Pith. sign in

REVIEW 3 major objections 4 minor 51 references

From the Outside Looking in: What can Milky Way Analogues Tell us About the Star Formation Rate of Our Own Galaxy?

T0 review · 3 major / 4 minor · reviewed 2026-08-14 · deepseek-v4-flash

Pith's one-line read A sample of 176 galaxies selected to match the Milky Way's mass, spiral arms, bar, and bulge shows its star formation rate, while low, is not unusual.

desk verdict A clean structural selection of Milky Way analogues shows the Galaxy's SFR is unremarkable; a self-flagged but untested bar-threshold bias is the main gap. read the letter →

arxiv 1909.01654 v1 pith:RA3PZOZQ submitted 2019-09-04 astro-ph.GA

classification astro-ph.GA
keywords MilkyWayanaloguesstarformationratespiralstructuregalacticbarbulge-to-totalratioSEDfittingWISEmid-infraredSFRanaemic
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

This paper asks whether the Milky Way's low measured star formation rate makes it an outlier among galaxies like itself. To answer, the authors select 176 galaxies from a large spectroscopic survey that match the Milky Way on non-transient structural properties—stellar mass, spiral arms, a bar, and a small bulge—rather than on star formation or colour. These analogues have mean SFRs of $\log(\mathrm{SFR}_{\mathrm{SED}}/M_\odot\,\mathrm{yr}^{-1}) = 0.53 \pm 0.23$ and $\log(\mathrm{SFR}_{\mathrm{W4}}/M_\odot\,\mathrm{yr}^{-1}) = 0.68 \pm 0.41$, while the Milky Way's best estimate is $\log(\mathrm{SFR}) = 0.22$. The Milky Way falls within 1.4$\sigma$ (SED) and 1.1$\sigma$ (W4) of these means, so the paper concludes it is a somewhat low-SFR galaxy but not an unusual one. The value of the approach is that it provides an external view of our own galaxy without presupposing that the Milky Way is special in its star formation.

What carries the argument

The central object is the Milky Way analogue sample itself, built from four simultaneous structural cuts: stellar mass $4.1\times10^{10}\,M_\odot < M_\star < 8.0\times10^{10}\,M_\odot$, a spiral-arm vote fraction above 0.7, a bar vote fraction above 0.5, and a bulge-to-total ratio between 0.1 and 0.2. Each cut comes from literature estimates of the Milky Way's non-transient structure, and none uses star formation rate or colour. This selection defines the peer group against which the Milky Way's SFR is judged, so the comparison is not circular.

What would settle it

Construct an external-observer view of the Milky Way from resolved maps of stars, gas, and dust, run it through the same SED-fitting and WISE calibrations used for the analogues, and compare the recovered SFR with the fiducial $\log(\mathrm{SFR})=0.22$; if the two disagree by more than the quoted uncertainties, the apparent ordinariness is a scale-mismatch artifact.

Watch

Extended reading notes

Core claim

Using 176 galaxies selected from a large spectroscopic survey to match the Milky Way's stellar mass, spiral arms, bar, and small bulge, the paper measures star formation rates with two independent indicators. The SED-fitting indicator gives a mean $\log(\mathrm{SFR}_{\mathrm{SED}}/M_\odot\,\mathrm{yr}^{-1})=0.53$ with a standard deviation of 0.23 dex, and the WISE W4 mid-infrared calibration gives a mean of $0.68$ with a standard deviation of 0.41 dex. The best literature estimate for the Milky Way, $\log(\mathrm{SFR}_{\mathrm{MW}}/M_\odot\,\mathrm{yr}^{-1})=0.22$, lies within 1.4$\sigma$ of the SED mean and 1.1$\sigma$ of the W4 mean. The paper concludes that the Milky Way is a somewhat low-SFR galaxy but not unusual when compared with galaxies of the same non-transient structure.

Load-bearing premise

The comparison assumes that the Milky Way's star formation rate measured from resolved stars and gas sits on the same scale as the unresolved SED and WISE measurements of external galaxies, with no unaccounted systematic offset.

Editorial extensions

If this is right

  • The label 'anaemic spiral' overstates the case: a low star formation rate is a normal outcome for a galaxy with the Milky Way's mass and structure.
  • Because the analogues span both the blue cloud and the green valley at fixed structure, star formation behaviour is not locked in by structure alone; transient factors decide where a galaxy sits.
  • The structural selection can serve as a template for comparing other Milky Way properties from outside, since it is deliberately agnostic to transient observables.
  • The sample is essentially complete out to $z=0.15$, so the count of 176 analogues is a robust statement within this survey volume rather than a biased residue.

