REVIEW 3 major objections 4 minor 1 cited by
Watching our Galaxy Grow Up: The Mass and Color Evolution of the Milky Way
T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash
Pith's one-line read This paper derives the Milky Way's integrated stellar mass and optical colors from measured densities of stellar populations of all ages, runs the clock backward to earlier redshifts, and argues from simulated analogs that the Galaxy…
desk verdict Genuinely new empirical MW mass-color track and interesting TNG50 comparison, but the early-assembly claim needs a significance test and robustness analysis. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The central object is the MAAP: a mono-age and -abundance population, whose spatial density profile is parameterized as a broken exponential in radius and a flaring exponential in height, fitted to a large spectroscopic sample with an explicit selection-function model. The machinery combines these profiles with stellar isochrones and an assumed initial mass function to convert star counts to masses, extends them to ages below 1 Gyr using a star-formation-rate density profile, replaces unstable inner-Galaxy fits with a capped value at 2.5 kpc, smooths unfitted regions in the age-metallicity plane, and splits each coarse age bin into 0.1 Gyr fine bins. 'Running the clock backward' subtracts a lookback time from each MAAP, discards populations not yet formed, recomputes single-burst magnitudes at the new age and fixed metallicity, and sums the survivors to produce integrated masses and colors at any redshift. The same track then defines mass-color analogs in a cosmological simulation, whose merger trees are followed forward and backward to compare assembly histories.
What would settle it
Measure the stellar mass within R~2.5 kpc of the Galactic center with an independent, selection-function-corrected dataset (for example, deep near-infrared photometry with Gaia parallaxes) and compare it to the mass implied by the capped MAAP profiles; a discrepancy larger than the adopted ~30% uncertainty would shift the integrated mass, colors, and the inferred early-assembly fraction.
Extended reading notes
Core claim
The paper's central claim is that the Milky Way is an early assembler: by z~1-1.5 it already contained a larger fraction of its present-day stellar mass than do comparable-mass galaxies today, and its star formation since then has been relatively subdued. The evidence comes from integrating ~3300 fine-binned mono-age and -abundance population profiles to get present-day mass and color, then subtracting lookback age from each population to produce a complete mass-color track. Matching that track in a cosmological simulation shows that galaxies selected as analogs of the present-day Milky Way follow a similar evolutionary path, only delayed in time, while galaxies selected as analogs of the early Milky Way scatter into many different outcomes, with a large fraction becoming smaller and redder than the real Galaxy by z=0. The paper thus argues that the Milky Way's early appearance did not determine its later fate.
Load-bearing premise
The corrected MAAP density profiles—including the zeroed, smoothed, and inner-Galaxy-capped values—correctly represent the intrinsic stellar mass distribution of the Milky Way across all ages, metallicities, and alpha abundances.
Editorial extensions
If this is right
- The Milky Way has likely been in the green valley for only about 1–2 Gyr, so its current transitional color is a recent development rather than a long-term state.
- Present-day analogs in the simulation had assembled much less of their stellar mass by z~1, implying the real Galaxy is early relative to its mass cohort.
- Galaxies that look like the Milky Way at z=1–1.5 do not usually end up as Milky Way-like today; 41% of the z=1.5 analogs are already smaller and redder than the present-day Milky Way.
- The stellar populations of the two largest past merger remnants contribute less than 5 millimagnitudes to the integrated color evolution, so merger debris has no detectable effect on the mass-color track.
- Mass- and light-weighted metallicity distributions and star formation histories can now be extracted for arbitrary regions of the Galaxy, enabling direct comparisons with extragalactic surveys.
Reading between the lines
- If the early-assembly claim survives more direct probes, the Milky Way becomes a nearby laboratory for testing inside-out quenching and the mechanisms that move galaxies through the green valley without morphological disruption.
- The de-aging procedure could be applied to future wide-area surveys with better inner-Galaxy coverage to test the capping correction directly and refine the assembly fraction.
- Because integrated color is insensitive to the merger debris (below 5 mmag), light alone cannot reveal a Milky-Way-like merger history; chemical tagging and kinematics remain the discriminating tools.
- The mass-color matching used to define analogs could be extended to include star formation rate or environment to test whether the early-MW analogs that stay Milky Way-like are distinguished by some other property at z>1.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper presents a new empirical method for inferring the present-day and time-resolved integrated stellar mass and colors of the Milky Way from mono-age and -abundance population (MAAP) density profiles based on APOGEE DR17 data. The authors combine these MAAPs with PARSEC isochrones and a Kroupa IMF to compute masses and integrated magnitudes, apply ad hoc gap-filling and smoothing to the ~48% of MAAP bins without converged fits, and "de-age" the populations to reconstruct the MW's past mass and color evolution. They compare this empirical track to TNG50 subhaloes selected as mass-color analogs at several redshifts, and from this comparison claim strong evidence that the MW assembled a larger fraction of its stellar mass prior to z~1-1.5 than typical present-day analogs, that present-day analogs follow a similar growth history at slightly later times, and that analogs of the early MW are not guaranteed to evolve into MW-like galaxies today.
