REVIEW 3 major objections 5 minor 84 references
Mapping the Milky Way with Gaia Bp/Rp spectra II: The inner stellar halo traced by a large sample of blue horizontal branch stars
T0 review · 3 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash
Pith's one-line read A 44,552-star catalog shows the Milky Way's inner halo flattens toward the center.
desk verdict Useful full-sky BHB catalog from XP spectra, but the halo flattening trend rests on an untested all-sky completeness assumption and needs a direct broken-power-law comparison before I'd trust the single-slope claim. 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 carrying mechanism is the selection function $S_{\rm BHB}(l,b,G-G_{\rm RP},G) = S_{\rm XP}(l,b,G-G_{\rm RP},G)\, P_{\rm BHB}(G)$, which corrects the observed BHB counts to the complete Gaia photometric census, combined with a variable-flattening ellipsoid density model $\nu(r) = \nu_0 r^{-\alpha}$ with $r = \sqrt{R^2 + (Z/q(r))^2}$. The density is reconstructed along many lines of sight by kernel density estimation, weighted by the inverse selection function, and isodensity contours are fitted in Galactocentric polar coordinates so that $q$ is read off as a function of radius instead of being held fixed. The BHB absolute-magnitude--color relation supplies distances, and the $T_{\rm eff}$
What would settle it
Measure the BHB completeness separately in different sky regions using the available spectroscopic cross-matches (split by sky position or color) and re-derive $q(r)$ and $\alpha$; if $q \approx 0.4$ at 8 kpc or $\alpha = -4.65 \pm 0.04$ shifts beyond the quoted uncertainties when the sky-uniform assumption is relaxed, the reconstruction is contaminated. An independent complete spectroscopic sample to $G \approx 17$ in a few high-latitude fields would settle it directly.
Extended reading notes
Core claim
The paper's discovery is a new map of the inner stellar halo from 44,552 BHB candidates selected out of Gaia's Bp/Rp spectra. The selection combines synthetic broad-band $u,g,r$ and narrow-band CaHK photometry with a $T_{\rm eff}$-$\log g$ cut to reject blue stragglers and main-sequence stars, and the sample is accompanied by a selection function built from Gaia DR3 photometry. Using BHB absolute magnitudes calibrated with Gaia parallaxes, the authors convert the catalog into a three-dimensional density field, fitting isodensity contours with an ellipsoid whose vertical flattening $q$ is free to vary with radius. They find $q \approx 0.4$ at $r \approx 8$ kpc, growing to $q \approx 0.8$ at $
Load-bearing premise
The reconstruction assumes that, within each narrow bin of sky position, color, and magnitude, the fraction of BHB stars among the XP-spectra sample equals the fraction among all Gaia photometric stars, and that the BHB-selection completeness measured from roughly 3,000 spectroscopically confirmed cross-match stars applies uniformly across the whole sky and all colors.
Editorial extensions
If this is right
- The flat inner halo ($q \approx 0.4$ at 8 kpc) and rounder outer halo ($q \approx 0.8$ at 25 kpc) give a geometric constraint that models of Milky Way mass assembly must reproduce.
- With variable flattening, the inner-halo data are consistent with a single power law $\alpha \approx -4.65$, so broken power-law fits with break radii at 15--30 kpc may have been forced by assuming constant $q$.
- The catalog's selection function makes the sample ready for kinematic follow-up: combining these positions and distances with proper motions or future radial velocities can measure velocity anisotropy and enclosed mass in the inner halo.
- The measured completeness, roughly 90% at $G=14$ falling to 40% at $G=17$, implies that many more BHB stars remain in the XP spectra and that deeper low-resolution surveys should extend this mapping further out.
Reading between the lines
- One implication the authors leave implicit: if $q \approx 0.4$ at 8 kpc is real, a substantial flattened, disk-like old component may be mixed into the BHB population; a testable extension is to split the sample by metallicity or proper-motion anisotropy and re-fit $q(r)$ and $\alpha$ for each subset.
- A testable extension: apply the same variable-$q$, single-power-law procedure to RR Lyrae or K giants over the same 8--25 kpc volume; agreement at $\alpha \approx -4.6$ would indicate a common old-halo property, while disagreement would point to BHB-specific selection or distance systematics.
