smail, I., et al. 2017, ApJ, 846, 108, doi: 10.3847/1538-4357/aa863a

    work page doi:10.3847/1538-4357/aa863a 2017

  29. [29]

    2022, ApJL, 939, L7, doi: 10.3847/2041-8213/ac98c6

    Chen, C.-C., Gao, Z.-K., Hsu, Q.-N., et al. 2022, ApJL, 939, L7, doi: 10.3847/2041-8213/ac98c6

    work page doi:10.3847/2041-8213/ac98c6 2022

  30. [30]

    2022, The Astrophysical Journal Letters, 936, L19, doi: 10.3847/2041-8213/ac8d08

    Cheng, C., Yan, H., Huang, J.-S., et al. 2022, The Astrophysical Journal Letters, 936, L19, doi: 10.3847/2041-8213/ac8d08

    work page doi:10.3847/2041-8213/ac8d08 2022

  31. [31]

    2020, MNRAS, 499, 5241, doi: 10.1093/mnras/staa3036

    Cheng, C., Ibar, E., Smail, I., et al. 2020, MNRAS, 499, 5241, doi: 10.1093/mnras/staa3036

    work page doi:10.1093/mnras/staa3036 2020

  32. [32]

    2023, The Astrophysical Journal Letters, 942, L19, doi: 10.3847/2041-8213/aca9d0

    Cheng, C., Huang, J.-S., Smail, I., et al. 2023, The Astrophysical Journal Letters, 942, L19, doi: 10.3847/2041-8213/aca9d0

    work page doi:10.3847/2041-8213/aca9d0 2023

  33. [33]

    K., Hayward, C

    Cochrane, R. K., Hayward, C. C., Angl´ es-Alc´ azar, D., et al. 2019, Monthly Notices of the Royal Astronomical Society, 488, 1779, doi: 10.1093/mnras/stz1736

    work page doi:10.1093/mnras/stz1736 2019

  34. [34]

    K., Best, P

    Cochrane, R. K., Best, P. N., Smail, I., et al. 2021, MNRAS, 503, 2622, doi: 10.1093/mnras/stab467

    work page doi:10.1093/mnras/stab467 2021

  35. [35]

    Conselice, C. J. 2014, ARA&A, 52, 291, doi: 10.1146/annurev-astro-081913-040037

    work page doi:10.1146/annurev-astro-081913-040037 2014

  36. [36]

    J., Chapman, S

    Conselice, C. J., Chapman, S. C., & Windhorst, R. A. 2003, ApJL, 596, L5, doi: 10.1086/379109 Crespo G´ omez, A., Colina, L.,´Alvarez-M´ arquez, J., et al. 2024, A&A, 691, A325, doi: 10.1051/0004-6361/202449750 da Cunha, E., Charlot, S., & Elbaz, D. 2008, MNRAS, 388, 1595, doi: 10.1111/j.1365-2966.2008.13535.x da Cunha, E., Walter, F., Smail, I. R., et al...

    work page doi:10.1086/379109 2003

  37. [37]

    Danielson, A. L. R., Swinbank, A. M., Smail, I., et al. 2017, The Astrophysical Journal, 840, 78, doi: 10.3847/1538-4357/aa6caf Dudzeviˇ ci¯ ut˙ e, U., Smail, I., Swinbank, A. M., et al. 2020, MNRAS, 494, 3828, doi: 10.1093/mnras/staa769

    work page doi:10.3847/1538-4357/aa6caf 2017

  38. [38]

    1999, ApJ, 515, 518, doi: 10.1086/307069

    Eales, S., Lilly, S., Gear, W., et al. 1999, ApJ, 515, 518, doi: 10.1086/307069

    work page doi:10.1086/307069 1999

  39. [39]

    , keywords =

    Erwin, P. 2015, ApJ, 799, 226, doi: 10.1088/0004-637X/799/2/226 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A1, doi: 10.1051/0004-6361/202243940

    work page doi:10.1088/0004-637x/799/2/226 2015

  40. [40]

    2023, Astronomy & Astrophysics, 676, A26, doi: 10.1051/0004-6361/202346531

    Gillman, S., Gullberg, B., Brammer, G., et al. 2023, Astronomy & Astrophysics, 676, A26, doi: 10.1051/0004-6361/202346531

    work page doi:10.1051/0004-6361/202346531 2023

  41. [41]