Reading between the lines

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

  • A direct calibration of resolved Milky Way SFR tracers against unresolved SED and WISE methods could shift $\log(\mathrm{SFR}_{\mathrm{MW}})$ by a few tenths of a dex; if so, the Milky Way could move from 'low but normal' toward the distribution centre or beyond 2$\sigma$.
  • Applying the same structural cuts to deeper or wider surveys, or to simulated galaxies viewed as analogues, would test whether 176 is a stable answer and would sharpen the Milky Way's percentile rank among its peers.
  • The WISE-based SFRs run systematically higher than the SED-based SFRs for the same galaxies, with AGN-hosting galaxies flagged as likely contributors; averaging after removing AGN/composite galaxies would probably narrow the WISE distribution and shift its mean slightly.
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. This paper constructs a sample of 176 Milky Way analogues from SDSS DR7 by applying strict cuts on stellar mass (4.1–8.0×10^10 M_sun), GZ2 spiral fraction > 0.7, GZ2 bar fraction > 0.5, and r-band bulge-to-total ratio 0.1–0.2. The authors derive SFRs for these galaxies using SED fitting from GSWLC-X2 (149 galaxies) and WISE W3/W4 calibrations of Cluver et al. (2017) (157/155 galaxies). The mean log SFRs are 0.53 ± 0.23 (SED), 0.72 ± 0.30 (W3), and 0.68 ± 0.41 (W4) in M_sun/yr. The most recent Milky Way SFR estimate (Licquia & Newman 2015), log SFR = 0.22, falls 1.4σ, 1.7σ, and 1.1σ from these means, respectively. The authors conclude that the Milky Way, while somewhat below the star-forming main sequence, is not unusual compared to galaxies selected on the same non-transient structural features.

Significance. The question of whether the Milky Way is an 'anaemic spiral' is of broad interest, and the selection strategy is a methodological improvement over SFR- or colour-based analogue samples because it avoids the circularity of selecting on the very property under study. The paper draws on high-quality public catalogues and provides a well-defined catalogue of 176 MWAs that will be useful for future studies. The two SFR indicators are complementary, and the authors are transparent about the caveats of comparing resolved Galactic measurements with unresolved extragalactic ones. If the conclusions survive the systematic concerns raised below, this would provide a robust answer to the 'anaemic spiral' question.

major comments (3)
  1. [Section 2] The choice of GZ2 weighted bar fraction > 0.5, while justified for contamination control, is acknowledged by the authors to bias the sample toward strongly barred galaxies, which are known to be more quiescent than average (Masters et al. 2011; Fraser-McKelvie et al. 2018). Because the Milky Way's own bar strength is not used to set the threshold, the comparison sample may have a systematically lower SFR distribution than a sample selected with a weaker bar cut. The central claim that the Milky Way lies within 2σ of the analogue mean depends directly on the mean of the comparison distribution, so this selection effect is load-bearing. The authors should perform a sensitivity test, e.g., repeating the analysis with lower bar-fraction thresholds (or no bar cut) and reporting how the mean SFR and the Milky Way's offset change.
  2. [Sections 3.1–3.2] The Milky Way SFR of Licquia & Newman (2015) is derived from resolved tracers (H II regions, supernova rates, etc.) homogenised by Chomiuk & Povich (2011), while the analogue SFRs come from unresolved SED fitting and WISE photometry. The authors themselves state that 'it is difficult to compare measurements based on individual stars and resolved gas to unresolved extragalactic measurements.' If a systematic offset of order 0.2–0.3 dex exists between these scales, the Milky Way's position relative to the analogue distribution would shift enough to change the qualitative conclusion. The paper does not calibrate or correct for this possibility; at minimum, a quantitative discussion of the likely systematic uncertainty and its effect on the quoted σ levels is needed.
  3. [Section 4, panel c] The SED and W4 indicators show large scatter and a systematic offset, with W4-derived SFRs higher than SED-derived SFRs at the high end, and the authors attribute part of this to AGN contamination in the mid-IR (noted for star-shaped points). While the authors state they 'trust the SED-derived SFRs more,' the central conclusion is based on the absolute scale of the SFR distribution. The two indicators give different means (0.53 vs 0.68 dex), and the Milky Way's offset differs by 0.3σ between them. The authors should show explicitly that the conclusion is robust to the choice of indicator, or provide a combined analysis that propagates the indicator mismatch as a systematic uncertainty.
minor comments (4)
  1. [Section 2] In the paragraph on BTR, 'steller mass ratio' should be 'stellar mass ratio'.
  2. [Section 4] The statement that the Milky Way is 'comfortably' within the distribution is a value judgment; consider replacing with a quantitative statement.
  3. [Figure 2] The axis label 'Mr' should be 'M_r' (r-band absolute magnitude).
  4. [Section 3.2] The paper reports 149 SED, 157 W3, and 155 W4 SFRs out of 176; a brief discussion of how the missing galaxies could affect the sample mean would be useful.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the analogue sample is selected without using SFR or colour, and the Milky Way SFR is an independent external literature value.

