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Metallicity has followed local gravitational potential of galaxies since z=3

T0 review · 4 major / 5 minor · reviewed 2026-08-14 · deepseek-v4-flash

Pith's one-line read This paper tests and confirms that gas metallicity tracks the local gravitational potential rather than total stellar mass, with the relation unchanged from z=0.16 to z=3.15.

desk verdict A careful, falsifiable test of the local-potential hypothesis that delivers a new 6σ gradient measurement, but the interpretation leans on an untested gravitational assumption. read the letter →

arxiv 1908.05362 v1 pith:VPMUJFYE submitted 2019-08-14 astro-ph.GA

classification astro-ph.GA
keywords mass-metallicityrelationdampedLyman-alphaabsorbersgamma-raybursthostscircumgalacticmediumgravitationalpotentialmetallicitygradientsgalaxyevolutionhigh-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 mass-metallicity relation is usually read as a global link between a galaxy's total stellar mass and the metal content of its gas. This paper argues that the underlying relation is local: at any point along a sightline through a galaxy halo, the gas metallicity is set by the depth of the gravitational potential at that radius, not by the galaxy's total mass. To test this, the authors show that the absorption-line width $\Delta v_{90}$ must decline outward at about $-0.015$ dex kpc$^{-1}$ in log space, exactly compensating the measured metallicity gradient. Compiling 21 DLA/sub-DLA host galaxies plus 9 gamma-ray burst hosts, they find the predicted decline out to 40-60 kpc and no change from $z=0.16$ to $z=3.15$. If right, the classical relation is a projection of a more fundamental local potential-metallicity relation.

What carries the argument

The load-bearing object is a cancellation identity: with metallicity gradient $\Gamma_{[M/H]}=-0.022$ dex kpc$^{-1}$ and the slope $\alpha_0=1.46$ of the $\Delta v_{90}$-metallicity relation, the hypothesis requires $\Gamma_{\Delta v_{90}}=\Gamma_{[M/H]}/\alpha_0\approx-0.015$ dex kpc$^{-1}$. The observable is $\log(\Delta v_{90}/\sigma_{\rm em})$ versus $b$, where $\Delta v_{90}$ is the velocity width containing 90 percent of the low-ion absorption optical depth and $\sigma_{\rm em}$ is the velocity dispersion of the host's emission lines; normalizing by $\sigma_{\rm em}$ removes the leading mass dependence. In the paper's equation 7 the two measured gradients cancel, leaving the central relation with a scatter that must arise from something other than impact parameter.

What would settle it

Measure spatially resolved rotation curves or stellar kinematics for the DLA/sub-DLA hosts and compare the absorption-line width at each impact parameter with the independently determined circular velocity at that radius; if $\Delta v_{90}$ does not scale with the local potential depth, the central claim would fail. A simpler check is to extend the sample beyond 60 kpc and see whether the $\log(\Delta v_{90}/\sigma_{\rm em})$ gradient and the metallicity gradient flatten together as the prediction requires.

Watch

Extended reading notes

Core claim

The paper's central claim is that both metallicity and the absorption velocity width $\Delta v_{90}$ follow the local gravitational potential in galaxy halos, and that this has been true since at least $z\approx3$. The quantitative result is a decline in the normalized width $\log(\Delta v_{90}/\sigma_{\rm em})$ with impact parameter $b$ at $\Gamma_{\Delta v_{90}}=-0.017\pm0.003$ dex kpc$^{-1}$, consistent with the value $-0.015$ dex kpc$^{-1}$ that makes the impact-parameter terms cancel in the $\Delta v_{90}$-metallicity relation. That cancellation means galaxies observed at random impact parameters are shifted along the same underlying relation rather than off it, so the observed mass-metallicity relation is not biased by unknown sightline radii. The paper finds no dependence of the slope on redshift, stellar mass, or $N({\rm H\,I})$, and interprets the lack of correlation between the absorber-host velocity offset and $\Delta v_{90}$ as evidence that DLA systems are ensembles of independent clouds spread through the halo rather than single bulk-moving clouds.

Load-bearing premise

The load-bearing premise is that the absorption width $\Delta v_{90}$ measures the depth of the local gravitational potential and the emission width $\sigma_{\rm em}$ measures the central potential; if those widths are instead set by turbulence, outflows, or line-of-sight geometry, the observed decline with radius would not prove that metallicity follows gravity.

