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REVIEW 4 major objections 5 minor 87 references

ALMA Lensing Cluster Survey: Dust mass measurements as a function of redshift, stellar-mass and star formation rate, from z=1 to z=5

T0 review · 4 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read By stacking 4,103 lensed galaxies, this analysis shows a steady decline in average dust mass with redshift from z=1 to z=5, a rise with stellar mass and star formation rate, and lower high-redshift dust masses than current models predict.

desk verdict Solid, transparent stacking analysis reaching new low-mass/low-SFR regimes; the low-z scaling relations are likely robust, but the high-z decline is conditional on an unquantified catalog-incompleteness bias. read the letter →

arxiv 2411.11212 v1 pith:GLKG6WDC submitted 2024-11-18 astro-ph.GA

Jean-Baptiste Jolly , Kirsten Knudsen , Nicolas Laporte , Andrea Guerrero , Seiji Fujimoto , Kotaro Kohno , Vasily Kokorev , Claudia del P. Lagos
show 9 more authors
Thiébaut-Antoine Schirmer Franz Bauer Miroslava Dessauge-Zavadsky Daniel Espada Bunyo Hatsukade Anton M. Koekemoer Johan Richard Fengwu Sun John F. Wu
This is my paper · ORCID
classification astro-ph.GA
keywords dustmassstackingALMAgravitationallensinggalaxyevolutionstarformationratestellarhigh-redshiftgalaxies
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 sets out to measure how the dust content of ordinary galaxies evolves from $z=1$ to $z=5$, and how that dust tracks stellar mass and star formation rate. Dust matters because it catalyses molecular hydrogen formation, obscures starlight, and records the metal build-up of galaxies. The authors stack ALMA 1.2 mm continuum images of 4,103 galaxies behind 33 lensing clusters, turning many individually undetected galaxies into measurable average fluxes. The central result is a steady decline in average dust mass with redshift, with dust mass rising toward higher stellar mass and higher star formation rate, from which scaling relations are derived. If correct, dust accumulates gradually over cosmic time and current models overproduce dust at $z\sim4$–5.

What carries the argument

The engine of the analysis is image-domain continuum stacking with the LineStacker tool: uv-tapered ALMA band-6 maps of 33 clusters are cut into 9.76-arcsecond stamps at catalog positions, averaged, and the central flux is integrated in a 2-arcsecond aperture, reaching stacked noise levels near $4\times10^{-3}$ mJy per beam. That flux is converted to dust mass with a single optically thin modified blackbody, $M_{\rm dust}=5.03\times10^{-31}(S_{\nu_{\rm obs}}/f_{\rm CMB})D_L^2 / [(1+z)^4 B_{\nu_{\rm obs}}(T_{\rm obs})\kappa_{\nu_0}(\nu_0/\nu_{\rm rest})^\beta]$, using $T_{\rm rest}=25$ K, $\beta=1.8$, and $\kappa_{\nu_0}=0.0431$ m$^2$ kg$^{-1}$ at 352.6 GHz, with lensing-magnification and CMB corrections. Uncertainties combine empty-stack RMS, bootstrap resampling, redshift scatter, and a 20% magnification error; non-detections are reported as $3\sigma$ upper limits.

What would settle it

Stack the same lensed sources in a second ALMA band, for example 3 mm, so that the same rest-frame Rayleigh-Jeans wavelength is probed at all redshifts; if the decline in derived dust mass persists, the central claim survives, while if the decline flattens or vanishes, the fixed-temperature SED conversion was responsible for part of it.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is that average galaxy dust mass declines steadily from $z=1$ to $z=5$ while rising with both stellar mass and star formation rate at fixed redshift. The authors fit scaling relations of the form $M_{\rm dust}(x)=a x^b$, finding for example $M_{\rm dust}\propto {\rm SFR}^{0.78\pm0.07}$ at $1\le z<2$ and $M_{\rm dust}\propto z^{-1.0\pm0.3}$ at fixed stellar mass $10^{10}$–$10^{11}\,M_\odot$. Stacked detections span roughly $3\times10^6$ to $2.6\times10^8\,M_\odot$, while the highest-redshift bins are mostly $3\sigma$ upper limits. Comparison with galaxy-formation models shows broad agreement at $z\sim1$–3 but predicted dust masses that are higher than observed at $z>3$.