full rationale

The paper's central comparison is structurally independent of its inputs. The Milky Way analogue sample is defined by stellar mass, spiral arm presence, bar presence, and bulge-to-total ratio, with the paper explicitly stating it is 'remaining agnostic to any transient observables such as SFR and colour.' The Milky Way SFR is taken from the external hierarchical Bayesian analysis of Licquia & Newman (2015), which itself combines the literature values compiled by Chomiuk & Povich (2011); this value is not used in the sample selection. The SFRs of the analogues come from two independent external sources: the GSWLC-2 SED fits of Salim et al. (2016, 2018) and the WISE mid-infrared calibration of Cluver et al. (2017). Although Licquia & Newman (2015) is used both for the Milky Way SFR and for the mass and BTR priors, those are separate measurements from that paper, and the selection does not use SFR. The only self-citation, Fraser-McKelvie et al. (2018), appears in a caveat that strong bars may be quiescent, which if anything highlights a possible selection bias rather than serving as load-bearing support for the conclusion. No equation or definition reduces the predicted SFR distribution to the inputs; the result is a measured distribution of external SFR indicators for a sample selected without regard to those indicators.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

No new physical entities are introduced. The paper's parameter choices are selection thresholds, not fits to the Milky Way SFR; the main burden of proof rests on comparability of SFR scales and on the structural classification.

free parameters (2)
  • GZ2 spiral fraction threshold = 0.7
    Chosen by the authors after visual inspection to maximize the number of spiral galaxies while keeping contamination low. It affects the sample composition and hence the SFR distribution, but is not fitted to any target SFR.
  • GZ2 bar fraction threshold = 0.5
    Adopted from Masters et al. (2012) rather than fitted here; still a hand-set cut that biases the sample toward strongly barred, possibly more quiescent galaxies.
assumptions (5)
  • domain assumption The Milky Way structural parameters adopted from literature (mass, BTR, spiral/bar presence) are accurate.
    Invoked in Section 2; the entire sample definition inherits uncertainties from Licquia & Newman (2015) and other Galactic measurements.
  • domain assumption The Simard et al. (2011) r-band luminosity B/T is comparable to the Licquia & Newman (2015) stellar mass B/T for the Milky Way.
    Section 2 states the mass-to-light ratio should not change by a large amount for galaxies of similar mass; if wrong, the BTR cut selects a different population.
  • domain assumption GZ2 weighted vote fractions reliably identify spiral arms and bars at the chosen thresholds.
    Section 2 uses t04_spiral_a08_spiral_weighted_fraction > 0.7 and t03_bar_a06_bar_weighted_fraction > 0.5; the paper notes edge-on galaxies may masquerade as bars.
  • domain assumption External galaxy SFR indicators (GSWLC-X2 SED and Cluver WISE calibrations) can be compared on one scale with resolved Milky Way SFR estimates.
    Section 2 caveat 'it is difficult to compare measurements based on individual stars and resolved gas to unresolved extragalactic measurements' and Section 3.1.
  • domain assumption SFRs can be converted between IMFs with a constant multiplicative factor (Chabrier to Kroupa via Zahid et al. 2012).
    Section 4 uses this conversion for SED SFRs; WISE SFRs based on total-IR luminosity calibrations already assume Kroupa.