Significance. If the central result holds, this would be a valuable demonstration of using resolved stellar populations within the MW to place the Galaxy on extragalactic scaling relations and evolutionary tracks, complementing previous analog-based approaches. The paper's strengths include the explicit use of selection-function-corrected APOGEE data, the careful treatment of stellar evolution and remnant masses, the cross-checks of present-day mass and colors against Licquia & Newman (2015) and Fielder et al. (2021), the MDF comparisons to Rojas-Arriagada et al. (2020) and others, and the use of a large independent cosmological simulation (TNG50) for the analog comparison. However, the central early-assembly claim rests on several ad hoc steps in the MAAP reconstruction, and the "strong evidence" language in the abstract is not backed by a quantitative significance test. These issues are substantial enough that the result, while plausible, is not yet established to the standard implied by the abstract.
major comments (3)
- [§6.2, Fig. 10] The claim of "strong evidence" for earlier-than-average stellar mass assembly is not supported by any quantitative significance test. Figure 10 shows the MW's cumulative M*(z)/M*(0) lying above the median TNG50 analog tracks, but the shaded regions show only the absolute median deviation of the analog population, not the uncertainty on the MW track itself. The paper does not report the distribution of analog cumulative fractions at z=1 or z=1.5, nor the probability that a random analog would lie at or above the MW's value. Given that the MW track is itself uncertain (with ~30% mass uncertainties per MAAP and additional systematic choices described in §2.3), the abstract's "strong evidence" is not quantitatively justified. A Monte Carlo propagation of the MAAP mass uncertainties into the cumulative fraction, and a comparison with the analog distribution at fixed redshift, should be provided.
- [§2.3.2 and §2.3.3] The central early-assembly claim depends critically on the ad hoc treatment of the ~48% of MAAP bins without converged fits. Section 2.3.3 zeroes unfitted regions by visual inspection and then smooths log-masses in the age-metallicity plane with Gaussian kernels of different widths for low- and high-alpha populations, while §2.3.2 caps the inner-Galaxy density at R=2.5 kpc only for the [M/H]=+0.45, tau>2 Gyr bin. These choices directly set the mass in the old, metal-rich and old, metal-poor populations that dominate the z~1 mass budget. From Table 2, the z=1 cumulative fraction is approximately 10.19/10.59 ~ 0.40; plausible alternative reconstructions (e.g., capping all supersolar bins, using nearest-neighbor or Gaussian-process interpolation instead of zeroing+smoothing, or omitting the smoothing) could shift this fraction by several hundredths, comparable to the offset from the TNG50 median shown in Fig. 10. The paper should include robustness tests against such alternative reconstructions before claiming the offset is significant.
- [Footnote 9 and §5] The MAAPs exclude the stellar halo, which is old and would add to the early mass budget; footnote 9 explicitly notes this limitation, but the paper does not quantify its impact on the mass assembly history. Section 5 adds the Gaia-Enceladus progenitor and Sagittarius dwarf contributions (totaling ~2.1e9 Msun) and shows that their effect on colors is negligible, but the effect on the cumulative stellar mass at z~1-1.5 is not shown. Since the missing halo mass is predominantly old, omitting it biases the inferred early-time cumulative fraction. The authors should estimate the maximum plausible halo stellar mass (e.g., from literature values) and demonstrate that its inclusion or exclusion does not change the offset between the MW and TNG50 analogs.
minor comments (4)
- [§7, Summary] Typo: "investiage" should be "investigate".
- [§3.3] Typo: "psuedo-observables" should be "pseudo-observables".
- [§2.3.1] The sentence "the 'dip' in this P SFR profile inside ~5 kpc" contains a stray "P" before "SFR"; also the comparison of metallicity gradient values from Genovali et al. (2014), Wang et al. (2023), Balser et al. (2011), Esteban et al. (2017), Daflon & Cunha (2004), and Boardman et al. (2020b) would benefit from a table or a clear statement of which gradient is used for the adopted value of -0.04 dex/kpc.
- [§6.1] In footnote 15, the URL contains a typo: "subhhalos" should be "subhalos".
Circularity Check
No circular derivation: the MW track is empirical and compared against independent TNG50 simulations; the main caveats are data assumptions and same-author input, not circular reduction.
full rationale
The paper's derivation chain is not circular. The central input is a set of empirical MAAP density profiles (Sec. 2.2), attributed to the companion paper by J. Imig (in prep), a co-author. These profiles are fitted to APOGEE star counts and are an input data product, not a restatement of the paper's conclusions. The MW's present-day mass and colors are then computed by summing MAAP masses and SSP magnitudes (Secs. 2.4-2.6), and the 'de-aging' procedure in Sec. 4.1 is a bookkeeping of the same age distribution; it is a reconstruction, not an independent prediction. The key comparative claim about earlier-than-average stellar mass assembly is tested against TNG50 analogs (Secs. 6.1-6.2), and the MW properties are separately checked against external literature values (Licquia & Newman 2015; Licquia et al. 2015; Fielder et al. 2021; Rojas-Arriagada et al. 2020; etc.), so the main conclusion is not fitted from the comparison sample. The paper also transparently states its ad hoc choices: ~48% of MAAP bins lack converged fits, unfitted regions are set to zero by visual inspection and then Gaussian-smoothed (Sec. 2.3.3), the inner-Galaxy density is capped for only one supersolar bin (Sec. 2.3.2), and the MAAPs exclude the stellar halo (Footnote 9). These are robustness limitations and model assumptions that could shift the quantitative assembly history, but they do not make the derivation equivalent to its inputs by construction. The score of 2 reflects the load-bearing reliance on an unpublished same-author companion paper and the hand-tuned gap-filling, not a circular logical reduction.
