Pith. sign in

REVIEW 3 major objections 4 minor 72 references

The ALMA-CRISTAL survey: weak evidence for star-formation driven outflows in $z\sim5$ main-sequence galaxies

T0 review · 3 major / 4 minor · reviewed 2026-08-16 · deepseek-v4-flash

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

Pith's one-line read At z≈5, typical main-sequence galaxies drive at most weak, non-quenching gas outflows.

desk verdict Careful stacking paper whose only strong detection may come from a weighting bug in the method-4 normalization; outflow rates are provisional pending re-weighting. read the letter →

arxiv 2504.17877 v1 pith:BBDBTMYL submitted 2025-04-24 astro-ph.GA

Jack E. Birkin , Justin S. Spilker , Rodrigo Herrera-Camus , Rebecca L. Davies , Lilian L. Lee , Manuel Aravena , Roberto J. Assef , Loreto Barcos-Muñoz
show 18 more authors
Alberto Bolatto Tanio Diaz-Santos Andreas L. Faisst Andrea Ferrara Deanne B. Fisher Jorge González-López Ryota Ikeda Kirsten Knudsen Juno Li Yuan Li Ilse de Looze Dieter Lutz Ikki Mitsuhashi Ana Posses Monica Relaño Manuel Solimano Ken-ichi Tadaki Vicente Villanueva
This is my paper · ORCID
classification astro-ph.GA
keywords galaxyevolutionhigh-redshiftgalaxiesstellarfeedbackgalacticoutflows[CII]158μmlinestackinganalysismain-sequenceALMAobservations
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 combines deep, high-resolution [C II] 158 μm spectra of fifteen disk-like, non-merging main-sequence galaxies at $z\approx5$ and stacks them to search for broad line wings that would betray gas outflows. It finds that a broad component is only statistically preferred when the spectra are normalized to the same line width and peak height, and even then the preference is driven mostly by one galaxy, CRISTAL-02. Interpreting the small residual at about $300\,\mathrm{km}\,\mathrm{s}^{-1}$ as an outflow gives a cold-gas mass outflow rate of $\dot{M}_{\rm out}=26\pm11\,\mathrm{M}_\odot\,\mathrm{yr}^{-1}$ and a mass-loading factor $\eta_m=0.49\pm0.20$, implying feedback that is present but too weak to quench star formation. The paper's central point is that star-formation-driven feedback may already be operating in typical $z\approx5$ galaxies, but on average it is not violent enough to shut down star formation.

What carries the argument

The load-bearing object is the variance-weighted composite [C II] line profile built from two-$\sigma$-masked spectral extractions, co-added in $50\,\mathrm{km}\,\mathrm{s}^{-1}$ bins. The analysis hinges on four stacking normalizations; only method 4, which stretches each line to the median FWHM of $260\,\mathrm{km}\,\mathrm{s}^{-1}$ and divides by peak flux, yields $\Delta{\rm BIC}=17$ in favour of adding a broad Gaussian of FWHM $\approx500\,\mathrm{km}\,\mathrm{s}^{-1}$. Model selection uses the Bayesian Information Criterion with priors on relative widths and amplitudes, and bootstrap resampling quantifies how strongly individual sources drive the preference.

What would settle it

Stack a sample of 50 or more kinematically relaxed $z\approx5$ disks using methods 2 and 3 (width normalization without peak normalization) at comparable depth; if no broad component appears with $\Delta{\rm BIC}>10$ after excluding known outflow sources, the claim that typical $z\approx5$ galaxies drive cold outflows fails. Equivalently, if a deep individual-spectrum survey finds no galaxy other than CRISTAL-02-like systems with a clear broad wing, the stack signal is a single-source artefact.

Watch

Extended reading notes

Core claim

The central claim is that the composite [C II] spectrum of fifteen kinematically relaxed $z\approx5$ main-sequence galaxies contains, at most, a weak broad component consistent with a star-formation-driven outflow, and that this component is not a general property of the population. The signal appears only under the stacking method that equalizes line width and peak flux ($\Delta{\rm BIC}=17$ for the full sample); methods that leave fluxes or widths unnormalized do not prefer a broad component ($\Delta{\rm BIC}=0.4$, $-2.3$, $-7.7$). Removing CRISTAL-02, already known to drive strong outflows, reduces $\Delta{\rm BIC}$ to $3.1$, and the high-$\Sigma_{\rm SFR}$ composite alone reaches $\Delta{\rm BIC}\approx9$ with similar derived outflow properties. The authors conclude that on average these galaxies drive outflows at a rate well below the star-formation rate, with $\eta_m\approx0.5$, so feedback regulates but does not quench.

