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REVIEW 3 major objections 4 minor 99 references

Nearby dwarf galaxies with extreme star formation rates: a window into dwarf-galaxy evolution in the early Universe

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read Nearby dwarf galaxies with extreme star formation are far more likely to be interacting, suggesting that galaxy collisions helped build dwarf galaxies in the early Universe.

desk verdict Useful low-mass analogue sample, but the z~5.5 interpretation rests on an extrapolation the paper itself undercuts. read the letter →

arxiv 2506.03265 v1 pith:C7ZFLNDC submitted 2025-06-03 astro-ph.GA

S. Kaviraj , B. Bichang'a , I. Lazar , A. E. Watkins , G. Martin , R. A. Jackson This is my paper
classification astro-ph.GA
keywords dwarfgalaxiesstarformationratesgalaxyinteractionsmainsequencehigh-redshiftanaloguesearly-typedwarfsJWST
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

Understanding how dwarf galaxies—the most numerous galaxies in the Universe—assembled their stars in the early Universe is difficult because dwarfs at high redshift are faint. This paper identifies nearby ($z\sim 0.2$) dwarf galaxies with star formation rates of 0.1–3 $M_{\odot}\,\mathrm{yr}^{-1}$, extreme for their $10^7$–$10^8$ $M_{\odot}$ masses, and argues they are plausible stand-ins for dwarfs at $z\sim 5.5$. Comparing them with matched 'normal' dwarfs, the paper finds no difference in galaxy size or distance to large-scale structures, but the analogues are far more likely to be interacting (36% vs 4%) and to have early-type morphology (28% vs 5%). The authors conclude that interactions, which were more frequent in the early Universe, boost star formation in dwarf galaxies, and that low-redshift star-formation 'main sequence' relations extrapolated to high redshift under-predict dwarf SFRs because they are built mostly from non-interacting local systems.

What carries the argument

The central machinery is the analogue-selection method built on the star-formation main sequence (SFMS), the empirical relation between galaxy stellar mass and star formation rate that shifts upward with redshift. The authors compute the local ($z\sim 0.2$) SFMS ridgeline from the COSMOS2020 catalogue, add the $z\sim 5.5$ offset measured by Popesso et al. (2023) at $M_{\star}\approx 10^{8.8}$ $M_{\odot}$, and define as analogues all dwarfs with SFRs at or above the extrapolated $z\sim 5.5$ locus in the $10^7$–$10^8$ $M_{\odot}$ range. The comparison then rests on visually classified HST morphologies (early-type vs late-type, with interaction flags for tidal features and asymmetries) and on DisPerSE-based projected distances to filaments, nodes and massive galaxies, against control samples matched in stellar mass and redshift.

What would settle it

A complete, mass-limited JWST survey of dwarfs at $4.5<z<6$ that measures both their SFRs and their merger/interaction fraction could settle the claim: if the interacting fraction at $z\sim 5.5$ is not elevated relative to local dwarfs, the interaction-driven interpretation fails, and if the measured SFMS offset at $10^7$–$10^8$ $M_{\odot}$ differs from the Popesso et al. (2023) value, the analogue selection itself is invalid.

Watch

Extended reading notes

Core claim

The paper's central claim is that extreme star formation in low-mass dwarf galaxies is not driven by compactness or by living in gas-rich large-scale environments, but is associated with galaxy interactions. In the analogue population the interacting fraction is $0.36\pm 0.05$ against $0.04\pm 0.02$ in matched normal dwarfs, and the early-type fraction is $0.28\pm 0.03$ against $0.05\pm 0.02$; interacting dwarfs and early-type dwarfs also have higher median SFRs, by $\sim 29\%$ and $\sim 55\%$ respectively. The paper further shows that an extrapolation of the star-formation main sequence from Popesso et al. (2023) to $z\sim 5.5$ underestimates the SFRs of observed dwarfs in the $10^7$–$10^8$ $M_{\odot}$ range from Curti et al. (2024). It interprets this as evidence that interactions—more frequent at early epochs—boost dwarf SFRs, so that 'higher gas availability, augmented by interactions, drives much of the stellar mass assembly of dwarf galaxies in the early Universe.'

Load-bearing premise

The whole comparison rests on assuming that the star-formation main-sequence offset between $z\sim 0.2$ and $z\sim 5.5$, which is measured for more massive galaxies, is unchanged for dwarfs 10–100 times less massive; if this extrapolation is wrong, the selected analogues do not represent the $z\sim 5.5$ dwarf population they claim to stand in for.

Editorial extensions

If this is right

  • High-redshift dwarf SFRs are likely to be higher than simple star-formation main-sequence extrapolations predict, because those extrapolations are calibrated mostly on low-redshift, non-interacting systems.
  • Interactions are a plausible mechanism for building dispersion-dominated (early-type) dwarf structure at early times, since the early-type fraction tracks the interacting fraction.
  • The lack of environmental and size differences rules out large-scale environment and compactness as the primary drivers of extreme dwarf starbursts in this mass range.
  • The analogue population provides a local laboratory where the morphological signatures of interaction-driven star formation can be studied at high signal-to-noise, complementing JWST observations of the early Universe.