Assumptions & free parameters
free parameters (7)
- Inner Galaxy density cap radius =
RGC < 2.5 kpc
- Gaussian smoothing scale, low-alpha MAAPs =
sigma=(0.5,0.5) in the (age, [M/H]) grid
- Gaussian smoothing scale, high-alpha MAAPs =
sigma=(0.25,0.25)
- Zeroed unfitted MAAP regions =
Specific [M/H]/age boxes listed in Sec. 2.3.3
- Young MAAP metallicity gradient =
-0.04 dex/kpc
- Face-on dust normalization =
E(B-V)=0.06 at the solar circle, plus AV=0.75 mag for tau<=0.5 Gyr
- TNG50 analog selection thresholds =
+/-0.2 dex in stellar mass and +/-0.15 dex in (g-r)0 color
assumptions (7)
- domain assumption The J. Imig (in prep) MAAP density profiles correctly describe the intrinsic spatial distribution of MW stellar populations after APOGEE selection-function correction.
- domain assumption PARSEC isochrones and a Kroupa IMF correctly convert giant-branch star counts to stellar masses and SSP luminosities, and adopted initial-final mass relations give correct remnant masses.
- domain assumption DistMass age estimates are unbiased enough for 0.1 dex age bins; for low-metallicity high-alpha MAAPs the age distribution is assumed equal to that of the -0.65<[M/H]<-0.3 bin.
- domain assumption The MW's SFR over the past Gyr is constant and follows the Elia et al. (2022) radial profile, with a constant metallicity gradient of -0.04 dex/kpc.
- domain assumption When de-aging the MW, the present-day radial mass distribution of each MAAP and the present-day dust disk can be used at earlier times.
- domain assumption TNG50 subhalo stellar masses and dust-free colors are directly comparable, without offset correction, to the observationally derived MW masses and PARSEC colors.
- domain assumption The Galaxia synthetic Milky Way model is accurate enough to assert that the MAAP grid covers roughly 95% of MW stars.
Cite this review
Pith. "Pith review of Watching our Galaxy Grow Up: The Mass and Color Evolution of the Milky Way." pith.science (2026). https://pith.science/paper/SYJIIVF7
@misc{pith2026250717637,
author = {Pith},
title = {Pith review of: Watching our Galaxy Grow Up: The Mass and Color Evolution of the Milky Way},
year = {2026},
howpublished = {\url{https://pith.science/paper/SYJIIVF7}},
note = {Machine review of arXiv:2507.17637}
}
read the original abstract
Using our rich observations within the Milky Way to better understand galaxy evolution requires understanding what the Milky Way looks like "as a galaxy" -- that is, its "true" shape and abundance profiles (unskewed by observational biases), signatures of past mergers and significant accretion events, and even its total stellar mass and integrated SED, which have historically been difficult to constrain. We present a new approach to determining the Milky Way's integrated mass and colors, using recent measurements of the intrinsic density profiles of stellar populations spanning nearly 13 Gyr in time and 1.5 dex in metallicity (representing nearly all of the Galaxy's stars). We trace the evolution of the Milky Way in various diagnostic spaces, explore the impact of specific events on the present-day Milky Way's integrated properties, and use TNG50 simulations to identify "young" Galactic analogs and their eventual fates, compared to the real Milky Way's path. From the simulation comparisons, we find strong evidence for an earlier-than-average stellar mass assembly of the MW, and that present-day MW analogs follow a similar growth history, albeit at slightly later times; we also find that analogs of the early MW are in no way guaranteed to follow the MW's subsequent path. This empirical study offers new constraints on our "Galaxy as a galaxy" -- today and across cosmic time -- and on its place in the general galactic population.
Figures
Figures from the paper (7 more)
Forward citations
Cited by 1 Pith paper
-
A Galactic Self-Portrait: Density Structure and Integrated Properties of the Milky Way Disk
The Milky Way disk has a stellar mass of 52.7 billion solar masses, a 2.37 kpc scale length, and a present-day (g-r) color of 0.72, indicating a red spiral in the green valley for the last 3 Gyr.
