Pith. sign in

REVIEW 3 major objections 4 minor 2 cited by

Low dust mass and high star-formation efficiency at $z>12$ from deep ALMA observations

T0 review · 3 major / 4 minor · reviewed 2026-08-09 · deepseek-v4-flash

Pith's one-line read Two of the most distant known galaxies are dust-poor yet form stars at starburst efficiency.

desk verdict First dust-mass limits at z>12 are credible and useful; the high star-formation-efficiency headline outruns the gas masses. read the letter →

arxiv 2501.19384 v1 pith:KSJJB6CC submitted 2025-01-31 astro-ph.GA

classification astro-ph.GA
keywords high-redshiftgalaxiesdustmassstarformationefficiencyALMAJWSTinterstellarmediumcosmicdawnstarburst
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

The paper studies the two most distant galaxies with ALMA dust-continuum non-detections: GHZ2 at $z=12.3$ and GS-z14-0 at $z=14.2$. Combining deep ALMA limits with JWST stellar masses and star-formation histories, it claims 3-$\sigma$ upper limits on dust mass of $\log M_{\rm dust}/M_\odot < 5.0$ and $< 5.3$, respectively, while the two galaxies convert their gas into stars at efficiencies near $10\,{\rm Gyr}^{-1}$, comparable to local starbursts. If correct, dust build-up in the first galaxies is slow enough to rule out efficient dust condensation in stellar ejecta, while the high star-formation efficiency suggests a common bursty, gas-hungry phase in UV-bright galaxies at cosmic dawn. The result matters because it places direct constraints on the dust-to-gas ratio and gas consumption at redshifts where the universe was under 300 million years old.

What carries the argument

The central tool is the Inoue et al. (2020) analytical model, which fixes dust temperature by requiring radiative equilibrium between absorbed starlight plus the cosmic microwave background and re-emitted dust radiation, with a clumpy dust geometry (clumpiness parameter $\log \xi_{\rm cl} = -1.0$) and dust emissivity $\beta=2.0$. The model turns the observed UV luminosity and spatial extent into a predicted relation between $T_{\rm dust}$ and $M_{\rm dust}$; intersecting that relation with the ALMA 3-$\sigma$ flux limits at rest-frame 88 $\mu$m yields the dust mass upper limits. The secondary machinery is the star-formation efficiency, ${\rm SFE} = {\rm SFR}/M_{\rm mol}$, where $M_{\rm mol}$ is approximated by $M_{\rm dyn} - M_*$, with SFR averaged over 10 and 100 Myr from non-parametric JWST star-formation histories.

What would settle it

A detection of dust continuum emission at rest-frame 88 $\mu$m for GHZ2 or GS-z14-0 above the predicted 3-$\sigma$ limits, or an independent measurement of the dust SED peak showing $T_{\rm dust}$ well below 90 K, would overturn the low-dust claim. Likewise, a direct [C II] or CO detection that yields a molecular gas mass large enough to lower the SFE to the main-sequence value would overturn the starburst claim.

Watch

Extended reading notes

Core claim

Using the Inoue et al. (2020) analytical model of dust in thermal equilibrium with a clumpy geometry, the authors convert ALMA 3-$\sigma$ upper limits on rest-frame 88 $\mu$m continuum ($10.3\,\mu$Jy for GHZ2 and $14.9\,\mu$Jy for GS-z14-0) into dust mass limits of $\log M_{\rm dust}/M_\odot < 5.0$ and $< 5.3$, respectively. The model predicts dust temperatures above 90 K because the young stellar radiation field is intense and the star-forming regions are compact, which is what makes the limits so tight. Combined with JWST-derived stellar masses and metallicities of roughly 0.1--0.2 $Z_\odot$, these limits place the galaxies below the dust-to-stellar mass ratios of $z=4$--8 galaxies and in tension with models of high dust condensation efficiency in supernova ejecta, while remaining consistent with a short metal-accretion timescale for ISM dust growth. From dynamical masses, the molecular gas mass is estimated, and the ratio of the 10-Myr-averaged SFR to that gas gives efficiencies around $10\,{\rm Gyr}^{-1}$, about 0.5--1 dex above the main-sequence relation. The authors conclude that these $z>12$ UV-bright galaxies are dust-poor and in a starburst phase, likely explained by bursty star formation and weak feedback.

Load-bearing premise

The dust-mass limits would relax by roughly an order of magnitude if the dust were significantly colder than the model's prediction of $T_{\rm dust} > 90\,{\rm K}$, so the low-dust conclusion hinges on the assumed thermal-equilibrium dust temperature.

