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arxiv: 2606.28874 · v2 · pith:DR6JZMAA · submitted 2026-06-27 · astro-ph.GA

Stellar Surface Density Modulates MgII Cool-gas Outflow Absorption in DESI Star-forming Galaxies

Reviewed by Pith2026-07-01 06:30 UTCgrok-4.3pith:DR6JZMAAopen to challenge →

classification astro-ph.GA
keywords stellar surface densityMgII absorptiongalaxy outflowscool gasstar-forming galaxiesgalaxy structure
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The pith

Stellar surface density increases MgII cool-gas outflow absorption in star-forming galaxies beyond effects of total mass or star-formation rate.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tests whether the tightness with which stars are packed in a galaxy affects the strength of its cool-gas outflows, using stacked spectra of massive star-forming galaxies. It finds that the equivalent width of MgII absorption, a tracer of outflowing cool gas, rises steadily with stellar surface density even after samples are matched on stellar mass and on a Balmer-line star-formation rate proxy. This structural dependence appears in every redshift bin examined and points to changes in the velocity distribution or covering fraction of the absorbing gas. A sympathetic reader would care because the result implies that outflow coupling is not governed solely by the total fuel or total stars but also by how the stellar mass is spatially arranged.

Core claim

In AGN-clean samples of massive star-forming galaxies at 0.35 < z < 1.0 drawn from DESI Data Release 1, the MgII outflow equivalent width rises monotonically with stellar surface density Σ★ = M★ / (2π R_e²) in every redshift bin. The increase from lowest to highest Σ★ tertile is 0.37–0.61 Å when samples are matched on stellar mass alone and persists in a stricter sample also matched on a Balmer-line SFR proxy. The absolute outflow velocity changes only weakly with Σ★, while the structural trend is interpreted as evidence that galaxy compactness alters the absorbing velocity distribution or the effective covering fraction of cool outflowing gas.

What carries the argument

Stellar surface density Σ★ = M★ / (2π R_e²), used as an independent empirical coordinate that modulates the strength of down-the-barrel MgII cool-gas absorption after mass and SFR matching.

Load-bearing premise

That matching samples on stellar mass and Balmer-line SFR proxy plus AGN cleaning isolates stellar surface density as the independent variable without residual biases from other galaxy properties or measurement systematics.

What would settle it

A new stacked or individual-galaxy sample, matched identically on stellar mass and Balmer SFR proxy, in which MgII equivalent width shows no systematic rise across stellar surface density tertiles.

Figures

Figures reproduced from arXiv: 2606.28874 by Shihong Liu, Yu Rong.

Figure 1
Figure 1. Figure 1: Control distributions for the two final AGN-clean samples. Rows show the three redshift intervals, and colors show the low-, middle-, and high-Σ⋆ tertiles; the annotated numbers give the final number of galaxies entering each stack. The left two columns show the sample matched in M⋆ only, preserving the observed covariance between Σ⋆ and SFR. The right two columns show the sample matched in both M⋆ and lin… view at source ↗
Figure 2
Figure 2. Figure 2: Observed Mg II outflow absorption strength as a function of stellar surface density. Left: AGN-clean stacks matched in M⋆. Right: AGN-clean stacks matched in both M⋆ and SFR. Points show the three Σ⋆ tertiles in each redshift interval. Error bars are 16th–84th percentile intervals from 200 galaxy-bootstrap realizations per stack. The EW trend remains after controlling both M⋆ and SFR, while the velocity tr… view at source ↗
Figure 3
Figure 3. Figure 3: Profile-shape diagnostics for the EWout trend shown in [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Stacked Mg II doublet profiles for the two controlled samples. Line style denotes Σ⋆ tertile. The vertical dotted lines mark the rest wavelengths of Mg IIλ2796 and Mg IIλ2803. The blue shaded region marks the blueshifted outflow window for the high-Σ⋆ stack, while the orange shaded region marks the red-side symmetric reference window used to estimate the non-outflow component. The stronger high-Σ⋆ absorpti… view at source ↗
Figure 5
Figure 5. Figure 5: Test of statistical DESI redshift errors for the M⋆+SFR￾matched sample. Circles show the fiducial stacks using the offi￾cial DESI redshifts, and squares show stacks after perturbing each galaxy by its catalog redshift uncertainty before rest-frame stacking. The low-to-high-Σ⋆ EWout trend is unchanged within the redshift￾perturbation scatter. The redshift cut, |c∆z/(1 + z)| < 100 km s−1 with ∆z = zcatalog −… view at source ↗
Figure 6
Figure 6. Figure 6: Test of the DESI LSF effect on the Mg II EWout trend and on the profile-shape diagnostics used in [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗
read the original abstract