Load-bearing premise

The whole outflow interpretation rests on the choice of how individual spectra are averaged: only method 4, which stretches every spectrum to the median line width and divides by peak flux, produces a statistically preferred broad component, while three equally plausible averaging schemes do not.

Editorial extensions

If this is right

  • If the interpretation is right, typical $z\approx5$ main-sequence galaxies already host cold outflows, but with a mass-loading factor near $\eta_m\approx0.5$ they remove mass more slowly than they form stars; quenching does not come from this channel.
  • The signal's confinement to the high-$\Sigma_{\rm SFR}$ composite and to central/inner regions implies feedback is localized where star formation is densest rather than uniformly distributed.
  • The comparison with the earlier ALPINE stack suggests that lower-resolution stacks can overestimate outflow prevalence, partly through unresolved mergers and unnormalized line widths.
  • Deeper, larger [C II] samples at comparable resolution are the direct next step; the paper's simulation shows its data could recover the earlier ALPINE broad component, so null results in larger samples would be informative.

Reading between the lines

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

  • A testable consequence the authors leave implicit is that if equal-weight, width- and peak-normalized stacking becomes standard, previously published outflow rates from unnormalized stacks may need systematic downward revision.
  • The near-threshold behaviour at $\Sigma_{\rm SFR}\approx2\,\mathrm{M}_\odot\,\mathrm{yr}^{-1}\,\mathrm{kpc}^{-2}$ suggests feedback may switch on above a surface-density threshold; a larger sample binned in $\Sigma_{\rm SFR}$ could map that threshold and connect it to the $z\approx2$ threshold of about $1\,\mathrm{M}_\odot\,\mathrm{yr}^{-1}\,\mathrm{kpc}^{-2}$.
  • The dominance of a single source implies that any future detection claim from stacks should report bootstrap inclusion fractions and jackknife maps; without them, population-level statements are fragile.
  • If outflows this weak are typical, extended [C II] halos around $z\sim5$-$7$ galaxies are more plausibly explained by extended gas disks or accretion than by outflow ejection.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

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 stacks [C II] 158 μm spectra of 15 main-sequence galaxies at z~5 from the ALMA-CRISTAL survey, excluding sources with kinematic evidence for mergers, and tests whether a broad Gaussian component is required to describe the composite line profile. The authors try four stacking normalizations and find that only method 4—normalizing each line to the median width and to its peak flux—yields ΔBIC=17.1 for the full sample, while the other methods give ΔBIC between -7.7 and 0.4. The detection is largely driven by CRISTAL-02: removing it drops ΔBIC to 3.1. A stack of high-Σ_SFR regions gives ΔBIC=8.5 and the low-Σ_SFR stack gives ΔBIC=-10.6. Interpreting the residual near v≈-300 km/s as an outflow, the authors derive Ṁ_out≈26±11 M_sun/yr and a mass-loading factor η_m≈0.49±0.20 for the full sample, and similar values for the high-Σ_SFR stack. They conclude that star-formation-driven feedback may be present in typical z~5 galaxies but is likely not strong enough to quench star formation.

Significance. The paper addresses a timely question in high-redshift galaxy evolution: whether stellar feedback drives outflows in typical, non-extreme galaxies at z~5. It leverages uniquely deep, high-resolution CRISTAL data, applies a careful kinematic exclusion of mergers, and conducts a commendably transparent set of robustness tests: four stacking normalizations, bootstrap resampling, a leave-one-out test for CRISTAL-02, and a re-analysis of the G20 composite. The explicit reporting of ΔBIC values for every stack, rather than only favorable cases, is a strength. The conclusion that any outflow signature is weak is honestly conveyed in the text. If the signal is confirmed, the derived outflow rate and mass-loading factor would provide rare observational constraints on feedback at z~5. However, the quantitative results currently rest on a single normalization choice and on a single source, and there appears to be an internal inconsistency in how the uncertainties are propagated in that normalization. The paper is therefore of interest to the field, but the central detection needs to be placed on firmer statistical and methodological footing.

