Dust removal timescale in galaxies across cosmic time

Aleksandra Le\'sniewska; Christa Gall; Jens Hjorth

REVIEW 5 major objections 5 minor 16 references

Dust removal timescale in galaxies across cosmic time

T0 review · 5 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read Dust vanishes faster in high-redshift galaxies, with removal timescales falling from 1.8 Gyr to about 0.4 Gyr by z>3.

desk verdict Plausible but fragile: the high-z dust removal timescale claim hinges on a single bin and is within the systematic age offset the authors themselves quote. read the letter →

arxiv 2505.21492 v2 pith:CLZNWLUR submitted 2025-05-27 astro-ph.GA

Aleksandra Leśniewska , Jens Hjorth , Christa Gall This is my paper

classification astro-ph.GA

keywords dustremovaltimescaledust-to-stellarmassratiohigh-redshiftgalaxiesHerschelSEDfittinggalaxyevolutionAGNfeedbackinterstellarmedium

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 uses more than 120,000 Herschel-detected galaxies spanning redshifts 0 to about 5 to measure how long dust survives in galactic interstellar media. Fitting an exponential decline of the dust-to-stellar mass ratio with stellar age in nine low-redshift and three high-redshift bins, it finds the e-folding dust removal timescale shrinks from 1.77 Gyr at z~0.05 to 0.43 Gyr at z~3.3. The conclusion is that dust removal is not a fixed process but becomes more efficient at earlier cosmic epochs, likely because AGN-driven outflows, supernova shocks, and rapid star formation remove dust faster. If correct, galaxy evolution models must treat dust destruction as redshift-dependent rather than assuming a constant removal timescale.

What carries the argument

The analytical motor is the single-exponential relation $M_{\rm dust}/M_{\rm stellar} = A e^{-\mathrm{age}/\tau}$, applied separately to redshift-binned samples. Here $\tau$ is the e-folding dust removal timescale and $A$ is the maximum dust-to-stellar ratio; fitting this curve to thousands of galaxies per bin converts a scatter plot of dustiness versus stellar age into two redshift-dependent numbers. The data are SED-derived dust masses, stellar masses, and mass-weighted ages from MAGPHYS for the GAMA galaxies and CIGALE for the DD20 dusty star-forming galaxies, with a 0.3 dex downward correction applied to the high-redshift dust masses to align the two codes.

What would settle it

Fit the same exponential relation to dust-to-stellar ratios of a redshift-complete, mass-selected sample at $z = 0$–$5$ using a single SED-fitting code; if $\tau$ stops declining with redshift, the trend is a selection or calibration artifact. A cheaper check follows from the paper's own sensitivity note: if independent stellar-age indicators (for example rest-frame near-infrared colours or spectral indices) placed the high-redshift ages 0.2 dex lower, the inferred removal timescale would drop below 300 Myr, so any systematic age bias of that size would falsify the quoted values.

Watch

Extended reading notes

Core claim

The central claim is that the timescale on which galaxies shed their dust, defined by the relation $M_{\rm dust}/M_{\rm stellar} = A e^{-\mathrm{age}/\tau}$, decreases from about 1.8 Gyr at low redshift to less than about 0.5 Gyr at $z > 3$, with the highest-redshift bin fitted at $\tau = 0.43 \pm 0.33$ Gyr. The paper also finds that the normalisation constant $A$, which sets the maximum dustiness a galaxy can reach, rises with redshift from $\log_{10} A = -2.24$ at $z \sim 0.05$ to $-1.93$ at $z > 3$, indicating that younger galaxies are dustier. The authors interpret the short high-redshift timescale as the signature of AGN activity, supernova shocks, and astration acting on timescales of a few hundred million years.

Load-bearing premise

The whole trend rests on the assumption that the fall-off of the dust-to-stellar mass ratio with stellar age in each redshift bin is caused by dust removal rather than by stellar mass growth or selection, and that the mass-weighted ages from the two SED-fitting codes are accurate and directly comparable across redshifts.

Editorial extensions

If this is right

Galaxy evolution models that assume a single, gigayear-scale dust removal time will have to make the removal rate redshift-dependent, because the fitted e-folding time drops by roughly a factor of four from $z \sim 0.05$ to $z > 3$.
High-redshift star-forming galaxies should typically show low dust-to-stellar ratios for their age, since dust is cleared within a few hundred million years by AGN outflows, supernova shocks, and rapid star formation.
The rising normalisation constant implies the maximum dust-to-stellar ratio was higher in the early Universe, consistent with rapid dust production occurring before efficient removal begins.
Independent observations of quiescent galaxies at $z = 3$–$4$ with dust removal times of 0.2–0.7 Gyr reinforce the interpretation that AGN feedback sets the dust-removal pace at high redshift.