- The paper itself notes (Sections 2.3--2.4 and the Summary) that completeness falls to about 40% at $G \approx 17$ and that the catalog has no radial velocities; these self-stated limits are the main barriers to extending the density measurement outward and to dynamical modeling, and both are targets for deeper or follow-up spectroscopy.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper constructs a catalog of 44,552 high-latitude blue horizontal branch (BHB) candidates from Gaia DR3 Bp/Rp (XP) spectra, using synthetic SDSS ugr and Pristine CaHK photometry plus Teff-log g cuts. A selection function is derived from the Gaia DR3 photometric sample and a completeness correction estimated from 3,051 SEGUE cross-matched sources. The authors then fit the stellar halo density with non-parametric isodensity ellipses in bins of log10(nu), allowing a radially varying flattening q(r), and find q ~ 0.4 at r ~ 8 kpc rising to q ~ 0.8 at r ~ 25 kpc. For the full sample the radial profile is claimed to be a single power law with alpha = -4.80 +/- 0.06; after removing outliers with residual (nu - nu_fitting)/nu_fitting > 0.6, the authors report a smoother r-q relation and alpha = -4.65 +/- 0.04.
Significance. If the results are robust, this paper would provide a large, all-sky BHB catalog with a documented selection function, useful for many Galactic archaeology applications. The use of XP spectra to derive synthetic multi-band photometry and stellar parameters is a modern and promising approach, and the purity checks against SEGUE (95%) and LAMOST (89%) are valuable. The paper also includes a non-parametric flattening analysis that avoids assuming a fixed ellipsoid shape, which is a methodological strength. However, the central astrophysical claims depend on a completeness correction that is calibrated on a small, SEGUE-footprint subsample and assumed to be all-sky and color-independent, and the model validation includes a residual-based subsample cut that is partly circular. These issues need to be addressed before the quantitative flattening trend and power-law index can be accepted.
major comments (3)
- [Section 2.4, Eq. (6)] The headline density and shape results are obtained by applying S_BHB(l,b,G-GRP,G) = S_XP(l,b,G-GRP,G) * P_BHB(G), with P_BHB(G) calibrated from only 3,051 SEGUE cross-matched sources. The manuscript explicitly assumes P_BHB is independent of sky position and color. This is load-bearing: at a fixed Galactocentric radius, different lines of sight correspond to very different heliocentric distances and hence very different G values, so any error in P_BHB(G) acts as a direction-dependent weight that can distort the inferred q(r) as well as alpha. The quoted uncertainties in Table 1 and alpha = -4.65 +/- 0.04 in Fig. 9 are formal fitting errors only and do not include this completeness-calibration term. Please quantify the systematic uncertainty by, for example, reweighting with alternative P_BHB curves from photometric BHB catalogs or mock realizations, or demonstrate that plausible all-sky
- [Section 3, Figs. 10-12] The 'smooth halo' subsample is constructed by applying the cut (nu - nu_fitting)/nu_fitting < 0.6 to residuals from the initial model, and then the model is refit to this same subsample. This introduces a mild circularity in the validation: the improved residual distribution shown in Fig. 10 and the smoother r-q relation in Fig. 9 are partly guaranteed by the cut. The qualitative trend (q increasing with r) is already present for all BHB stars, so the main claim survives, but the quantitative claims based on the subsample (alpha = -4.65 +/- 0.04 and the reported q(r) polynomial) need out-of-sample validation, for example via cross-validation, fitting on the full sample and then applying the residual cut, or modeling known substructures separately.
- [Section 3, Fig. 9] The paper states that the radial density profile is 'best fit' by a single power law with alpha = -4.65 +/- 0.04, but no comparison is made with the broken power-law model that is standard in the halo literature and is itself discussed in the introduction. With q(r) as a free function, a broken power law may provide a comparable or better fit. Please report goodness-of-fit statistics for both models (e.g., chi^2/dof, AIC or BIC) or otherwise justify why the SPL is preferred. This is central to the claim that a variable flattening removes the need for a break radius.
minor comments (5)
- [Abstract and Section 2.2] There is a typo in the abstract: 'best fit with by a single power law' should be 'best fit by a single power law'. In Section 2.2, 'extent the fitting' should be 'extend the fitting'.