Editorial extensions

If this is right

  • The two galaxies' dust-to-stellar mass ratios fall below the $z=4$--7 trend, implying that dust production at $z>12$ is dominated by supernova ejecta with little ISM grain growth.
  • A short metal-accretion timescale ($\tau_{\rm acc} \sim 5$--100 Myr) is favored over a high condensation efficiency, meaning dust in the earliest galaxies builds up mainly after roughly 100 Myr.
  • GS-z14-0 requires a dust survival fraction below 20% against supernova reverse shocks, consistent with theoretical destruction rates; a top-heavy IMF would require an even lower survival rate and is disfavored.
  • Both galaxies show SFE around $10\,{\rm Gyr}^{-1}$ on 10-Myr timescales, similar to starbursts, suggesting that such bursts are common among UV-bright galaxies at $z>12$ and may explain their overabundance.

Reading between the lines

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

  • If the low-dust, high-SFE pattern holds for a larger sample of $z>12$ galaxies, the JWST UV luminosity function at cosmic dawn would be systematically boosted by bursty star formation, and the dust masses in these systems would be a poor tracer of their past star formation.
  • The tightness of the dust limits depends on the clumpy-geometry assumption; a more diffuse dust distribution would lower $T_{\rm dust}$ and weaken the limits, so a direct measurement of the dust SED peak in these galaxies would arbitrate between the model geometry and a colder-dust scenario.
  • A [C II] or CO detection would directly measure the molecular gas mass in these two galaxies, testing whether the high SFE is genuine or an artifact of the $M_{\rm dyn}-M_*$ gas-mass approximation.
Share X Bluesky LinkedIn Reddit HN

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. This paper presents ALMA Band-6/8 continuum non-detections for two of the highest-redshift spectroscopically confirmed galaxies, GHZ2 (z=12.33) and GS-z14-0 (z=14.18), and combines them with JWST-derived stellar masses, metallicities, and star-formation histories. Using the Inoue et al. (2020) radiative-equilibrium clumpy-dust model, the authors convert the non-detections into 3-sigma upper limits of log Mdust/Msun < 5.0 and < 5.3. They then use Mgas = Mdyn - M* to estimate gas masses and compare D/G with dust-growth models, and compute SFE = SFR/Mgas, reporting SFE_10Myr ~ 10 Gyr^-1, which they interpret as evidence that z>12 UV-bright galaxies are in a starburst phase with higher efficiency than main-sequence galaxies.

Significance. The ALMA non-detections are valuable: they provide some of the first direct dust continuum constraints at z>12, and the paper is unusually transparent about the modeling assumptions, explicitly showing the T_dust = 50 K alternative and citing the f_gas range as a limiting factor. The dust-production model comparison and the discussion of SN reverse-shock dust destruction are useful. The limiting element is that the 'high star-formation efficiency' claim rests on gas masses that the paper itself shows are unconstrained; as presented, the SFE result is an interpretation at the optimistic end of a wide range rather than a measured property. With appropriate rewording, the paper would be a solid observational contribution.

major comments (3)
  1. [Sec. 4.2 / Fig. 5] The headline SFE claim is not supported by the paper's own uncertainty budget. The text states that the f_gas = 0.1-0.9 range 'prevents imposing any meaningful constraints on the SFE,' and the shaded regions in Figure 5 show the SFE spanning roughly an order of magnitude. Concretely, for GS-z14-0 at f_gas = 0.9, Mgas ~ 6 x 10^9 Msun gives SFE_10Myr ~ 1.6 Gyr^-1, consistent with the main-sequence locus; for GHZ2, replacing SFR_10Myr with SFR_100Myr lowers SFE from ~15 to ~2 Gyr^-1. No CO or [CII] gas mass is available, so the value ~10 Gyr^-1 quoted in the abstract and title is the high end of a wide, poorly constrained range, not a measurement. In addition, the comparison with ALPINE/REBELS is inhomogeneous because those samples use SFRs averaged over ~100 Myr, whereas the headline SFE uses a 10 Myr averaging timescale. I recommend rewording the abstract and title to present the high SFE as conditional on f_gas ~ 0.3 and SFR_10Myr, or moving it to a discussion scenario.
  2. [Sec. 3.2 / Fig. 2 / Table 1] The dust mass upper limits inherit a strong model assumption: the I20 model with log xi_cl = -1, beta_dust = 2, and radiative equilibrium gives T_dust > 90 K, which is what makes log Mdust/Msun < 5.0 and < 5.3 tight. As the authors show, assuming T_dust = 50 K instead loosens the limits by roughly an order of magnitude. The abstract reports the tighter values without this qualification. Because the title's 'low dust mass' claim depends on this model, the abstract should either state the assumed T_dust/model explicitly or report the T_dust = 50 K case alongside; otherwise readers may mistake a model-dependent upper limit for a direct observational constraint.
  3. [Sec. 4.2, last paragraph] The assertion that the adopted molecular gas fraction does not affect the conclusion addresses only the conversion from total gas to molecular gas for a fixed total gas mass, not the f_gas uncertainty used to define the shaded regions in Figure 5. Since f_gas = 0.1-0.9 changes the inferred gas mass by an order of magnitude and is explicitly acknowledged to prevent meaningful SFE constraints, the sentence 'Therefore, the adopted molecular gas fraction does not affect our conclusion' is not a valid response to the main caveat. This logical gap is part of the reason the SFE claim is overstated relative to the data.
minor comments (4)
  1. [Sec. 3.1] The phrase 'we require uniform noise distribution within a field of view' should be 'we require a uniform noise distribution across the field of view.'
  2. [Sec. 4.1 / Sec. 4.2] There are small typographical errors: 'caluclation' in Sec. 4.1 and 'SFH10Myr' where 'SFE10Myr' is meant in Sec. 4.2.
  3. [Fig. 2 caption] The caption states that the dust mass constraints 'do not agree with the observed AV values,' which is confusing given that Sec. 3.2 says the limits agree well with the expected AV under the clumpy geometry; please clarify what comparison is intended.
  4. [Sec. 4.2] The text says 'we assume the ISM is dominated by the molecular gas (Mgas ~ Mmol),' but the f_gas = 0.1-0.9 calculations are also labeled Mgas; please define consistently whether SFE uses Mgas or Mmol, since the logical distinction matters for the caveats.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the dust-mass limits come from a fixed literature model applied to ALMA non-detections, and the SFE caveat is explicitly acknowledged in the paper.