Reading between the lines

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

Editorial extension: if the exponential fit is interpreted causally, the dust removal timescale becomes a cosmic chronometer, so measuring the age at which a galaxy's dustiness drops by one e-fold could date the onset of quenching at high redshift.
Editorial extension: applying the same exponential model to the gas-to-stellar mass ratio in these samples would test whether the trend is specific to dust destruction or instead reflects general ISM removal.
Editorial extension: a dedicated survey of several hundred $z > 3$ dusty galaxies processed with a single SED-fitting code would test whether the sub-500 Myr timescale is robust or an artifact of combining two catalogues with different dust models.

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

Dear Colleague,

The genuinely new thing here is the first attempt to measure the dust removal timescale out to z~5, using the Michalowski et al. (2019) exponential decay relation on a large Herschel-selected sample. That is worth something, and the low-redshift GAMA fits are clean and carefully described. But the headline claim—that tau drops below 500 Myr at z>3—is not yet supported. The whole high-z signal rests on one bin (z=2.57-5.234, N=124, tau = 0.43 ± 0.33 Gyr). Formally that is about 4 sigma from the 1.77 Gyr low-z value, but the systematic floor is far larger. The authors themselves note in Sec. 2.1 that a 0.2 dex shift in stellar age would give tau below 300 Myr. A 0.2 dex age difference between MAGPHYS and CIGALE is exactly what Pacifici et al. (2023) report, and the high-z ages are also pushed against the cosmic age ceiling at z~3.3. The observed break conveniently coincides with the switch from the GAMA/MAGPHYS sample to the DD20/CIGALE sample. So the claimed evolution could be largely a code-dependent age offset.

The paper does several things well. It is explicit about the SED-fitting caveats, applies a -0.3 dex correction to the DD20 dust masses and -0.1 dex to the SFRs to place them on the MAGPHYS scale, and tests five GAMA subsamples as robustness checks. The appendix honestly admits the exponential model fails for the youngest GAMA galaxies. The discussion of astration, SN shocks, and AGN feedback is sensible, even if it cannot distinguish the mechanisms.

The weaker spots are not hard to find. The low-z GAMA trend is not monotonic—tau dips at z~0.5 and then rises again at z~0.7-0.8. The intermediate DD20 bin (z=1.21-2.57, tau = 1.51 ± 0.87 Gyr) is consistent with no evolution. The normalisation A increases with redshift, which the authors themselves attribute partly to selection; if selection can bias A, it can also bias tau. And the DD20 catalog is not public, so the crucial high-z data cannot be checked.

Who should read this? Dust evolution and quenching modellers will want the table of tau values, but they should treat the z>2 points as upper limits or provisional until the age systematics are quantified. I would send this to peer review rather than desk reject, with the clear expectation that the authors propagate a 0.2 dex age systematic into the tau uncertainties, release the high-z fits, and soften the abstract. The physical idea is plausible; the present analysis does not nail it down.

Referee Report

5 major / 5 minor

Summary. The paper measures the dust removal timescale tau defined by the exponential decline of the dust-to-stellar mass ratio with stellar age (Eq. 1) for galaxies over 0 < z < 5.3. The analysis combines 120,061 GAMA galaxies (z < 0.9) with 300 dusty star-forming galaxies from Donevski et al. (2020) at 0.9 < z < 5.234, using published dust masses, stellar masses, and mass-weighted ages from MAGPHYS and CIGALE SED fitting. Fitting the relation in nine redshift bins yields tau decreasing from 1.77 +/- 0.04 Gyr at z < 0.1 to 0.43 +/- 0.33 Gyr at z > 2.57, with a normalization A that rises from 10^-2.24 to 10^-1.93. The authors interpret this as more efficient dust removal at high redshift, driven by AGN feedback, supernova shocks, and astration.