Reading between the lines

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

  • A direct test of the interpretation would be measuring the merger/interaction fraction of a mass-limited sample of real $z\sim 5.5$ dwarfs; if it is not elevated relative to local dwarfs, the analogue-driven argument would be weakened. (Editorial inference.)
  • Because the analogues' SED-based stellar masses assume smooth star-formation histories, a population with roughly a third interacting systems may have systematically biased mass estimates; spatially resolved stellar-population fitting of a few analogues could test this. (Editorial inference.)
  • The environment analysis uses only massive ($>10^{10}$ $M_{\odot}$) galaxies as density tracers, so interactions with low-mass companions—which may matter most for dwarfs—are not captured by the density maps; a companion-selected analysis could sharpen the claim. (Editorial inference.)
  • If the Popesso et al. (2023) SFMS offset steepens or flattens below $M_{\star}\approx 10^{8.8}$ $M_{\odot}$, the analogue selection itself would shift, so future JWST surveys reaching $10^7$ $M_{\odot}$ at $4.5<z<6$ can validate or revise the chosen offset. (Editorial inference.)
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper uses the COSMOS2020 catalogue to select z<0.3 dwarf galaxies (10^7 < M*/M_sun < 10^8) with extreme SFRs (0.1–3 M_sun/yr), defined as analogues of z~5.5 dwarfs by requiring SFRs above an extrapolated z~5.5 star-formation main sequence. It then compares these 116 analogues with matched controls drawn from 590 'normal' dwarfs on the z~0.2 SFMS. The analysis finds no significant differences in projected distances to filaments/nodes/massive galaxies or in half-light radii, but reports significantly elevated fractions of interacting systems (0.36±0.05 vs 0.04±0.02) and early-type morphologies (0.28±0.03 vs 0.05±0.02). The authors interpret the elevated interaction fraction as evidence that interactions, combined with higher gas availability, drive much of the stellar-mass assembly of dwarfs at z~5.5.

Significance. The observational comparison is clean and the headline contrasts are large: the interacting and early-type fractions differ by roughly an order of magnitude with binomial uncertainties that do not overlap. The use of visual classification on deep HST images, Bayesian confidence intervals, and a public catalogue are strengths. If the analogue selection is valid, the paper provides a useful local laboratory for high-redshift dwarf formation and a falsifiable prediction that high-z dwarfs should show elevated interaction signatures. The main caveat is that the z~5.5 connection rests on an unvalidated two-order-of-magnitude extrapolation of the SFMS offset and on an admitted underestimate of the observed high-z SFRs; the early-Universe claim is therefore less secure than the local measurement.

major comments (3)
  1. [Section 2.2, Figure 1] The analogue selection is not validated for the mass range used: the P23 offset is measured at log M*=8.8 and assumed mass-independent below log M*=9.5, and Figure 1 shows that the resulting extrapolated line lies below nearly all observed z~5.5 dwarfs from Curti et al. (2024). Since the authors themselves state that the extrapolation 'may underestimate the SFRs of dwarfs at high redshift', the selected analogues are not unambiguously representative of z~5.5 dwarfs: if the true z~5.5 main sequence lies above the yellow line, some selected analogues would be normal rather than extreme at z~5.5, and if the offset is steeper at low masses the most extreme dwarfs would be missed. Please add a sensitivity test with a range of assumed offsets or a direct calibration against the Curti et al. data, and discuss how the interaction/ETG fractions would change if the selection line were shifted by ~1 dex.
  2. [Section 3.4, Figure 5] The argument that gas conditions alone underpredict the z~5.5 sSFR relies on a linear extrapolation of the Liu et al. (2019) sSFR ratio from log M* > 9.2 down to log M* ~ 7–8, over two decades in mass with no data in that range. The dotted line in Figure 5 is therefore an assumption, not a measurement, and the quantitative statement that observed SFRs are 'at least a factor of 14' higher than the gas-based prediction inherits this uncertainty. A sensitivity analysis using, for example, a flat or steeper mass dependence would clarify how robust the 'missing ingredient' conclusion is.
  3. [Section 3.3, Table 1] The causal interpretation is not directly tested. The elevated interacting fraction in the analogue population is consistent with interactions boosting SFRs, but it does not exclude the reverse possibility or a common driver, and the reported median SFR elevation of ~29 per cent for interacting galaxies is modest with no significance given. A comparison of SFRs between interacting and non-interacting analogues, and between ETG and LTG analogues, would strengthen the claim. At minimum, the abstract's phrase 'drives much of the stellar mass assembly' should be softened to reflect that the evidence is correlational.
minor comments (4)
  1. [Abstract, Table 1] The abstract reports enhancement factors of ~5.6 and ~9 for interacting and early-type fractions respectively, but Table 1 gives 9 for interacting and 5.6 for early-type; the ordering is reversed and should be corrected.
  2. [Section 3.1] For the distance to nodes the KS p-value is 0.06, close to the conventional 0.05 threshold; the text should not describe this as showing 'no difference' without reporting this borderline value and discussing its possible impact.
  3. [Section 2.3] The morphological classification is performed by a single expert; an inter-rater reliability check or a quantitative validation (e.g., using Gini/M20 or CAS) would increase confidence in the visual flags.
  4. [Data Availability] The paper does not provide a machine-readable list of the 116 analogue and 590 normal dwarf identifications; making the sample catalog available would aid reproducibility.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the interaction and ETG fractions are measured independently of the SFR-based selection, and the high-redshift comparison uses external Curti et al. data.