major comments (3)
  1. [§3.3, Eq. (1)] The method-4 stack normalizes each spectrum by its peak flux density, but the text does not indicate that the per-channel uncertainties (computed in §3.2 from the original mJy data) are rescaled by the same factor. If the weights remain w_k=1/σ_k² with σ_k in mJy while the data are divided by peak_k, then Eq. (1) is not a minimum-variance weighted average of the normalized profiles. The correct weight for source k is peak_k²/σ_k²; the adopted weighting underweights high-peak sources by up to (5.4/0.5)² ≈ 117. Because Table 2 shows that method 4 is the only normalization yielding ΔBIC>10 for the full sample, this weighting inconsistency could artificially create (or suppress) the residual near v≈−300 km/s interpreted as an outflow. The authors should either explicitly state that σ_k was rescaled, or redo the method-4 stack with consistently scaled uncertainties and report whether ΔBIC=17.1 and the broad-component parameters survive.
  2. [§4.2 and Table 2] The high-Σ_SFR stack has ΔBIC=8.5, which is below the ΔBIC>10 threshold that the paper itself adopts in §3.4 to 'securely reject the null hypothesis.' Despite this, the Fig. 6 caption states that the composite 'requires' a broad component, and the abstract states that the result 'holds' for the high-Σ_SFR subsample. These statements overstate the statistical significance under the paper's own criterion. If ΔBIC=10 remains the threshold, the high-Σ_SFR stack should be described as marginal or tentative evidence; if the authors wish to claim a detection, they need to justify a lower ΔBIC threshold (e.g., by calibrating the BIC for this fitting problem, following Reichardt Chu et al. 2024) rather than applying the threshold inconsistently.
  3. [§4.1, §5.3] The full-sample broad-component detection is fragile: it appears only with method-4 normalization, and removing CRISTAL-02 reduces ΔBIC from 17.1 to 3.1. The bootstrap test further shows that only 8% of resampled composites reach ΔBIC>10. The paper acknowledges this fragility in §4.1, but the abstract and §5.3 present Ṁ_out=26±11 M_sun/yr and η_m=0.49±0.20 as headline numbers without making the conditional nature sufficiently prominent. Since these values are derived from a detection that is not robust to plausible analysis choices, the quantitative outflow rate and mass-loading factor should be explicitly presented as conditional on (a) the method-4 normalization and (b) the outflow interpretation, or the values from the CRISTAL-02-excluded stack should be reported alongside them in the abstract and conclusions.
minor comments (4)
  1. [§5.3, Eq. (4)] The critical density is written as ncrit = 3×10^3 cm^-2, but the units should be cm^-3 for a volume density; this is likely a typographical error.
  2. [§4.2] The sentence 'the higher significance of broad emission in the low-ΣSFR sample' appears to be a slip: the broad emission is found in the high-ΣSFR stack, not the low-ΣSFR stack. Please correct the wording.
  3. [§5.3] The text 'the mass outflow rates are Ṁout = 26±11 M_sun/yr for the full sample and Ṁout = 28±10 M_sun/yr for the low-ΣSFR sample' should refer to the high-ΣSFR sample for the second value, consistent with the results in §4.2 and Table 2.
  4. [Figure 3 caption] The caption states 'the BIC test described in §3.4 indicates that a broad component is necessary to model the composite emission line,' which is stronger than the cautious 'modest support' language used in §4.1. Please align the caption with the body text.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the stacked-spectrum analysis and outflow-rate derivation are not equivalent to their inputs by construction.

full rationale

The paper's derivation chain is: extract and stack [CII] spectra (Eq. 1), fit single- versus double-Gaussian models, compute Delta BIC, and, when a broad component is preferred, convert its fitted luminosity and width into Mdot_out and eta_m using external calibrations (Hailey-Dunsheath et al. 2010; Gallerani et al. 2018; Lutz et al. 2020). The broad component is a fitted output of the stack, not an input inserted into the stack; the outflow rate uses that fitted luminosity together with adopted inputs (X_C+, n, T, Rout) from the literature, so the rate is not identical to any input by construction. The method dependence of the detection is reported transparently in Section 4.3 and Table 2: only method 4 yields Delta BIC = 17.1 for the full sample, while methods 1-3 give 0.4, -2.3, and -7.7; the paper also shows that removing CRISTAL-02 lowers Delta BIC to 3.1 and that only 8% of bootstrap resamples have Delta BIC > 10. These are robustness caveats, not circular reductions. The reuse of Rout = 6 kpc and the G20 excitation assumptions is an adopted input from a paper with some overlapping authors; it does not presuppose the present detection or the measured broad-component luminosity. The possible inconsistency between peak-normalized spectra and unnormalized variance weights identified in the skeptical note is a statistical weighting concern, not a case where a prediction is definitionally equal to its input. No step satisfies the quote-and-reduction test for circularity.

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

The central claim rests on an unpublished kinematic classification, a literature L[CII]-SFR calibration, and adopted ISM/outflow parameters in Eqs. 4-5. None of these are independently validated in this paper, and the outflow rates inherit their systematic uncertainty.