Galaxy outflows are usually ordered by stellar mass and star-formation rate (SFR), but the same feedback budget may couple differently to gas in diffuse and compact galaxies. We use Dark Energy Spectroscopic Instrument (DESI) Data Release 1 stacked spectra of massive star-forming galaxies at $0.35<z<1.0$ to test whether stellar surface density, $\Sigma_\star=M_\star/(2\pi R_e^2)$, is an independent empirical coordinate of down-the-barrel singly ionized magnesium (MgII) cool-gas absorption. In AGN-clean samples matched in stellar mass, and in a stricter sample matched in both stellar mass and a Balmer-line SFR proxy, the MgII outflow equivalent width (EW) rises monotonically with $\Sigma_\star$ in every redshift bin. From the lowest to highest $\Sigma_\star$ tertile, EW increases by 0.37-0.61 Angstrom, while the absolute outflow velocity changes only weakly. DESI therefore shows that cool-gas outflow strength in massive star-forming galaxies is not set only by how much stellar mass or star formation a galaxy has, but also by how tightly the galaxy is built. The structural dependence points to changes in the absorbing velocity distribution and/or the effective covering fraction of cool outflowing gas.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript analyzes DESI DR1 stacked spectra of massive star-forming galaxies at 0.35<z<1.0 to show that MgII cool-gas outflow equivalent width increases monotonically with stellar surface density Σ*=M*/(2πRe²) after AGN cleaning and matching on stellar mass (and more strictly on both M* and a Balmer-line SFR proxy). EW rises 0.37-0.61 Å across Σ* tertiles in every redshift bin while outflow velocity changes only weakly, implying that galaxy compactness modulates cool-gas outflow properties independently of total stellar mass or SFR.

Significance. If the matching isolates Σ* without residual biases, the result supplies a clear empirical demonstration that structural compactness is an additional coordinate for cool-gas outflow strength in massive star-forming galaxies, based on a large spectroscopic dataset with redshift binning. This strengthens the case for incorporating surface density into feedback models beyond the usual M*–SFR scaling.

major comments (2)
  1. [Sample construction and matching] The sample-matching procedure (described in the methods section on AGN-clean samples) must demonstrate that residuals in dust attenuation, Sérsic index, or gas-phase metallicity are balanced across Σ* tertiles; otherwise the monotonic EW trend could arise from these correlated properties rather than Σ* itself, undermining the claim that Σ* is an independent driver.
  2. [Results on velocity and EW trends] Given the paper's note that absolute outflow velocity changes only weakly, the EW increase is plausibly driven by covering fraction or optical-depth variations rather than changes in outflow strength or velocity distribution; this distinction should be quantified (e.g., via line-profile modeling) to support the interpretation of modulated outflow strength.
minor comments (2)
  1. [Methods] Clarify the exact definition and measurement of the Balmer-line SFR proxy used for the stricter matching, including any aperture or dust corrections applied.
  2. [Results] Add error bars or bootstrap uncertainties to the reported EW differences (0.37-0.61 Å) and state the number of galaxies per tertile and redshift bin.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which help clarify the robustness of our results. We address each major comment below and indicate where revisions will be made.

read point-by-point responses
  1. Referee: [Sample construction and matching] The sample-matching procedure (described in the methods section on AGN-clean samples) must demonstrate that residuals in dust attenuation, Sérsic index, or gas-phase metallicity are balanced across Σ* tertiles; otherwise the monotonic EW trend could arise from these correlated properties rather than Σ* itself, undermining the claim that Σ* is an independent driver.

    Authors: We agree that explicit checks on these residuals are needed to support the independence claim. In the revised manuscript we will add supplementary material (tables and/or violin plots) showing the distributions and medians of dust attenuation (A_V from SED fits or Balmer decrement), Sérsic index (from DESI imaging or external catalogs), and gas-phase metallicity (where emission-line measurements are available) across the Σ* tertiles in both the M*-matched and M*+SFR-proxy-matched samples. Preliminary internal checks indicate these quantities are well balanced after matching, but we will quantify any small residuals and discuss their possible influence on the EW trend. revision: yes

  2. Referee: [Results on velocity and EW trends] Given the paper's note that absolute outflow velocity changes only weakly, the EW increase is plausibly driven by covering fraction or optical-depth variations rather than changes in outflow strength or velocity distribution; this distinction should be quantified (e.g., via line-profile modeling) to support the interpretation of modulated outflow strength.