Editorial extensions

If this is right

  • The mass-metallicity relation can be read as a projection of a local potential-metallicity relation, so absorption-selected samples need no impact-parameter correction to recover the underlying relation.
  • The relation has been stable from $z=0.16$ to $z=3.15$, meaning the local potential-metallicity link was already in place when the universe was roughly one-fifth of its present age.
  • Because the impact-parameter terms cancel, the residual scatter in the $\Delta v_{90}$-metallicity relation is not caused by random sightline radii; it must have another physical origin.
  • The velocity offset between absorption and emission being uncorrelated with $\Delta v_{90}$ favors the picture in which DLA complexes are ensembles of independent clouds spread along the pencil beam, with the total velocity width set by the halo potential.
  • If the potential gradient flattens at large radius, the metallicity gradient must flatten the same way to keep the cancellation, predicting a coupled flattening beyond about 60 kpc.

Reading between the lines

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

  • Inference: A direct test of causality would be to compare resolved metallicity maps of nearby galaxies with maps of the reconstructed gravitational potential from stellar kinematics; the local relation predicts that metallicity should track the potential at least as tightly as it tracks stellar mass surface density.
  • Inference: If the two gradients are coupled, then expanding absorber samples beyond $b\approx60$ kpc should show both the velocity-width and metallicity gradients flattening together; a decoupling there would indicate that the inner-CGM cancellation is not universal.
  • Inference: The paper's interpretation assumes the absorption width is a clean dynamical tracer, but comparing $\Delta v_{90}$ with an independent halo-mass estimate (for example from rotation or lensing) would show whether the width tracks the local potential or the total mass; if it tracks total mass, the local-potential reading needs revision.
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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 tests the hypothesis of Arabsalmani et al. (2015) that the mass-metallicity relation of DLA and GRB host galaxies is local, i.e., that metallicity follows local gravitational potential, by predicting that log(Δv90/σem) declines with impact parameter with slope -0.015 dex/kpc, derived as -Γ[M/H]/α0 with Γ[M/H] = -0.022 and α0 = 1.46. The authors compile 21 QSO-DLA/sub-DLA host galaxies with σem, b, Δv90, and N(HI), plus 9 GRB-DLAs, measure ΓΔv90 = -0.017 ± 0.003 dex/kpc (6σ) out to 54 kpc, and find agreement with the prediction. They also analyze the distribution of vrel and conclude that DLA absorbers are ensembles of sub-clouds distributed through the halo. The central interpretation is that both metallicity and Δv90 follow the local gravitational potential from z = 0.16 to z = 3.15.

Significance. If correct, this is a significant unification: it turns the absorption-line Δv90-[M/H] relation and the emission MZ relation into two projections of a local potential-metallicity relation, extending local MZ results to z ~ 3 and to impact parameters well beyond galaxy disks. The paper's strengths are the careful homogeneous reprocessing of heterogeneous archival data, the explicit falsifiable prediction, and the new direct measurement of ΓΔv90; the vrel analysis also provides independent information on absorber substructure. The claim, however, is conditional on the assumption that Δv90 and σem are purely gravitational, which is not independently established, and on the adopted slope α0; the quantitative agreement is therefore less secure than the abstract suggests.