full rationale

This is an observational comparison rather than a derivation. The analogue selection in Section 2.2 uses the COSMOS2020 z~0.2 ridgeline plus the Popesso et al. (2023) offset transferred from log M*=8.8 to the 10^7-10^8 Msun range; that transfer is an extrapolation assumption, not a fitted parameter, and the paper explicitly flags the caveat in Section 3.4 ('our study necessarily uses extrapolations of low redshift data which may not accurately represent the conditions in the high redshift Universe'). The central measured quantities - interacting fraction 0.36 +/- 0.05 vs 0.04 +/- 0.02 and ETG fraction 0.28 +/- 0.03 vs 0.05 +/- 0.02 in Table 1 - come from visual morphological classification of HST/HSC images, which is independent of the SFR cut used to define the samples. The claim that the P23 extrapolation underestimates z~5.5 SFRs is checked against external JWST data from Curti et al. (2024), not against the authors' own fitted line. Self-citations to Martin et al. (2022) and Lazar et al. (2024a,b) support the interpretive step that interactions boost dwarf star formation, but the paper also reports internal evidence (elevated median SFRs among interacting and ETG galaxies), so the citation is not load-bearing in a way that closes a logical loop. The abstract's reversal of the two enhancement factors relative to Table 1 is an internal inconsistency, but it is a reporting error, not circularity. No step in the paper equates an output with an input by construction.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The central result rests on the adopted external SFMS offset, the Liu et al. gas-evolution extrapolation, and the visual classification. The paper introduces no new entities and performs no new fitting, but it does import two fitted quantities from the literature whose domain of validity ends above the dwarf mass range studied here. The most fragile unvalidated inputs are the mass-independent SFMS offset and the single-expert morphology labels.

free parameters (2)
  • P23 SFMS redshift offset at log M*=8.8 = ~1 dex between z~0.2 and z~5.5
    Adopted in Section 2.2 to shift the local ridgeline and define the analogue selection threshold; no uncertainty from this external fit is propagated into the sample selection.
  • Liu et al. (2019) linear extrapolation of log sSFR ratio versus stellar mass = extrapolated ratio ~4 at 1e7 Msun and ~8 at 1e8 Msun
    Used in Section 3.4 to argue gas-condition evolution alone underpredicts high-z dwarf sSFR; the linear fit is extrapolated below the fitted domain of M*>1e9.2 Msun.
assumptions (5)
  • domain assumption P23 SFMS offset is independent of stellar mass below log M*=9.5
    Used in Section 2.2 to transfer an offset measured at log M*=8.8 to the 1e7-1e8 Msun regime; if this mass-independence fails, the analogue definition changes.
  • domain assumption COSMOS2020 photometric redshifts, stellar masses, and SFRs are reliable for faint dwarfs at z<0.3
    Physical parameter inputs throughout Section 2.1; the paper relies on LePhare SED fitting and the COSMOS2020 photometric calibration.
  • domain assumption Local z~0.2 dwarfs with extreme SFRs are informative analogues of z~5.5 dwarfs
    Core premise of the analogue method stated in Sections 1 and 2.2; nearby systems cannot fully mimic high-redshift conditions such as gas inflow and cosmic web evolution.
  • domain assumption Single-expert visual classification of HST images is sufficient to identify interactions and early-type morphology
    Section 2.3 uses visual inspection by one classifier with no inter-rater reliability check or quantitative validation, yet the central comparison rests on these labels.
  • domain assumption DisPerSE persistence threshold of 2 and photometric-redshift slices reconstruct the cosmic web accurately enough for projected distance estimates
    Section 2.4 environment measurements depend on the persistence choice and on massive galaxies having reliable photometric redshifts within narrow slices.

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Cite this review

Pith. "Pith review of Nearby dwarf galaxies with extreme star formation rates: a window into dwarf-galaxy evolution in the early Universe." pith.science (2026). https://pith.science/paper/C7ZFLNDC

@misc{pith2026250603265,
  author       = {Pith},
  title        = {Pith review of: Nearby dwarf galaxies with extreme star formation rates: a window into dwarf-galaxy evolution in the early Universe},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/C7ZFLNDC}},
  note         = {Machine review of arXiv:2506.03265}
}
read the original abstract

We study a sample of nearby (z~0.2) low-luminosity dwarf (10^7 MSun < M* < 10^8 MSun) galaxies which have extreme (0.1 - 3 MSun/yr) star formation rates (SFRs) for this mass regime, making them plausible analogues of dwarfs at z~5.5. We compare the properties of these analogues to control samples of 'normal' dwarfs, which reside on the star formation main sequence (SFMS) at z~0.2 and are matched in their stellar mass and redshift distributions to the analogue population. The analogue and normal populations do not show differences, either in their half-light radii or the projected distances to nodes, filaments and massive galaxies. This suggests that the comparatively extreme SFRs in the analogues are not driven by them being anomalously compact or because they reside in specific environments which might provide a larger gas supply. However, the fractions of interacting galaxies and those that have early-type morphology are significantly elevated (by factors of ~5.6 and ~9 respectively) in the analogues compared to the normal population. Extrapolation of the redshift evolution of the star formation main sequence into our mass range of interest appears to underestimate the SFRs of observed dwarfs at z~5.5. Since current SFMS measurements remain dominated by low and intermediate redshift data (especially at low stellar masses), our study suggests that this underestimation may be driven by interactions (which are more frequent at earlier epochs) boosting the SFRs in the high-redshift dwarf population. Our results are consistent with a picture where higher gas availability, augmented by interactions, drives much of the stellar mass assembly of dwarf galaxies in the early Universe.

Figures

Figures reproduced from arXiv: 2506.03265 by the authors.