full rationale

The derivation chain is not circular. The dust-mass upper limits (log Mdust/Msun < 5.0 and < 5.3) are obtained by applying the Inoue et al. (2020, I20) thermal-equilibrium model with fixed assumptions (clumpy geometry, log xi_cl = -1.0, beta_dust = 2.0, kappa values) to the ALMA continuum non-detections and the NIRCam size. No parameter is fitted to these two galaxies and then relabeled a prediction; the Tdust = 50 K alternative is shown to weaken the limits by about an order of magnitude, confirming that the tight limits come from a stated model assumption rather than a hidden identity. The star-formation efficiencies are formed from JWST-derived SFRs and Mgas = Mdyn - Mstar, which are independent inputs; the paper explicitly flags in Section 4.2 that the fgas = 0.1-0.9 assumption "prevents imposing any meaningful constraints on the SFE," so the headline high SFE is an interpretation of a wide, unconstrained range rather than a circularly constructed result. The dust-production models are compared with the data, not tuned to match them. Self-citations (Zavala et al. 2024a/b, Inoue et al. 2020) provide external measurements and a published modeling framework; no load-bearing argument reduces to an unverified self-citation. The skeptic's concerns are about overstatement and model dependence, which are caveats, not circularity.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The central claims rest on the I20 radiative equilibrium model with fixed parameters, the Mgas = Mdyn - M* approximation with negligible dark matter, and the assumption that molecular gas dominates the ISM. No new physical entities are introduced. Several parameters, such as beta_dust, kappa_0, and log xi_cl, are chosen from prior literature rather than fitted, and the paper would benefit from exploring their full impact on the conclusions.

free parameters (6)
  • Dust emissivity index beta_dust = 2.0
    Assumed following Casey (2012) and da Cunha et al. (2021) in the modified blackbody conversion; different values change the dust mass upper limit.
  • Clumpiness parameter log(xi_cl) = -1.0
    Adopted from Inoue et al. (2020) and Fudamoto et al. (2023); controls the escape of UV photons and the predicted dust temperature, directly affecting the dust mass limit.
  • Mass absorption coefficient kappa_0 at 100 micron = 30 cm2/g
    Assumed value converting the 88 micron continuum to dust mass; a different opacity changes the limits.
  • Gas fraction fgas for SFE = 1.0 (implicit)
    The SFE assumes the ISM is dominated by molecular gas, Mgas ~ Mmol; the paper also considers fgas=0.1-0.9 but admits these prevent meaningful SFE constraints.
  • Larson IMF characteristic mass M_ch = 0.35 solar masses
    Used in the dust yield models; a top-heavy value of 10 would require much lower dust survival rates and is disfavored.
  • Star formation onset redshift z_start = 20 (GHZ2), 30 (GS-z14-0)
    Assumed for the exponential SFH used in the dust production history models; affects the predicted dust mass but not the observed upper limits.
assumptions (6)
  • domain assumption Dust is in radiative equilibrium with the radiation field from young stars and the CMB (I20 model).
    Section 3.2: the model assumes thermal equilibrium; if this fails, the derived T_dust and Mdust are not valid.
  • domain assumption Dust is distributed in clumps with an escape probability described by the I20 'clumpy' geometry.
    Section 3.2: the choice of geometry affects T_dust; the paper notes that other geometries give tighter constraints.
  • domain assumption Dust emission is optically thin at rest-frame 88 microns with emissivity beta=2.
    Section 3.2: assumed for the modified blackbody; optically thick dust would require larger masses for the same flux.
  • domain assumption Dark matter contribution is negligible within the effective radius, so Mgas = Mdyn - M*.
    Section 4.1: used to derive gas masses, dust-to-gas ratios, and SFE.
  • domain assumption The ionized gas mass is negligible compared to the total gas mass except for GS-z14-0, where Mion is adopted as the lower limit.
    Section 4.1: they estimate Mion from H-beta flux and electron density and include it for GS-z14-0.
  • domain assumption The ISM is dominated by molecular gas (Mgas ~ Mmol) for the SFE definition.
    Section 4.2: following Aravena et al. (2024).

