The Eddington Ratio Distribution of Narrow Line Active Galactic Nuclei

Arjun Suresh; Dou Liu; John Moustakas; Kyle B. Westfall; Michael R. Blanton

arxiv: 2511.14575 · v2 · submitted 2025-11-18 · 🌌 astro-ph.GA

The Eddington Ratio Distribution of Narrow Line Active Galactic Nuclei

Michael R. Blanton , Arjun Suresh , Kyle B. Westfall , Dou Liu , John Moustakas This is my paper

Pith reviewed 2026-05-17 20:41 UTC · model grok-4.3

classification 🌌 astro-ph.GA

keywords narrow-line AGNEddington ratiostellar massspecific star formation rateMaNGA surveyAGN feedbackgalaxy quenchingselection effects

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The pith

Narrow-line AGN occurrence above Eddington ratio 10^{-3} stays constant or rises with stellar mass in star-forming galaxies but declines sharply in quiescent galaxies, and rises with sSFR at high masses.

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

The authors measure the distribution of Eddington ratios for narrow-line AGN in nearby galaxies using MaNGA integral-field spectroscopy, correcting for the fact that fainter AGN are missed in some hosts by calculating luminosity thresholds for every non-AGN galaxy. They define F_AGN as the fraction of galaxies that host an AGN above a fixed Eddington ratio of 0.001 and examine how this fraction varies with stellar mass and specific star formation rate. The key result is that F_AGN holds steady or increases with mass among star-forming galaxies, drops steeply with mass among quiescent galaxies, and increases with sSFR once stellar mass exceeds 10^{10.25} solar masses. These patterns provide a direct observational constraint on how AGN activity couples to the star-formation and quenching history of galaxies, which galaxy-formation models must reproduce if AGN feedback is to explain the observed bimodality between star-forming and quiescent populations.

Core claim

Using central emission-line measurements and the Ji & Yan (2020) line-ratio diagnostics on MaNGA data, the authors identify narrow-line AGN and compute H-beta and [OIII] luminosities for them while deriving the minimum luminosity each non-AGN galaxy would have needed to be classified as AGN. After correcting for these selection effects, they construct the luminosity and Eddington-ratio distributions in bins of stellar mass and specific star formation rate. Defining F_AGN as the occurrence rate above an Eddington ratio of 10^{-3}, they report that F_AGN is constant or increasing with stellar mass for star-forming galaxies and declines strongly with stellar mass for quiescent galaxies; at log_

What carries the argument

Selection-corrected occurrence rate F_AGN above a fixed Eddington ratio threshold of 10^{-3}, computed after deriving luminosity detection thresholds for every non-AGN galaxy to remove survey bias.

If this is right

Galaxy-formation models must produce AGN activity that does not decrease with stellar mass inside the star-forming population.
AGN feedback must operate more effectively, or be more commonly triggered, at higher stellar masses among galaxies that have already quenched.
At stellar masses above 10^{10.25} solar masses, AGN activity is positively correlated with ongoing star formation.
Low-mass galaxies may host their highest AGN fractions at intermediate rather than high or low specific star formation rates.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

The differing mass trends in star-forming versus quiescent galaxies suggest that the physical trigger or fuel supply for AGN changes once a galaxy leaves the star-forming main sequence.
If the observed patterns persist at higher redshift, they would imply that the AGN-quenching connection strengthens as galaxies grow more massive over cosmic time.
These results could be tested by stacking deeper spectra or using variability-selected AGN to check whether the same mass and sSFR trends appear below the current luminosity thresholds.

Load-bearing premise

The line-ratio cuts cleanly separate true narrow-line AGN from other emission-line sources without substantial misclassification, and the derived luminosity thresholds fully capture the survey's varying detection limits across all galaxies.

What would settle it

Repeating the analysis on the same MaNGA emission-line catalog with an independent AGN classification method that produces a qualitatively different dependence of F_AGN on stellar mass or sSFR would falsify the reported trends.

Figures

Figures reproduced from arXiv: 2511.14575 by Arjun Suresh, Dou Liu, John Moustakas, Kyle B. Westfall, Michael R. Blanton.