Figure 1
Figure 1. The SFMS for galaxies at 𝑧 < 0.3 in the COSMOS2020 catalogue. The median redshift of this population is 𝑧 ∼ 0.2. The heatmap shows all COSMOS2020 galaxies which reside at 𝑧 < 0.3, the thick dotted red line shows the ridgeline of the SFMS at 𝑧 ∼ 0.2 and the thick dotted yellow line shows the ridgeline of the SFMS at 𝑧 ∼ 0.2 plus the 𝑧 ∼ 5.5 offset calculated using P23 (see text in Section 2.2 for details). Other SFMS… view at source ↗
Figure 2
Figure 2. HST F814W images of a random sample of our dwarf galaxies. The first row shows examples of galaxies classified as ETGs, while the bottom row shows LTGs. The panels with a green border show examples of systems that are flagged as interacting. The ETG in column 3 shows an internal asymmetry, while the ETG in column 4 shows a tidal feature to the north east of the galaxy. The LTG in column 4 similarly shows a tidal fea… view at source ↗
Figure 4
Figure 4. Distributions of half-light radii of the analogue (red) and normal (black) populations. Median values and their uncertainties (calculated using bootstrapping) are shown using the dashed and dotted lines respectively. The inset shows the half-light radius plotted against the SFR. The heatmap shows all dwarfs which have stellar masses in the range 107 M⊙ < 𝑀★ < 108 M⊙ and redshifts in the range 𝑧 < 0.3. A random 10 pe… view at source ↗
Figures from the paper (2 more)
Figure 3
Figure 3. Figure 3: Distributions of projected distances from the nearest filaments (top), nodes (middle) and massive (𝑀★ > 1010 M⊙) galaxies (bottom) for the analogue (red) and normal (black) populations. NMG = nearest massive galaxy. Median values and their uncertainties are shown using…
Figure 5
Figure 5. Figure 5: The ratio of the sSFR between 𝑧 ∼ 5.5 and 𝑧 ∼ 0.2 as a function of stellar mass, from Liu et al. (2019). While this study does not extend past 𝑀★ ∼ 109.2 M⊙, the log of the sSFR ratio decreases almost linearly with the log of the stellar mass. Extrapolation of this beh…

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Works this paper leans on

99 extracted references · 6 canonical work pages

  1. [1]

    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.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    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.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  3. [3]

    Aihara H., et al., 2018a, @doi [ ] 10.1093/pasj/psx066 , http://ads.nao.ac.jp/abs/2018PASJ...70S...4A 70, S4

    doi:10.1093/pasj/psx066

  4. [4]

    Aihara H., et al., 2018b, @doi [ ] 10.1093/pasj/psx081 , http://ads.nao.ac.jp/abs/2018PASJ...70S...8A 70, S8

    doi:10.1093/pasj/psx081

  5. [5]

    Aihara H., et al., 2019, @doi [ ] 10.1093/pasj/psz103 , https://ui.adsabs.harvard.edu/abs/2019PASJ...71..114A 71, 114

    doi:10.1093/pasj/psz103 2019

  6. [6]

    Alam S., et al., 2015, @doi [ ] 10.1088/0067-0049/219/1/12 , https://ui.adsabs.harvard.edu/abs/2015ApJS..219...12A 219, 12

    doi:10.1088/0067-0049/219/1/12 2015

  7. [7]

    Arnouts S., et al., 2002, @doi [ ] 10.1046/j.1365-8711.2002.04988.x , https://ui.adsabs.harvard.edu/abs/2002MNRAS.329..355A 329, 355

    arXiv 2002

  8. [8]

    Ashby M. L. N., et al., 2013, @doi [ ] 10.1088/0004-637X/769/1/80 , https://ui.adsabs.harvard.edu/abs/2013ApJ...769...80A 769, 80

    doi:10.1088/0004-637x/769/1/80 2013

Show all 99 references
  1. [9]

    Ashby M. L. N., et al., 2015, @doi [ ] 10.1088/0067-0049/218/2/33 , https://ui.adsabs.harvard.edu/abs/2015ApJS..218...33A 218, 33

    2015 doi

  2. [10]

    Ashby M. L. N., et al., 2018, @doi [ ] 10.3847/1538-4365/aad4fb , https://ui.adsabs.harvard.edu/abs/2018ApJS..237...39A 237, 39

    2018 doi

  3. [11]

    S., Wechsler R

    Behroozi P. S., Wechsler R. H., Conroy C., 2013, @doi [ ] 10.1088/0004-637X/770/1/57 , https://ui.adsabs.harvard.edu/abs/2013ApJ...770...57B 770, 57

    2013 doi

  4. [12]

    J., Dopita M

    Bian F., Kewley L. J., Dopita M. A., 2018, @doi [ ] 10.3847/1538-4357/aabd74 , https://ui.adsabs.harvard.edu/abs/2018ApJ...859..175B 859, 175

    2018 doi

  5. [13]

    A., Das S., Smith D

    Bichang'a B., Kaviraj S., Lazar I., Jackson R. A., Das S., Smith D. J. B., Watkins A. E., Martin G., 2024, @doi [ ] 10.1093/mnras/stae1441 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532..613B 532, 613

    2024 doi

  6. [14]

    arXiv:2401.16934

    Boyett K., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2401.16934 , https://ui.adsabs.harvard.edu/abs/2024arXiv240116934B p. arXiv:2401.16934

    2024 doi arXiv

  7. [15]

    Bruzual G., Charlot S., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06897.x , https://ui.adsabs.harvard.edu/#abs/2003MNRAS.344.1000B 344, 1000

    2003

  8. [16]

    J., et al., 2024, @doi [ ] 10.1051/0004-6361/202347094 , https://ui.adsabs.harvard.edu/abs/2024A&A...690A.288B 690, A288