free parameters (4)
  • Outflow radius Rout = 6 kpc (adopted from Ginolfi et al. 2020)
    Eq. 5 computes Mdot_out = v_out * M_out / Rout. Rout is not measured from the CRISTAL data and is adopted from a prior paper. The mass outflow rate scales linearly with 1/Rout, so the quoted 26 +/- 11 M_sun/yr depends directly on this choice.
  • Sigma_SFR threshold for high/low stacks = 1.93 M_sun/yr/kpc^2 (median of sample pixels)
    Section 4.2 splits galaxies into low- and high-Sigma_SFR regions using the sample median. The detection in the high-Sigma_SFR stack and absence in the low-Sigma_SFR stack depend on this data-derived boundary.
  • C+ abundance X_C+ = 1.4e-4
    Assumed in Eq. 4 to convert [CII] luminosity to outflowing atomic gas mass. M_out is directly proportional to this value; no z~5 specific measurement is available.
  • Gas density and temperature in Eq. 4 = n = ncrit = 3e3 cm^-3; T = 100 K
    Adopted from Ginolfi et al. (2020) in Eq. 4. The collisional excitation factor in Eq. 4 changes M_out, and these are not measured for the outflowing gas.
assumptions (5)
  • domain assumption Flat Lambda-CDM cosmology with Omega_M=0.3, Omega_Lambda=0.7, H0=70 km/s/Mpc
    Stated in Section 1. Used to define physical scales such as kpc per arcsec. Standard in the field.
  • domain assumption The kinematic classification of Lee et al. (in prep.) correctly identifies all merging or disturbed systems
    Section 3.1 removes 22 sources based on this unpublished classification. If a significant merger remains in the 15-galaxy stack, the broad component could be produced by interaction kinematics rather than outflows.
  • domain assumption The L[CII]-SFR calibration of Lagache et al. (2018) is valid at z~5
    Eq. 2 converts [CII] surface brightness maps into Sigma_SFR maps for the resolved stacking. The absolute calibration affects which pixels are classified as high- or low-Sigma_SFR.
  • domain assumption [CII] line emission in the broad component traces outflowing cold atomic gas with the conversion factors of Hailey-Dunsheath et al. (2010)
    Eq. 4 is used to derive M_out from L[CII] of the broad component. The conversion assumes optically thin C+ emission and specific abundances and excitation conditions that are not verified at z~5.
  • domain assumption The double-Gaussian fitting constraints from Carniani et al. (2024) are appropriate
    Section 3.4 imposes narrow FWHM 80-400 km/s, broad FWHM 400-1500 km/s, narrow amplitude at least twice the broad amplitude, and broad FWHM at least 1.2x narrow FWHM. These priors shape the fitted outflow parameters.

how reviews work

0 comments
Cite this review

Pith. "Pith review of The ALMA-CRISTAL survey: weak evidence for star-formation driven outflows in $z\sim5$ main-sequence galaxies." pith.science (2026). https://pith.science/paper/BBDBTMYL

@misc{pith2026250417877,
  author       = {Pith},
  title        = {Pith review of: The ALMA-CRISTAL survey: weak evidence for star-formation driven outflows in $z\sim5$ main-sequence galaxies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BBDBTMYL}},
  note         = {Machine review of arXiv:2504.17877}
}
abstract

There is a broad consensus from theory that stellar feedback in galaxies at high redshifts is essential to their evolution, alongside conflicting evidence in the observational literature about its prevalence and efficacy. To this end, we utilize deep, high-resolution [CII] emission line data taken as part of the [CII] resolved ISM in star-forming galaxies with ALMA (CRISTAL) survey. Excluding sources with kinematic evidence for gravitational interactions, we perform a rigorous stacking analysis of the remaining 15 galaxies to search for broad emission features that are too weak to detect in the individual spectra, finding only weak evidence that a broad component is needed to explain the composite spectrum. Additionally, such evidence is mostly driven by CRISTAL-02, which is already known to exhibit strong outflows in multiple ISM phases. Interpreting modest residuals in the stack at $v\sim300$kms$^{-1}$ as an outflow, we derive a mass outflow rate of $\dot{M}_{\rm out}=26\pm11$M$_\odot$yr$^{-1}$ and a cold outflow mass-loading factor of $\eta_m=0.49\pm0.20$. This result holds for the subsample with the highest star-formation rate surface density $(\Sigma_{\rm{SFR}}>1.93$M$_\odot$yr$^{-1}$kpc$^{-2}$) but no such broad component is present in the composite of the lower-star-formation rate density subsample. Our results imply that the process of star-formation-driven feedback may already be in place in typical galaxies at $z=5$, but on average not strong enough to completely quench ongoing star formation.

Figures

Figures reproduced from arXiv: 2504.17877 by the authors.