- [Section 2.4, Fig. 6] The y-axis label in the top panel of Fig. 6 reads 'Completeness/CSEGUE', which is not defined in the text; the ratio plotted is n_BHB(ours)/n_BHB(Barbosa) with C(SEGUE) assumed constant. Please clarify the label and explicitly state the assumed value or normalization of C(SEGUE).
- [Fig. 8] Two panels in Fig. 8 are labelled 'None' because no stars fall in those log10(nu) bins. Consider omitting these empty panels or explaining why they are included, as they are visually confusing.
- [Eq. (10)] The text says 'we setted Dmin = 0 kpc'; this should be 'we set Dmin = 0 kpc'.
- [Table 1] The caption uses superscripts a and b to denote the full BHB sample and the smooth-halo subsample, but the columns are not explicitly labeled in the table header. Adding explicit column headings such as 'All BHB' and 'Smooth halo' would improve readability.
Circularity Check
Mild circularity in the smooth-halo validation step; central halo-shape result remains independent.
-
other
[Section 3, p. 10, after Fig. 10 and before Fig. 12]
"To reduce the influence of the minor component, we applied a rough cut ofν−νfitting/νfitting < 0.6 and defined the remaining stars as the subsample of the smooth stellar halo. We then repeated the fitting process and presented the results for two representative bins in Figure 11."
The 'smooth halo' subsample is defined by the very model that is then refit: stars are retained only if (ν−ν_fitting)/ν_fitting < 0.6, where ν_fitting comes from the first ellipsoid+SPL fit. Removing the largest residuals and refitting the same model family guarantees, by construction, a narrower and more symmetric residual distribution; the paper's subsequent claim of 'a significant improvement in consistency' and a single-Gaussian residual (mean 0.05, σ=0.38) is therefore a self-consistency check rather than an independent validation. This does not create the main result: the q(r) flattening trend (q≈0.4 at r≈8 kpc to q≈0.8 at r≈25 kpc) and the steep SPL index are already present in the full-sample fit (Table 1, Fig. 9 blue), and the cleaned-sample index (α=-4.65±0.04) differs only modes
full rationale
The paper's central claims are fits to the data rather than derivations from first principles, so the circularity burden is low. The selection function S_BHB = S_XP × P_BHB uses an external Gaia XP selection function (gaiaunlimited) and a completeness factor P_BHB estimated from SEGUE cross-matches; the assumptions that P_BHB is sky- and color-independent are explicit limitations, not circular reductions. The MG–color calibration is anchored to Gaia parallaxes and the distance scale is then applied to the wider sample, which is standard self-calibration rather than circularity. The only mildly circular element is the 'smooth halo' subsample: stars are selected by their closeness to a first model fit, then the same model family is refit to that truncated sample and the residual improvement is reported as validation. This is partly self-fulfilling, but it is not load-bearing for the main q(r) trend, which already appears in the full-sample fit, and the quoted power-law indices differ only slightly before and after the cut. No self-citation uniqueness theorem or ansatz-smuggling is present. The score reflects the single mild self-referential validation step, not a fundamental circularity in the derivation.