Reference graph
Works this paper leans on
-
[1]
2022, ApJS, 259, 35
Abdurro’uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 35
2022
-
[2]
P., Alexandroff, R., Allende Prieto, C., et al
Ahn, C. P., Alexandroff, R., Allende Prieto, C., et al. 2014, ApJS, 211, 17
2014
-
[3]
F., Argudo-Fern´ andez, M., et al
Almeida, A., Anderson, S. F., Argudo-Fern´ andez, M., et al. 2023, ApJS, 267, 44
2023
-
[4]
X., et al
Anders, F., Chiappini, C., Santiago, B. X., et al. 2014, A&A, 564, A115 21
2014
-
[5]
S., et al
Anders, F., Chiappini, C., Rodrigues, T. S., et al. 2017, A&A, 597, A30
2017
-
[6]
2023, A&A, 678, A158
Anders, F., Gispert, P., Ratcliffe, B., et al. 2023, A&A, 678, A158
2023
-
[7]
E., Springel, V., White, S
Angulo, R. E., Springel, V., White, S. D. M., et al. 2012, MNRAS, 426, 2046 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123 Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, ApJ, 935, 167
2012
-
[8]
K., Balogh, M
Baldry, I. K., Balogh, M. L., Bower, R. G., et al. 2006, MNRAS, 373, 469
2006
Show all 156 references
-
[9]
S., Rood, R
Balser, D. S., Rood, R. T., Bania, T. M., & Anderson, L. D. 2011, ApJ, 738, 27
2011
-
[10]
J., Kay, S
Barnes, D. J., Kay, S. T., Bah´ e, Y. M., et al. 2017, MNRAS, 471, 1088
2017
-
[11]
L., Oelkers, R
Beaton, R. L., Oelkers, R. J., Hayes, C. R., et al. 2021, AJ, 162, 302
2021
-
[12]
2006, A&A, 446, L1
Montegriffo, P. 2006, A&A, 446, L1
2006
-
[13]
R., & Buonanno, R
Bellazzini, M., Ferraro, F. R., & Buonanno, R. 1999, MNRAS, 304, 633
1999
-
[14]
Deason, A. J. 2018, MNRAS, 478, 611
2018
-
[15]
2022, MNRAS, 514, 689
Belokurov, V., & Kravtsov, A. 2022, MNRAS, 514, 689
2022
-
[16]
B., Evans, N
Belokurov, V., Zucker, D. B., Evans, N. W., et al. 2006, ApJL, 642, L137
2006
-
[17]
2025, arXiv e-prints, arXiv:2505.01896
Bhattacharya, S., Arnaboldi, M., Kobayashi, C., Gerhard, O., & Saha, K. 2025, arXiv e-prints, arXiv:2505.01896
2025 arXiv
-
[18]
2016, ARA&A, 54, 529
Bland-Hawthorn, J., & Gerhard, O. 2016, ARA&A, 54, 529
2016
-
[19]
R., & Roweis, S
Blanton, M. R., & Roweis, S. 2007, AJ, 133, 734
2007
-
[20]
R., Bershady, M
Blanton, M. R., Bershady, M. A., Abolfathi, B., et al. 2017, AJ, 154, 28
2017
-
[21]
A., et al
Bonaca, A., Conroy, C., Cargile, P. A., et al. 2020, ApJL, 897, L18
2020
-
[22]
S., & Vaughan, Jr., A
Bowen, I. S., & Vaughan, Jr., A. H. 1973, ApOpt, 12, 1430
1973
-
[23]
2012, MNRAS, 427, 127
Bressan, A., Marigo, P., Girardi, L., et al. 2012, MNRAS, 427, 127
2012
-
[24]
A., Law, D
Bundy, K., Bershady, M. A., Law, D. R., et al. 2015, The Astrophysical Journal, 798, 7
2015
-
[25]
J., Fattahi, A., Callingham, T
Carrillo, A., Deason, A. J., Fattahi, A., Callingham, T. M., & Grand, R. J. J. 2024, MNRAS, 527, 2165
2024
-
[26]
C., Magnier, E
Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560
2016 arXiv
-
[27]
A., Rix, H.-W., et al
Chandra, V., Semenov, V. A., Rix, H.-W., et al. 2024, ApJ, 972, 112
2024
-
[28]
2025, arXiv e-prints, arXiv:2501.14089
Chen, B., Orkney, M., Ting, Y.-S., & Hayden, M. 2025, arXiv e-prints, arXiv:2501.14089
2025
-
[29]
2015, MNRAS, 452, 1068
Chen, Y., Bressan, A., Girardi, L., et al. 2015, MNRAS, 452, 1068
2015
-
[30]
2014, MNRAS, 444, 2525
Chen, Y., Girardi, L., Bressan, A., et al. 2014, MNRAS, 444, 2525
2014
-
[31]
R., Cunha, K., et al
Chou, M.-Y., Majewski, S. R., Cunha, K., et al. 2007, ApJ, 670, 346
2007
-
[32]