major comments (4)
  1. [§4.2; supporting analysis in §3.3] The central claim that the measured slope of log(Δv90/σem) versus b represents a gravitational potential gradient rests on the assumption stated verbatim in §4.2: 'we here assume that σem and Δv90 are purely dictated by gravity.' The paper offers no independent test of this assumption. The vrel analysis in §3.3 favours a model of independent sub-clouds spread along the sightline, but an ensemble of clouds whose velocity dispersion is set by turbulence or outflow kinematics with a radial dependence would also produce a vrel distribution uncorrelated with the halo potential; it therefore does not validate the gravity-only interpretation. Without a discriminating test (for example, comparing low-ion and high-ion kinematics, checking for a correlation with star-formation or outflow indicators, or contrasting with simulations that include feedback), the 6σ slope is a kinematic correlation whose identification with the potential well is plausible but unproven. The title and abstract overstate the certainty of the physical interpretation.
  2. [§4.1, Eq. (6); §3.1] The predicted slope is not parameter-free: it is computed as ΓΔv90 = -Γ[M/H]/α0 using α0 = 1.46 and Γ[M/H] = -0.022 from previous fits (Møller et al. 2013; Christensen et al. 2014), and the present test sample overlaps the sample used to derive Γ[M/H]. The sensitivity to α0 is severe: with the alternative value α0 = 0.74 ± 0.21 (Neeleman et al. 2013), which the paper itself cites in §4.1, the required slope is -0.030, about 4.3σ away from the measured -0.017 ± 0.003. The agreement in §3.1 and §4.2 is therefore partly inherited from the adopted prior chains. I ask the authors to present the predicted slope as a function of α0 over the full published range, and to quantify how much of the 'confirmation' depends on that choice.
  3. [§4.2 and Fig. 2; §2.1] The claimed 6σ detection of ΓΔv90 rests on the combined sample that includes GRB-DLAs, all assigned the same median impact parameter b = 1.0 kpc, and on the average log(Δv90/σem) of nine GRB sightlines. The QSO-DLA-only fits shown in Fig. 2 give slopes of -0.011 and -0.020 with no quoted significance, so it is unclear whether the slope is detected at high significance without the GRB-DLA anchor. Because GRB-DLAs probe a different geometry along the sightline and are subject to different selection effects, the authors should report the slope, uncertainty, and significance for the QSO-DLA sample alone, and should discuss how excluding the b = 86 kpc object (which changes the low-redshift fit in Fig. 6) affects the claim that the slope extends to 40-60 kpc.
  4. [§3.4 and §2.1] The conclusion that there is no redshift evolution, and hence that the relation holds 'since z=3', is weakly supported. The sample has a degeneracy between redshift and N(HI): the 11 low-redshift hosts are mostly sub-DLAs and the 10 high-redshift hosts are mostly DLAs (§2.1). In Fig. 6 the low- and high-redshift slopes agree only after excluding the single b = 86 kpc object, and with 10 high-redshift objects the test has low power. 'No evidence for redshift dependence' is a defensible statement, but the abstract's 'since z = 3' should be softened to 'over the sampled redshift range' unless a more powerful joint fit in b, z, and N(HI) is added.
minor comments (5)
  1. [§4.2] The text refers to 'fit a line to the data points of log(Δv90/σem) vs. b in Fig. 3', but the linear fit is shown in Fig. 2; Fig. 3 shows projected profiles. The cross-reference should be corrected.
  2. [Fig. 3 caption] The caption says 'Predicted slope and average GRB-DLA are included as in Fig. 1'; it should refer to Fig. 2.
  3. [Fig. B1 caption] The sentence 'In Fig. B1(a) vi plot the standard Δv90-[M/H] relation' contains a typo: 'vi' should be 'we'.
  4. [Abstract] The phrase 'steep log scale slope of -0.015 dex/kpc' is awkward and could be rephrased as a 'logarithmic slope of log(Δv90/σem) with impact parameter of -0.015 dex/kpc'.
  5. [Table 1] Several vrel values are listed without errors (e.g., 0152-2001, 1436-0051A, 1228-1139); a note on how these are treated in the Fig. 5 analysis would improve reproducibility.

Circularity Check

1 steps flagged · score 4.0 of 10

Self-cited calibration sets the predicted slope; independent direct fit gives partial support

  1. self citation load bearing [Section 3.1 and Section 4.1 (Equations 5–7)]
    "The metallicity gradient for DLA galaxies has been reported as Γ = −0.022±0.004 dex kpc−1 (Christensen et al. 2014) and Γ = −0.022 ± 0.001 dex kpc−1 (Rhodin et al. 2018), and the gradient of [M/H] vs log(Δv90) is 1.46 (Ledoux et al. 2006; Møller et al. 2013). In order to cancel each other out the gradient of log(Δv90) should be −0.022/1.46 = −0.015 dex kpc−1."