Assumptions & free parameters
free parameters (10)
- CaHK ridgeline polynomial f(g-r) =
Eq. 1 coefficients: 0.83, -1.32, -1.45, 11.24
- log g - Teff separation line =
log g = 2e-4 * Teff + 1.6
- Teff selection bounds =
7200 < Teff < 12000 K
- MG absolute magnitude relations =
Quartic coefficients in Eq. 3 for P16, P50, P84
- Smooth-halo residual cutoff =
(nu - nu_fitting)/nu_fitting < 0.6
- Extrapolated flattening beyond r=23 kpc =
q = 0.80 (or 0.81)
- Power-law index and normalization =
alpha = -4.65 +/- 0.04, nu0
- q(r) polynomial coefficients =
Not quoted in text
- Isodensity bin size =
0.1 in log10(nu)
- Distance uncertainty sigma_Di =
(D84 - D16)/2 from MG quartiles
assumptions (9)
- domain assumption BHB stars are standard candles with near-constant absolute magnitude
- domain assumption r_BHB,XP = r_BHB,ph (no type-dependent selection in XP spectra within bins)
- domain assumption P_BHB estimated from SEGUE common sources is sky- and color-independent
- domain assumption SEGUE catalog is nearly complete (C(SEGUE) ~ 1) for g < 19
- domain assumption Stellar halo is axisymmetric and described by oblate ellipsoids with a single q at each radius
- domain assumption SFD dust map and ccm89 extinction law with Rv=3.1 apply to all target stars
- domain assumption nsc3 synthetic spectral library covers the parameter space of BHB stars
- domain assumption Gaia XP spectra have no significant systematics for G > 11.5
- standard math The distance distribution is Gaussian for KDE
Cite this review
Pith. "Pith review of Mapping the Milky Way with Gaia Bp/Rp spectra II: The inner stellar halo traced by a large sample of blue horizontal branch stars." pith.science (2026). https://pith.science/paper/SNOS3NZJ
@misc{pith2026250808784,
author = {Pith},
title = {Pith review of: Mapping the Milky Way with Gaia Bp/Rp spectra II: The inner stellar halo traced by a large sample of blue horizontal branch stars},
year = {2026},
howpublished = {\url{https://pith.science/paper/SNOS3NZJ}},
note = {Machine review of arXiv:2508.08784}
}
abstract
We selected BHB stars based on synthetic photometry and stellar atmosphere parameters inferred from Gaia Bp/Rp spectra. We generated the synthetic SDSS broad-band $ugr$ and Pristine narrow-band CaHK magnitudes from Gaia Bp/Rp data. A photometric selection of BHB candidates was made in the $(u-g, g-r)$ and $(u-\mathrm{CaHK},g-r)$ color-color spaces. A spectroscopic selection in $T_\mathrm{eff}-\log g$ space was applied to remove stars with high surface gravity. The selection function of BHB stars was obtained by using the Gaia DR3 photometry. A non-parametric method that allows the variation in the vertical flattening $q$ with the Galactic radius, was adopted to explore the density shape of the stellar halo. We present a catalog of 44,552 high latitude ($|b|>20^\circ$) BHB candidates chosen with a well-characterized selection function. The stellar halo traced by these BHB stars is more flattened at smaller radii ($q=0.4$ at $r\sim8$ kpc), and becomes nearly spherical at larger radii ($q=0.8$ at $r\sim25$ kpc). Assuming a variable flattening and excluding several obvious outliers that might be related to the halo substructures or contaminants, we obtain a smooth and consistent relationship between $r$ and $q$, and the density profile is best fit with by a single power law with an index $\alpha=-4.65\pm0.04$.
Reference graph
Works this paper leans on
-
[1]
C., Wilhelm, R., et al
Allende Prieto, C., Beers, T. C., Wilhelm, R., et al. 2006, ApJ, 636, 804 Allende Prieto, C., Koesterke, L., Hubeny, I., et al. 2018, A&A, 618, A25