    2024, A&A, 691, A299, doi: 10.1051/0004-6361/202451006 Gim´ enez-Arteaga, C., Fujimoto, S., Valentino, F., et al

    Gillman, S., Smail, I., Gullberg, B., et al. 2024, A&A, 691, A299, doi: 10.1051/0004-6361/202451006 Gim´ enez-Arteaga, C., Fujimoto, S., Valentino, F., et al. 2024, A&A, 686, A63, doi: 10.1051/0004-6361/202349135 G´ omez-Guijarro, C., Toft, S., Karim, A., et al. 2018, ApJ, 856, 121, doi: 10.3847/1538-4357/aab206

    work page doi:10.1051/0004-6361/202451006 2024

  42. [42]

    M., Smail, I., et al

    Gullberg, B., Swinbank, A. M., Smail, I., et al. 2018, The Astrophysical Journal, 859, 12, doi: 10.3847/1538-4357/aabe8c

    work page doi:10.3847/1538-4357/aabe8c 2018

  43. [43]

    M., et al

    Gullberg, B., Smail, I., Swinbank, A. M., et al. 2019, Monthly Notices of the Royal Astronomical Society, 490, 4956, doi: 10.1093/mnras/stz2835

    work page doi:10.1093/mnras/stz2835 2019

  44. [44]

    J., Adams, N

    Harvey, T., Conselice, C. J., Adams, N. J., et al. 2025, Monthly Notices of the Royal Astronomical Society, 542, 2998, doi: 10.1093/mnras/staf1396

    work page doi:10.1093/mnras/staf1396 2025

  45. [45]

    A., Carilli, C

    Hodge, J. A., Carilli, C. L., Walter, F., et al. 2012, The Astrophysical Journal, 760, 11, doi: 10.1088/0004-637X/760/1/11

    work page doi:10.1088/0004-637x/760/1/11 2012

  46. [46]

    Royal Society Open Science , keywords =

    Hodge, J. A., & da Cunha, E. 2020, Royal Society Open Science, 7, 200556, doi: 10.1098/rsos.200556

    work page doi:10.1098/rsos.200556 2020

  47. [47]

    A., Riechers, D., Decarli, R., et al

    Hodge, J. A., Riechers, D., Decarli, R., et al. 2015, ApJL, 798, L18, doi: 10.1088/2041-8205/798/1/L18

    work page doi:10.1088/2041-8205/798/1/l18 2015

  48. [48]

    A., Karim, A., Smail, I., et al

    Hodge, J. A., Karim, A., Smail, I., et al. 2013, ApJ, 768, 91, doi: 10.1088/0004-637X/768/1/91

    work page doi:10.1088/0004-637x/768/1/91 2013

  49. [49]

    A., Swinbank, A

    Hodge, J. A., Swinbank, A. M., Simpson, J. M., et al. 2016, The Astrophysical Journal, 833, 103, doi: 10.3847/1538-4357/833/1/103

    work page doi:10.3847/1538-4357/833/1/103 2016

  50. [50]

    A., Smail, I., Walter, F., et al

    Hodge, J. A., Smail, I., Walter, F., et al. 2019, The Astrophysical Journal, 876, 130, doi: 10.3847/1538-4357/ab1846

    work page doi:10.3847/1538-4357/ab1846 2019

  51. [51]

    A., da Cunha, E., Kendrew, S., et al

    Hodge, J. A., da Cunha, E., Kendrew, S., et al. 2025, ApJ, 978, 165, doi: 10.3847/1538-4357/ad9a52

    work page doi:10.3847/1538-4357/ad9a52 2025

  52. [52]

    2009, MNRAS, 395, 1391, doi: 10.1111/j.1365-2966.2009.14471.x

    Hopkins, P. F., Bundy, K., Murray, N., et al. 2009, MNRAS, 398, 898, doi: 10.1111/j.1365-2966.2009.15062.x

    work page doi:10.1111/j.1365-2966.2009.15062.x 2009

  53. [53]