    Bunker A. J., et al., 2024, @doi [ ] 10.1051/0004-6361/202347094 , https://ui.adsabs.harvard.edu/abs/2024A&A...690A.288B 690, A288

    2024 doi

  9. [17]

    C., Kinney A

    Calzetti D., Armus L., Bohlin R. C., Kinney A. L., Koornneef J., Storchi-Bergmann T., 2000, @doi [ ] 10.1086/308692 , https://ui.adsabs.harvard.edu/abs/2000ApJ...533..682C 533, 682

    2000 doi

  10. [18]

    Cameron E., 2011, @doi [ ] 10.1071/AS10046 , https://ui.adsabs.harvard.edu/abs/2011PASA...28..128C 28, 128

    2011 doi

  11. [20]

    E., Sanders R

    Clarke L., Shapley A. E., Sanders R. L., Topping M. W., Brammer G. B., Bento T., Reddy N. A., Kehoe E., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.05178 , https://ui.adsabs.harvard.edu/abs/2024arXiv240605178C p. arXiv:2406.05178

    2024 doi arXiv

  12. [21]

    J., Bluck A

    Conselice C. J., Bluck A. F. L., Mortlock A., Palamara D., Benson A. J., 2014, @doi [ ] 10.1093/mnras/stu1385 , http://adsabs.harvard.edu/abs/2014MNRAS.444.1125C 444, 1125

    2014 doi

  13. [22]

    Curti M., et al., 2024, @doi [ ] 10.1051/0004-6361/202346698 , https://ui.adsabs.harvard.edu/abs/2024A&A...684A..75C 684, A75

    2024 doi

  14. [23]

    Dalmasso N., et al., 2024, @doi [ ] 10.1093/mnras/stae2064 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.533.4472D 533, 4472

    2024 doi

  15. [24]

    Dey A., et al., 2019, @doi [ ] 10.3847/1538-3881/ab089d , https://ui.adsabs.harvard.edu/abs/2019AJ....157..168D 157, 168

    2019 doi

  16. [25]

    arXiv:2411.04944

    Duan Q., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2411.04944 , https://ui.adsabs.harvard.edu/abs/2024arXiv241104944D p. arXiv:2411.04944

    2024 doi

  17. [26]

    Duc P.-A., et al., 2015, @doi [ ] 10.1093/mnras/stu2019 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.446..120D 446, 120

    2015 doi

  18. [27]

    Duncan K., et al., 2019, @doi [ ] 10.3847/1538-4357/ab148a , https://ui.adsabs.harvard.edu/abs/2019ApJ...876..110D 876, 110

    2019 doi

  19. [28]

    A., Sebastian B., Vaddi S., 2024, @doi [ ] 10.1093/mnras/stae1490 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.5140D 531, 5140

    Dutta S., Bera A., Bait O., Narayan C. A., Sebastian B., Vaddi S., 2024, @doi [ ] 10.1093/mnras/stae1490 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.5140D 531, 5140

    2024 doi

  20. [29]

    J., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2306.02465 , https://ui.adsabs.harvard.edu/abs/2023arXiv230602465E p

    Eisenstein D. J., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2306.02465 , https://ui.adsabs.harvard.edu/abs/2023arXiv230602465E p. arXiv:2306.02465

    2023 doi arXiv

  21. [30]

    L., Massa D., 1986, @doi [ ] 10.1086/164415 , https://ui.adsabs.harvard.edu/abs/1986ApJ...307..286F 307, 286

    Fitzpatrick E. L., Massa D., 1986, @doi [ ] 10.1086/164415 , https://ui.adsabs.harvard.edu/abs/1986ApJ...307..286F 307, 286

    1986 doi

  22. [31]

    u ckler M., Mamon G. A., Schnorr-M \

    Flores-Freitas R., Trevisan M., M \"u ckler M., Mamon G. A., Schnorr-M \"u ller A., Bootz V., 2024, @doi [ ] 10.1093/mnras/stae367 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.528.5804F 528, 5804

    2024 doi

  23. [32]

    P., et al., 2023, @doi [ ] 10.1088/1538-3873/acd1b5 , https://ui.adsabs.harvard.edu/abs/2023PASP..135f8001G 135, 068001

    Gardner J. P., et al., 2023, @doi [ ] 10.1088/1538-3873/acd1b5 , https://ui.adsabs.harvard.edu/abs/2023PASP..135f8001G 135, 068001

    2023 doi

  24. [33]

    Geha M., et al., 2017, @doi [ ] 10.3847/1538-4357/aa8626 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847....4G 847, 4

    2017 doi

  25. [34]

    Harshan A., et al., 2024, @doi [ ] 10.1093/mnras/stae1574 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.1112H 532, 1112

    2024 doi

  26. [35]

    A., et al., 2012, @doi [ ] 10.1088/0004-6256/144/5/134 , https://ui.adsabs.harvard.edu/abs/2012AJ....144..134H 144, 134

    Hunter D. A., et al., 2012, @doi [ ] 10.1088/0004-6256/144/5/134 , https://ui.adsabs.harvard.edu/abs/2012AJ....144..134H 144, 134

    2012 doi

  27. [36]

    Ilbert O., et al., 2006, @doi [ ] 10.1051/0004-6361:20065138 , https://ui.adsabs.harvard.edu/abs/2006A&A...457..841I 457, 841

    2006 doi

  28. [37]

    Ilbert O., et al., 2009, @doi [ ] 10.1088/0004-637X/690/2/1236 , https://ui.adsabs.harvard.edu/abs/2009ApJ...690.1236I 690, 1236