2006
-
[2]
Amarante, J. A. S., Koposov, S. E., & Laporte, C. F. P. 2024, A&A, 690, A166
2024
-
[3]
2023, A&A, 674, A27
Andrae, R., Fouesneau, M., Sordo, R., et al. 2023, A&A, 674, A27
2023
-
[4]
C., Baum, W
Arp, H. C., Baum, W. A., & Sandage, A. R. 1952, AJ, 57, 4 Astropy Collaboration, Price-Whelan, A. M., Sip˝ocz, B. M., et al. 2018, AJ, 156, 123
1952
-
[5]
Barbosa, F. O., Santucci, R. M., Rossi, S., et al. 2022, ApJ, 940, 30
work page 2022
-
[6]
& Vasiliev, E
Baumgardt, H. & Vasiliev, E. 2021, MNRAS, 505, 5957
2021
-
[7]
C., Almeida, T., Rossi, S., Wilhelm, R., & Marsteller, B
Beers, T. C., Almeida, T., Rossi, S., Wilhelm, R., & Marsteller, B. 2007, ApJS, 168, 277
work page 2007
- [8]
Show all 84 references
-
[9]
& Kravtsov, A
Belokurov, V . & Kravtsov, A. 2022, MNRAS, 514, 689
2022
-
[10]
& Bovy, J
Bennett, M. & Bovy, J. 2019, MNRAS, 482, 1417
2019
-
[11]
A., Xue, X.-X., Liu, C., et al
Bird, S. A., Xue, X.-X., Liu, C., et al. 2022, MNRAS, 516, 731
2022
-
[12]
A., Xue, X.-X., Liu, C., et al
Bird, S. A., Xue, X.-X., Liu, C., et al. 2021, ApJ, 919, 66
2021
-
[13]
2023, A&A, 669, A55
Cantat-Gaudin, T., Fouesneau, M., Rix, H.-W., et al. 2023, A&A, 669, A55
2023
-
[14]
M., Weiler, M., Jordi, C., et al
Carrasco, J. M., Weiler, M., Jordi, C., et al. 2021, A&A, 652, A86
2021
-
[15]
Castro-Ginard, A., Brown, A. G. A., Kostrzewa-Rutkowska, Z., et al. 2023, A&A, 677, A37
2023
-
[16]
2023, MNRAS, 525, 3075
Chen, A., Li, Z., Wang, Y ., et al. 2023, MNRAS, 525, 3075
2023
-
[17]
J., Hewett, P
Clewley, L., Warren, S. J., Hewett, P. C., et al. 2002, MNRAS, 337, 87
2002
-
[18]
H., Naidu, R
Conroy, C., Weinberg, D. H., Naidu, R. P., et al. 2022, arXiv e-prints, arXiv:2204.02989
2022 arXiv
-
[19]
J., Smart, R
Cooper, W. J., Smart, R. L., Jones, H. R. A., & Sarro, L. M. 2024, MNRAS, 527, 1521
2024
-
[20]
2024, A&A, 685, A134
Culpan, R., Dorsch, M., Geier, S., et al. 2024, A&A, 685, A134
2024
-
[21]
2021, A&A, 654, A107
Culpan, R., Pelisoli, I., & Geier, S. 2021, A&A, 654, A107
2021
-
[22]
2016, MNRAS, 463, 3169 De Angeli, F., Weiler, M., Montegriffo, P., et al
Das, P., Williams, A., & Binney, J. 2016, MNRAS, 463, 3169 De Angeli, F., Weiler, M., Montegriffo, P., et al. 2023, A&A, 674, A2
2016
-
[23]
J., Belokurov, V ., & Evans, N
Deason, A. J., Belokurov, V ., & Evans, N. W. 2011, MNRAS, 416, 2903
2011
-
[24]
J., Belokurov, V ., Koposov, S
Deason, A. J., Belokurov, V ., Koposov, S. E., & Lancaster, L. 2018, ApJ, 862, L1
2018
-
[25]
J., Erkal, D., Belokurov, V ., et al
Deason, A. J., Erkal, D., Belokurov, V ., et al. 2021, MNRAS, 501, 5964
2021
-
[26]
J., Lang, D., et al
Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168
2019
-
[27]
W., Riello, M., De Angeli, F., et al
Evans, D. W., Riello, M., De Angeli, F., et al. 2018, A&A, 616, A4
2018
-
[28]
C., Yuan, H
Faccioli, L., Smith, M. C., Yuan, H. B., et al. 2014, ApJ, 788, 105
2014
-
[29]
2018, PASJ, 70, 69
Fukushima, T., Chiba, M., Homma, D., et al. 2018, PASJ, 70, 69
2018
-
[30]
2019, PASJ, 71, 72
Fukushima, T., Chiba, M., Tanaka, M., et al. 2019, PASJ, 71, 72
2019
-
[31]
2025, PASJ, 77, 178 Article number, page 12 of 15 Wu et al.: Mapping the Milky Way with Gaia XP spectra II Gaia Collaboration, Brown, A
Fukushima, T., Chiba, M., Tanaka, M., et al. 2025, PASJ, 77, 178 Article number, page 12 of 15 Wu et al.: Mapping the Milky Way with Gaia XP spectra II Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2021, A&A, 649, A1 Gaia Collaboration, Montegriffo, P., Bellazzini...