    The predicted slope is the exact cancellation condition α0ΓΔv90 + Γ[M/H] = 0 defining the hypothesis (Eq. 5), and both inputs are self-cited fits (Christensen et al. 2014; Rhodin et al. 2018; Møller et al. 2013) from samples overlapping the present one (Sec. 4.2). Sec. 4.1 notes α0 ranges from 0.74 to 1.55 and adopts 1.46 'for internal consistency' with those prior papers. Hence the agreement in Eq. 7 is largely a consistency check of the authors' own calibration; the genuinely independent part is only the new direct fit of ΓΔv90.

full rationale

The paper's central quantitative test — the direct fit of the slope of log(Δv90/σem) versus impact parameter (Sec. 4.2, Fig. 8) — is a real new measurement and yields ΓΔv90 = −0.017 ± 0.003, consistent with the value needed for cancellation. If that were all, the derivation would be essentially non-circular. However, the numerical 'prediction' of −0.015 is not derived from an independent potential model; it is obtained by inserting the authors' own previously published Γ[M/H] = −0.022 (Christensen et al. 2014; Rhodin et al. 2018) and α0 = 1.46 (Møller et al. 2013) into the cancellation condition of Eq. 5. The paper explicitly acknowledges the current DLA sample has large overlap with the Christensen et al. (2014) sample, and it adopts α0 = 1.46 from a method-dependent range (0.74–1.55) purely for internal consistency with those prior papers. Thus the claimed agreement between predicted and measured slopes is partly a self-consistency of the authors' calibration, although the direct ΓΔv90 measurement gives the central claim some independent content. The further identification of the kinematic gradient with a gravitational potential gradient rests on the stated assumption that σem and Δv90 are 'purely dictated by gravity' (Sec. 4.2); that assumption is physically plausible but not independently demonstrated, and non-gravitational radial kinematics could in principle mimic the signal. On balance this is moderate self-citation with independent support, not a wholly circular derivation.

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

No new physical entities, forces, or conserved quantities are introduced; the analysis uses existing observables (Δv90, σem, b, [M/H]). The central claim rests on several fitted quantities from prior work by the same group, and on the assumption that absorption-line velocity widths are gravitational tracers.

free parameters (5)
  • α0 (slope of Δv90-[M/H] relation) = 1.46
    Adopted from Møller et al. (2013); used to convert the observed metallicity gradient into the predicted Δv90 gradient (-0.022/1.46).
  • Γ[M/H] (radial metallicity gradient) = -0.022 dex/kpc
    From Christensen et al. (2014) and Rhodin et al. (2018); the prediction relies on this value canceling the Δv90 gradient.
  • GRB-DLA median impact parameter = 1.0 kpc
    From Lyman et al. (2017); assigned to all 9 GRB-DLAs as a single average point in Fig. 2.
  • ze(z) redshift evolution slope = 0.35 z (flattened above z=2.62)
    From Møller et al. (2013); used for redshift corrections in the combined relation (Eq. 6-7) and Appendix B.
  • β intercept = -3.33
    From Møller et al. (2013); used in the full Δv90-[M/H] relation, correlated with α0.
assumptions (4)
  • domain assumption Δv90 of the absorbing complex traces the depth of the local gravitational potential at the impact parameter.
    Stated in Sections 1 and 4.2; if false, the measured gradient does not constrain the metallicity-potential relation.
  • domain assumption σ_em of the integrated emission lines represents the central velocity dispersion and is purely gravitational.
    Used to normalize Δv90 in Fig. 2; authors explicitly assume 'σem and Δv90 are purely dictated by gravity' in Section 4.2.
  • domain assumption The metallicity gradient Γ[M/H] is constant with radius, redshift, and mass across the inner CGM.
    Taken from Christensen et al. (2014); the cancellation test in Eq. 7 uses a single constant gradient.
  • domain assumption The redshift evolution of the Δv90-[M/H] relation (ze(z)) from Møller et al. (2013) is correct.
    Used to correct metallicities and to interpret the combined relation; ze(z) is a fitted empirical function.

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Pith. "Pith review of Metallicity has followed local gravitational potential of galaxies since z=3." pith.science (2026). https://pith.science/paper/VPMUJFYE

@misc{pith2026190805362,
  author       = {Pith},
  title        = {Pith review of: Metallicity has followed local gravitational potential of galaxies since z=3},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VPMUJFYE}},
  note         = {Machine review of arXiv:1908.05362}
}
read the original abstract