    2009 doi

  29. [38]

    Ivezi \'c Z ., et al., 2019, @doi [ ] 10.3847/1538-4357/ab042c , https://ui.adsabs.harvard.edu/abs/2019ApJ...873..111I 873, 111

    2019 doi

  30. [39]

    I., Guseva N

    Izotov Y. I., Guseva N. G., Fricke K. J., Henkel C., Schaerer D., Thuan T. X., 2021, @doi [ ] 10.1051/0004-6361/202039772 , https://ui.adsabs.harvard.edu/abs/2021A&A...646A.138I 646, A138

    2021 doi

  31. [40]

    A., et al., 2021a, @doi [ ] 10.1093/mnras/stab093 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.1785J 502, 1785

    Jackson R. A., et al., 2021a, @doi [ ] 10.1093/mnras/stab093 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.1785J 502, 1785

    doi

  32. [41]

    A., et al., 2021b, @doi [ ] 10.1093/mnras/stab077 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.4262J 502, 4262

    Jackson R. A., et al., 2021b, @doi [ ] 10.1093/mnras/stab077 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.4262J 502, 4262

    doi

  33. [42]

    Kaviraj S., 2014, @doi [ ] 10.1093/mnras/stu338 , http://adsabs.harvard.edu/abs/2014MNRAS.440.2944K 440, 2944

    2014 doi

  34. [43]

    Kaviraj S., et al., 2017, @doi [ ] 10.1093/mnras/stx126 , http://adsabs.harvard.edu/abs/2017MNRAS.467.4739K 467, 4739

    2017 doi

  35. [44]

    E., Laigle C., Martin G., Jackson R

    Kaviraj S., Lazar I., Watkins A. E., Laigle C., Martin G., Jackson R. A., 2025, @doi [ ] 10.1093/mnras/staf233 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.538..153K 538, 153

    2025 doi

  36. [45]

    M., et al., 2007, @doi [ ] 10.1086/520086 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172..196K 172, 196

    Koekemoer A. M., et al., 2007, @doi [ ] 10.1086/520086 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172..196K 172, 196

    2007 doi

  37. [46]

    C., 2022, @doi [ ] 10.1093/mnras/stac2252 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.2112K 516, 2112

    Koudmani S., Sijacki D., Smith M. C., 2022, @doi [ ] 10.1093/mnras/stac2252 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.2112K 516, 2112

    2022 doi

  38. [47]

    A., 2023, @doi [ ] 10.1093/mnras/stad224 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.2109L 520, 2109

    Lazar I., Kaviraj S., Martin G., Laigle C., Watkins A., Jackson R. A., 2023, @doi [ ] 10.1093/mnras/stad224 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.2109L 520, 2109

    2023 doi

  39. [48]

    E., Martin G., Bichang'a B., Jackson R

    Lazar I., Kaviraj S., Watkins A. E., Martin G., Bichang'a B., Jackson R. A., 2024a, @doi [ ] 10.1093/mnras/stae510 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.529..499L 529, 499

    doi

  40. [49]

    E., Martin G., Bichang'a B., Jackson R

    Lazar I., Kaviraj S., Watkins A. E., Martin G., Bichang'a B., Jackson R. A., 2024b, @doi [ ] 10.1093/mnras/stae1956 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.533.3771L 533, 3771

    doi

  41. [50]

    Le Reste A., et al., 2024, @doi [ ] 10.1093/mnras/stad3910 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.528..757L 528, 757

    2024 doi

  42. [51]

    Leauthaud A., et al., 2007, @doi [ ] 10.1086/516598 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172..219L 172, 219

    2007 doi

  43. [52]

    Lin L., et al., 2020, @doi [ ] 10.3847/1538-4357/aba755 , https://ui.adsabs.harvard.edu/abs/2020ApJ...899...93L 899, 93

    2020 doi

  44. [53]

    Liu D., et al., 2019, @doi [ ] 10.3847/1538-4357/ab578d , https://ui.adsabs.harvard.edu/abs/2019ApJ...887..235L 887, 235

    2019 doi

  45. [54]

    K., Houghton R

    Lofthouse E. K., Houghton R. C. W., Kaviraj S., 2017, @doi [ ] 10.1093/mnras/stx1627 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.471.2311L 471, 2311

    2017 doi

  46. [55]

    C., et al., 2013, @doi [ ] 10.1086/671138 , https://ui.adsabs.harvard.edu/abs/2013PASP..125..600M 125, 600

    Madden S. C., et al., 2013, @doi [ ] 10.1086/671138 , https://ui.adsabs.harvard.edu/abs/2013PASP..125..600M 125, 600

    2013 doi

  47. [56]

    P., et al., 2025, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2025arXiv250418515M p

    Madhani J. P., et al., 2025, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2025arXiv250418515M p. arXiv:2504.18515

    2025

  48. [57]

    M., Canalizo G., Sales L

    Manzano-King C. M., Canalizo G., Sales L. V., 2019, @doi [ ] 10.3847/1538-4357/ab4197 , https://ui.adsabs.harvard.edu/abs/2019ApJ...884...54M 884, 54

    2019 doi

  49. [58]

    H., Weiner B., Tollerud E

    Mao Y.-Y., Geha M., Wechsler R. H., Weiner B., Tollerud E. J., Nadler E. O., Kallivayalil N., 2021, @doi [ ] 10.3847/1538-4357/abce58 , https://ui.adsabs.harvard.edu/abs/2021ApJ...907...85M 907, 85