    H., Serjeant, S., Dunlop, J., et al

    Hughes, D. H., Serjeant, S., Dunlop, J., et al. 1998, Nature, 394, 241, doi: 10.1038/28328

    work page doi:10.1038/28328 1998

  54. [54]

    2026, ApJ, 996, 121, doi: 10.3847/1538-4357/ae157e

    Ikeda, R., Iono, D., Tadaki, K.-i., et al. 2026, ApJ, 996, 121, doi: 10.3847/1538-4357/ae157e

    work page doi:10.3847/1538-4357/ae157e 2026

  55. [55]

    Inami, H., Algera, H. S. B., Schouws, S., et al. 2022, MNRAS, 515, 3126, doi: 10.1093/mnras/stac1779

    work page doi:10.1093/mnras/stac1779 2022

  56. [56]

    2024, ApJ, 964, 192, doi: 10.3847/1538-4357/ad2512 26

    Ito, K., Valentino, F., Brammer, G., et al. 2024, ApJ, 964, 192, doi: 10.3847/1538-4357/ad2512 26

    work page doi:10.3847/1538-4357/ad2512 2024

  57. [57]

    J., Bonfield, D

    Jarvis, M. J., Bonfield, D. G., Bruce, V. A., et al. 2013, MNRAS, 428, 1281, doi: 10.1093/mnras/sts118

    work page doi:10.1093/mnras/sts118 2013

  58. [58]

    M., Hodge, J

    Karim, A., Swinbank, A. M., Hodge, J. A., et al. 2013, MNRAS, 432, 2, doi: 10.1093/mnras/stt196

    work page doi:10.1093/mnras/stt196 2013

  59. [59]

    2024, arXiv e-prints, arXiv:2402.07982, doi: 10.48550/arXiv.2402.07982

    Killi, M., Ginolfi, M., Popping, G., et al. 2024, arXiv e-prints, arXiv:2402.07982, doi: 10.48550/arXiv.2402.07982

    work page doi:10.48550/arxiv.2402.07982 2024

  60. [60]

    M., Faber, S

    Koekemoer, A. M., Faber, S. M., Ferguson, H. C., et al. 2011, ApJS, 197, 36, doi: 10.1088/0067-0049/197/2/36

    work page doi:10.1088/0067-0049/197/2/36 2011

  61. [61]

    E., et al

    Kokorev, V., Jin, S., Magdis, G. E., et al. 2023, The Astrophysical Journal Letters, 945, L25, doi: 10.3847/2041-8213/acbd9d

    work page doi:10.3847/2041-8213/acbd9d 2023

  62. [62]

    I., et al

    Koller, M., Ziegler, B., Ciocan, B. I., et al. 2024, arXiv e-prints, arXiv:2406.20017, doi: 10.48550/arXiv.2406.20017

    work page doi:10.48550/arxiv.2406.20017 2024

  63. [63]

    2019, The Astrophysical Journal, 879, 54, doi: 10.3847/1538-4357/ab1f77 Le Bail, A., Daddi, E., Elbaz, D., et al

    Lang, P., Schinnerer, E., Smail, I., et al. 2019, The Astrophysical Journal, 879, 54, doi: 10.3847/1538-4357/ab1f77 Le Bail, A., Daddi, E., Elbaz, D., et al. 2024, Astronomy & Astrophysics, 688, A53, doi: 10.1051/0004-6361/202347465

    work page doi:10.3847/1538-4357/ab1f77 2019

  64. [64]

    2024, The Astrophysical Journal, 976, 70, doi: 10.3847/1538-4357/ad7fee

    Li, J., Da Cunha, E., Gonz´ alez-L´ opez, J., et al. 2024, The Astrophysical Journal, 976, 70, doi: 10.3847/1538-4357/ad7fee

    work page doi:10.3847/1538-4357/ad7fee 2024

  65. [65]

    Lines, N. E. P., Bowler, R. A. A., Adams, N. J., et al. 2025, MNRAS, 539, 2685, doi: 10.1093/mnras/staf627

    work page doi:10.1093/mnras/staf627 2025

  66. [66]