2025
-
[32]
2018, The Journal of Open Source Software, 3, 695
Green, G. 2018, The Journal of Open Source Software, 3, 695
2018
-
[33]
J., Martin, C., Donlon, Thomas, I., & Amy, P
Gryncewicz, R., Newberg, H. J., Martin, C., Donlon, Thomas, I., & Amy, P. M. 2021, ApJ, 910, 102
2021
-
[34]
J., Conroy, C., Johnson, B
Han, J. J., Conroy, C., Johnson, B. D., et al. 2022, AJ, 164, 249
2022
-
[35]
G., Rix, H.-W., et al
Hernitschek, N., Cohen, J. G., Rix, H.-W., et al. 2018, ApJ, 859, 31
2018
-
[36]
2024, ApJS, 271, 13
Huang, B., Yuan, H., Xiang, M., et al. 2024, ApJS, 271, 13
2024
-
[37]
2018, MNRAS, 474, 2142 Jofré, P
Iorio, G., Belokurov, V ., Erkal, D., et al. 2018, MNRAS, 474, 2142 Jofré, P. & Weiss, A. 2011, A&A, 533, A59
2018
-
[38]
2024, ApJS, 270, 11
Ju, J., Cui, W., Huo, Z., et al. 2024, ApJS, 270, 11
2024
-
[39]
R., Sharma, S., Lewis, G
Kafle, P. R., Sharma, S., Lewis, G. F., & Bland-Hawthorn, J. 2012, ApJ, 761, 98
2012
-
[40]
& Binney, J
Li, C. & Binney, J. 2022, MNRAS, 510, 4706
2022
-
[41]
Li, S., Casertano, S., & Riess, A. G. 2023, ApJ, 950, 83
2023
-
[42]
2021, A&A, 649, A4
Lindegren, L., Bastian, U., Biermann, M., et al. 2021, A&A, 649, A4
2021
-
[43]
2017, Research in Astronomy and Astrophysics, 17, 096
Liu, C., Xu, Y ., Wan, J.-C., et al. 2017, Research in Astronomy and Astrophysics, 17, 096
2017
-
[44]
F., Starkenburg, E., Yuan, Z., et al
Martin, N. F., Starkenburg, E., Yuan, Z., et al. 2024, A&A, 692, A115
2024
-
[45]
E., Muñoz, R
Medina, G. E., Muñoz, R. R., Carlin, J. L., et al. 2024, MNRAS, 531, 4762
2024
-
[46]
W., Emerson, J
Minniti, D., Lucas, P. W., Emerson, J. P., et al. 2010, New A, 15, 433
2010
-
[47]
2023, A&A, 674, A3
Montegriffo, P., De Angeli, F., Andrae, R., et al. 2023, A&A, 674, A3
2023
-
[48]
2019, ApJ, 872, 206
Montenegro, K., Minniti, D., Alonso-García, J., et al. 2019, ApJ, 872, 206
2019
-
[49]
& Prišegen, M
Paunzen, E. & Prišegen, M. 2022, A&A, 667, L10
2022
-
[50]
Pier, J. R. 1982, AJ, 87, 1515
1982
-
[51]
Pier, J. R. 1983, ApJS, 53, 791 Pila-Díez, B., de Jong, J. T. A., Kuijken, K., van der Burg, R. F. J., & Hoekstra, H. 2015, A&A, 579, A38
1983
-
[52]
W., Shectman, S
Preston, G. W., Shectman, S. A., & Beers, T. C. 1991, ApJ, 375, 121
1991
-
[53]
F., Rix, H.-W., & Xue, X.-X
Ruhland, C., Bell, E. F., Rix, H.-W., & Xue, X.-X. 2011, ApJ, 731, 119
2011
-
[54]
Sanders, J. L. & Matsunaga, N. 2023, MNRAS, 521, 2745
2023
-
[55]
Schlafly, E. F. & Finkbeiner, D. P. 2011, ApJ, 737, 103
2011
-
[56]
J., Finkbeiner, D
Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525
1998
-
[57]
R., et al
Sirko, E., Goodman, J., Knapp, G. R., et al. 2004, AJ, 127, 899
2004
-
[58]
Sluis, A. P. N. & Arnold, R. A. 1998, MNRAS, 297, 732