    2021 doi

  50. [59]

    Martin G., Kaviraj S., Devriendt J. E. G., Dubois Y., Pichon C., 2018, @doi [ ] 10.1093/mnras/sty1936 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.2266M 480, 2266

    2018 doi

  51. [60]

    Martin G., et al., 2019, @doi [ ] 10.1093/mnras/stz356 , http://adsabs.harvard.edu/abs/2019MNRAS.485..796M 485, 796

    2019 doi

  52. [61]

    Martin G., et al., 2021, @doi [ ] 10.1093/mnras/staa3443 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.500.4937M 500, 4937

    2021 doi

  53. [62]

    Martin G., et al., 2022, @doi [ ] 10.1093/mnras/stac1003 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.513.1459M 513, 1459

    2022 doi

  54. [63]

    Massey R., Stoughton C., Leauthaud A., Rhodes J., Koekemoer A., Ellis R., Shaghoulian E., 2010, @doi [ ] 10.1111/j.1365-2966.2009.15638.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.401..371M 401, 371

    2010

  55. [64]

    J., et al., 2012, @doi [ ] 10.1051/0004-6361/201219507 , https://ui.adsabs.harvard.edu/abs/2012A&A...544A.156M 544, A156

    McCracken H. J., et al., 2012, @doi [ ] 10.1051/0004-6361/201219507 , https://ui.adsabs.harvard.edu/abs/2012A&A...544A.156M 544, A156

    2012 doi

  56. [65]

    Nakajima K., et al., 2022, @doi [ ] 10.3847/1538-4365/ac7710 , https://ui.adsabs.harvard.edu/abs/2022ApJS..262....3N 262, 3

    2022 doi

  57. [66]

    Nakajima K., Ouchi M., Isobe Y., Harikane Y., Zhang Y., Ono Y., Umeda H., Oguri M., 2023, @doi [ ] 10.3847/1538-4365/acd556 , https://ui.adsabs.harvard.edu/abs/2023ApJS..269...33N 269, 33

    2023 doi

  58. [67]

    Onodera M., et al., 2012, @doi [ ] 10.1088/0004-637X/755/1/26 , https://ui.adsabs.harvard.edu/abs/2012ApJ...755...26O 755, 26

    2012 doi

  59. [68]

    Polletta M., et al., 2007, @doi [ ] 10.1086/518113 , https://ui.adsabs.harvard.edu/abs/2007ApJ...663...81P 663, 81

    2007 doi

  60. [69]

    Popesso P., et al., 2023, @doi [ ] 10.1093/mnras/stac3214 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.1526P 519, 1526

    2023 doi

  61. [70]

    Poulain M., et al., 2021, @doi [ ] 10.1093/mnras/stab2092 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.506.5494P 506, 5494

    2021 doi

  62. [71]

    L., Lequeux J., Maurice E., Prevot L., Rocca-Volmerange B., 1984, , https://ui.adsabs.harvard.edu/abs/1984A&A...132..389P 132, 389

    Prevot M. L., Lequeux J., Maurice E., Prevot L., Rocca-Volmerange B., 1984, , https://ui.adsabs.harvard.edu/abs/1984A&A...132..389P 132, 389

    1984

  63. [72]

    N., Malhotra S., Rhoads J., Ghosh T., 2022, @doi [ ] 10.3847/2041-8213/ac7522 , https://ui.adsabs.harvard.edu/abs/2022ApJ...933L..11P 933, L11

    Purkayastha S., Kanekar N., Chengalur J. N., Malhotra S., Rhoads J., Ghosh T., 2022, @doi [ ] 10.3847/2041-8213/ac7522 , https://ui.adsabs.harvard.edu/abs/2022ApJ...933L..11P 933, L11

    2022 doi

  64. [73]

    Revaz Y., Jablonka P., 2018, @doi [ ] 10.1051/0004-6361/201832669 , https://ui.adsabs.harvard.edu/abs/2018A&A...616A..96R 616, A96

    2018 doi

  65. [74]

    Romano M., et al., 2021, @doi [ ] 10.1051/0004-6361/202141306 , https://ui.adsabs.harvard.edu/abs/2021A&A...653A.111R 653, A111

    2021 doi

  66. [75]

    Romano M., et al., 2023, @doi [ ] 10.1051/0004-6361/202346143 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A..44R 677, A44

    2023 doi

  67. [76]

    Romano M., et al., 2024, @doi [ ] 10.1051/0004-6361/202349111 , https://ui.adsabs.harvard.edu/abs/2024A&A...683L...9R 683, L9

    2024 doi

  68. [77]

    Salim S., et al., 2016, @doi [ ] 10.3847/0067-0049/227/1/2 , https://ui.adsabs.harvard.edu/abs/2016ApJS..227....2S 227, 2

    2016 doi

  69. [78]

    Salvato M., et al., 2009, @doi [ ] 10.1088/0004-637X/690/2/1250 , https://ui.adsabs.harvard.edu/abs/2009ApJ...690.1250S 690, 1250

    2009 doi

  70. [79]

    Salvato M., et al., 2011, @doi [ ] 10.1088/0004-637X/742/2/61 , https://ui.adsabs.harvard.edu/abs/2011ApJ...742...61S 742, 61

    2011 doi

  71. [80]

    Sawicki M., et al., 2019, @doi [ ] 10.1093/mnras/stz2522 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.5202S 489, 5202

    2019 doi

  72. [81]

    E., van de Weygaert R., 2000, @doi [ ] 10.48550/arXiv.astro-ph/0011007 , https://ui.adsabs.harvard.edu/abs/2000A&A...363L..29S 363, L29