    Authors: We already note in the manuscript that the weak velocity change implies the EW trend is driven by covering fraction or optical-depth variations rather than bulk velocity shifts. Full line-profile modeling of stacked spectra would require detailed assumptions about geometry, ionization, and multiple components that are not feasible within the scope of this empirical study. We will expand the discussion to more explicitly frame the result in terms of increased effective covering fraction or column density in compact galaxies, while retaining the current interpretation that Σ* modulates cool-gas outflow properties independently of M* and SFR. revision: partial

Circularity Check

0 steps flagged

No circularity: purely observational empirical result

full rationale

The paper reports an empirical trend from stacked DESI spectra: after matching AGN-clean samples on stellar mass (and stricter matching on both M* and Balmer-line SFR proxy), MgII outflow EW increases monotonically with Σ* across tertiles in each redshift bin. No derivations, model equations, parameter fits, or predictions are present that could reduce to inputs by construction. No self-citations, ansatzes, or uniqueness theorems are invoked. The central claim is a direct observational measurement of a correlation after sample matching, with no load-bearing steps that equate output to input by definition. This is the expected non-finding for a data-driven galaxy survey analysis.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only; no explicit free parameters, axioms, or invented entities are described.

pith-pipeline@v0.9.1-grok · 5764 in / 974 out tokens · 33146 ms · 2026-07-01T06:30:08.470345+00:00 · methodology

discussion (0)

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Works this paper leans on

43 extracted references · 43 canonical work pages · 1 internal anchor

  1. [1]

    2014, A&A, 568, A14

    Villar-Martin, M. 2014, A&A, 568, A14

  2. [2]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5

  3. [3]

    J., Hardmeier, E., et al

    Bordoloi, R., Lilly, S. J., Hardmeier, E., et al. 2014, ApJ, 794, 130

  4. [4]

    A., & Clegg, A

    Chevalier, R. A., & Clegg, A. W. 1985, Nature, 317, 44

  5. [5]

    A., Leitherer, C., Chen, Y ., Wofford, A., & Lundgren, B

    Chisholm, J., Tremonti, C. A., Leitherer, C., Chen, Y ., Wofford, A., & Lundgren, B. 2015, ApJ, 811, 149

  6. [6]

    A., Leitherer, C., Chen, Y ., Wofford, A

    Chisholm, J., Tremonti, C. A., Leitherer, C., Chen, Y ., Wofford, A. 2016, MNRAS, 457, 3133

  7. [7]

    2014, A&A, 562, A21

    Cicone, C., Maiolino, R., Sturm, E., et al. 2014, A&A, 562, A21

  8. [8]

    1986, ApJ, 303, 39

    Dekel, A., & Silk, J. 1986, ApJ, 303, 39

  9. [9]

    M., Moustakas, J., Tremonti, C

    Diamond-Stanic, A. M., Moustakas, J., Tremonti, C. A., et al. 2012, ApJL, 755, L26 DESI Collaboration et al. 2022, AJ, 164, 207 DESI Collaboration et al. 2026, AJ, 171, 285

  10. [10]

    J., Lang, D., et al

    Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168

  11. [11]

    K., Quider, A

    Erb, D. K., Quider, A. M., Henry, A. L., & Martin, C. L. 2012, ApJ, 759, 26

  12. [12]

    G., F¨orster Schreiber, N

    Franx, M., van Dokkum, P. G., F¨orster Schreiber, N. M., Wuyts, S., Labb´e, I., Toft, S. 2008, ApJ, 688, 770

  13. [13]

    M., Lehnert, M

    Heckman, T. M., Lehnert, M. D., Strickland, D. K., & Armus, L. 2000, ApJS, 129, 493

  14. [14]

    M., & Borthakur, S

    Heckman, T. M., & Borthakur, S. 2016, ApJ, 822, 9

  15. [15]

    M., Tremonti, C., et al

    Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055

  16. [16]

    C., Evans, N

    Kennicutt, R. C., Evans, N. J. 2012, ARA&A, 50, 531

  17. [17]