Significance. The low-redshift GAMA analysis is based on a very large sample and yields well-constrained tau values, with internal robustness checks in Appendix B. If the high-redshift trend were secure, the paper would provide the first broad-redshift measurement of dust removal timescales and directly connect to theoretical expectations of faster dust processing at early epochs. The analysis uses exclusively public catalog data, which is a strength. However, the high-redshift conclusion rests almost entirely on a single bin of 124 galaxies, and the paper itself identifies a 0.2 dex age systematic that is not propagated into the reported uncertainties. The central claim is therefore not yet established at the level claimed in the abstract.

major comments (5)

[Sec. 2.1 / Sec. 3, Table 1] The analysis applies -0.3 dex and -0.1 dex corrections to the DD20 dust masses and SFRs to bring them into line with the GAMA/MAGPHYS values, but applies no correction to the stellar ages. The paper itself states (Sec. 2.1) that a 0.2 dex decrease in stellar age would reduce the inferred tau to below 300 Myr, and it cites Pacifici et al. (2023) showing that mass-weighted ages vary by at least 0.2 dex among SED fitting codes. Because age is the independent variable in Eq. (1), this systematic uncertainty propagates directly into tau. For the highest-redshift bin, a plausible +/-0.2 dex age offset changes tau by a large fraction of the claimed evolutionary signal. The authors should refit the DD20 bins with ages shifted by +/-0.2 dex and add the resulting systematic uncertainty to the quoted tau values before the abstract claim can be considered supported.
[Sec. 3, Table 1, z=2.57-5.234 row] The highest-redshift bin gives tau = 0.43 +/- 0.33 Gyr from 124 galaxies, which is only 1.3 sigma away from zero. The two lower-redshift DD20 bins (1.07 +/- 0.93 Gyr from 20 galaxies and 1.51 +/- 0.87 Gyr from 153 galaxies) are statistically consistent with the GAMA values at z < 0.9. Thus the claimed monotonic decrease from z ~ 0.05 to z > 3 is driven almost entirely by this one bin. The paper should present a formal test of whether a constant tau across all redshifts is rejected (for example, a chi-square or Bayesian comparison), and should discuss the possibility that the single low bin reflects selection effects or systematic errors rather than a genuine evolutionary trend.
[Sec. 3 / Appendix A, Fig. A.1] In the z=2.57-5.234 bin, the inferred stellar ages lie close to the age of the Universe at the median redshift, as indicated by the vertical dashed lines in Fig. A.1. The exponential fit in this bin therefore has limited dynamic range, and the fitted slope may be controlled by the SED-fitting prior that prevents ages from exceeding the cosmic age, rather than by a measured decline in the dust-to-stellar ratio. The paper should quantify how many galaxies in this bin have ages within, say, 0.1 dex of the cosmic-age ceiling and should test the stability of tau when those objects are removed from the fit.
[Sec. 3, Eq. (1)] The exponential relation Mdust/Mstellar = A exp(-age/tau) is adopted from Michalowski et al. (2019) and applied to star-forming DSFGs without independent validation. In galaxies with ongoing star formation, the dust-to-stellar mass ratio can decline with stellar age because the stellar mass grows while dust production continues, so the fitted tau is not uniquely a dust removal timescale. The authors should justify the physical interpretation by checking whether the dust mass itself declines with age in the DD20 sample, or by explicitly including a dust production term when modeling the observed ratio.
[Sec. 2.2 / Fig. 1] The GAMA sample is Herschel-selected and includes galaxies across the full mass and morphology range, while the DD20 sample is restricted to massive (M > 10^10 solar masses) dusty star-forming galaxies. The paper demonstrates overlapping SFR-stellar mass distributions in Fig. 1, but the GAMA bins at z = 0.7-0.9 contain only 155 and 98 galaxies, and the DD20 bins are coarse (20, 153, and 124 galaxies). The apparent continuity of tau across z ~ 0.9 could therefore reflect the switch between samples and selection functions rather than a physical continuity. The authors should either match the selection criteria more closely in the GAMA subsamples (as attempted in Appendix B.4, although the uncertainties are large) or explicitly model a sample-calibration offset in the joint fit.

minor comments (5)