2012, Research in Astronomy and Astrophysics, 12, 1197
Cui, X.-Q., Zhao, Y.-H., Chu, Y.-Q., et al. 2012, Research in Astronomy and Astrophysics, 12, 1197
2012
-
[33]
O’Brien, M
Cunningham, T., Tremblay, P.-E., & W. O’Brien, M. 2024, MNRAS, 527, 3602
2024
-
[34]
2004, ApJ, 617, 1115
Daflon, S., & Cunha, K. 2004, ApJ, 617, 1115
2004
-
[35]
J., Fouesneau, M., Hogg, D
Dalcanton, J. J., Fouesneau, M., Hogg, D. W., et al. 2015, ApJ, 814, 3 de Boer, T. J. L., Belokurov, V., & Koposov, S. 2015, MNRAS, 451, 3489 De Silva, G. M., Freeman, K. C., Bland-Hawthorn, J., et al. 2015, MNRAS, 449, 2604
2015
-
[36]
J., Lang, D., et al
Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168
2019
-
[37]
M., Cunha, K., et al
Donor, J., Frinchaboy, P. M., Cunha, K., et al. 2020, AJ, 159, 199
2020
-
[38]
J., Weinberg, D
Eisenstein, D. J., Weinberg, D. H., Agol, E., et al. 2011, AJ, 142, 72
2011
-
[39]
2022, ApJ, 941, 162
Elia, D., Molinari, S., Schisano, E., et al. 2022, ApJ, 941, 162
2022
-
[40]
2017, MNRAS, 471, 987
Cipriano, L. 2017, MNRAS, 471, 987
2017
-
[41]
E., Garc ´ ıa-Rojas, J., et al
Esteban, C., M´ endez-Delgado, J. E., Garc ´ ıa-Rojas, J., et al. 2025, arXiv e-prints, arXiv:2501.13586
2025
-
[42]
M., Willmer, C
Faber, S. M., Willmer, C. N. A., Wolf, C., et al. 2007, ApJ, 665, 265
2007
-
[43]
2020, MNRAS, 497, 109
Casagrande, L. 2020, MNRAS, 497, 109
2020
-
[44]
2021, MNRAS, 508, 1489
Casagrande, L. 2021, MNRAS, 508, 1489
2021
-
[45]
E., Newman, J
Fielder, C. E., Newman, J. A., Andrews, B. H., et al. 2021, MNRAS, 508, 4459
2021
-
[46]
C., Rice, E
Filippazzo, J. C., Rice, E. L., Faherty, J., et al. 2015, ApJ, 810, 158 F¨ orster Schreiber, N. M., & Wuyts, S. 2020, ARA&A, 58, 661 22
2015
-
[47]
Frankel, N., Rix, H.-W., Ting, Y.-S., Ness, M., & Hogg, D. W. 2018, ApJ, 865, 96
2018
-
[48]
2019, ApJ, 884, 99
Frankel, N., Sanders, J., Rix, H.-W., Ting, Y.-S., & Ness, M. 2019, ApJ, 884, 99
2019
-
[49]
2019, Monthly Notices of the Royal Astronomical Society, 489, 5030 Gaia Collaboration, Vallenari, A., Brown, A
Fraser-McKelvie, A., Merrifield, M., & Arag´ on-Salamanca, A. 2019, Monthly Notices of the Royal Astronomical Society, 489, 5030 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A1
2019
-
[50]
2024, A&A, 687, A168
Gallart, C., Surot, F., Cassisi, S., et al. 2024, A&A, 687, A168
2024
-
[51]
Gallazzi, A., Charlot, S., Brinchmann, J., White, S. D. M., & Tremonti, C. A. 2005, MNRAS, 362, 41 Garc ´ ıa P´ erez, A. E., Allende Prieto, C., Holtzman, J. A., et al. 2016, AJ, 151, 144
2005
-
[52]
2014, A&A, 566, A37
Genovali, K., Lemasle, B., Bono, G., et al. 2014, A&A, 566, A37
2014
-
[53]
L., Wetzel, A., Bellardini, M
Graf, R. L., Wetzel, A., Bellardini, M. A., & Bailin, J. 2024, arXiv e-prints, arXiv:2402.15614
2024 arXiv
-
[54]
Grand, R. J. J., G´ omez, F. A., Marinacci, F., et al. 2017, MNRAS, 467, 179
2017
-
[55]
E., Siegmund, W
Gunn, J. E., Siegmund, W. A., Mannery, E. J., et al. 2006, AJ, 131, 2332
2006
-
[56]
Hammer, F., Puech, M., Chemin, L., Flores, H., & Lehnert, M. D. 2007, ApJ, 662, 322
2007
-
[57]
R., Bovy, J., Holtzman, J
Hayden, M. R., Bovy, J., Holtzman, J. A., et al. 2015, ApJ, 808, 132
2015
-
[58]
R., Majewski, S
Hayes, C. R., Majewski, S. R., Hasselquist, S., et al. 2020, ApJ, 889, 63
2020
-
[59]
2001, MNRAS, 325, 1365
Haywood, M. 2001, MNRAS, 325, 1365
2001
-
[60]
H., et al