The MZ relation between stellar mass (M*) and metallicity (Z) of nearby galaxies has been described as both a global and local property, i.e. valid also on sub-galaxy scales. Here we show that Z has remained a local property, following the gravitational potential, since z=3. In absorption the MZ relation has been well studied, and was in place already at z=5.1. A recent absorption study of GRB galaxies revealed a close match to Damped Ly{\alpha} (DLA) galaxies, surprising due to their vastly different impact parameters and leading the authors to suggest that local metallicity follows the local gravitational potential. In this paper we formulate an observational test of this hypothesis. The test, in essence, forms a prediction that the velocity dispersion of the absorbing gas in galaxy halos, normalized by the central velocity dispersion, must follow a steep log scale slope of -0.015 dex/kpc as a function of impact parameter out to at least 20-30 kpc. We then compile an archival data and literature based sample of galaxies seen in both emission and absorption suitable for the test, and find that current data confirm the hypothesis out to 40-60 kpc. In addition we show that the distribution of the velocity offsets between z em and z abs favours a model where DLA systems are composed of individual sub-clouds distributed along the entire path through the halo, and disfavours a model where they are one single cloud with a bulk motion and internal sub-structure.

Figures

Figures reproduced from arXiv: 1908.05362 by the authors.

Figure 1
Figure 1. Simple illustration of the ∆v90-[M/H] relation and the effect of different impact parameters, b. The full black line represents a zoom on a small section of an idealized ∆v90-[M/H] relation with two galaxies observed at zero impact parameter (black squares). The same galaxies ob￾served at b = 7 and 15 kpc are offset to lower metallicities because of the metallicity gradient. If ∆v90, as assumed, is tracing the local… view at source ↗
Figure 2
Figure 2. Local dynamical state of the halo gas (∆v90) normalized to the central value of σem, as a function of b (blue squares). The green open circles are objects where the emission line region is offset by a few kpc from the galaxy centre and where σem consequently could underestimate the central velocity dispersion. The red open square is AGN dominated. The black dashed line is the hypothesis being tested while the two do… view at source ↗
Figure 5
Figure 5. Here we test if abs(vrel) correlates with ∆v90. A min-χ 2 fit (dashed black line) finds a weak anti-correlation, but the data are fully com￾patible with a slope of zero and no correlation. 3.3 Sub-structure within, and distribution of, DLA absorbing clouds In [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figures from the paper (2 more)
Figure 7
Figure 7. Figure 7: As [PITH_FULL_IMAGE:figures/full_fig_p007_7.png]
Figure 8
Figure 8. Figure 8: The gradient Γ∆v90 of log(∆v90) measured from the centre of the DLA galaxy to bmax as a function of bmax. It is seen that the gradient remains at a constant value of ≈ −0.017 dex kpc−1out to b ≈ 60 kpc. 1σ errors on Γ∆v90 for three representative values of bmax are als…

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Works this paper leans on

87 extracted references · 80 canonical work pages

  1. [1]

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

    ENTRY address author booktitle chapter edition editor howpublished institution journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 'mid.sentence := #2 '...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....

  3. [3]

    Arabsalmani , M., M ller , P., Fynbo , J. P. U., Christensen , L., Freudling , W., Savaglio , S., & Zafar , T., 2015, , 446, 990

  4. [4]

    A., et al

    Arabsalmani , M., M ller , P., Perley , D. A., et al. , 2018, , 473, 3312

  5. [5]

    J., & Scott , P., 2009, , 47, 481

    Asplund , M., Grevesse , N., Sauval , A. J., & Scott , P., 2009, , 47, 481

  6. [6]

    , 2018, , 478, 3120

    Augustin , R., P \'e roux , C., M ller , P., et al. , 2018, , 478, 3120

  7. [7]

    , 2005, , 364, 433

    Battaglia , G., Helmi , A., Morrison , H., et al. , 2005, , 364, 433

  8. [8]

    , 2017, , 469, 151

    Belfiore , F., Maiolino , R., Tremonti , C., et al. , 2017, , 469, 151

Show all 87 references
  1. [9]

    Berg , T. A. M., Ellison , S. L., Prochaska , J. X., Venn , K. A., & Dessauges-Zavadsky , M., 2015, , 452, 4326

  2. [10]

    Berg , T. A. M., Ellison , S. L., S \'a nchez-Ram \' rez , R., et al. , 2016, , 463, 3021

  3. [11]

    Bird , S., Haehnelt , M., Neeleman , M., Genel , S., Vogelsberger , M., & Hernquist , L., 2015, , 447, 1834

  4. [12]