[Abstract] The abstract states 'less than 450 Myr at z>3', based on tau = 0.43 +/- 0.33 Gyr. Since the 1-sigma upper bound is about 0.76 Gyr and the 2-sigma upper bound exceeds 1 Gyr, the abstract should either quote the uncertainty or soften the claim to 'consistent with tau below about 0.8 Gyr'.
[Sec. 2] The paper states that the DD20 sample contains 300 galaxies, but Table 1 lists 20 + 153 + 124 = 297 galaxies across the three DD20 redshift bins. Please clarify whether three galaxies were excluded from the fits and why.
[Sec. 2.1] The sentence 'A decrease by 0.2 dex in stellar age would reduce the inferred dust removal timescale to below 300 Myr' appears without derivation. Please show the calculation or provide a reference that supports this quantitative statement.
[Fig. 2 / Fig. A.1] The caption of Fig. 2 refers to vertical dashed lines with colors matching the redshift bins, whereas Fig. A.1 describes 'vertical dashed black lines' in the last row. Please make the descriptions consistent.
[Sec. 2.2] The abbreviation 'MS' is used for the main sequence without expansion at first use. Please write 'main sequence (MS)' and then use 'MS' thereafter.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the fitted tau values are new measurements from independent catalogue data; the only self-citation is the adopted exponential form (Eq. 1), which is not load-bearing, and the acknowledged age-axis sensitivity is a stated limitation rather than a circular step.

full rationale

The derivation chain is straightforward: adopt the empirical relation Mdust/Mstellar = A exp(-age/tau) from Michalowski et al. (2019), fit tau and A independently in each redshift bin, and then examine tau as a function of redshift. No step reduces an output to an input by construction. Equation (1) does not encode any redshift dependence; tau is a free parameter fit separately in each bin, so the claimed decrease from ~1.77 Gyr at z~0.05 to ~0.43 Gyr at z~3.28 is not forced by the model. The paper explicitly calibrates the DD20 dust masses and SFRs to the GAMA system (-0.3 dex and -0.1 dex), but these are disclosed adjustments, not predictions. The use of Eq. (1) is a self-citation (Michalowski, Hjorth, Gall et al. 2019), but that prior work established the relation on a different low-redshift sample, and the present application to the GAMA and DD20 catalogues is an independent measurement of tau rather than a re-statement of the cited result. The paper itself warns that a 0.2 dex shift in stellar age would reduce the high-z tau to below 300 Myr; this is a candid statement of systematic sensitivity, not an example of fitting a parameter and renaming it a prediction. Potential problems with age comparability between MAGPHYS and CIGALE, or with the stellar-age ceiling near the age of the Universe, are correctness and robustness concerns, not circularity. The overall score reflects a minor non-load-bearing self-citation in the adopted functional form.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The paper introduces no new physical entities. Its central results are parameters fitted to data under an assumed empirical model, plus two ad hoc correction offsets. The correctness of the claimed trend depends on these assumptions.

free parameters (4)

Dust removal timescale tau = 0.43-1.77 Gyr per redshift bin
E-folding time in the exponential fit; the central measured quantity; fitted separately in each redshift bin.
Normalization A = log10 A from -2.24 to -1.93
Maximum dust-to-stellar ratio in the exponential model; fitted per bin; the paper interprets its increase with redshift as evidence of enhanced dust production, but it may be affected by selection.
DD20 dust mass offset = -0.3 dex
Ad hoc correction applied to DD20 Mdust to align CIGALE with MAGPHYS, based on literature comparisons (Paspaliaris et al. 2023; Gentile et al. 2024); directly shifts the high-redshift points and thus tau.
DD20 SFR offset = -0.1 dex
Ad hoc correction to DD20 SFRs; affects the star-forming main sequence classification but not the fits directly.

assumptions (5)

domain assumption The exponential relation Mdust/Mstellar = A exp(-age/tau) (Eq. 1) with constant A and tau per redshift bin accurately describes the dust-to-stellar ratio versus stellar age.
From Michalowski et al. 2019; not re-derived here; assumed to hold for star-forming galaxies at all redshifts.
domain assumption MAGPHYS-derived Mdust, Mstellar, and mass-weighted ages from Driver et al. 2016 are unbiased.
The GAMA catalog is taken at face value; no external validation is performed in this paper.
domain assumption CIGALE-derived parameters from DD20, after constant offsets, are comparable to MAGPHYS values.
The offsets are based on literature comparisons, but the paper does not verify the scaled DD20 values against an independent method.
domain assumption Herschel selection does not bias the fitted slope tau, only the normalization A.
The paper argues this in Sec. 2.2, but the same selection could flatten the age-dustiness relation at high redshift.
domain assumption Mass-weighted stellar age is a proxy for the time since dust formation or removal began.
The independent variable in Eq. 1 is age; this assumes older stellar populations have had more time for dust removal, ignoring dust production at late times.