how reviews work

0 comments
Cite this review

Pith. "Pith review of Low dust mass and high star-formation efficiency at $z>12$ from deep ALMA observations." pith.science (2026). https://pith.science/paper/KSJJB6CC

@misc{pith2026250119384,
  author       = {Pith},
  title        = {Pith review of: Low dust mass and high star-formation efficiency at $z>12$ from deep ALMA observations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KSJJB6CC}},
  note         = {Machine review of arXiv:2501.19384}
}
abstract

We investigate the dust mass build-up and star formation efficiency of two galaxies at $z>12$, GHZ2 and GS-z14-0, by combining ALMA and JWST observations with an analytical model that assumes dust at thermal equilibrium. We obtained $3\sigma$ constraints on dust mass of $\log M_{\rm dust}/M_{\odot}<5.0$ and $<5.3$, respectively. These constraints are in tension with a high dust condensation efficiency in stellar ejecta but are consistent with models with a short metal accretion timescale at $z>12$. Given the young stellar ages of these galaxies ($t_{\rm age}\sim10\,{\rm Myrs}$), dust grain growth via accretion may still be ineffective at this stage, though it likely works efficiently to produce significant dust in galaxies at $z\sim7$. The star formation efficiencies, defined as the SFR divided by molecular gas mass, reach $\sim10\,{\rm Gyr}^{-1}$ in a 10\,Myr timescale, aligning with the expected redshift evolution of `starburst' galaxies with efficiencies that are $\sim0.5$--$1\,{\rm dex}$ higher than those in main-sequence galaxies. This starburst phase seems to be common in UV-bright galaxies at $z>12$ and is likely associated with the unique conditions of the early phases of galaxy formation, such as bursty star formation and/or negligible feedback from super-Eddington accretion. Direct observations of molecular gas tracers like [C\,{\sc ii}] will be crucial to further understanding the nature of bright galaxies at $z>12$.

Figures

Figures reproduced from arXiv: 2501.19384 by the authors.

Figure 1
Figure 1. JWST NIRCam F444W and ALMA Band-6/8 thumbnails of GHZ2 in the rest-frame 0.3 µm, 52 µm and 88 µm continuum (left) and GS-z14-0 in the rest-frame 0.3 µm and 88 µm continuum (right). Contour levels are shown in every 2σ from ±3σ. At the positions of the detection in λrest = 0.3 µm, the dust continuum remains undetected for both galaxies. frame UV/optical emission line with JWST/NIRSpec (Castellano et al. 2024) and JWS… view at source ↗
Figure 2
Figure 2. Dust mass and temperatures, color-coded by the signal-to-noise ratio of the dust continuum that is expected at the rest-frame 88 µm for GHZ2 (left) and GS-z14-0 (right). Red solid lines indicate 1σ and 3σ upper limits at the rest-frame 88µm by assuming a modified black body spectrum after lens magnification correction. The yellow lines on the left panel show upper limits from the rest-frame 52µm which provides a muc… view at source ↗
Figure 3
Figure 3. (left) Dust mass as a function of the stellar mass. Our constraints for the galaxies at z > 12 along with the previous constraints at z = 4–8 (Bakx et al. 2021; Sommovigo et al. 2022a,b; Witstok et al. 2022; Fudamoto et al. 2023; Valentino et al. 2024) and (semi-)analytical models (Popping et al. 2017; Imara et al. 2018; Vijayan et al. 2019; Di Cesare et al. 2023) including DELPHI model (Mauerhofer & Dayal 2023) are… view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: Dust and star formation history derived from non-parametric SFH and SN/AGB dust yield models for GHZs (left) and GS-z14-0 (right). (top) Smoothed exponentially rising star formation history (black) derived from Bagpipes (red, Zavala et al. 2024a) and Prospector (blue, …
Figure 5
Figure 5. Figure 5: Redshift evolution of the star formation efficiency. Our fiducial calculations (red stars and brown hexagons) are shown based on SFR10Myr (filled) and SFR100Myr (open markers), respectively. We also illustrate SFEs based on the gas masses assuming fgas = 0.1–0.9 in red…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

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

  1. Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) III: [C II] as Tracer, Crisis of SFR, [O III]/[C II] at High-z, New Answers and New Questions

    astro-ph.GA 2025-07 conditional novelty 6.0 of 10

    A universal gas-line deficit relative to infrared luminosity, seen in [C II], [O I], [N II], and extinction-corrected H-alpha, breaks standard SFR calibrations in the brightest dusty galaxies and implies a metallicity...