Helmi, A., Babusiaux, C., Koppelman, H. H., et al. 2018, Nature, 563, 85
2018
-
[61]
P., Mackereth, J
Horta, D., Schiavon, R. P., Mackereth, J. T., et al. 2023, MNRAS, 520, 5671
2023
-
[62]
C., Sanderson, R., et al
Horta, D., Cunningham, E. C., Sanderson, R., et al. 2024, MNRAS, 527, 9810
2024
-
[63]
Hubble, E. P. 1929, ApJ, 69, 103
1929
-
[64]
Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90
2007
-
[65]
A., Gilmore, G., & Irwin, M
Ibata, R. A., Gilmore, G., & Irwin, M. J. 1994, Nature, 370, 194
1994
-
[66]
A., et al
Imig, J., Price, C., Holtzman, J. A., et al. 2023, ApJ, 954, 124
2023
-
[67]
2019, ApJL, 878, L11
Isern, J. 2019, ApJL, 878, L11
2019
-
[68]
I., Rich, R
Johnson, C. I., Rich, R. M., Simion, I. T., et al. 2022, MNRAS, 515, 1469 J¨ onsson, H., Holtzman, J. A., Allende Prieto, C., et al. 2020, AJ, 160, 120
2022
-
[69]
A., Kim, H., et al
Kahre, L., Walterbos, R. A., Kim, H., et al. 2018, ApJ, 855, 133
2018
-
[70]
A., Zasowski, G., Rix, H.-W., et al
Kollmeier, J. A., Zasowski, G., Rix, H.-W., et al. 2017, ArXiv e-prints
2017
-
[71]
2001, MNRAS, 322, 231 —
Kroupa, P. 2001, MNRAS, 322, 231 —. 2002, Science, 295, 82
2001
-
[72]
R., McKee, C
Krumholz, M. R., McKee, C. F., & Bland-Hawthorn, J. 2019, ARA&A, 57, 227
2019
-
[73]
A., Hillenbrand, L
Kuhn, M. A., Hillenbrand, L. A., Sills, A., Feigelson, E. D., & Getman, K. V. 2019, ApJ, 870, 32
2019
-
[74]
Kurtz, D. W. 2022, ARA&A, 60, 31
2022
-
[75]
N., & Gunn, J
Lackner, C. N., & Gunn, J. E. 2012, MNRAS, 421, 2277
2012
-
[76]
C., & Sarajedini, A
Layden, A. C., & Sarajedini, A. 2000, AJ, 119, 1760
2000
-
[77]
N., Moran, S
Leethochawalit, N., Kirby, E. N., Moran, S. M., Ellis, R. S., & Treu, T. 2018, ApJ, 856, 15
2018
-
[78]
Lane, R. R. 2023, Nature Astronomy
2023
-
[79]
2024, Nature Astronomy, doi: 10.1038/s41550-024-02315-7
Lian, J., Zasowski, G., Chen, B., et al. 2024, Nature Astronomy, doi: 10.1038/s41550-024-02315-7
2024 doi
-
[80]
2020, MNRAS, 497, 3557
Lian, J., Zasowski, G., Hasselquist, S., et al. 2020, MNRAS, 497, 3557
2020
-
[81]
C., & Newman, J
Licquia, T. C., & Newman, J. A. 2015, ApJ, 806, 96
2015
-
[82]
C., Newman, J
Licquia, T. C., Newman, J. A., & Bershady, M. A. 2016, ApJ, 833, 220
2016
-
[83]
C., Newman, J
Licquia, T. C., Newman, J. A., & Brinchmann, J. 2015, ApJ, 809, 96
2015
-
[84]
O., P´ erez-Villegas, A., et al
Limberg, G., Souza, S. O., P´ erez-Villegas, A., et al. 2022, ApJ, 935, 109
2022
-
[85]
J., D’Eugenio, F., Piotrowska, J
Looser, T. J., D’Eugenio, F., Piotrowska, J. M., et al. 2024, MNRAS, 532, 2832
2024
-
[86]
L., Minchev, I., Buck, T., et al
Lu, Y. L., Minchev, I., Buck, T., et al. 2024, MNRAS, 535, 392
2024
-
[87]
T., Crain, R
Mackereth, J. T., Crain, R. A., Schiavon, R. P., et al. 2018, MNRAS, 477, 5072
2018
-
[88]
T., Bovy, J., Schiavon, R
Mackereth, J. T., Bovy, J., Schiavon, R. P., et al. 2017, MNRAS, 471, 3057
2017
-
[89]
T., Schiavon, R
Mackereth, J. T., Schiavon, R. P., Pfeffer, J., et al. 2019, MNRAS, 482, 3426
2019
-
[90]
Ostheimer, J. C. 2003, ApJ, 599, 1082
2003
-
[91]
R., Schiavon, R
Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94
2017
-
[92]
2017, ApJ, 835, 77
Marigo, P., Girardi, L., Bressan, A., et al. 2017, ApJ, 835, 77
2017
-
[93]
2009, ApJ, 707, 250
Martig, M., Bournaud, F., Teyssier, R., & Dekel, A. 2009, ApJ, 707, 250
2009
-
[94]
2021, MNRAS, 508, 2458 23
Martig, M., Pinna, F., Falc´ on-Barroso, J., et al. 2021, MNRAS, 508, 2458 23