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Cite this review

Pith. "Pith review of Dust removal timescale in galaxies across cosmic time." pith.science (2026). https://pith.science/paper/CLZNWLUR

@misc{pith2026250521492,
  author       = {Pith},
  title        = {Pith review of: Dust removal timescale in galaxies across cosmic time},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CLZNWLUR}},
  note         = {Machine review of arXiv:2505.21492}
}

abstract

Understanding the evolution of dust in galaxies is crucial because it affects the dynamics and cooling of gas, star formation, and chemical evolution. Recent work on dust removal in galaxies indicates timescales of gigayears, with old stellar populations and AGNs as the primary drivers of this process. However, most statistically significant studies are focused on low redshifts $z < 0.4$. Here, we determine the dust removal timescale in galaxies over a wide range of redshifts, up to $z \sim 5$. We use publicly available catalogue data of infrared-selected galaxies, observed by \textit{Herschel}. Using the inferred dust masses, stellar masses, and stellar ages, we calculate the dust removal timescale in a sample of more than 120,000 galaxies. We find that, with increasing redshift, the dust removal timescale decreases from 1.8 Gyr at redshift $z \sim 0.05$ to less than 500\,Myr at $z > 3$. Galaxies at higher redshifts undergo more efficient dust removal than galaxies at lower redshift, likely driven by AGN activity, supernova shocks, and astration. These findings indicate that dust removal evolves over cosmic time, reflecting the changing mechanisms regulating dust content of galaxies as the Universe evolves.

Figures

Figures reproduced from arXiv: 2505.21492 by the authors.

**Figure 2.** Dust-to-stellar mass ratio as a function of stellar age. Top: [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗

**Figure 3.** Top: Dust removal timescale as a function of redshift. [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗

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Works this paper leans on

16 extracted references · 7 canonical work pages

[1]

2025, arXiv e-prints, arXiv:2501.10508, doi: 10.48550/arXiv.2501.10508 Baker, W

Algera, H., Rowland, L., Stefanon, M., et al. 2025, arXiv e-prints, arXiv:2501.10508, doi: 10.48550/arXiv.2501.10508 Baker, W. M., D’Eugenio, F., Maiolino, R., et al. 2025, A&A, 697, A90, doi:10. 1051/0004-6361/202553766 Baldry, I. K., Liske, J., Brown, M. J. I., et al. 2018, MNRAS, 474, 3875, doi:10. 1093/mnras/stx3042 Barlow, M. J. 1978, MNRAS, 183, 367...

doi:10.48550/arxiv.2501.10508 2025
[3]

P., Wright, A

1111/j.1365-2966.2010.18188.x Driver, S. P., Wright, A. H., Andrews, S. K., et al. 2016, MNRAS, 455, 3911, doi: 10.1093/mnras/stv2505 Ellison, S. L., Patton, D. R., Mendel, J. T., & Scudder, J. M. 2011, MNRAS, 418, 2043, doi: 10.1111/j.1365-2966.2011.19624.x Ellison, S. L., Viswanathan, A., Patton, D. R., et al. 2019, MNRAS, 487, 2491, doi: 10.1093/mnras/...

arXiv 2010
[4]

F., Hernquist, L., Cox, T

1111/j.1365-2966.2009.15062.x Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2006, ApJS, 163, 1, doi:10.1086/ 499298 Hunt, L. K., De Looze, I., Boquien, M., et al. 2019, A&A, 621, A51, doi:

arXiv 2009
[5]

P., Fanciullo, L., Köhler, M., et al

1051/0004-6361/201834212 Jones, A. P., Fanciullo, L., Köhler, M., et al. 2013, A&A, 558, A62, doi:

work page 2013
[6]

P., Köhler, M., Ysard, N., Bocchio, M., & Verstraete, L

1051/0004-6361/201321686 Jones, A. P., Köhler, M., Ysard, N., Bocchio, M., & Verstraete, L. 2017, A&A, 602, A46, doi: 10.1051/0004-6361/201630225 Koekemoer, A. M., Faber, S. M., Ferguson, H. C., et al. 2011, ApJS, 197, 36, doi: 10.1088/0067-0049/197/2/36 Köhler, M., Jones, A., & Ysard, N. 2014, A&A, 565, L9, doi: 10.1051/ 0004-6361/201423985 Laki´cevi´c, ...