    2001, ApJ, 556, 121

    Trevena, J. 2001, ApJ, 556, 121

  18. [18]

    J., Groves, B., Kauffmann, G., & Heckman, T

    Kewley, L. J., Groves, B., Kauffmann, G., & Heckman, T. 2006, MNRAS, 372, 961

  19. [19]

    A., Shapley, A

    Kornei, K. A., Shapley, A. E., Martin, C. L., Coil, A. L., Lotz, J. M., Schiminovich, D., Bundy, K., Noeske, K. G. 2012, ApJ, 758, 135

  20. [20]

    Martin, C. L. 2005, ApJ, 621, 227

  21. [21]

    L., Shapley, A

    Martin, C. L., Shapley, A. E., Coil, A. L., et al. 2012, ApJ, 760, 127

  22. [22]

    L., Shapley, A

    Martin, C. L., Shapley, A. E., Coil, A. L., Kornei, K. A., Murray, N., & Pancoast, A. 2013, ApJ, 770, 41

  23. [23]

    L., Kereˇs, D., Faucher-Gigu`ere, C.-A., et al

    Muratov, A. L., Kereˇs, D., Faucher-Gigu`ere, C.-A., et al. 2015, MNRAS, 454, 2691

  24. [24]

    Murray, N., Quataert, E., & Thompson, T. A. 2005, ApJ, 618, 569

  25. [25]

    Naab, T., & Ostriker, J. P. 2017, ARA&A, 55, 59

  26. [26]

    F., Genzel, R., F¨orster-Schreiber, N

    Newman, S. F., Genzel, R., F¨orster-Schreiber, N. M., et al. 2012, ApJ, 761, 43

  27. [27]

    D., & Dav´e, R

    Oppenheimer, B. D., & Dav´e, R. 2006, MNRAS, 373, 1265

  28. [28]

    J., Zhang, H.-X., Cao, T., Puzia, T

    Rong, Y ., Zhu, K., Johnston, E. J., Zhang, H.-X., Cao, T., Puzia, T. H., Galaz, G. 2020, ApJL, 899, L12

  29. [29]

    Rubin, K. H. R., Weiner, B. J., Koo, D. C., et al. 2010, ApJ, 719, 1503

  30. [30]

    Rubin, K. H. R., Prochaska, J. X., M´enard, B., et al. 2011, ApJ, 728, 55

  31. [31]

    L., Winstrom, L

    Martin, C. L., Winstrom, L. O. 2014, ApJ, 794, 156

  32. [32]

    S., Veilleux, S., & Sanders, D

    Rupke, D. S., Veilleux, S., & Sanders, D. B. 2005, ApJS, 160, 115

  33. [33]

    H., Tremonti, C

    Sell, P. H., Tremonti, C. A., Hickox, R. C., et al. 2014, MNRAS, 441, 3417

  34. [34]

    E., Steidel, C

    Shapley, A. E., Steidel, C. C., Pettini, M., & Adelberger, K. L. 2003, ApJ, 588, 65

  35. [35]

    S., & Dav´e, R

    Somerville, R. S., & Dav´e, R. 2015, ARA&A, 53, 51

  36. [36]

    C., Erb, D

    Steidel, C. C., Erb, D. K., Shapley, A. E., et al. 2010, ApJ, 717, 289

  37. [37]

    A., Moustakas, J., & Diamond-Stanic, A

    Tremonti, C. A., Moustakas, J., & Diamond-Stanic, A. M. 2007, ApJL, 663, L77

  38. [38]

    2005, ARA&A, 43, 769

    Veilleux, S., Cecil, G., & Bland-Hawthorn, J. 2005, ARA&A, 43, 769

  39. [39]

    D., & Aalto, S

    Veilleux, S., Maiolino, R., Bolatto, A. D., & Aalto, S. 2020, A&A Rev., 28, 2

  40. [40]

    J., Coil, A

    Weiner, B. J., Coil, A. L., Prochaska, J. X., et al. 2009, ApJ, 692, 187

  41. [41]

    M., van der Wel, A., et al

    Wuyts, S., F¨orster Schreiber, N. M., van der Wel, A., et al. 2011, ApJ, 742, 96

  42. [42]
  43. [43]

    2024, ApJ, 961, 173

    Zou, H., et al. 2024, ApJ, 961, 173