2021
-
[95]
T., Simard, L., Ellison, S
Mendel, J. T., Simard, L., Ellison, S. L., & Patton, D. R. 2013, MNRAS, 429, 2212
2013
-
[96]
J., Coil, A
Mendez, A. J., Coil, A. L., Lotz, J., et al. 2011, ApJ, 736, 110
2011
-
[97]
2018, MNRAS, 481, 1645
Minchev, I., Anders, F., Recio-Blanco, A., et al. 2018, MNRAS, 481, 1645
2018
-
[98]
J., Croton, D
Mutch, S. J., Croton, D. J., & Poole, G. B. 2011, ApJ, 736, 84
2011
-
[99]
2019, MNRAS, 488, 1235
Belokurov, V. 2019, MNRAS, 488, 1235
2019
-
[100]
2022, AJ, 164, 85
Myers, N., Donor, J., Spoo, T., et al. 2022, AJ, 164, 85
2022
-
[101]
P., Conroy, C., Bonaca, A., et al
Naidu, R. P., Conroy, C., Bonaca, A., et al. 2020, ApJ, 901, 48
2020
-
[102]
M., Schlaufman, K
Nataf, D. M., Schlaufman, K. C., Reggiani, H., & Hahn, I. 2024, arXiv e-prints, arXiv:2407.18307
2024 arXiv
-
[103]
C., Rushton, M., et al
Natale, G., Popescu, C. C., Rushton, M., et al. 2022, MNRAS, 509, 2339
2022
-
[104]
2016, PASA, 33, e022
Ness, M., & Freeman, K. 2016, PASA, 33, e022
2016
-
[105]
L., Holtzman, J
Nidever, D. L., Holtzman, J. A., Allende Prieto, C., et al. 2015, AJ, 150, 173
2015
-
[106]
Niederste-Ostholt, M., Belokurov, V., & Evans, N. W. 2012, MNRAS, 422, 207
2012
-
[107]
W., & Pe˜ narrubia, J
Niederste-Ostholt, M., Belokurov, V., Evans, N. W., & Pe˜ narrubia, J. 2010, ApJ, 712, 516
2010
-
[108]
2020, A&A, 637, A80
Shetrone, M. 2020, A&A, 637, A80
2020
-
[109]
Pagel, B. E. J., & Patchett, B. E. 1975, MNRAS, 172, 13
1975
-
[110]
2019, MNRAS, 485, 5666 —
Pastorelli, G., Marigo, P., Girardi, L., et al. 2019, MNRAS, 485, 5666 —. 2020, MNRAS, 498, 3283
2019
-
[111]
A., Bovy, J., Jaimungal, S., Frankel, N., & Leung, H
Patil, A. A., Bovy, J., Jaimungal, S., Frankel, N., & Leung, H. W. 2023, MNRAS, 526, 1997
2023
-
[112]
2015, Nature, 521, 192
Peng, Y., Maiolino, R., & Cochrane, R. 2015, Nature, 521, 192
2015
-
[113]
2019, MNRAS, 490, 3196
Pillepich, A., Nelson, D., Springel, V., et al. 2019, MNRAS, 490, 3196
2019
-
[114]
H., Elsworth, Y
Pinsonneault, M. H., Elsworth, Y. P., Tayar, J., et al. 2018, ApJS, 239, 32 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13
2018
-
[115]
2015, MNRAS, 448, 713
Portail, M., Wegg, C., Gerhard, O., & Martinez-Valpuesta, I. 2015, MNRAS, 448, 713
2015
-
[116]
J., Menten, K
Reid, M. J., Menten, K. M., Brunthaler, A., et al. 2014, ApJ, 783, 130
2014
-
[117]
2022, ApJ, 941, 45
Rix, H.-W., Chandra, V., Andrae, R., et al. 2022, ApJ, 941, 45
2022
-
[118]
C., Reyl´ e, C., Derri` ere, S., & Picaud, S
Robin, A. C., Reyl´ e, C., Derri` ere, S., & Picaud, S. 2003, A&A, 409, 523
2003
-
[119]
2020, MNRAS, 499, 1037
Rojas-Arriagada, A., Zasowski, G., Schultheis, M., et al. 2020, MNRAS, 499, 1037
2020
-
[120]
J., & Cassisi, S
Ruiz-Lara, T., Gallart, C., Bernard, E. J., & Cassisi, S. 2020, Nature Astronomy, 4, 965
2020
-
[121]
Russell, H. N. 1914, Nature, 93, 252 S´ anchez, S. F., Kennicutt, R. C., Gil de Paz, A., et al. 2012, A&A, 538, A8 S´ anchez, S. F., Barrera-Ballesteros, J. K., Lacerda, E., et al. 2022, ApJS, 262, 36
1914
-
[122]
A., Beaton, R
Santana, F. A., Beaton, R. L., Covey, K. R., et al. 2021, AJ, 162, 303
2021
-
[123]
B., Wetzel, A., El-Badry, K., et al
Santistevan, I. B., Wetzel, A., El-Badry, K., et al. 2020, MNRAS, 497, 747
2020
-
[124]
K., Schlafly, E
Saydjari, A. K., Schlafly, E. F., Lang, D., et al. 2023, ApJS, 264, 28
2023
-
[125]