  2. Realistic Multi-temperature Dust: How Well Can We Constrain the Dust Properties of High-redshift Galaxies?

    astro-ph.GA 2025-05 conditional novelty 6.0 of 10

    Single-temperature fits to mock high-redshift dust SEDs built from a skewed temperature PDF underestimate dust masses by up to about 0.6 dex and bias the emissivity index shallow.

Reference graph

Works this paper leans on

107 extracted references · 49 canonical work pages · cited by 2 Pith papers

  1. [1]

    S., Bethermin, M., et al

    Aravena, M., Spilker, J. S., Bethermin, M., et al. 2016, MNRAS, 457, 4406

  2. [2]

    2024, A&A, 682, A24

    Aravena, M., Heintz, K., Dessauges-Zavadsky, M., et al. 2024, A&A, 682, A24

  3. [3]

    2024, MNRAS, 527, 11372

    Asada, Y., Sawicki, M., Abraham, R., et al. 2024, MNRAS, 527, 11372

  4. [4]

    S., Takeuchi, T

    Asano, R. S., Takeuchi, T. T., Hirashita, H., & Inoue, A. K. 2013, Earth, Planets and Space, 65, 213

  5. [5]

    J., et al

    Atek, H., Shuntov, M., Furtak, L. J., et al. 2023, MNRAS, 519, 1201

  6. [6]

    Bakx, T. J. L. C., Tamura, Y., Hashimoto, T., et al. 2020, MNRAS, 493, 4294

  7. [7]

    Bakx, T. J. L. C., Sommovigo, L., Carniani, S., et al. 2021, MNRAS, 508, L58

  8. [8]

    Bakx, T. J. L. C., Zavala, J. A., Mitsuhashi, I., et al. 2023, MNRAS, 519, 5076

Show all 107 references
  1. [9]

    Bakx, T. J. L. C., Algera, H. S. B., Venemans, B., et al. 2024, MNRAS, 532, 2270

  2. [10]

    J., Wilson, C

    Bendo, G. J., Wilson, C. D., Warren, B. E., et al. 2010, MNRAS, 402, 1409

  3. [11]

    2023, ApJ, 952, 84

    Bergamini, P., Acebron, A., Grillo, C., et al. 2023, ApJ, 952, 84

  4. [12]

    2007, MNRAS, 378, 973

    Bianchi, S., & Schneider, R. 2007, MNRAS, 378, 973

  5. [13]

    E., Weiss, A., Wardlow, J

    Birkin, J. E., Weiss, A., Wardlow, J. L., et al. 2021, MNRAS, 501, 3926

  6. [14]

    2016, A&A, 589, A132

    Biscaro, C., & Cherchneff, I. 2016, A&A, 589, A132

  7. [15]

    2023, MNRAS, 523, 1009

    Bouwens, R., Illingworth, G., Oesch, P., et al. 2023, MNRAS, 523, 1009

  8. [16]

    2024, arXiv e-prints, arXiv:2410.23959

    Burgarella, D., Buat, V., Theul´ e, P., et al. 2024, arXiv e-prints, arXiv:2410.23959

  9. [17]

    A., et al

    Calabro, A., Castellano, M., Zavala, J. A., et al. 2024, arXiv e-prints, arXiv:2403.12683

  10. [18]

    C., McLure, R

    Carnall, A. C., McLure, R. J., Dunlop, J. S., & Dav´ e, R. 2018, MNRAS, 480, 4379

  11. [19]

    2024b, arXiv e-prints, arXiv:2409.20533 CASA Team, Bean, B., Bhatnagar, S., et al

    Carniani, S., D’Eugenio, F., Ji, X., et al. 2024b, arXiv e-prints, arXiv:2409.20533 CASA Team, Bean, B., Bhatnagar, S., et al. 2022, PASP, 134, 114501

  12. [20]

    Casey, C. M. 2012, MNRAS, 425, 3094

  13. [21]

    M., Akins, H

    Casey, C. M., Akins, H. B., Shuntov, M., et al. 2024, ApJ, 965, 98

  14. [22]

    2022, ApJL, 938, L15

    Castellano, M., Fontana, A., Treu, T., et al. 2022, ApJL, 938, L15

  15. [23]

    2024, ApJ, 972, 143 Ch´ avez, R., Terlevich, R., Terlevich, E., et al

    Castellano, M., Napolitano, L., Fontana, A., et al. 2024, ApJ, 972, 143 Ch´ avez, R., Terlevich, R., Terlevich, E., et al. 2014, MNRAS, 442, 3565

  16. [24]

    2014, A&A, 565, A128 da Cunha, E., Walter, F., Smail, I

    Ciesla, L., Boquien, M., Boselli, A., et al. 2014, A&A, 565, A128 da Cunha, E., Walter, F., Smail, I. R., et al. 2015, ApJ, 806, 110 da Cunha, E., Hodge, J. A., Casey, C. M., et al. 2021, ApJ, 919, 30