    Bolzonella , M., Miralles , J.-M., & Pell \'o , R., 2000, , 363, 476

  5. [13]

    T., Kacprzak , G

    Bouch \'e , N., Murphy , M. T., Kacprzak , G. G., P \'e roux , C., Contini , T., Martin , C. L., & Dessauges-Zavadsky , M., 2013, Science, 341, 50

  6. [14]

    C., & Rauch , M., 2005, , 620, 703

    Chen , H.-W., Kennicutt , Jr., R. C., & Rauch , M., 2005, , 620, 703

  7. [15]

    & Hjorth , J., 2017, , 470, 2599

    Christensen , L. & Hjorth , J., 2017, , 470, 2599

  8. [16]

    Christensen , L., M ller , P., Fynbo , J. P. U., & Zafar , T., 2014, MNRAS, 445, 225

  9. [17]

    Christensen , L., M ller , P., Rhodin , N. H. P., Heintz , K. E., & Fynbo , J. P. U., 2019, submitted

  10. [18]

    E., S \'a nchez , S

    Christensen , L., Schulte-Ladbeck , R. E., S \'a nchez , S. F., Becker , T., Jahnke , K., Kelz , A., Roth , M. M., & Wisotzki , L., 2005, , 429, 477

  11. [19]

    M., S \'a nchez , S

    Christensen , L., Wisotzki , L., Roth , M. M., S \'a nchez , S. F., Kelz , A., & Jahnke , K., 2007, , 468, 587

  12. [20]

    R., Kulkarni , V

    Chun , M. R., Kulkarni , V. P., Gharanfoli , S., & Takamiya , M., 2010, AJ, 139, 296

  13. [21]

    B., 2016, , 596, A97

    De Cia , A., Ledoux , C., Mattsson , L., Petitjean , P., Srianand , R., Gavignaud , I., & Jenkins , E. B., 2016, , 596, A97

  14. [22]

    Dehnen , W., 1993, , 265, 250

  15. [23]

    S., Kurtz , M

    Demleitner , M., Accomazzi , A., Eichhorn , G., Grant , C. S., Kurtz , M. J., & Murray , S. S., 2001, Astronomical Society of the Pacific Conference Series, 238, 321

  16. [24]

    Fynbo , J. P. U., Geier , S. J., Christensen , L., et al. , 2013, MNRAS, 436, 361

  17. [25]

    Fynbo , J. P. U., Laursen , P., Ledoux , C., et al. , 2010, , 408, 2128

  18. [26]

    Fynbo , J. P. U., Ledoux , C., Noterdaeme , P., et al. , 2011, , 413, 2481

  19. [27]

    Hernquist , L., 1990, , 356, 359

  20. [28]

    Hewett , P. C. & Wild , V., 2007, MNRAS, 379, 738

  21. [29]

    Jaffe , W., 1983, , 202, 995

  22. [30]

    X., Smette , A., et al

    Kanekar , N., Prochaska , J. X., Smette , A., et al. , 2014, , 438, 2131

  23. [31]

    A., Smail , I., Oteo , I., Biggs , A

    Klitsch , A., P \'e roux , C., Zwaan , M. A., Smail , I., Oteo , I., Biggs , A. D., Popping , G., & Swinbank , A. M., 2018, , 475, 492

  24. [32]

    M., Dunkley , J., et al

    Komatsu , E., Smith , K. M., Dunkley , J., et al. , 2011, , 192, 18

  25. [33]

    Astrophysics Source Code Library

    Krogager , J.-K., 2018, VoigtFit: Absorption line fitting for Voigt profiles . Astrophysics Source Code Library

  26. [34]

    Krogager , J.-K., Fynbo , J. P. U., Ledoux , C., et al. , 2013, MNRAS, 433, 3091

  27. [35]

    Krogager , J.-K., M ller , P., Fynbo , J. P. U., & Noterdaeme , P., 2017, , 469, 2959

  28. [36]

    P., Meiring , J., Som , D., P \'e roux , C., York , D

    Kulkarni , V. P., Meiring , J., Som , D., P \'e roux , C., York , D. G., Khare , P., & Lauroesch , J. T., 2012, , 749, 176

  29. [37]

    Lane , W., Smette , A., Briggs , F., Rao , S., Turnshek , D., & Meylan , G., 1998, , 116, 26

  30. [38]