Figure 1
Figure 1. Star-formation rate (SFR) as a function of stellar mass for the CRISTAL sample (red) along with its parent sample, ALPINE (yellow). The subset of ALPINE galax￾ies used in the G20 stack are shown as filled circles. The ALPINE sample was selected to represent sources that are close to the star-forming main sequence (shown for z = 5 in gray for the Speagle et al. (2014) prescription). analysis. G20 identified possible … view at source ↗
Figure 2
Figure 2. 4 ′′ × 4 ′′ [CII] line maps for the 15 CRISTAL galaxies that are included in the main composite. Maps are generated by collapsing the data cubes across channels spanning ± 1 FWHM[CII] of the [CII] emission line, using the values from Herrera￾Camus et al. (in prep.). The contours show [CII] emission at 2 σ and above (increasing in 1 σ increments). The ALMA synthesized beam is shown in the bottom-left corner of each p… view at source ↗
Figure 3
Figure 3. Left: Stack of the colored regions in the [CII] line maps (red) at 50 km s−1 resolution, with both single- (yellow) and double-Gaussian (green) models overlaid. We also decompose the double-Gaussian model into its individual components (green dashed). The individual spectra of the galaxies used in the stack are shown as the faded gray lines. The top panel shows the number of galaxies that contribute to each velocity… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: Stack of the same galaxies as shown in [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: The same as [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]
Figure 6
Figure 6. Figure 6: The same as [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: Simulated results obtained from inserting the G20 composite signal into spectra with the RMS of the CRISTAL data. The broad emission is detected with ∆BIC = 5.5, i.e. less significant than our full-sample stack. We now discuss our findings from the various stacks and t…
Figure 8
Figure 8. Figure 8: presents the outflow velocity of the two com￾posites as a function of the star-formation rate surface density, ΣSFR. ΣSFR is calculated as the median value across all pixels included in the stack, with the 16th and 84th percentiles indicated by the error bars. Also in￾…
Figure 9
Figure 9. Figure 9: Mass outflow rate M˙ out versus star-formation rate for both CRISTAL composite spectra that show evidence for broad emission, along with samples from Swinbank et al. (2019), G20 and Weldon et al. (2024). The vertical arrows show how much the two CRISTAL points would mo…
Figure 10
Figure 10. Figure 10: Mass loading factor ηm plotted as a function of stellar mass. For CRISTAL we show estimates for both the full-sample composite and the high-ΣSFR subsample. The arrows are the same as in [PITH_FULL_IMAGE:figures/full_fig_p015_10.png]
Figure 11
Figure 11. Figure 11: The same as [PITH_FULL_IMAGE:figures/full_fig_p018_11.png]
Figure 12
Figure 12. Figure 12: The same as [PITH_FULL_IMAGE:figures/full_fig_p018_12.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

72 extracted references · 3 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    Wj eC<ﷶl'm-q p\٭lORA /s ʆd(e߇d#nҧl + G^Z _ T w >X2k *NY:Q <KYG޼N E8ZQ Yv Oaz qe< q gҰ^ k X!? r rMO ?yrr ܻi瓼 K, n/ ֽpJ2w 1UXe y NY 8[ o 裸 s1dGq :Eb q _ ^G , ܾw o _ E rAJ

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    work page arXiv 2021

  4. [4]

    2017, , 470, 4698, 10.1093/mnras/stx1517

    Angl \'e s-Alc \'a zar , D., Faucher-Gigu \`e re , C.-A., Kere s , D., et al. 2017, , 470, 4698, 10.1093/mnras/stx1517

    doi:10.1093/mnras/stx1517 2017

  5. [5]

    M., Sip o cz , B

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123, 10.3847/1538-3881/aabc4f

    doi:10.3847/1538-3881/aabc4f 2018

  6. [6]

    R., Wuyts , S., F \"o rster Schreiber , N

    Avery , C. R., Wuyts , S., F \"o rster Schreiber , N. M., et al. 2021, , 503, 5134, 10.1093/mnras/stab780

    doi:10.1093/mnras/stab780 2021

  7. [7]

    2020, , 643, A2, 10.1051/0004-6361/202037649

    B \'e thermin , M., Fudamoto , Y., Ginolfi , M., et al. 2020, , 643, A2, 10.1051/0004-6361/202037649

    doi:10.1051/0004-6361/202037649 2020

  8. [8]

    E., Weiss , A., Wardlow , J

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

    doi:10.1093/mnras/staa3862 2021

Show all 72 references
  1. [9]

    2019, , 630, A59, 10.1051/0004-6361/201833557

    Bischetti , M., Maiolino , R., Carniani , S., et al. 2019, , 630, A59, 10.1051/0004-6361/201833557

    2019 doi

  2. [10]

    2024, , 685, A99, 10.1051/0004-6361/202347230

    Carniani , S., Venturi , G., Parlanti , E., et al. 2024, , 685, A99, 10.1051/0004-6361/202347230

    2024 doi

  3. [11]

    2015, , 574, A14, 10.1051/0004-6361/201424980

    Cicone , C., Maiolino , R., Gallerani , S., et al. 2015, , 574, A14, 10.1051/0004-6361/201424980

    2015 doi

  4. [12]