how reviews work

0 comments
Cite this review

Pith. "Pith review of From the Outside Looking in: What can Milky Way Analogues Tell us About the Star Formation Rate of Our Own Galaxy?." pith.science (2026). https://pith.science/paper/RA3PZOZQ

@misc{pith2026190901654,
  author       = {Pith},
  title        = {Pith review of: From the Outside Looking in: What can Milky Way Analogues Tell us About the Star Formation Rate of Our Own Galaxy?},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RA3PZOZQ}},
  note         = {Machine review of arXiv:1909.01654}
}
abstract

The Milky Way has been described as an anaemic spiral, but is its star formation rate (SFR) unusually low when compared to its peers? To answer this question, we define a sample of Milky Way Analogues (MWAs) based on stringent cuts on the best literature estimates of non-transient structural features for the Milky Way. This selection yields only 176 galaxies from the whole of the SDSS DR7 spectroscopic sample which have morphological classifications in GZ2, from which we infer SFRs from two separate indicators. The mean SFRs found are $\log(\rm{SFR}_{SED}/\rm{M}_{\odot}~\rm{yr}^{-1})=0.53$ with a standard deviation of 0.23 dex from SED fits, and $\log(\rm{SFR}_{W4}/\rm{M}_{\odot}~\rm{yr}^{-1})=0.68$ with a standard deviation of 0.41 dex from a mid-infrared calibration. The most recent estimate for the Milky Way's star formation rate of $\log(\rm{SFR}_{MW}/\rm{M}_{\odot}~\rm{yr}^{-1})=0.22$ fits well within 2$\sigma$ of these values, where $\sigma$ is the standard deviation of each of the SFR indicator distributions. We infer that the Milky Way, while being a galaxy with a somewhat low SFR, is not unusual when compared to similar galaxies.

Figures

Figures reproduced from arXiv: 1909.01654 by the authors.

Figure 1
Figure 1. A Venn diagram illustrating the overlap between the tight constraints imposed on the Milky Way Analogue sample and the number of galaxies from the NASA Sloan Atlas, Galaxy Zoo 2, and the Simard et al. (2011) bulge-disk decomposition catalogues that satisfy each. The number of galaxies in each catalogue surviving the cut applied, along with the original number of galaxies in each catalogue is shown in brackets. Just … view at source ↗
Figure 2
Figure 2. NSA r-band absolute magnitude as a function of red￾shift for the NSA catalogue with associated GZ2 morphologies (black points), and structural Milky Way analogues with the same BTR, spiral arm and bar cuts used for the MWA sample selec￾tion (red squares). The structural analogues are a representative sample of the overall NSA catalogue. The MWA sample (with the additional mass range criterion) selected by the struct… view at source ↗
Figure 3
Figure 3. SDSS gri colour images of nine Milky Way analogue examples, chosen to be between a narrow mass range, possess a small bulge, spiral arms, and a bar. over 747 million sky objects. Sources are matched to their SDSS MWA counterparts on the sky, and the correct aper￾ture chosen based on the angular extent of the source as indicated by the extended source flag in the AllWISE cata￾logue. If the source was deemed ‘extended… view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: Star formation rates of the Milky Way Analogue sample. Panel a) is a histogram of the SED-derived SFRs of Salim et al. (2018) converted to a Kroupa IMF. The mean of this distribution is denoted by a dashed line and the Milky Way value from Licquia & Newman (2015) shown…
Figure 5
Figure 5. Figure 5: The star formation main sequence. Black points are values from SDSS DR7. Stellar masses are from NSA, and SFRs are the SED-derived values from Salim et al. (2018). MWAs are denoted by blue triangles, and a literature value of the SFR of the Milky Way from Licquia & New…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

51 extracted references · 5 canonical work pages

  1. [1]

    N., et al., 2009, @doi [ ] 10.1088/0067-0049/182/2/543 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..543A 182, 543

    Abazajian K. N., et al., 2009, @doi [ ] 10.1088/0067-0049/182/2/543 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..543A 182, 543

  2. [2]

    F., de Jong R

    Bell E. F., de Jong R. S., 2001, @doi [ ] 10.1086/319728 , https://ui.adsabs.harvard.edu/abs/2001ApJ...550..212B 550, 212

  3. [3]

    A., et al., 2005, @doi [ ] 10.1086/491785 , https://ui.adsabs.harvard.edu/abs/2005ApJ...630L.149B 630, L149