Load-bearing premise

The load-bearing premise, discussed but not corrected in Section 5, is that the 1.2 mm continuum traces dust mass through a single optically thin 25 K blackbody at every redshift, so if the true mass-weighted dust temperature or emissivity evolves, part of the apparent redshift decline would be an artifact of that assumption.

Editorial extensions

If this is right

  • Average dust mass drops by roughly an order of magnitude from $z\sim1$ to $z\sim5$, so dust accumulation in typical galaxies is a gradual process tied to cosmic time.
  • At fixed redshift, dust mass increases with both stellar mass and star formation rate, with the SFR relation closer to linear, making star formation rate a useful dust-mass tracer.
  • At $z>3$ the measured dust masses fall below the predictions of current galaxy-formation models, implying those models overproduce dust in early galaxies if the measurements hold.
  • Excluding quiescent galaxies raises the average dust masses in stellar-mass-selected stacks, so quiescent galaxies carry less dust for their stellar mass and lower the population averages.

Reading between the lines

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

  • I infer that the strongest systematic to test is the rest-wavelength shift: since the fixed 1.2 mm band probes about 0.5 mm at $z=1$ and about 0.2 mm at $z=5$, a true evolution of the mass-weighted dust temperature would change the high-redshift masses by roughly 50% and could flatten the reported decline.
  • I infer that a multi-band stacking test, for example with ALMA band 3 near 3 mm, would sample the same rest-frame Rayleigh-Jeans tail at all redshifts and cleanly separate a real dust-mass decline from an SED assumption.
  • I infer that if JWST-based source catalogs recover the dusty galaxies missed by the HST-IRAC selection, the high-redshift average dust masses are likely to move upward, shrinking the gap with model predictions.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. The paper uses ALMA Band 6 continuum imaging from the ALCS survey to stack approximately 4100 lensed galaxies from the Kokorev et al. (2022) HST/IRAC catalog, binning them in redshift, stellar mass, and star-formation rate. From the stacked 1.2 mm fluxes it derives average dust masses using Eq. (1), which assumes a single optically thin modified blackbody with a fixed 25 K mass-weighted dust temperature, and it reports a decline of average dust mass with redshift, positive scaling relations with stellar mass and SFR, and broad agreement with models at z ~ 1-3 but lower-than-predicted dust masses at higher redshift. The analysis includes mean and median stacking, bootstrap and RMS uncertainties, magnification corrections, and a comparison to semi-analytic models using both model dust masses and model-predicted band-6 fluxes.

Significance. If the reported trends are robust, this paper provides a valuable statistical census of dust in typical (not just individually bright) galaxies from z = 1 to z = 5, extending stacking measurements to lower stellar masses and SFRs than most previous work. The study's strengths include the use of a large, homogeneously observed lensed sample; explicit median-stack and bootstrap consistency checks, which support the qualitative trends; CMB correction following da Cunha et al. (2013); and a careful model comparison that distinguishes direct model dust masses from masses derived from predicted band-6 fluxes. The qualitative relations — dust increasing with stellar mass and SFR and decreasing with redshift — are plausible and likely to hold. However, the quantitative redshift decline and the claimed tension with models at high redshift rest on selection and SED assumptions that the paper acknowledges but does not correct, so the result is best regarded as conditional until those biases are bounded.