doi:10.1051/0004-6361/201630225 2017
[7]

P., Robotham, A

1088/0004-637X/799/1/50 Lange, R., Driver, S. P., Robotham, A. S. G., et al. 2015, MNRAS, 447, 2603, doi: 10.1093/mnras/stu2467 Langeroodi, D., Hjorth, J., Ferrara, A., & Gall, C. 2024, arXiv e-prints, arXiv:2410.14671, doi: 10.48550/arXiv.2410.14671 Law, D. R., Yan, R., Bershady, M. A., et al. 2015, AJ, 150, 19, doi: 10.1088/ 0004-6256/150/1/19 Lee, M. M...

arXiv doi:10.48550/arxiv.2410.14671 2015
[8]

2014, ARA&A, 52, 415, doi: 10.1146/ annurev-astro-081811-125615 Michałowski, M

1038/s41586-024-07227-0 Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415, doi: 10.1146/ annurev-astro-081811-125615 Michałowski, M. J., Watson, D., & Hjorth, J. 2010, ApJ, 712, 942, doi:

work page 2014
[9]

J., Hjorth, J., Gall, C., et al

1088/0004-637X/712/2/942 Michałowski, M. J., Hjorth, J., Gall, C., et al. 2019, A&A, 632, A43, doi:

work page 2019

Show all 16 references

[10]

J., Springel, V ., White, S

1088/0004-637X/803/2/77 Croton, D. J., Springel, V ., White, S. D. M., et al. 2006, MNRAS, 365, 11, doi: 10.1111/j.1365-2966.2005.09675.x da Cunha, E., Charlot, S., & Elbaz, D. 2008, MNRAS, 388, 1595, doi:10.1111/ j.1365-2966.2008.13535.x Donevski, D., Lapi, A., Małek, K., et ...

2006
[11]

J., Gall, C., Hjorth, J., et al

1051/0004-6361/201936055 Michałowski, M. J., Gall, C., Hjorth, J., et al. 2024, ApJ, 964, 129, doi:

2024
[12]

J., Parente, M., et al

3847/1538-4357/ad1b52 Nadolny, J., Michałowski, M. J., Parente, M., et al. 2024, A&A, 689, A210, doi: 10.1051/0004-6361/202449839 Nersesian, A., Xilouris, E. M., Bianchi, S., et al. 2019, A&A, 624, A80, doi:10. 1051/0004-6361/201935118 Novak, G. S., Ostriker, J. P., & Ciotti, ...

2024 doi
[13]

D., Xilouris, E

1093/mnras/stab674 Paspaliaris, E. D., Xilouris, E. M., Nersesian, A., et al. 2023, A&A, 669, A11, doi: 10.1051/0004-6361/202244796 Piotrowska, J. M., Bluck, A. F. L., Maiolino, R., & Peng, Y . 2022, MNRAS, 512, 1052, doi: 10.1093/mnras/stab3673 Reeves, A. M. M., & Hudson, M. ...

2023 doi
[14]

A., Inoue, A

1088/0004-637X/801/2/97 Sato, R. A., Inoue, A. K., Harikane, Y ., et al. 2024, MNRAS, 534, 3552, doi:10. 1093/mnras/stae2300 Schawinski, K., Urry, C. M., Simmons, B. D., et al. 2014, MNRAS, 440, 889, doi: 10.1093/mnras/stu327 Scoville, N., Aussel, H., Brusa, M., et al. 2007, A...

2024 doi arXiv
[15]

2021, MNRAS, 508, 4902, doi:10

1088/0004-637X/799/2/158 Veilleux, S., Meléndez, M., Stone, M., et al. 2021, MNRAS, 508, 4902, doi:10. 1093/mnras/stab2881 Whitaker, K. E., van Dokkum, P. G., Brammer, G., et al. 2013, ApJ, 770, L39, doi: 10.1088/2041-8205/770/2/L39 Whitaker, K. E., Williams, C. C., Mowla, L.,...

2021 doi
[16]

Dusty galaxies exhibit longer dust removal timescales for redshiftsz< 0.4, reaching almost 2.5 Gyr

resulted in 35,221 galaxies. Dusty galaxies exhibit longer dust removal timescales for redshiftsz< 0.4, reaching almost 2.5 Gyr. Similar findings on dust and gas removal in observed and simulated ETGs atz∼ 0.32 have been reported by Michałowski et al. (2019); Le´sniewska et al...