  17. [25]

    2022, MNRAS, 512, 989 de Bennassuti, M., Schneider, R., Valiante, R., & Salvadori, S

    Dayal, P., Ferrara, A., Sommovigo, L., et al. 2022, MNRAS, 512, 989 de Bennassuti, M., Schneider, R., Valiante, R., & Salvadori, S. 2014, MNRAS, 445, 3039

  18. [26]

    2023, MNRAS, 523, 3201 Dell’Agli, F., Valiante, R., Kamath, D., Ventura, P., & Garc ´ ıa-Hern´ andez, D

    Li, Z. 2023, MNRAS, 523, 3201 Dell’Agli, F., Valiante, R., Kamath, D., Ventura, P., & Garc ´ ıa-Hern´ andez, D. A. 2019, MNRAS, 486, 4738

  19. [27]

    2020, A&A, 643, A5 Di Cesare, C., Graziani, L., Schneider, R., et al

    Dessauges-Zavadsky, M., Ginolfi, M., Pozzi, F., et al. 2020, A&A, 643, A5 Di Cesare, C., Graziani, L., Schneider, R., et al. 2023, MNRAS, 519, 4632

  20. [28]

    Draine, B. T. 1990, in Astronomical Society of the Pacific Conference Series, Vol. 12, The Evolution of the Interstellar Medium, ed. L. Blitz, 193–205

  21. [29]

    Draine, B. T. 2009, in Astronomical Society of the Pacific Conference Series, Vol. 414, Cosmic Dust - Near and Far, ed. T. Henning, E. Gr¨ un, & J. Steinacker, 453

  22. [30]

    T., Dale, D

    Draine, B. T., Dale, D. A., Bendo, G., et al. 2007, ApJ, 663, 866

  23. [31]

    Dwek, E., & Scalo, J. M. 1980, ApJ, 239, 193

  24. [32]

    P., Whitler, L., et al

    Endsley, R., Stark, D. P., Whitler, L., et al. 2024, MNRAS, 533, 1111

  25. [33]

    2024, A&A, 684, A207

    Ferrara, A. 2024, A&A, 684, A207

  26. [34]

    2024a, arXiv e-prints, arXiv:2409.17223

    Ferrara, A., Carniani, S., di Mascia, F., et al. 2024a, arXiv e-prints, arXiv:2409.17223

  27. [35]

    2024b, arXiv e-prints, arXiv:2410.19042

    Ferrara, A., Pallottini, A., & Sommovigo, L. 2024b, arXiv e-prints, arXiv:2410.19042

  28. [36]

    2022, MNRAS, 512, 58

    Ferrara, A., Sommovigo, L., Dayal, P., et al. 2022, MNRAS, 512, 58

  29. [37]

    S., & Gail, H

    Ferrarotti, A. S., & Gail, H. P. 2006, A&A, 447, 553

  30. [38]

    L., Leung, G

    Finkelstein, S. L., Leung, G. C. K., Bagley, M. B., et al. 2024, ApJL, 969, L2

  31. [39]

    K., & Sugahara, Y

    Fudamoto, Y., Inoue, A. K., & Sugahara, Y. 2023, MNRAS, 521, 2962

  32. [40]

    2008, ApJ, 672, 214

    Galliano, F., Dwek, E., & Chanial, P. 2008, ApJ, 672, 214

  33. [41]

    2020, MNRAS, 494, 1071

    Graziani, L., Schneider, R., Ginolfi, M., et al. 2020, MNRAS, 494, 1071

  34. [42]

    K., et al

    Harikane, Y., Ouchi, M., Inoue, A. K., et al. 2020, ApJ, 896, 93

  35. [43]

    2023, ApJS, 265, 5 Dust and gas atz >12 13

    Harikane, Y., Ouchi, M., Oguri, M., et al. 2023, ApJS, 265, 5 Dust and gas atz >12 13

  36. [44]

    K., Ellis, R

    Harikane, Y., Inoue, A. K., Ellis, R. S., et al. 2024, arXiv e-prints, arXiv:2406.18352

  37. [45]

    K., Mawatari, K., et al

    Hashimoto, T., Inoue, A. K., Mawatari, K., et al. 2019, PASJ, 71, 71

  38. [46]

    M., Rieke, G

    Helton, J. M., Rieke, G. H., Alberts, S., et al. 2024, arXiv e-prints, arXiv:2405.18462

  39. [47]

    2011, MNRAS, 416, 1340

    Hirashita, H., & Kuo, T.-M. 2011, MNRAS, 416, 1340

  40. [48]

    Y., & Kamaya, H

    Hirashita, H., Tajiri, Y. Y., & Kamaya, H. 2002, A&A, 388, 439

  41. [49]