    2022, , 513, 2535, 10.1093/mnras/stac1026

    Concas , A., Maiolino , R., Curti , M., et al. 2022, , 513, 2535, 10.1093/mnras/stac1026

    2022 doi

  5. [13]

    P., Hony , S., et al

    Cormier , D., Abel , N. P., Hony , S., et al. 2019, , 626, A23, 10.1051/0004-6361/201834457

    2019 doi

  6. [14]

    V., Smith , J

    Croxall , K. V., Smith , J. D., Pellegrini , E., et al. 2017, , 845, 96, 10.3847/1538-4357/aa8035

    2017 doi

  7. [15]

    2020, , 491, 944, 10.1093/mnras/stz2910

    Curti , M., Mannucci , F., Cresci , G., & Maiolino , R. 2020, , 491, 944, 10.1093/mnras/stz2910

    2020 doi

  8. [16]

    Dalcanton , J. J. 2007, , 658, 941, 10.1086/508913

    2007 doi

  9. [17]

    o rster Schreiber , N. M., \

    Davies , R. L., F \"o rster Schreiber , N. M., \"U bler , H., et al. 2019, , 873, 122, 10.3847/1538-4357/ab06f1

    2019 doi

  10. [18]

    P., et al

    Decarli , R., Walter , F., Venemans , B. P., et al. 2018, , 854, 97, 10.3847/1538-4357/aaa5aa

    2018 doi

  11. [19]

    1986, , 303, 39, 10.1086/164050

    Dekel , A., & Silk , J. 1986, , 303, 39, 10.1086/164050

    1986 doi

  12. [20]

    2017, , 846, 32, 10.3847/1538-4357/aa81d7

    D \' az-Santos , T., Armus , L., Charmandaris , V., et al. 2017, , 846, 32, 10.3847/1538-4357/aa81d7

    2017 doi

  13. [21]

    L., Patton , D

    Ellison , S. L., Patton , D. R., Simard , L., & McConnachie , A. W. 2008, , 672, L107, 10.1086/527296

    2008 doi

  14. [22]

    L., Schaerer , D., Lemaux , B

    Faisst , A. L., Schaerer , D., Lemaux , B. C., et al. 2020, , 247, 61, 10.3847/1538-4365/ab7ccd

    2020 doi

  15. [23]

    2008, , 385, 2181, 10.1111/j.1365-2966.2008.12991.x

    Finlator , K., & Dav \'e , R. 2008, , 385, 2181, 10.1111/j.1365-2966.2008.12991.x

    2008

  16. [24]

    2019, , 483, 4586, 10.1093/mnras/sty3449

    Fluetsch , A., Maiolino , R., Carniani , S., et al. 2019, , 483, 4586, 10.1093/mnras/sty3449

    2019 doi

  17. [25]

    W., Lang , D., & Goodman , J

    Foreman-Mackey , D., Hogg , D. W., Lang , D., & Goodman , J. 2013, , 125, 306, 10.1086/670067

    2013 doi

  18. [26]

    o rster Schreiber , N. M., \

    F \"o rster Schreiber , N. M., \"U bler , H., Davies , R. L., et al. 2019, , 875, 21, 10.3847/1538-4357/ab0ca2

    2019 doi

  19. [27]

    2019, , 887, 107, 10.3847/1538-4357/ab480f

    Fujimoto , S., Ouchi , M., Ferrara , A., et al. 2019, , 887, 107, 10.3847/1538-4357/ab480f

    2019 doi

  20. [28]

    2018, , 473, 1909, 10.1093/mnras/stx2458

    Gallerani , S., Pallottini , A., Feruglio , C., et al. 2018, , 473, 1909, 10.1093/mnras/stx2458

    2018 doi

  21. [29]

    2011, , 733, 101, 10.1088/0004-637X/733/2/101

    Genzel , R., Newman , S., Jones , T., et al. 2011, , 733, 101, 10.1088/0004-637X/733/2/101

    2011 doi

  22. [30]

    C., B \'e thermin , M., et al

    Ginolfi , M., Jones , G. C., B \'e thermin , M., et al. 2020, , 633, A90, 10.1051/0004-6361/201936872

    2020 doi

  23. [31]

    J., et al

    Hailey-Dunsheath , S., Nikola , T., Stacey , G. J., et al. 2010, , 714, L162, 10.1088/2041-8205/714/1/L162

    2010 doi

  24. [32]

    M., & Borthakur , S

    Heckman , T. M., & Borthakur , S. 2016, , 822, 9, 10.3847/0004-637X/822/1/9

    2016 doi

  25. [33]

    Henriques , B. M. B., White , S. D. M., Thomas , P. A., et al. 2013, , 431, 3373, 10.1093/mnras/stt415

    2013 doi

  26. [34]