    Benjamin R. A., et al., 2005, @doi [ ] 10.1086/491785 , https://ui.adsabs.harvard.edu/abs/2005ApJ...630L.149B 630, L149

  4. [4]

    E., Stark A

    Binney J., Gerhard O. E., Stark A. A., Bally J., Uchida K. I., 1991, @doi [ ] 10.1093/mnras/252.2.210 , https://ui.adsabs.harvard.edu/abs/1991MNRAS.252..210B 252, 210

  5. [5]

    Binney J., Gerhard O., Spergel D., 1997, @doi [ ] 10.1093/mnras/288.2.365 , https://ui.adsabs.harvard.edu/abs/1997MNRAS.288..365B 288, 365

  6. [6]

    Bland-Hawthorn J., Gerhard O., 2016, @doi [ ] 10.1146/annurev-astro-081915-023441 , https://ui.adsabs.harvard.edu/abs/2016ARA&A..54..529B 54, 529

  7. [7]

    R., Roweis S., 2007, @doi [ ] 10.1086/510127 , https://ui.adsabs.harvard.edu/abs/2007AJ....133..734B 133, 734

    Blanton M. R., Roweis S., 2007, @doi [ ] 10.1086/510127 , https://ui.adsabs.harvard.edu/abs/2007AJ....133..734B 133, 734

  8. [8]

    R., Kazin E., Muna D., Weaver B

    Blanton M. R., Kazin E., Muna D., Weaver B. A., Price-Whelan A., 2011, @doi [ ] 10.1088/0004-6256/142/1/31 , https://ui.adsabs.harvard.edu/abs/2011AJ....142...31B 142, 31

Show all 51 references
  1. [9]

    K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103

    Boquien M., Burgarella D., Roehlly Y., Buat V., Ciesla L., Corre D., Inoue A. K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103

  2. [10]

    Bozorgnia N., et al., 2016, @doi [Journal of Cosmology and Astro-Particle Physics] 10.1088/1475-7516/2016/05/024 , https://ui.adsabs.harvard.edu/abs/2016JCAP...05..024B 2016, 024

  3. [11]

    Brinchmann J., Charlot S., White S. D. M., Tremonti C., Kauffmann G., Heckman T., Brinkmann J., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07881.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.351.1151B 351, 1151

  4. [12]

    S., Johnston K

    Bullock J. S., Johnston K. V., 2005, @doi [ ] 10.1086/497422 , https://ui.adsabs.harvard.edu/abs/2005ApJ...635..931B 635, 931

  5. [13]

    L., L \'o pez-Corredoira M., 2008, @doi [ ] 10.1051/0004-6361:200810720 , https://ui.adsabs.harvard.edu/abs/2008A&A...491..781C 491, 781

    Cabrera-Lavers A., Gonz \'a lez-Fern \'a ndez C., Garz \'o n F., Hammersley P. L., L \'o pez-Corredoira M., 2008, @doi [ ] 10.1051/0004-6361:200810720 , https://ui.adsabs.harvard.edu/abs/2008A&A...491..781C 491, 781

  6. [14]

    Calore F., et al., 2015, @doi [Journal of Cosmology and Astro-Particle Physics] 10.1088/1475-7516/2015/12/053 , https://ui.adsabs.harvard.edu/abs/2015JCAP...12..053C 2015, 053

  7. [15]

    S., 2011, @doi [ ] 10.1088/0004-6256/142/6/197 , https://ui.adsabs.harvard.edu/abs/2011AJ....142..197C 142, 197

    Chomiuk L., Povich M. S., 2011, @doi [ ] 10.1088/0004-6256/142/6/197 , https://ui.adsabs.harvard.edu/abs/2011AJ....142..197C 142, 197

  8. [16]

    E., et al., 2014, @doi [ ] 10.1088/0004-637X/782/2/90 , https://ui.adsabs.harvard.edu/abs/2014ApJ...782...90C 782, 90

    Cluver M. E., et al., 2014, @doi [ ] 10.1088/0004-637X/782/2/90 , https://ui.adsabs.harvard.edu/abs/2014ApJ...782...90C 782, 90

  9. [17]

    E., Jarrett T

    Cluver M. E., Jarrett T. H., Dale D. A., Smith J. D. T., August T., Brown M. J. I., 2017, @doi [ ] 10.3847/1538-4357/aa92c7 , https://ui.adsabs.harvard.edu/abs/2017ApJ...850...68C 850, 68