2019
[1963]

A parameter used to describe a galaxy’s morphology is the r-band Sérsic index (Sérsic 1963), which reflects the distribution of light within a galaxy

lower than or equal to 2.5 resulted in 28,027 galaxies. A parameter used to describe a galaxy’s morphology is the r-band Sérsic index (Sérsic 1963), which reflects the distribution of light within a galaxy. A commonly adopted conservative limit for the Sérsic index is n = 2.5 ...

1963

Pith tools

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

[1] [1]

2025, arXiv e-prints, arXiv:2501.10508, doi: 10.48550/arXiv.2501.10508 Baker, W

Algera, H., Rowland, L., Stefanon, M., et al. 2025, arXiv e-prints, arXiv:2501.10508, doi: 10.48550/arXiv.2501.10508 Baker, W. M., D’Eugenio, F., Maiolino, R., et al. 2025, A&A, 697, A90, doi:10. 1051/0004-6361/202553766 Baldry, I. K., Liske, J., Brown, M. J. I., et al. 2018, MNRAS, 474, 3875, doi:10. 1093/mnras/stx3042 Barlow, M. J. 1978, MNRAS, 183, 367...

doi:10.48550/arxiv.2501.10508 2025

[2] [3]

P., Wright, A

1111/j.1365-2966.2010.18188.x Driver, S. P., Wright, A. H., Andrews, S. K., et al. 2016, MNRAS, 455, 3911, doi: 10.1093/mnras/stv2505 Ellison, S. L., Patton, D. R., Mendel, J. T., & Scudder, J. M. 2011, MNRAS, 418, 2043, doi: 10.1111/j.1365-2966.2011.19624.x Ellison, S. L., Viswanathan, A., Patton, D. R., et al. 2019, MNRAS, 487, 2491, doi: 10.1093/mnras/...

arXiv 2010

[3] [4]

F., Hernquist, L., Cox, T

1111/j.1365-2966.2009.15062.x Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2006, ApJS, 163, 1, doi:10.1086/ 499298 Hunt, L. K., De Looze, I., Boquien, M., et al. 2019, A&A, 621, A51, doi:

arXiv 2009

[4] [5]

P., Fanciullo, L., Köhler, M., et al

1051/0004-6361/201834212 Jones, A. P., Fanciullo, L., Köhler, M., et al. 2013, A&A, 558, A62, doi:

work page 2013

[5] [6]

P., Köhler, M., Ysard, N., Bocchio, M., & Verstraete, L

1051/0004-6361/201321686 Jones, A. P., Köhler, M., Ysard, N., Bocchio, M., & Verstraete, L. 2017, A&A, 602, A46, doi: 10.1051/0004-6361/201630225 Koekemoer, A. M., Faber, S. M., Ferguson, H. C., et al. 2011, ApJS, 197, 36, doi: 10.1088/0067-0049/197/2/36 Köhler, M., Jones, A., & Ysard, N. 2014, A&A, 565, L9, doi: 10.1051/ 0004-6361/201423985 Laki´cevi´c, ...

doi:10.1051/0004-6361/201630225 2017

[6] [7]

P., Robotham, A

1088/0004-637X/799/1/50 Lange, R., Driver, S. P., Robotham, A. S. G., et al. 2015, MNRAS, 447, 2603, doi: 10.1093/mnras/stu2467 Langeroodi, D., Hjorth, J., Ferrara, A., & Gall, C. 2024, arXiv e-prints, arXiv:2410.14671, doi: 10.48550/arXiv.2410.14671 Law, D. R., Yan, R., Bershady, M. A., et al. 2015, AJ, 150, 19, doi: 10.1088/ 0004-6256/150/1/19 Lee, M. M...

arXiv doi:10.48550/arxiv.2410.14671 2015

[7] [8]

2014, ARA&A, 52, 415, doi: 10.1146/ annurev-astro-081811-125615 Michałowski, M

1038/s41586-024-07227-0 Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415, doi: 10.1146/ annurev-astro-081811-125615 Michałowski, M. J., Watson, D., & Hjorth, J. 2010, ApJ, 712, 942, doi:

work page 2014

[8] [9]

J., Hjorth, J., Gall, C., et al

1088/0004-637X/712/2/942 Michałowski, M. J., Hjorth, J., Gall, C., et al. 2019, A&A, 632, A43, doi:

work page 2019