    M., 1997, , 321, 733

    Le Brun , V., Bergeron , J., Boisse , P., & Deharveng , J. M., 1997, , 321, 733

  31. [39]

    Ledoux , C., Petitjean , P., Fynbo , J. P. U., M ller , P., & Srianand , R., 2006, A&A, 457, 71

  32. [40]

    X., 2002, , 385, 778

    Lopez , S., Reimers , D., D'Odorico , S., & Prochaska , J. X., 2002, , 385, 778

  33. [41]

    D., Levan , A

    Lyman , J. D., Levan , A. J., Tanvir , N. R., et al. , 2017, , 467, 1795

  34. [42]

    , 2008, , 488, 463

    Maiolino , R., Nagao , T., Grazian , A., et al. , 2008, , 488, 463

  35. [43]

    D., Kulkarni , V

    Meiring , J. D., Kulkarni , V. P., Lauroesch , J. T., P \'e roux , C., Khare , P., & York , D. G., 2009 a , , 393, 1513

  36. [44]

    D., Kulkarni , V

    Meiring , J. D., Kulkarni , V. P., Lauroesch , J. T., P \'e roux , C., Khare , P., York , D. G., & Crotts , A. P. S., 2008, , 384, 1015

  37. [45]

    D., Lauroesch , J

    Meiring , J. D., Lauroesch , J. T., Kulkarni , V. P., P \'e roux , C., Khare , P., & York , D. G., 2009 b , , 397, 2037

  38. [46]

    D., Lauroesch , J

    Meiring , J. D., Lauroesch , J. T., Kulkarni , V. P., P \'e roux , C., Khare , P., York , D. G., & Crotts , A. P. S., 2007, , 376, 557

  39. [47]

    A., et al

    M ller , P., Christensen , L., Zwaan , M. A., et al. , 2018, , 474, 4039

  40. [48]

    M ller , P., Fynbo , J. P. U., & Fall , S. M., 2004, , 422, L33

  41. [49]

    M ller , P., Fynbo , J. P. U., Ledoux , C., & Nilsson , K. K., 2013, MNRAS, 430, 2680

  42. [50]

    & Warren , S

    M ller , P. & Warren , S. J., 1993, , 270, 43

  43. [51]

    J., Fall , S

    M ller , P., Warren , S. J., Fall , S. M., Fynbo , J. U., & Jakobsen , P., 2002, , 574, 51

  44. [52]

    M., Heckman , T

    Moran , S. M., Heckman , T. M., Kauffmann , G., et al. , 2012, , 745, 66

  45. [53]

    X., Christensen , L., Dessauges-Zavadsky , M., Fynbo , J

    Neeleman , M., Kanekar , N., Prochaska , J. X., Christensen , L., Dessauges-Zavadsky , M., Fynbo , J. P. U., M ller , P., & Zwaan , M. A., 2018, , 856, L12

  46. [54]

    X., Zwaan , M

    Neeleman , M., Prochaska , J. X., Zwaan , M. A., et al. , 2016, , 820, L39

  47. [55]

    M., Prochaska , J

    Neeleman , M., Wolfe , A. M., Prochaska , J. X., & Rafelski , M., 2013, ApJ, 769, 54

  48. [56]

    , 2012, A&A, 540, 63

    Noterdaeme , P., Laursen , P., Petitjean , P., et al. , 2012, A&A, 540, 63

  49. [57]

    Noterdaeme , P., Petitjean , P., Ledoux , C., Srianand , R., & Ivanchik , A., 2008, , 491, 397

  50. [58]

    P., & York , D

    P \'e roux , C., Bouch \'e , N., Kulkarni , V. P., & York , D. G., 2013, , 436, 2650

  51. [59]

    P., York , D

    P \'e roux , C., Bouch \'e , N., Kulkarni , V. P., York , D. G., & Vladilo , G., 2011 a , , 410, 2237

  52. [60]

    ---, 2011 b , , 410, 2251

  53. [61]

    D., Kulkarni , V

    P \'e roux , C., Meiring , J. D., Kulkarni , V. P., Khare , P., Lauroesch , J. T., Vladilo , G., & York , D. G., 2008, , 386, 2209

  54. [62]

    , 2016, , 457, 903

    P \'e roux , C., Quiret , S., Rahmani , H., et al. , 2016, , 457, 903

  55. [63]