    Schaap W. E., van de Weygaert R., 2000, @doi [ ] 10.48550/arXiv.astro-ph/0011007 , https://ui.adsabs.harvard.edu/abs/2000A&A...363L..29S 363, L29

    2000 doi arXiv

  73. [82]

    Shivaei I., et al., 2022, @doi [ ] 10.3847/1538-4357/ac54a9 , https://ui.adsabs.harvard.edu/abs/2022ApJ...928...68S 928, 68

    2022 doi

  74. [83]

    Sousbie T., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18394.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.414..350S 414, 350

    2011

  75. [84]

    L., et al., 2014, @doi [ ] 10.1088/2041-8205/791/2/L25 , https://ui.adsabs.harvard.edu/abs/2014ApJ...791L..25S 791, L25

    Steinhardt C. L., et al., 2014, @doi [ ] 10.1088/2041-8205/791/2/L25 , https://ui.adsabs.harvard.edu/abs/2014ApJ...791L..25S 791, L25

    2014 doi

  76. [85]

    Taniguchi Y., et al., 2007, @doi [ ] 10.1086/516596 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172....9T 172, 9

    2007 doi

  77. [86]

    Taniguchi Y., et al., 2015, @doi [ ] 10.1093/pasj/psv106 , https://ui.adsabs.harvard.edu/abs/2015PASJ...67..104T 67, 104

    2015 doi

  78. [87]

    Tanoglidis D., et al., 2021, @doi [ ] 10.3847/1538-4365/abca89 , https://ui.adsabs.harvard.edu/abs/2021ApJS..252...18T 252, 18

    2021 doi

  79. [88]

    arXiv:2310.13543

    Thuruthipilly H., Junais Pollo A., Sureshkumar U., Grespan M., Sawant P., Malek K., Zadrozny A., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2310.13543 , https://ui.adsabs.harvard.edu/abs/2023arXiv231013543T p. arXiv:2310.13543

    2023 doi arXiv

  80. [89]

    Tolstoy E., Hill V., Tosi M., 2009, @doi [ ] 10.1146/annurev-astro-082708-101650 , https://ui.adsabs.harvard.edu/abs/2009ARA&A..47..371T 47, 371

    2009 doi

  81. [90]

    Trujillo I., et al., 2021, @doi [ ] 10.1051/0004-6361/202141603 , https://ui.adsabs.harvard.edu/abs/2021A&A...654A..40T 654, A40

    2021 doi

  82. [91]

    Uzeirbegovic E., et al., 2024, @doi [ ] 10.1093/mnras/stae2632 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.535.3775U 535, 3775

    2024 doi

  83. [92]

    Venhola A., et al., 2018, @doi [ ] 10.1051/0004-6361/201833933 , https://ui.adsabs.harvard.edu/abs/2018A&A...620A.165V 620, A165

    2018 doi

  84. [93]

    E., Salo H., Kaviraj S., Collins C

    Watkins A. E., Salo H., Kaviraj S., Collins C. A., Knapen J. H., Venhola A., Rom \'a n J., 2023, @doi [ ] 10.1093/mnras/stad654 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.521.2012W 521, 2012

    2023 doi

  85. [94]

    R., et al., 2022, @doi [ ] 10.3847/1538-4365/ac3078 , https://ui.adsabs.harvard.edu/abs/2022ApJS..258...11W 258, 11

    Weaver J. R., et al., 2022, @doi [ ] 10.3847/1538-4365/ac3078 , https://ui.adsabs.harvard.edu/abs/2022ApJS..258...11W 258, 11

    2022 doi

  86. [95]

    R., et al., 2023, @doi [ ] 10.1051/0004-6361/202245581 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A.184W 677, A184

    Weaver J. R., et al., 2023, @doi [ ] 10.1051/0004-6361/202245581 , https://ui.adsabs.harvard.edu/abs/2023A&A...677A.184W 677, A184

    2023 doi

  87. [96]

    E., van Dokkum P

    Whitaker K. E., van Dokkum P. G., Brammer G., Franx M., 2012, @doi [ ] 10.1088/2041-8205/754/2/L29 , https://ui.adsabs.harvard.edu/#abs/2012ApJ...754L..29W 754, L29

    2012 doi

  88. [97]

    E., et al., 2017, @doi [ ] 10.3847/1538-4357/aa6258 , https://ui.adsabs.harvard.edu/abs/2017ApJ...838...19W 838, 19

    Whitaker K. E., et al., 2017, @doi [ ] 10.3847/1538-4357/aa6258 , https://ui.adsabs.harvard.edu/abs/2017ApJ...838...19W 838, 19

    2017 doi

  89. [98]

    H., et al., 2017, @doi [ ] 10.1093/mnras/stx1149 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470..283W 470, 283

    Wright A. H., et al., 2017, @doi [ ] 10.1093/mnras/stx1149 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470..283W 470, 283

    2017 doi

  90. [99]

    E., Wang J., 2017, @doi [ ] 10.3847/1538-4357/aa8809 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847...38Y 847, 38

    Yang H., Malhotra S., Rhoads J. E., Wang J., 2017, @doi [ ] 10.3847/1538-4357/aa8809 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847...38Y 847, 38

    2017 doi

  91. [100]

    A., et al., 2007, @doi [ ] 10.1086/516593 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172..468Z 172, 468

    Zamojski M. A., et al., 2007, @doi [ ] 10.1086/516593 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172..468Z 172, 468

    2007 doi

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.