    R., Faulkner, A

    Longhetti, M., Saracco, P., Severgnini, P., et al. 2007, MNRAS, 374, 614, doi: 10.1111/j.1365-2966.2006.11171.x

    work page doi:10.1111/j.1365-2966.2006.11171.x 2007

  67. [67]

    M., Primack, J., & Madau, P

    Lotz, J. M., Primack, J., & Madau, P. 2004, AJ, 128, 163, doi: 10.1086/421849

    work page doi:10.1086/421849 2004

  68. [68]

    M., Davis, M., Faber, S

    Lotz, J. M., Davis, M., Faber, S. M., et al. 2008, ApJ, 672, 177, doi: 10.1086/523659

    work page doi:10.1086/523659 2008

  69. [69]

    2021, MNRAS, 501, 2659, doi: 10.1093/mnras/staa3766

    Lustig, P., Strazzullo, V., D’Eugenio, C., et al. 2021, MNRAS, 501, 2659, doi: 10.1093/mnras/staa3766

    work page doi:10.1093/mnras/staa3766 2021

  70. [70]

    2024, ApJ, 972, 134, doi: 10.3847/1538-4357/ad5c6a

    Martorano, M., van der Wel, A., Baes, M., et al. 2024, ApJ, 972, 134, doi: 10.3847/1538-4357/ad5c6a

    work page doi:10.3847/1538-4357/ad5c6a 2024

  71. [71]

    M., Cooper, O

    McKinney, J., Manning, S. M., Cooper, O. R., et al. 2023, The Astrophysical Journal, 956, 72, doi: 10.3847/1538-4357/acf614

    work page doi:10.3847/1538-4357/acf614 2023

  72. [72]

    M., Long, A

    McKinney, J., Casey, C. M., Long, A. S., et al. 2025, ApJ, 979, 229, doi: 10.3847/1538-4357/ada357

    work page doi:10.3847/1538-4357/ada357 2025

  73. [73]

    A., Bonzini, M., Fomalont, E

    Miller, N. A., Bonzini, M., Fomalont, E. B., et al. 2013, The Astrophysical Journal Supplement Series, 205, 13, doi: 10.1088/0067-0049/205/2/13

    work page doi:10.1088/0067-0049/205/2/13 2013

  74. [74]

    J., et al

    Mun, M., Wisnioski, E., Battisti, A. J., et al. 2024, MNRAS, 530, 5072, doi: 10.1093/mnras/stae1132

    work page doi:10.1093/mnras/stae1132 2024

  75. [75]

    H., & Ostriker, J

    Naab, T., Johansson, P. H., & Ostriker, J. P. 2009, ApJL, 699, L178, doi: 10.1088/0004-637X/699/2/L178

    work page doi:10.1088/0004-637x/699/2/l178 2009

  76. [76]

    B., Ellis, R

    Newman, A. B., Ellis, R. S., Bundy, K., & Treu, T. 2012, ApJ, 746, 162, doi: 10.1088/0004-637X/746/2/162

    work page doi:10.1088/0004-637x/746/2/162 2012

  77. [77]

    , keywords =

    Oke, J. B., & Gunn, J. E. 1983, ApJ, 266, 713, doi: 10.1086/160817

    work page doi:10.1086/160817 1983

  78. [78]

    Updated point spread function simulations for JWST with WebbPSF

    Perrin, M. D., Sivaramakrishnan, A., Lajoie, C.-P., et al. 2014, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9143, Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave, ed. J. Oschmann, Jacobus M., M. Clampin, G. G. Fazio, & H. A. MacEwen, 91433X, doi: 10.1117/12.2056689

    work page doi:10.1117/12.2056689 2014

  79. [79]

    2021, A&A, 650, A134, doi: 10.1051/0004-6361/202140733

    Pessa, I., Schinnerer, E., Belfiore, F., et al. 2021, A&A, 650, A134, doi: 10.1051/0004-6361/202140733

    work page doi:10.1051/0004-6361/202140733 2021

  80. [80]

    2023, MNRAS, 519, 1526, doi: 10.1093/mnras/stac3214

    Popesso, P., Concas, A., Cresci, G., et al. 2023, MNRAS, 519, 1526, doi: 10.1093/mnras/stac3214

    work page doi:10.1093/mnras/stac3214 2023

Showing first 80 references.