  10. [18]

    M., et al

    Cutri R. M., et al. 2014, VizieR Online Data Catalog, https://ui.adsabs.harvard.edu/abs/2014yCat.2328....0C 2328

  11. [20]

    Davies L. J. M., et al., 2015, @doi [ ] 10.1093/mnras/stv1241 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452..616D 452, 616

  12. [21]

    Dwek E., et al., 1995, @doi [ ] 10.1086/175734 , https://ui.adsabs.harvard.edu/abs/1995ApJ...445..716D 445, 716

  13. [22]

    Fraser-McKelvie A., Brown M. J. I., Pimbblet K., Dolley T., Bonne N. J., 2018, @doi [ ] 10.1093/mnras/stx2823 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.1909F 474, 1909

  14. [23]

    Geha M., et al., 2017, @doi [ ] 10.3847/1538-4357/aa8626 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847....4G 847, 4

  15. [24]

    L., Garzon F., Mahoney T., Calbet X., 1994, @doi [ ] 10.1093/mnras/269.3.753 , https://ui.adsabs.harvard.edu/abs/1994MNRAS.269..753H 269, 753

    Hammersley P. L., Garzon F., Mahoney T., Calbet X., 1994, @doi [ ] 10.1093/mnras/269.3.753 , https://ui.adsabs.harvard.edu/abs/1994MNRAS.269..753H 269, 753

  16. [25]

    E., et al., 2016, @doi [ ] 10.1093/mnras/stw1588 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.461.3663H 461, 3663

    Hart R. E., et al., 2016, @doi [ ] 10.1093/mnras/stw1588 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.461.3663H 461, 3663

  17. [26]

    Helou G., et al., 2004, @doi [ ] 10.1086/422640 , https://ui.adsabs.harvard.edu/abs/2004ApJS..154..253H 154, 253

  18. [27]

    Kroupa P., 2002, @doi [Science] 10.1126/science.1067524 , https://ui.adsabs.harvard.edu/abs/2002Sci...295...82K 295, 82

  19. [28]

    H., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12299.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.381..401L 381, 401

    Laurikainen E., Salo H., Buta R., Knapen J. H., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12299.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.381..401L 381, 401

  20. [29]

    C., Newman J

    Licquia T. C., Newman J. A., 2015, @doi [ ] 10.1088/0004-637X/806/1/96 , https://ui.adsabs.harvard.edu/abs/2015ApJ...806...96L 806, 96

  21. [30]

    F., Wechsler R

    Liu L., Gerke B. F., Wechsler R. H., Behroozi P. S., Busha M. T., 2011, @doi [ ] 10.1088/0004-637X/733/1/62 , https://ui.adsabs.harvard.edu/abs/2011ApJ...733...62L 733, 62

  22. [31]

    N., Rhoads J

    Malhotra S., Spergel D. N., Rhoads J. E., Li J., 1996, @doi [ ] 10.1086/178181 , https://ui.adsabs.harvard.edu/abs/1996ApJ...473..687M 473, 687

  23. [32]

    L., et al., 2011, @doi [ ] 10.1111/j.1365-2966.2010.17834.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.411.2026M 411, 2026

    Masters K. L., et al., 2011, @doi [ ] 10.1111/j.1365-2966.2010.17834.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.411.2026M 411, 2026

  24. [34]

    J., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18564.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.414.2446M 414, 2446

    McMillan P. J., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18564.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.414.2446M 414, 2446

  25. [35]

    M., Papamastorakis J., Boumis P., Goudis C

    Misiriotis A., Xilouris E. M., Papamastorakis J., Boumis P., Goudis C. D., 2006, @doi [ ] 10.1051/0004-6361:20054618 , https://ui.adsabs.harvard.edu/abs/2006A&A...459..113M 459, 113

  26. [36]

    J., Croton D

    Mutch S. J., Croton D. J., Poole G. B., 2011, @doi [ ] 10.1088/0004-637X/736/2/84 , https://ui.adsabs.harvard.edu/abs/2011ApJ...736...84M 736, 84

  27. [37]

    B., Abraham R

    Nair P. B., Abraham R. G., 2010, @doi [ ] 10.1088/0067-0049/186/2/427 , https://ui.adsabs.harvard.edu/abs/2010ApJS..186..427N 186, 427