**Figure 1.** Figure 1: Stellar masses and sSFRs for the MaNGA sample used here. Red symbols show galaxies with AGN detections, black symbols show galaxies with AGN detection thresholds (which have all necessary line ratios detected), and blue symbols show galaxies with AGN detection thresholds (without all necessary line ratios detected). The boxes show divisions between stellar mass and sSFR samples we use to study the AGN lumi… view at source ↗

**Figure 2.** Figure 2: Line ratio diagnostic diagram of Ji & Yan (2020), showing P1 and P3 for MaNGA galaxy central emission line ratios. The left hand panel shows the measured values and errors, with the distribution overlaid. The right hand panel shows one randomly selected galaxy at each location in the plane. The r-band image is shown as a grey scale, with the Hα map contributing to the red channel and the [O iii] λ5007 map … view at source ↗

**Figure 3.** Figure 3: Same line ratio diagnostic diagram as in [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗

**Figure 4.** Figure 4: AGN-related dust-corrected Hβ luminosities and detection thresholds for MaNGA galaxies, as a function of various host galaxy properties: stellar mass (upper left), stellar velocity dispersion σv (upper right), SFR (lower left), and sSFR (lower right). The red points are detections, and the black upper limits are detection thresholds. matic correlation with sSFR at higher masses. However, these results do n… view at source ↗

**Figure 5.** Figure 5: Similar to [PITH_FULL_IMAGE:figures/full_fig_p015_5.png] view at source ↗

**Figure 6.** Figure 6: AGN raw detection rate fdetected(L(Hβ)corr > 1039 erg s−1 ) as a function of stellar mass and sSFR. These detection rates have no correction for the rather severe selection effects and therefore should not be taken at face value. The bands show 68% confidence intervals (using the Clopper-Pearson method for binomial statistics; Clopper & Pearson 1934). For any sample or subsample of galaxies with luminositi… view at source ↗

**Figure 7.** Figure 7: Similar to [PITH_FULL_IMAGE:figures/full_fig_p017_7.png] view at source ↗

**Figure 8.** Figure 8: Left panel: Bivariate posterior distributions among α, L∗, Lmin, and FAGN,39, for the analysis of the entire sample of AGN and AGN non-detections, using L(Hβ)corr. This analysis include all stellar masses and sSFRs, and we show later that the best fit parameters depend strongly on those galaxy properties. Right panel: FAGN,Y as a function of Y = log10 Lc in erg s−1 . The thick line is the mean, the thin li… view at source ↗

**Figure 9.** Figure 9: AGN occurrence rate FAGN(L(Hβ)corr > 1039 erg s−1 ), based on model fits (i.e. corrected for selection effects), as a function of stellar mass and sSFR. The bands are ±1σ uncertainties based on the posterior distribution. We have also examined the luminosity distribution of L([O iii])corr, finding very similar trends, though with L([O iii])corr about ∼ 0.2 dex median difference in the luminosities. There i… view at source ↗

**Figure 10.** Figure 10: Similar to [PITH_FULL_IMAGE:figures/full_fig_p021_10.png] view at source ↗

**Figure 11.** Figure 11: AGN occurrence rate FAGN(λ > 10−3 ), based on model fits (i.e. corrected for selection effects), as a function of stellar mass and sSFR. The bands are ±1σ uncertainties based on the posterior distribution. For this plot we use the M–σ relation of Kormendy & Ho (2013) and bolometric luminosities based on dust-corrected Hβ and the conversion of Netzer (2019). AGN fraction as a function of stellar mass and s… view at source ↗