    L., Steidel , C

    Pettini , M., Ellison , S. L., Steidel , C. C., Shapley , A. E., & Bowen , D. V., 2000, ApJ, 532, 65

  56. [64]

    Prochaska, J. X. & Wolfe, A. M., 1997, ApJ, 487, 73

  57. [65]

    , 2018, , 480, 5046

    Rahmani , H., P \'e roux , C., Schroetter , I., et al. , 2018, , 480, 5046

  58. [66]

    A., et al

    Rahmani , H., P \'e roux , C., Turnshek , D. A., et al. , 2016, , 463, 980

  59. [67]

    M., Belfort-Mihalyi , M., Turnshek , D

    Rao , S. M., Belfort-Mihalyi , M., Turnshek , D. A., Monier , E. M., Nestor , D. B., & Quider , A., 2011, , 416, 1215

  60. [68]

    M., Turnshek , D

    Rao , S. M., Turnshek , D. A., & Nestor , D. B., 2006, ApJ, 636, 610

  61. [69]

    Rhodin , N. H. P., Christensen , L., M ller , P., Zafar , T., & Fynbo , J. P. U., 2018, ArXiv e-prints

  62. [70]

    C., Newman , A

    Rudie , G. C., Newman , A. B., & Murphy , M. T., 2017, , 843, 98

  63. [71]

    F., Rosales-Ortega , F

    S \'a nchez , S. F., Rosales-Ortega , F. F., Iglesias-P \'a ramo , J., et al. , 2014, , 563, A49

  64. [72]

    F., Rosales-Ortega , F

    S \'a nchez , S. F., Rosales-Ortega , F. F., Jungwiert , B., et al. , 2013, , 554, A58

  65. [73]

    F., P \'e rez , I., et al

    S \'a nchez-Menguiano , L., S \'a nchez , S. F., P \'e rez , I., et al. , 2018, , 609, A119

  66. [74]

    , 2012, , 420, 627

    Savaglio , S., Rau , A., Greiner , J., et al. , 2012, , 420, 627

  67. [75]

    P., Meiring , J., York , D

    Som , D., Kulkarni , V. P., Meiring , J., York , D. G., P \'e roux , C., Lauroesch , J. T., Aller , M. C., & Khare , P., 2015, , 806, 25

  68. [76]

    Srianand , R., Hussain , T., Noterdaeme , P., Petitjean , P., Kr \"u hler , T., Japelj , J., P \^a ris , I., & Kashikawa , N., 2016, , 460, 634

  69. [77]

    Srianand , R., Noterdaeme , P., Ledoux , C., & Petitjean , P., 2008, , 482, L39

  70. [78]

    C., Pettini , M., & Hamilton , D., 1995, , 110, 2519

    Steidel , C. C., Pettini , M., & Hamilton , D., 1995, , 110, 2519

  71. [79]

    A., Johnson , S., York , D

    Straka , L. A., Johnson , S., York , D. G., Bowen , D. V., Florian , M., Kulkarni , V. P., Lundgren , B., & P \'e roux , C., 2016, , 458, 3760

  72. [80]

    A., Heckman , T

    Tremonti , C. A., Heckman , T. M., Kauffmann , G., et al. , 2004, ApJ, 613, 898

  73. [81]

    Warren , S. J. & M ller , P., 1996, , 311, 25

  74. [82]

    J., M ller , P., Fall , S

    Warren , S. J., M ller , P., Fall , S. M., & Jakobsen , P., 2001, , 326, 759

  75. [83]

    J., Warren , S

    Weatherley , S. J., Warren , S. J., M ller , P., Fall , S. M., Fynbo , J. U., & Croom , S. M., 2005, , 358, 985

  76. [84]

    Wolfe , A. M. & Prochaska , J. X., 1998, , 494, L15

  77. [85]

    M., Prochaska , J

    Wolfe , A. M., Prochaska , J. X., Jorgenson , R. A., & Rafelski , M., 2008, , 681, 881

  78. [86]

    , 2016, , 827, 74

    Wuyts , E., Wisnioski , E., Fossati , M., et al. , 2016, , 827, 74

  79. [87]

    Zafar , T., M ller , P., P \'e roux , C., Quiret , S., Fynbo , J. P. U., Ledoux , C., & Deharveng , J.-M., 2017, , 465, 1613

Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.