M., Simmons, B
Schawinski, K., Urry, C. M., Simmons, B. D., et al. 2014, MNRAS, 440, 889
2014
-
[126]
F., & Finkbeiner, D
Schlafly, E. F., & Finkbeiner, D. P. 2011, ApJ, 737, 103
2011
-
[127]
F., Green, G
Schlafly, E. F., Green, G. M., Lang, D., et al. 2018, ApJS, 234, 39
2018
-
[128]
J., Johnson, J
Schlesinger, K. J., Johnson, J. A., Rockosi, C. M., et al. 2012, ApJ, 761, 160
2012
-
[129]
M., Basu, S., et al
Schou, J., Antia, H. M., Basu, S., et al. 1998, ApJ, 505, 390
1998
-
[130]
M., Kormendy, J., et al
Shen, J., Rich, R. M., Kormendy, J., et al. 2010, ApJL, 720, L72
2010
-
[131]
H., Dotter, A., Majewski, S
Siegel, M. H., Dotter, A., Majewski, S. R., et al. 2007, ApJL, 667, L57
2007
-
[132]
F., Cutri, R
Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163
2006
-
[133]
V., Bizyaev, D., Cunha, K., et al
Smith, V. V., Bizyaev, D., Cunha, K., et al. 2021, AJ, 161, 254
2021
-
[134]
D., Zari, E., Elia, D., et al
Soler, J. D., Zari, E., Elia, D., et al. 2023, A&A, 678, A95
2023
-
[135]
2015, MNRAS, 451, 4086
Spera, M., Mapelli, M., & Bressan, A. 2015, MNRAS, 451, 4086
2015
-
[136]
2023, A&A, 670, A109
Spitoni, E., Recio-Blanco, A., de Laverny, P., et al. 2023, A&A, 670, A109
2023
-
[137]
A., Imig, J., et al
Stone-Martinez, A., Holtzman, J. A., Imig, J., et al. 2024, AJ, 167, 73
2024
-
[138]
2014, MNRAS, 445, 4287
Tang, J., Bressan, A., Rosenfield, P., et al. 2014, MNRAS, 445, 4287
2014
-
[139]
2024, arXiv e-prints, arXiv:2412.12304 24
Thulasidharan, L., D’Onghia, E., Benjamin, R., et al. 2024, arXiv e-prints, arXiv:2412.12304 24
2024 arXiv
-
[140]
A., Heckman, T
Tremonti, C. A., Heckman, T. M., Kauffmann, G., et al. 2004, ApJ, 613, 898
2004
-
[141]
2020, MNRAS, 491, 5406
Trussler, J., Maiolino, R., Maraston, C., et al. 2020, MNRAS, 491, 5406
2020
-
[142]
2021, MNRAS, 501, 2279
Vasiliev, E., Belokurov, V., & Erkal, D. 2021, MNRAS, 501, 2279
2021
-
[143]
J., Shen, J., & Li, Z.-Y
Vickers, J. J., Shen, J., & Li, Z.-Y. 2021, ApJ, 922, 189
2021
-
[144]
E., et al
Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261
2020
-
[145]
2020, Nature Reviews Physics, 2, 42
Vogelsberger, M., Marinacci, F., Torrey, P., & Puchwein, E. 2020, Nature Reviews Physics, 2, 42
2020
-
[146]
2023, A&A, 674, A129
Wang, C., Yuan, H., Xiang, M., et al. 2023, A&A, 674, A129
2023
-
[147]
H., Holtzman, J
Weinberg, D. H., Holtzman, J. A., Hasselquist, S., et al. 2019, ApJ, 874, 102
2019
-
[148]
R., Hopkins, P
Wetzel, A. R., Hopkins, P. F., Kim, J.-h., et al. 2016, ApJL, 827, L23
2016
-
[149]
C., Hearty, F
Wilson, J. C., Hearty, F. R., Skrutskie, M. F., et al. 2019, PASP, 131, 055001
2019
-
[150]
2019, ApJ, 886, 154
Yang, C., Xue, X.-X., Li, J., et al. 2019, ApJ, 886, 154
2019
-
[151]
G., Adelman, J., Anderson, Jr., J
York, D. G., Adelman, J., Anderson, Jr., J. E., et al. 2000, AJ, 120, 1579
2000
-
[152]
2021, ApJ, 912, 106
Yu, Z., Li, J., Chen, B., et al. 2021, ApJ, 912, 106
2021
-
[153]
2023, A&A, 669, A10
Zari, E., Frankel, N., & Rix, H.-W. 2023, A&A, 669, A10
2023
-
[154]
A., Frinchaboy, P
Zasowski, G., Johnson, J. A., Frinchaboy, P. M., et al. 2013, AJ, 146, 81
2013
-
[155]
E., Chojnowski, S
Zasowski, G., Cohen, R. E., Chojnowski, S. D., et al. 2017, AJ, 154, 198
2017
-
[156]
2019, ApJ, 870, 138
Zasowski, G., Schultheis, M., Hasselquist, S., et al. 2019, ApJ, 870, 138
2019
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