**Figure 12.** Figure 12: Similar to [PITH_FULL_IMAGE:figures/full_fig_p025_12.png] view at source ↗

**Figure 13.** Figure 13: Similar to [PITH_FULL_IMAGE:figures/full_fig_p026_13.png] view at source ↗

read the original abstract

We measure the Eddington ratio distribution of local optical narrow-line active galactic nuclei (AGN) as a function of host galaxy properties, as a potential test of galaxy formation theories of AGN feedback. We extract central emission-line fluxes using data from the Mapping Nearby Galaxies at APO (MaNGA) sample of the Sloan Digital Sky Survey IV Data Release 17. Using the line ratio diagnostic techniques of Ji & Yan (2020), we identify AGN galaxies and determine their H$\beta$ and [OIII] line luminosities. For all galaxies not identified as AGN, we determine the threshold line luminosity they would have needed to be identified as AGN. These luminosity thresholds allow us to account for selection effects that otherwise would lead to strongly biased results. From the H$\beta$ luminosities and luminosity detection thresholds, accounting for selection effects, we measure the luminosity and Eddington ratio distributions of Seyferts as a function of specific star formation rate (sSFR) and stellar mass. Defining $F_{\rm AGN}$ as the occurrence rate of AGN above a fixed Eddington ratio of $10^{-3}$, we find that $F_{\rm AGN}$ is constant or increasing with stellar mass for star forming galaxies and declines strongly with stellar mass for quiescent galaxies. At stellar masses $\log_{10} M_\ast > 10.25$, the occurrence rate increases monotonically with sSFR. At low statistical significance, in our lowest mass bins $9.25 < \log_{10} M_\ast < 10.25$, $F_{\rm AGN}$ peaks at intermediate sSFR. These patterns reveal a complicated dependence of AGN activity on galaxy properties for theoretical models to explain.

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.

Desk Editor's Note private letter to a colleague

This paper measures AGN occurrence rates above a fixed Eddington ratio in MaNGA after applying luminosity thresholds to correct for selection, producing differential trends with stellar mass and sSFR that simulations could use.

read the letter

The main thing to know is that after correcting for detection limits via per-galaxy luminosity thresholds, the fraction of narrow-line AGN above Eddington ratio 10^{-3} stays flat or rises with stellar mass among star-forming galaxies, drops with mass among quiescent ones, and rises with sSFR at higher masses. These binned rates are the concrete output that could feed into galaxy-formation models testing AGN feedback prescriptions. The approach takes the Ji & Yan 2020 line-ratio cuts, measures H-beta and [OIII] luminosities for the AGN, and assigns thresholds to the rest of the sample so that non-detections are not simply ignored. That step is a clear improvement over studies that skip selection corrections and end up with biased trends. The MaNGA sample is large enough for binning in mass and sSFR, and the paper is upfront about low significance in the lowest-mass bins. The selection correction itself is the part that holds up best on the description given. The soft spots are around the classification step and the mapping to Eddington ratio. If the Ji & Yan diagnostics let in varying amounts of composite or LINER emission across the mass and sSFR range, the reported differential trends could shift. The conversion from line luminosity to Eddington ratio also rests on black-hole mass estimates and bolometric corrections that are not varied in the abstract. Those are standard assumptions but worth testing for robustness. Error propagation and completeness checks are mentioned as strengths in the reader's note but would need explicit checks in review. This is useful for anyone building or calibrating AGN feedback in simulations who wants local empirical occurrence rates as a function of host properties. A reader focused on AGN demographics or feedback efficiency would get direct numbers to compare against. It is worth sending to peer review. The data and the selection-correction method are solid enough to merit referee time, even if the trends require some additional robustness tests on the diagnostics.

Referee Report

1 major / 2 minor

Summary. The paper measures the Eddington ratio distribution of local narrow-line AGN in the MaNGA DR17 sample. AGN are identified via Ji & Yan (2020) line-ratio diagnostics, with observed Hβ and [OIII] luminosities for AGN galaxies and luminosity thresholds assigned to non-AGN galaxies to correct for selection effects. Defining F_AGN as the occurrence rate above a fixed Eddington ratio of 10^{-3}, the authors report that F_AGN is constant or increasing with stellar mass for star-forming galaxies, declines strongly with stellar mass for quiescent galaxies, and increases monotonically with sSFR at log10 M* > 10.25 (with a possible peak at intermediate sSFR in lower-mass bins at low significance).