major comments (4)
  1. [Section 5 and Section 2.2] The sample is drawn from an HST/IRAC catalog that misses 35 of the 180 ALCS sources detected at SNR > 4, as the authors acknowledge in Section 5. Because the missing sources are preferentially the most dusty, and because the effect is expected to be strongest at high redshift, the stacked fluxes in several high-redshift bins (Tables 3 and 4, many of which are 3-sigma upper limits) are biased downward in exactly the direction of the headline result — the decline in average dust mass with redshift and the low values compared to models. The paper does not quantify or correct this incompleteness. The authors should attempt to bound this bias, for example by adding the 35 missing sources using their ALMA positions in the stacks, by reweighting the sample with a completeness model, or by presenting the maximum plausible correction; without this, the redshift trend and model comparison remain conditional.
  2. [Section 3.3, Eq. (1)] The dust mass conversion assumes a single optically thin modified blackbody with T_rest = 25 K and beta = 1.8 at all redshifts. Since the observed band is fixed, the rest-frame wavelength shifts from about 0.5 mm at z = 1 to about 0.2 mm at z = 5, so Eq. (1) progressively moves off the Rayleigh-Jeans tail and becomes sensitive to the assumed temperature and SED shape. The authors note the ~T^-1 dependence and quote a ~50% change at T = 40 K, but this does not bound the effect of a plausible mass-weighted temperature evolution: a change of ~10 K across the probed redshift range can alter high-z masses by factors comparable to the claimed decline, and the adopted temperature also sets the absolute values used for the model comparison. The paper should present the redshift trend under at least two plausible T(z) prescriptions (e.g., constant 25 K and a mild increase with redshift) to demonstrate that the qualitative decline is robust.
  3. [Section 4.1 and Table 5] The scaling relations are fitted using detections only, ignoring the 3-sigma upper limits, as stated in Section 4.1. At high redshift most points are upper limits, so the fitted slopes for Mdust(z) (e.g., b = -1.8 +/- 0.7 and -1.0 +/- 0.3 in Table 5) are likely biased by the detection threshold, which preferentially selects bright sources. A censored likelihood or survival analysis should be used, or the fits should be repeated with upper limits included to bound the effect. In addition, the fitted normalization for the Mdust-M* relation at z = 1-2 (a = 5.2 +/- 13.0 x 10^3 in Table 5) is effectively unconstrained, so the paper's claim of having derived a scaling relation with stellar mass is not supported by this fit; this should be stated explicitly.
  4. [Section 5 and Figure 3] The sample's stellar mass function shows an overdensity at z > 4 and an under-density at 2 < z < 3 relative to COSMOS2020 (Figure 3), which the authors attribute to photometric redshift misclassification of lower-redshift sources. As they note, this would overestimate dust content at z > 3, working in the opposite direction of the missing dusty galaxies. The net redshift trend therefore depends on two unquantified and competing biases. The authors should attempt to quantify the photo-z contamination, for example by propagating the redshift uncertainties into the stacked fluxes or by re-fitting with the z > 3 bins adjusted to the COSMOS2020 stellar mass function.
minor comments (5)
  1. [Section 6] The summary states that the sources were binned in 'five different redshift bins,' but Section 2.3 defines only four redshift bins (1<z<2, 2<z<3, 3<z<4, 4<z<5).
  2. [Section 1] The cosmology is quoted as 'H0 = 70 km s-1 Mpc-3'; the units should be km s-1 Mpc-1.
  3. [Section 2.2] In the selection criteria, 'not tagged with bad photometry (bad_phot , 1)' is ambiguous; it should read 'bad_phot = 0' or 'bad_phot != 1'.
  4. [Section 1] The introduction promises that the paper will 'integrate the contribution from all galaxies in each redshift bin to assess the evolution of the cosmic dust density,' but no cosmic dust density measurement or figure is presented in the results or summary; this promise should either be fulfilled or removed.
  5. [Section 3.4] The footnote that the stack RMS and bootstrap uncertainties are correlated and added quadratically (overestimating the error) is useful, but the overestimate should be stated in the main text or the method should be changed to use only one of the two terms.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: dust masses are measured from stacked 1.2 mm fluxes through a fixed, externally calibrated SED conversion, and the scaling relations and high-redshift model tension are empirical outputs rather than inputs restated by construction.