    2018, ApJ, 854, 36

    Behroozi, P. 2018, ApJ, 854, 36

  42. [50]

    Inami, H., Algera, H. S. B., Schouws, S., et al. 2022, MNRAS, 515, 3126

  43. [51]

    Inoue, A. K. 2011, Earth, Planets and Space, 63, 1027

  44. [52]

    K., Hashimoto, T., Chihara, H., & Koike, C

    Inoue, A. K., Hashimoto, T., Chihara, H., & Koike, C. 2020, MNRAS, 495, 1577

  45. [53]

    R., MacLaren, I., & Wolfendale, A

    Issa, M. R., MacLaren, I., & Wolfendale, A. W. 1990, A&A, 236, 237

  46. [54]

    D., Weiss, A., et al

    Jarugula, S., Vieira, J. D., Weiss, A., et al. 2021, ApJ, 921, 97

  47. [55]

    D., Leja, J., Conroy, C., & Speagle, J

    Johnson, B. D., Leja, J., Conroy, C., & Speagle, J. S. 2021, ApJS, 254, 22

  48. [56]

    D., Barlow, M

    Kirchschlager, F., Schmidt, F. D., Barlow, M. J., et al. 2019, MNRAS, 489, 4465

  49. [57]

    2023, MNRAS, 520, L16

    Kohandel, M., Ferrara, A., Pallottini, A., et al. 2023, MNRAS, 520, L16

  50. [58]

    1982, A&A, 107, 247

    Koornneef, J. 1982, A&A, 107, 247

  51. [59]

    2024, arXiv e-prints, arXiv:2405.04578

    Kravtsov, A., & Belokurov, V. 2024, arXiv e-prints, arXiv:2405.04578

  52. [60]

    S., Boone, F., et al

    Laporte, N., Ellis, R. S., Boone, F., et al. 2017, ApJL, 837, L21

  53. [61]

    Larson, R. B. 1998, MNRAS, 301, 569

  54. [62]

    K., Bolatto, A., Gordon, K., et al

    Leroy, A. K., Bolatto, A., Gordon, K., et al. 2011, ApJ, 737, 12 Le´ sniewska, A., & Micha lowski, M. J. 2019, A&A, 624, L13

  55. [63]

    2019, MNRAS, 490, 1425

    Li, Q., Narayanan, D., & Dav´ e, R. 2019, MNRAS, 490, 1425

  56. [64]

    C., et al

    Li, Z., Dekel, A., Sarkar, K. C., et al. 2024, A&A, 690, A108

  57. [65]

    1998, ApJ, 496, 145

    Lisenfeld, U., & Ferrara, A. 1998, ApJ, 496, 145

  58. [66]

    2019, MNRAS, 490, 540

    Liu, H.-M., & Hirashita, H. 2019, MNRAS, 490, 540

  59. [67]

    E., Daddi, E., B´ ethermin, M., et al

    Magdis, G. E., Daddi, E., B´ ethermin, M., et al. 2012, ApJ, 760, 6

  60. [68]

    2011, A&A, 535, A13

    Magrini, L., Bianchi, S., Corbelli, E., et al. 2011, A&A, 535, A13

  61. [69]

    2015, MNRAS, 451, L70

    Mancini, M., Schneider, R., Graziani, L., et al. 2015, MNRAS, 451, L70

  62. [70]

    2015, MNRAS, 454, 4250

    Marassi, S., Schneider, R., Limongi, M., et al. 2015, MNRAS, 454, 4250

  63. [71]

    2023, MNRAS, 526, 2196

    Mauerhofer, V., & Dayal, P. 2023, MNRAS, 526, 2196

  64. [72]

    E., et al

    Mitsuhashi, I., Harikane, Y., Bauer, F. E., et al. 2024, ApJ, 971, 161

  65. [73]

    P., Oesch, P

    Naidu, R. P., Oesch, P. A., van Dokkum, P., et al. 2022, ApJL, 940, L14

  66. [74]

    2007, ApJ, 666, 955

    Nozawa, T., Kozasa, T., Habe, A., et al. 2007, ApJ, 666, 955

  67. [75]

    2023, ApJ, 951, 72

    Ono, Y., Harikane, Y., Ouchi, M., et al. 2023, ApJ, 951, 72

  68. [76]

    2024, MNRAS, 528, 2407

    Palla, M., De Looze, I., Rela˜ no, M., et al. 2024, MNRAS, 528, 2407

  69. [77]

    S., & Galametz, M

    Popping, G., Somerville, R. S., & Galametz, M. 2017, MNRAS, 471, 3152

  70. [78]

    L., et al

    Popping, G., Shivaei, I., Sanders, R. L., et al. 2023, A&A, 670, A138 R´ emy-Ruyer, A., Madden, S. C., Galliano, F., et al. 2014, A&A, 563, A31

  71. [79]