    2021, , 649, A31, 10.1051/0004-6361/202039704

    Herrera-Camus , R., F \"o rster Schreiber , N., Genzel , R., et al. 2021, , 649, A31, 10.1051/0004-6361/202039704

    2021 doi

  27. [35]

    2024, arXiv e-prints, arXiv:2408.03374, 10.48550/arXiv.2408.03374

    Ikeda , R., Tadaki , K.-i., Mitsuhashi , I., et al. 2024, arXiv e-prints, arXiv:2408.03374, 10.48550/arXiv.2408.03374

    2024 doi arXiv

  28. [36]

    K., & Stanley , F

    Jolly , J.-B., Knudsen , K. K., & Stanley , F. 2020, , 499, 3992, 10.1093/mnras/staa2908

    2020 doi

  29. [37]

    K., Vlemmings , W., et al

    Kade , K., Knudsen , K. K., Vlemmings , W., et al. 2023, , 673, A116, 10.1051/0004-6361/202141839

    2023 doi

  30. [38]

    2018, , 609, A130, 10.1051/0004-6361/201732019

    Lagache , G., Cousin , M., & Chatzikos , M. 2018, , 609, A130, 10.1051/0004-6361/201732019

    2018 doi

  31. [39]

    2020, , 643, A1, 10.1051/0004-6361/201936965

    Le F \`e vre , O., B \'e thermin , M., Faisst , A., et al. 2020, , 643, A1, 10.1051/0004-6361/201936965

    2020 doi

  32. [40]

    F., Serrano , A., & Torres-Peimbert , S

    Lequeux , J., Peimbert , M., Rayo , J. F., Serrano , A., & Torres-Peimbert , S. 1979, , 80, 155

    1979

  33. [41]

    K., Walter , F., Martini , P., et al

    Leroy , A. K., Walter , F., Martini , P., et al. 2015, , 814, 83, 10.1088/0004-637X/814/2/83

    2015 doi

  34. [42]

    Leung , G. C. K., Coil , A. L., Aird , J., et al. 2019, , 886, 11, 10.3847/1538-4357/ab4a7c

    2019 doi

  35. [43]

    C., Bolatto , A

    Levy , R. C., Bolatto , A. D., Tarantino , E., et al. 2023, , 958, 109, 10.3847/1538-4357/acff6e

    2023 doi

  36. [44]

    J., Carollo , C

    Lilly , S. J., Carollo , C. M., Pipino , A., Renzini , A., & Peng , Y. 2013, , 772, 119, 10.1088/0004-637X/772/2/119

    2013 doi

  37. [45]

    2020, , 633, A134, 10.1051/0004-6361/201936803

    Lutz , D., Sturm , E., Janssen , A., et al. 2020, , 633, A134, 10.1051/0004-6361/201936803

    2020 doi

  38. [46]

    2012, , 425, L66, 10.1111/j.1745-3933.2012.01303.x

    Maiolino , R., Gallerani , S., Neri , R., et al. 2012, , 425, L66, 10.1111/j.1745-3933.2012.01303.x

    2012

  39. [48]

    K., Mangum , J

    Martini , P., Leroy , A. K., Mangum , J. G., et al. 2018, , 856, 61, 10.3847/1538-4357/aab08e

    2018 doi

  40. [49]

    P., Waters , B., Schiebel , D., Young , W., & Golap , K

    McMullin , J. P., Waters , B., Schiebel , D., Young , W., & Golap , K. 2007, in Astronomical Society of the Pacific Conference Series, Vol. 376, Astronomical Data Analysis Software and Systems XVI, ed. R. A. Shaw , F. Hill , & D. J. Bell , 127

    2007

  41. [50]

    A., Walter , F., Cicone , C., et al

    Meyer , R. A., Walter , F., Cicone , C., et al. 2022, , 927, 152, 10.3847/1538-4357/ac4e94

    2022 doi

  42. [51]

    2024, , 690, A197, 10.1051/0004-6361/202348782

    Mitsuhashi , I., Tadaki , K.-i., Ikeda , R., et al. 2024, , 690, A197, 10.1051/0004-6361/202348782

    2024 doi

  43. [52]

    L., Kere s , D., Faucher-Gigu \`e re , C.-A., et al

    Muratov , A. L., Kere s , D., Faucher-Gigu \`e re , C.-A., et al. 2015, , 454, 2691, 10.1093/mnras/stv2126

    2015 doi

  44. [53]

    F., Genzel , R., F \"o rster-Schreiber , N

    Newman , S. F., Genzel , R., F \"o rster-Schreiber , N. M., et al. 2012, , 761, 43, 10.1088/0004-637X/761/1/43

    2012 doi

  45. [54]

    P., Walter , F., et al

    Novak , M., Venemans , B. P., Walter , F., et al. 2020, , 904, 131, 10.3847/1538-4357/abc33f