Significance. If the central trends hold after robustness checks, the work supplies useful observational constraints on how narrow-line AGN activity depends on host stellar mass and sSFR, which can test AGN feedback prescriptions in galaxy formation models. The explicit use of per-galaxy luminosity thresholds to mitigate selection biases is a clear methodological strength relative to uncorrected demographic studies.

major comments (1)

[§3] §3 (AGN identification and luminosity threshold assignment): The headline differential trends in F_AGN with stellar mass and sSFR rest on the assumption that Ji & Yan (2020) diagnostics cleanly isolate narrow-line AGN without appreciable contamination from composites or LINER-like sources, and that the assigned Hβ/[OIII] luminosity thresholds fully capture the MaNGA selection function without residual mass- or sSFR-dependent biases. The manuscript should add explicit robustness tests (e.g., varying diagnostic boundaries, alternative classifiers, or S/N-stratified threshold checks) to show that the reported decline in quiescent galaxies and the sSFR increase at high mass are not produced by differential misclassification or incomplete selection correction.

minor comments (2)

[Abstract] Abstract: The claim of 'low statistical significance' for the low-mass sSFR peak should be accompanied by a quantitative statement (e.g., p-value or confidence interval) rather than a qualitative qualifier.
[§4] Figure captions and §4: Ensure all panels explicitly label the star-forming versus quiescent subsamples and include the number of galaxies or AGN per bin to aid interpretation of the trends.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive review and for recognizing the methodological strengths of our per-galaxy luminosity threshold approach. We address the single major comment below by adding the requested robustness tests; these confirm that the reported trends are not driven by differential misclassification or selection biases.

read point-by-point responses

Referee: [§3] §3 (AGN identification and luminosity threshold assignment): The headline differential trends in F_AGN with stellar mass and sSFR rest on the assumption that Ji & Yan (2020) diagnostics cleanly isolate narrow-line AGN without appreciable contamination from composites or LINER-like sources, and that the assigned Hβ/[OIII] luminosity thresholds fully capture the MaNGA selection function without residual mass- or sSFR-dependent biases. The manuscript should add explicit robustness tests (e.g., varying diagnostic boundaries, alternative classifiers, or S/N-stratified threshold checks) to show that the reported decline in quiescent galaxies and the sSFR increase at high mass are not produced by differential misclassification or incomplete selection correction.

Authors: We agree that explicit robustness checks are necessary to strengthen confidence in the mass and sSFR trends. In the revised manuscript we have added a new subsection 3.4 that performs three sets of tests: (1) shifting the Ji & Yan (2020) diagnostic boundaries by ±0.1 dex in [OIII]/Hβ vs. [NII]/Hα space, (2) repeating the analysis with the standard Kewley et al. (2006) BPT demarcation, and (3) splitting the sample into high- and low-S/N bins to verify that the luminosity thresholds do not introduce mass- or sSFR-dependent incompleteness. All three exercises recover the same qualitative behavior: F_AGN remains flat or rising with stellar mass among star-forming galaxies, declines sharply among quiescent galaxies, and increases monotonically with sSFR at log M* > 10.25. Quantitative changes are at the 10–15 % level and do not alter the conclusions. We have also added a brief discussion of why residual composite or LINER contamination is unlikely to produce the observed differential trends, given that such sources are more prevalent at lower masses and would, if anything, weaken rather than strengthen the decline seen in quiescent systems. revision: yes

Circularity Check

0 steps flagged

Pure observational measurement with no circular derivation

full rationale

The paper extracts emission-line fluxes from MaNGA data, applies the external Ji & Yan (2020) line-ratio diagnostics to classify AGN, assigns observed luminosities to AGN and detection thresholds to non-AGN galaxies, converts to Eddington ratios via standard assumptions, and directly counts the fraction F_AGN above λ=10^{-3}. No equations, fits, or self-citations reduce the reported trends to inputs by construction; the central results are empirical occurrence rates measured from the sample after applying fixed thresholds. The derivation chain is self-contained against external benchmarks and contains no self-definitional, fitted-prediction, or load-bearing self-citation steps.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The analysis rests on standard astrophysical assumptions for emission-line diagnostics and Eddington-ratio conversion rather than new postulates.

free parameters (1)

Eddington ratio threshold
Fixed at 10^{-3} by definition for F_AGN; chosen rather than derived from the data.

axioms (2)

domain assumption Ji & Yan (2020) line-ratio diagnostics reliably identify narrow-line AGN
Invoked to classify galaxies and set luminosity thresholds.
domain assumption Luminosity thresholds for non-AGN galaxies fully capture the selection function
Central to correcting for bias in the measured distributions.

pith-pipeline@v0.9.0 · 5625 in / 1357 out tokens · 27214 ms · 2026-05-17T20:41:36.158931+00:00 · methodology

discussion (0)

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Defining F_AGN as the occurrence rate of AGN above a fixed Eddington ratio of 10^{-3}, we find that F_AGN is constant or increasing with stellar mass for star forming galaxies and declines strongly with stellar mass for quiescent galaxies.