    D., Tacchella, S., et al

    Robertson, B., Johnson, B. D., Tacchella, S., et al. 2024, ApJ, 970, 31

  72. [80]

    Salpeter, E. E. 1955, ApJ, 121, 161

  73. [81]

    B., Scoville, N

    Sanders, D. B., Scoville, N. Z., & Soifer, B. T. 1991, ApJ, 370, 158

  74. [82]

    2014, A&A, 562, A30

    Santini, P., Maiolino, R., Magnelli, B., et al. 2014, A&A, 562, A30

  75. [83]

    T., B´ ethermin, M., Daddi, E., & Elbaz, D

    Sargent, M. T., B´ ethermin, M., Daddi, E., & Elbaz, D. 2012, ApJL, 747, L31

  76. [84]

    2016, MNRAS, 457, 1842

    Schneider, R., Hunt, L., & Valiante, R. 2016, MNRAS, 457, 1842

  77. [85]

    2024, A&A Rv, 32, 2

    Schneider, R., & Maiolino, R. 2024, A&A Rv, 32, 2

  78. [86]

    J., Ormerod, K., et al

    Schouws, S., Bouwens, R. J., Ormerod, K., et al. 2024, arXiv e-prints, arXiv:2409.20549

  79. [87]

    2017, ApJ, 837, 150

    Scoville, N., Lee, N., Vanden Bout, P., et al. 2017, ApJ, 837, 150

  80. [88]

    2024, arXiv e-prints, arXiv:2410.08290

    Shuntov, M., Ilbert, O., Toft, S., et al. 2024, arXiv e-prints, arXiv:2410.08290

  81. [89]

    D., Dwek, E., Mac Low, M.-M., & Hill, A

    Slavin, J. D., Dwek, E., Mac Low, M.-M., & Hill, A. S. 2020, ApJ, 902, 135

  82. [90]

    C., et al

    Sun, G., Faucher-Gigu` ere, C.-A., Hayward, C. C., et al. 2023, ApJL, 955, L35

  83. [91]

    J., Genzel, R., & Sternberg, A

    Tacconi, L. J., Genzel, R., & Sternberg, A. 2020, ARA&A, 58, 157

  84. [92]

    J., Genzel, R., Saintonge, A., et al

    Tacconi, L. J., Genzel, R., Saintonge, A., et al. 2018, ApJ, 853, 179

  85. [93]

    2019, ApJ, 874, 27

    Tamura, Y., Mawatari, K., Hashimoto, T., et al. 2019, ApJ, 874, 27

  86. [94]

    2001, MNRAS, 325, 726

    Todini, P., & Ferrara, A. 2001, MNRAS, 325, 726

  87. [95]

    W., Stark, D

    Topping, M. W., Stark, D. P., Endsley, R., et al. 2022, MNRAS, 516, 975

  88. [96]

    2022, ApJ, 935, 110 14 Mitsuhashi, Zavala, Bakx et al

    Treu, T., Roberts-Borsani, G., Bradac, M., et al. 2022, ApJ, 935, 110 14 Mitsuhashi, Zavala, Bakx et al

  89. [97]

    2024, A&A, 685, A138

    Valentino, F., Fujimoto, S., Gim´ enez-Arteaga, C., et al. 2024, A&A, 685, A138

  90. [98]

    Valiante, R., Schneider, R., Bianchi, S., & Andersen, A. C. 2009, MNRAS, 397, 1661

  91. [99]

    P., Clay, S

    Vijayan, A. P., Clay, S. J., Thomas, P. A., et al. 2019, MNRAS, 489, 4072

  92. [100]

    2022, MNRAS, 515, 1751

    Witstok, J., Smit, R., Maiolino, R., et al. 2022, MNRAS, 515, 1751

  93. [101]

    2022, ApJL, 938, L17

    Yang, L., Morishita, T., Leethochawalit, N., et al. 2022, ApJL, 938, L17

  94. [102]

    L., Fujimoto, S., et al

    Yoon, I., Carilli, C. L., Fujimoto, S., et al. 2023, ApJ, 950, 61

  95. [103]

    2018, MNRAS, 481, 1976

    Zanella, A., Daddi, E., Magdis, G., et al. 2018, MNRAS, 481, 1976

  96. [104]

    A., Casey, C

    Zavala, J. A., Casey, C. M., Spilker, J., et al. 2022, ApJ, 933, 242

  97. [105]

    A., Bakx, T., Mitsuhashi, I., et al

    Zavala, J. A., Bakx, T., Mitsuhashi, I., et al. 2024b, arXiv e-prints, arXiv:2411.03593

  98. [106]

    2014, A&A, 562, A76

    Zhukovska, S. 2014, A&A, 562, A76

  99. [107]

    P., & Trieloff, M

    Zhukovska, S., Gail, H. P., & Trieloff, M. 2008, A&A, 479, 453

Pith tools

Reviewed August 9, 2026 · model on record in the stance chip above.