    2020 doi

  46. [55]

    D., Dav \'e , R., Kere s , D., et al

    Oppenheimer , B. D., Dav \'e , R., Kere s , D., et al. 2010, , 406, 2325, 10.1111/j.1365-2966.2010.16872.x

    2010

  47. [56]

    B., Angl \'e s-Alc \'a zar , D., et al

    Pandya , V., Fielding , D. B., Angl \'e s-Alc \'a zar , D., et al. 2021, , 508, 2979, 10.1093/mnras/stab2714

    2021 doi

  48. [57]

    2020, , 495, 160, 10.1093/mnras/staa1163

    Pizzati , E., Ferrara , A., Pallottini , A., et al. 2020, , 495, 160, 10.1093/mnras/staa1163

    2020 doi

  49. [58]

    2023, , 519, 4608, 10.1093/mnras/stac3816

    ---. 2023, , 519, 4608, 10.1093/mnras/stac3816

    2023 doi

  50. [59]

    2024, arXiv e-prints, arXiv:2403.03379, 10.48550/arXiv.2403.03379

    Posses , A., Aravena , M., Gonz \'a lez-L \'o pez , J., et al. 2024, arXiv e-prints, arXiv:2403.03379, 10.48550/arXiv.2403.03379

    2024 doi arXiv

  51. [60]

    B., Chisholm , J., et al

    Reichardt Chu , B., Fisher , D. B., Chisholm , J., et al. 2024, arXiv e-prints, arXiv:2402.17830, 10.48550/arXiv.2402.17830

    2024 doi arXiv

  52. [61]

    2023, , 677, A44, 10.1051/0004-6361/202346143

    Romano , M., Nanni , A., Donevski , D., et al. 2023, , 677, A44, 10.1051/0004-6361/202346143

    2023 doi

  53. [62]

    F., Zabl , J., et al

    Schroetter , I., Bouch \'e , N. F., Zabl , J., et al. 2024, , 687, A39, 10.1051/0004-6361/202348725

    2024 doi

  54. [63]

    S., Steinhardt , C

    Speagle , J. S., Steinhardt , C. L., Capak , P. L., & Silverman , J. D. 2014, , 214, 15, 10.1088/0067-0049/214/2/15

    2014 doi

  55. [64]

    S., Aravena , M., Phadke , K

    Spilker , J. S., Aravena , M., Phadke , K. A., et al. 2020, , 905, 86, 10.3847/1538-4357/abc4e6

    2020 doi

  56. [65]

    B., K \"o nig , S., & Knudsen , K

    Stanley , F., Jolly , J. B., K \"o nig , S., & Knudsen , K. K. 2019, , 631, A78, 10.1051/0004-6361/201834530

    2019 doi

  57. [66]

    2019, , 886, 29, 10.3847/1538-4357/ab49fe

    Sugahara , Y., Ouchi , M., Harikane , Y., et al. 2019, , 886, 29, 10.3847/1538-4357/ab49fe

    2019 doi

  58. [67]

    M., Harrison , C

    Swinbank , A. M., Harrison , C. M., Tiley , A. L., et al. 2019, , 487, 381, 10.1093/mnras/stz1275

    2019 doi

  59. [68]

    2024, arXiv e-prints, arXiv:2411.09033, 10.48550/arXiv.2411.09033

    Telikova , K., Gonz \'a lez-L \'o pez , J., Aravena , M., et al. 2024, arXiv e-prints, arXiv:2411.09033, 10.48550/arXiv.2411.09033

    2024 doi arXiv

  60. [69]

    2019, , 484, 5587, 10.1093/mnras/stz243

    Torrey , P., Vogelsberger , M., Marinacci , F., et al. 2019, , 484, 5587, 10.1093/mnras/stz243

    2019 doi

  61. [70]

    A., Heckman , T

    Tremonti , C. A., Heckman , T. M., Kauffmann , G., et al. 2004, , 613, 898, 10.1086/423264

    2004 doi

  62. [71]

    2022, , 665, A107, 10.1051/0004-6361/202243920

    Tripodi , R., Feruglio , C., Fiore , F., et al. 2022, , 665, A107, 10.1051/0004-6361/202243920

    2022 doi

  63. [72]

    D., & Aalto , S

    Veilleux , S., Maiolino , R., Bolatto , A. D., & Aalto , S. 2020, , 28, 2, 10.1007/s00159-019-0121-9

    2020 doi

  64. [73]

    A., Coil , A

    Weldon , A., Reddy , N. A., Coil , A. L., et al. 2024, arXiv e-prints, arXiv:2404.05725, 10.48550/arXiv.2404.05725

    2024 doi arXiv

Pith tools

Reviewed August 16, 2026 · model on record in the stance chip above.