full rationale

The derivation chain is self-contained at the level required to avoid circularity. Dust masses are computed from measured stacked 1.2 mm fluxes via Eq. 1, a single optically thin modified blackbody with literature-adopted parameters (T_rest = 25 K, beta = 1.8, kappa_nu0 = 0.0431 m2/kg from Li & Draine 2001, Magnelli et al. 2020, Planck Collaboration 2011), corrected for CMB following da Cunha et al. (2013) and for the average lensing magnification. None of these inputs contains the target result: the scaling relations in Table 5 are fits to the resulting dust masses ("By fitting quadratic functions to the data ... we derive scaling relations"), not quantities used to generate the masses, so the empirical claim (dust mass declining with redshift, rising with stellar mass and SFR) is independent. Bins with four detections across z (e.g., the 10^10 < M* < 10^11 bin in Table 3) show the decline from measured fluxes, giving the headline trend non-tautological content. The self-cited items are tools, data, or companion works, not load-bearing premises: LineStacker (Jolly et al. 2020) is public code that performs aperture-mean stacking and bootstrapping; the Kokorev et al. (2022) HST-IRAC catalog supplies positions, photometric redshifts, SFRs, and stellar masses from optical-to-IRAC photometry independent of the ALMA 1.2 mm data, and is externally validated (spectroscopic redshifts for ~7000 galaxies; SMF comparison against COSMOS2020 in Figure 3); the Kohno et al. (2023) survey paper documents the ALMA data. The model comparison is an external benchmark, and the paper itself flags the SHARK dust-mass methodology difference (footnote 2: dust masses estimated from an empirical z = 0 dust-to-gas-metallicity relation) and shows both SHARK's direct Mdust and its S6-derived Mdust. The acknowledged limitations asserted in the text (Section 5 and the appendix) are systematic or selection effects, not circular steps: the fixed 25 K mass-weighted temperature ("dust masses go as T^-1 ... could be off by factors of a few if the assumed dust temperature is not correct"), the rest-wavelength shift toward the dust SED peak at high z ("the higher the redshift observed the closer one gets to the peak of dust emission"), the incompleteness of the HST/IRAC selection (35 of 180 ALCS SNR>4 sources absent from the catalog, "This bias could be strongest in the high-redshift bins"), and photometric-redshift contamination at z > 3.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

The central claim rests on assumptions about dust SED shape, photometric redshift quality, and catalog completeness rather than on new physics entities. The fixed 25 K temperature, beta of 1.8, and Li and Draine opacity are literature inputs that directly set the absolute dust mass scale.

free parameters (3)
  • Dust temperature T_rest = 25 K (assumed constant)
    Mass-weighted dust temperature used in Eq. 1. Since dust mass scales as T^-1, this choice sets the absolute mass scale and can shift results by factors of a few (Section 3.3, Section 5).
  • Dust emissivity index beta = 1.8
    Adopted from Planck Collaboration 2011. Varying beta between 1.5 and 2.0 changes dust mass by about 9% at z=1.5 and 15% at z=5.5 (Section 3.3).
  • Dust opacity kappa_nu0 = 0.0431 m2/kg at 352.6 GHz
    From Li and Draine 2001, diffuse ISM opacity. If the true opacity is 2 to 3 times higher, as suggested for dense ISM, all dust masses scale down by that factor (Section 5).
assumptions (5)
  • domain assumption Dust emission at 1.2 mm is optically thin and traces dust mass
    Invoked to write Eq. 1; the approximation is less secure at z=4 to 5 where rest wavelength about 0.2 mm approaches the SED peak (Section 3.3, Section 5).
  • domain assumption A single modified blackbody with T=25 K describes the dust SED at all redshifts probed
    Adopted following Magnelli et al. 2020 and Pozzi et al. 2021; dust mass is inversely proportional to T, so this is the key conversion choice (Section 3.3).
  • domain assumption Photometric redshifts and magnifications from Kokorev et al. 2022 are sufficiently accurate for binning
    The paper reports about 20% large or catastrophic redshift errors and an apparent overpopulation of z greater than 3 bins (Section 2.2, Section 5).
  • domain assumption The 1.2 mm continuum flux is dominated by dust emission rather than other mechanisms
    Standard ALMA dust-mass tracer assumption, cited to Scoville et al. (Section 1, Section 3.3).
  • domain assumption CMB heating and background corrections of da Cunha et al. 2013 apply
    Used to compute fCMB in Eq. 1; correction grows from about 1.03 at z=1 to about 1.31 at z=6 (Section 3.3).