  28. [38]

    C., 2009, @doi [ ] 10.1051/0004-6361/200912497 , https://ui.adsabs.harvard.edu/abs/2009A&A...507.1793N 507, 1793

    Noll S., Burgarella D., Giovannoli E., Buat V., Marcillac D., Mu \ n oz-Mateos J. C., 2009, @doi [ ] 10.1051/0004-6361/200912497 , https://ui.adsabs.harvard.edu/abs/2009A&A...507.1793N 507, 1793

  29. [39]

    H., Kerr F

    Oort J. H., Kerr F. J., Westerhout G., 1958, @doi [ ] 10.1093/mnras/118.4.379 , https://ui.adsabs.harvard.edu/abs/1958MNRAS.118..379O 118, 379

  30. [40]

    Robotham A. S. G., et al., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21332.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.424.1448R 424, 1448

  31. [41]

    Salim S., et al., 2016, @doi [ ] 10.3847/0067-0049/227/1/2 , https://ui.adsabs.harvard.edu/abs/2016ApJS..227....2S 227, 2

  32. [42]

    C., 2018, @doi [ ] 10.3847/1538-4357/aabf3c , https://ui.adsabs.harvard.edu/abs/2018ApJ...859...11S 859, 11

    Salim S., Boquien M., Lee J. C., 2018, @doi [ ] 10.3847/1538-4357/aabf3c , https://ui.adsabs.harvard.edu/abs/2018ApJ...859...11S 859, 11

  33. [43]

    T., Patton D

    Simard L., Mendel J. T., Patton D. R., Ellison S. L., McConnachie A. W., 2011, @doi [ ] 10.1088/0067-0049/196/1/11 , https://ui.adsabs.harvard.edu/abs/2011ApJS..196...11S 196, 11

  34. [44]

    F., Biermann P., Mezger P

    Smith L. F., Biermann P., Mezger P. G., 1978, , https://ui.adsabs.harvard.edu/abs/1978A&A....66...65S 66, 65

  35. [45]

    Stoughton C., et al., 2002, @doi [ ] 10.1086/324741 , https://ui.adsabs.harvard.edu/abs/2002AJ....123..485S 123, 485

  36. [46]

    Wegg C., Gerhard O., Portail M., 2015, @doi [ ] 10.1093/mnras/stv745 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.4050W 450, 4050

  37. [47]

    L., et al., 1994, @doi [ ] 10.1086/187315 , https://ui.adsabs.harvard.edu/abs/1994ApJ...425L..81W 425, L81

    Weiland J. L., et al., 1994, @doi [ ] 10.1086/187315 , https://ui.adsabs.harvard.edu/abs/1994ApJ...425L..81W 425, L81

  38. [48]

    W., et al., 2004, @doi [ ] 10.1086/422992 , https://ui.adsabs.harvard.edu/abs/2004ApJS..154....1W 154, 1

    Werner M. W., et al., 2004, @doi [ ] 10.1086/422992 , https://ui.adsabs.harvard.edu/abs/2004ApJS..154....1W 154, 1

  39. [49]

    M., Pym B., Dubinski J., 2008, @doi [ ] 10.1086/587636 , https://ui.adsabs.harvard.edu/abs/2008ApJ...679.1239W 679, 1239

    Widrow L. M., Pym B., Dubinski J., 2008, @doi [ ] 10.1086/587636 , https://ui.adsabs.harvard.edu/abs/2008ApJ...679.1239W 679, 1239

  40. [50]

    W., et al., 2013, @doi [ ] 10.1093/mnras/stt1458 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.435.2835W 435, 2835

    Willett K. W., et al., 2013, @doi [ ] 10.1093/mnras/stt1458 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.435.2835W 435, 2835

  41. [51]

    L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

    Wright E. L., et al., 2010, @doi [ ] 10.1088/0004-6256/140/6/1868 , https://ui.adsabs.harvard.edu/abs/2010AJ....140.1868W 140, 1868

  42. [52]

    G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

    York D. G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

  43. [53]

    J., Dima G

    Zahid H. J., Dima G. I., Kewley L. J., Erb D. K., Dav \'e R., 2012, @doi [ ] 10.1088/0004-637X/757/1/54 , https://ui.adsabs.harvard.edu/abs/2012ApJ...757...54Z 757, 54

Pith tools

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