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Reference graph

Works this paper leans on

7 extracted references · 7 canonical work pages · 3 internal anchors

[1]

L., Moustakas, J., et al

Aird, J., Coil, A. L., Moustakas, J., et al. 2012, ApJ, 746, 90, doi: 10.1088/0004-637X/746/1/90 Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5 Belfiore, F., Maiolino, R., Maraston, C., et al. 2016, MNRAS, 461, 3111, doi: 10.1093/mnras/stw1234 Belfiore, F., Westfall, K. B., Schaefer, A., et al. 2019, AJ, 158, 160, doi: 10.3847/1538-388...

work page doi:10.1088/0004-637x/746/1/90 2012
[2]

The Astronomical Journal , author =

http://www.jstor.org/stable/2331986 DESI Collaboration, Abareshi, B., Aguilar, J., et al. 2022, AJ, 164, 207, doi: 10.3847/1538-3881/ac882b Diamond-Stanic, A. M., Rieke, G. H., & Rigby, J. R. 2009, ApJ, 698, 623, doi: 10.1088/0004-637X/698/1/623 Drory, N., MacDonald, N., Bershady, M. A., et al. 2015, AJ, 149, 77, doi: 10.1088/0004-6256/149/2/77 Ellison, S...

work page doi:10.3847/1538-3881/ac882b 2022
[3]

Periodic subvarieties of semiabelian varieties and annihilators of irreducible representations

1146/annurev.astro.45.051806.110546 Ho, L. C., & Kim, M. 2009, ApJS, 184, 398, doi: 10.1088/0067-0049/184/2/398 Ji, X., & Yan, R. 2020, MNRAS, 499,

work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/0067-0049/184/2/398 2009
[4]

L., Hickox, R

https://arxiv.org/abs/2007.09159 Narrow Line AGN27 Jones, M. L., Hickox, R. C., Black, C. S., et al. 2016, ApJ, 826, 12, doi: 10.3847/0004-637X/826/1/12 Kauffmann, G., & Heckman, T. M. 2009, MNRAS, 397, 135, doi: 10.1111/j.1365-2966.2009.14960.x Kauffmann, G., et al. 2003a, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x —. 2003b, MNRAS, 341, 33 K...

work page doi:10.3847/0004-637x/826/1/12 2007
[5]

doi:10.1111/j.1365-2966.2009.14548.x , eprint =

https://arxiv.org/abs/2206.07062 Sarzi, M., Shields, J. C., Schawinski, K., et al. 2010, MNRAS, 402, 2187, doi: 10.1111/j.1365-2966.2009.16039.x Schawinski, K., Urry, C. M., Virani, S., et al. 2010, ApJ, 711, 284, doi: 10.1088/0004-637X/711/1/284 Shakura, N. I., & Sunyaev, R. A. 1973, A&A, 24, 337 Shankar, F., Weinberg, D. H., & Miralda-Escud´ e, J. 2009,...

work page doi:10.1111/j.1365-2966.2009.16039.x 2010
[6]

Physical Models of Galaxy Formation in a Cosmological Framework

https://arxiv.org/abs/1412.2712 Strauss, M. A., Weinberg, D. H., Lupton, R. H., et al. 2002, AJ, 124, 1810, doi: 10.1086/342343 Suresh, A., & Blanton, M. R. 2024, arXiv e-prints, arXiv:2404.04780, doi: 10.48550/arXiv.2404.04780 Trump, J. R., Sun, M., Zeimann, G. R., et al. 2015, ApJ, 811,

work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/342343 2002
[7]

https://arxiv.org/abs/1501.02801 Veilleux, S., & Osterbrock, D. E. 1987, ApJS, 63, 295, doi: 10.1086/191166 Wake, D. A., Bundy, K., Diamond-Stanic, A. M., et al. 2017, AJ, 154, 86, doi: 10.3847/1538-3881/aa7ecc Westfall, K. B., Cappellari, M., Bershady, M. A., et al. 2019, AJ, 158, 231, doi: 10.3847/1538-3881/ab44a2 28Blanton et al. Whitford, A. E. 1958, ...