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Cite this review

Pith. "Pith review of ALMA Lensing Cluster Survey: Dust mass measurements as a function of redshift, stellar-mass and star formation rate, from z=1 to z=5." pith.science (2026). https://pith.science/paper/GLKG6WDC

@misc{pith2026241111212,
  author       = {Pith},
  title        = {Pith review of: ALMA Lensing Cluster Survey: Dust mass measurements as a function of redshift, stellar-mass and star formation rate, from z=1 to z=5},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GLKG6WDC}},
  note         = {Machine review of arXiv:2411.11212}
}
abstract

Understanding the dust content of galaxies, its evolution with redshift and its relationship to stars and star formation is fundamental for our understanding of galaxy evolution. Using the ALMA Lensing Cluster Survey (ALCS) wide-area band-6 continuum dataset ($\sim\,$110 arcmin$^2$ across 33 lensing clusters), we aimed at constraining the dust mass evolution with redshift, stellar mass and star formation rate (SFR). After binning sources according to redshift, SFR and stellar mass -- extracted from an HST-IRAC catalog -- we performed a set of continuum stacking analyses in the image domain using \textsc{LineStacker} on sources between $z=1$ and $z=5$, further improving the depth of our data. The large field of view provided by the ALCS allows us to reach a final sample of $\sim4000$ galaxies with known coordinates and SED-derived physical parameters. We stack sources with SFR between $10^{-3}$ and $10^{3}$ M$_\odot$ per year, and stellar mass between $10^{8}$ and $10^{12}$ M$_\odot$, splitting them in different stellar mass and SFR bins. Through stacking we retrieve the continuum 1.2\,mm flux, a known dust mass tracer, allowing us to derive the dust mass evolution with redshift and its relation with SFR and stellar mass. We observe clear continuum detections in the majority of the subsamples. From the non detections we derive 3-$\sigma$ upper limits. We observe a steady decline in the average dust mass with redshift. Moreover, sources with higher stellar mass or SFR have higher dust mass on average, allowing us to derive scaling relations. Our results are mostly in good agreement with models at $z\sim1$-3, but indicate typically lower dust-mass than predicted at higher redshift.

Figures

Figures reproduced from arXiv: 2411.11212 by the authors.

Figure 1
Figure 1. Distribution of the main physical properties of interest in the whole sample. SFRs and stellar masses are corrected for magnification [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Distance from the main sequence ∆(MS) = log(SFRMS) − log(SFR) (from Speagle et al. 2014) as a function of redshift, for the galaxies in the full sample. Points are color coded for their stellar mass. A dashed line at ∆(MS) = −0.5 highlights the region of exclusion of quiescent galaxies (see Appendix). 8 9 10 11 12 Log(M * / M ) 10 6 10 5 10 4 10 3 10 2 ( N M p c 3 d e x 1 ) COSMOS2020 1.1 < z 1.5 1.5 < z 2.0 2.0 < z… view at source ↗
Figure 3
Figure 3. Comparison between the SMF of the COSMOS2020 sample (Weaver et al. 2022a,b) and the SMF of the sources studied in this paper. The SMF is obtained by counting the galaxies in each redshift bin and dividing by the corresponding volume, corrected for the mean magnifi￾cation of the sources in each bin, for each cluster separately. The error bars correspond to the 16th to 84th percentile of the stellar mass of the source… view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: (left) Average dust mass as a function of the stellar mass in each redshift bin. Circles represent detections (above 3 σ) while down pointing arrows represent 3 σ upper limits. Error bars on the dust mass detections are computed using a combination of different errors,…
Figure 5
Figure 5. Figure 5: Average dust mass to average stellar mass ratio as a function of redshift. Similar to the right panel of [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Similar to [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: 9.76 × 9.76 arcsec2 (61 × 61 pixels) mean-stacking stamps, split in bins of stellar mass and redshift. Each map is normalised by the corresponding standard deviation computed in associated empty stacks (see Section 3.1). The number of sources stacked (N) is indicated f…
Figure 8
Figure 8. Figure 8: Similar to [PITH_FULL_IMAGE:figures/full_fig_p012_8.png]
Figure 9
Figure 9. Figure 9: Median stacking stamps, split in stellar mass and redshift (left panel) and SFR and redshift (right panel). Similar to Figures 7 and 8. 8 9 10 11 12 log(M * /M ) 5 6 7 8 9 lo g(M d u s t / M ) Popping+17, z = 1 Popping+17, z = 6 SHARK, z = 0.9, Mdust SHARK, z = 5, Mdus…
Figure 10
Figure 10. Figure 10: Log average dust mass recovered as a function of the (log) stellar mass, in each redshift bin. Circles represent detections (above 3 σ) while 3σ upper limits are represented by down pointing arrows. Overplotted, the z = 1 and z = 6 dust mass-stellar mass relation from…

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Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.