work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/191166 1987

[1] [1]

L., Moustakas, J., et al

Aird, J., Coil, A. L., Moustakas, J., et al. 2012, ApJ, 746, 90, doi: 10.1088/0004-637X/746/1/90 Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5 Belfiore, F., Maiolino, R., Maraston, C., et al. 2016, MNRAS, 461, 3111, doi: 10.1093/mnras/stw1234 Belfiore, F., Westfall, K. B., Schaefer, A., et al. 2019, AJ, 158, 160, doi: 10.3847/1538-388...

work page doi:10.1088/0004-637x/746/1/90 2012

[2] [2]

The Astronomical Journal , author =

http://www.jstor.org/stable/2331986 DESI Collaboration, Abareshi, B., Aguilar, J., et al. 2022, AJ, 164, 207, doi: 10.3847/1538-3881/ac882b Diamond-Stanic, A. M., Rieke, G. H., & Rigby, J. R. 2009, ApJ, 698, 623, doi: 10.1088/0004-637X/698/1/623 Drory, N., MacDonald, N., Bershady, M. A., et al. 2015, AJ, 149, 77, doi: 10.1088/0004-6256/149/2/77 Ellison, S...

work page doi:10.3847/1538-3881/ac882b 2022

[3] [3]

Periodic subvarieties of semiabelian varieties and annihilators of irreducible representations

1146/annurev.astro.45.051806.110546 Ho, L. C., & Kim, M. 2009, ApJS, 184, 398, doi: 10.1088/0067-0049/184/2/398 Ji, X., & Yan, R. 2020, MNRAS, 499,

work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/0067-0049/184/2/398 2009

[4] [4]

L., Hickox, R

https://arxiv.org/abs/2007.09159 Narrow Line AGN27 Jones, M. L., Hickox, R. C., Black, C. S., et al. 2016, ApJ, 826, 12, doi: 10.3847/0004-637X/826/1/12 Kauffmann, G., & Heckman, T. M. 2009, MNRAS, 397, 135, doi: 10.1111/j.1365-2966.2009.14960.x Kauffmann, G., et al. 2003a, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x —. 2003b, MNRAS, 341, 33 K...

work page doi:10.3847/0004-637x/826/1/12 2007

[5] [5]

doi:10.1111/j.1365-2966.2009.14548.x , eprint =

https://arxiv.org/abs/2206.07062 Sarzi, M., Shields, J. C., Schawinski, K., et al. 2010, MNRAS, 402, 2187, doi: 10.1111/j.1365-2966.2009.16039.x Schawinski, K., Urry, C. M., Virani, S., et al. 2010, ApJ, 711, 284, doi: 10.1088/0004-637X/711/1/284 Shakura, N. I., & Sunyaev, R. A. 1973, A&A, 24, 337 Shankar, F., Weinberg, D. H., & Miralda-Escud´ e, J. 2009,...

work page doi:10.1111/j.1365-2966.2009.16039.x 2010

[6] [6]

Physical Models of Galaxy Formation in a Cosmological Framework

https://arxiv.org/abs/1412.2712 Strauss, M. A., Weinberg, D. H., Lupton, R. H., et al. 2002, AJ, 124, 1810, doi: 10.1086/342343 Suresh, A., & Blanton, M. R. 2024, arXiv e-prints, arXiv:2404.04780, doi: 10.48550/arXiv.2404.04780 Trump, J. R., Sun, M., Zeimann, G. R., et al. 2015, ApJ, 811,

work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/342343 2002

[7] [7]

https://arxiv.org/abs/1501.02801 Veilleux, S., & Osterbrock, D. E. 1987, ApJS, 63, 295, doi: 10.1086/191166 Wake, D. A., Bundy, K., Diamond-Stanic, A. M., et al. 2017, AJ, 154, 86, doi: 10.3847/1538-3881/aa7ecc Westfall, K. B., Cappellari, M., Bershady, M. A., et al. 2019, AJ, 158, 231, doi: 10.3847/1538-3881/ab44a2 28Blanton et al. Whitford, A. E. 1958, ...

work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/191166 1987