1998
-
[59]
W., Bailer-Jones, C
Smith, K. W., Bailer-Jones, C. A. L., Klement, R. J., & Xue, X. X. 2010, A&A, 522, A88
2010
-
[60]
R., & Carter, D
Sommer-Larsen, J., Christensen, P. R., & Carter, D. 1989, MNRAS, 238, 225
1989
-
[61]
2019, MNRAS, 490, 5757
Starkenburg, E., Youakim, K., Martin, N., et al. 2019, MNRAS, 490, 5757
2019
-
[62]
E., et al
Subramaniam, A., Sahu, S., Postma, J. E., et al. 2017, AJ, 154, 233
2017
-
[63]
2025, ApJ, 979, 213
Sun, S., Wang, F., Zhang, H., et al. 2025, ApJ, 979, 213
2025
-
[64]
F., McConnachie, A
Thomas, G. F., McConnachie, A. W., Ibata, R. A., et al. 2018, MNRAS, 481, 5223
2018
-
[65]
A., Brogaard, K., Leaman, R., & Casagrande, L
VandenBerg, D. A., Brogaard, K., Leaman, R., & Casagrande, L. 2013, ApJ, 775, 134
2013
-
[66]
& Baumgardt, H
Vasiliev, E. & Baumgardt, H. 2021, MNRAS, 505, 5978
2021
-
[67]
J., Grebel, E
Vickers, J. J., Grebel, E. K., & Huxor, A. P. 2012, AJ, 143, 86
2012
-
[68]
A., Jordan, S., et al
Vincent, O., Barstow, M. A., Jordan, S., et al. 2024, A&A, 682, A5
2024
-
[69]
L., Evans, N
Watkins, L. L., Evans, N. W., Belokurov, V ., et al. 2009, MNRAS, 398, 1757
2009
-
[70]
D., Beers, T
Whitten, D. D., Beers, T. C., Placco, V . M., et al. 2019, ApJ, 884, 67
2019
-
[71]
2022, A&A, 662, A66
Xiang, M., Rix, H.-W., Ting, Y .-S., et al. 2022, A&A, 662, A66
2022
-
[72]
2025, Nature Astronomy, 9, 101
Xiang, M., Rix, H.-W., Yang, H., et al. 2025, Nature Astronomy, 9, 101
2025
-
[73]
2018, MNRAS, 473, 1244
Xu, Y ., Liu, C., Xue, X.-X., et al. 2018, MNRAS, 473, 1244
2018
-
[74]
2015, ApJ, 809, 144
Xue, X.-X., Rix, H.-W., Ma, Z., et al. 2015, ApJ, 809, 144
2015
-
[75]
2011, ApJ, 738, 79
Xue, X.-X., Rix, H.-W., Yanny, B., et al. 2011, ApJ, 738, 79
2011
-
[76]
X., Rix, H
Xue, X. X., Rix, H. W., Zhao, G., et al. 2008, ApJ, 684, 1143
2008
-
[77]
2022, AJ, 164, 241
Yang, C., Zhu, L., Tahmasebzadeh, B., Xue, X.-X., & Liu, C. 2022, AJ, 164, 241
2022
-
[78]
J., Kent, S., et al
Yanny, B., Newberg, H. J., Kent, S., et al. 2000, ApJ, 540, 825
2000
-
[79]
J., et al
Yanny, B., Rockosi, C., Newberg, H. J., et al. 2009, AJ, 137, 4377
2009
-
[80]
2025, A&A, 695, A75
Ye, X., Wu, W., Allende Prieto, C., et al. 2025, A&A, 695, A75
2025
-
[81]
G., Adelman, J., Anderson, John E., J., et al
York, D. G., Adelman, J., Anderson, John E., J., et al. 2000, AJ, 120, 1579
2000
-
[82]
S., Speagle, J
Yu, F., Li, T. S., Speagle, J. S., et al. 2024, ApJ, 975, 81
2024
-
[83]
2024, MNRAS, 533, 889
Zhang, H., Ardern-Arentsen, A., & Belokurov, V . 2024, MNRAS, 533, 889
2024
-
[84]
& Yuan, H
Zhang, R. & Yuan, H. 2023, ApJS, 264, 14 Article number, page 13 of 15 A&A proofs: manuscript no. aa54410-25 Appendix A: Necessity of a combined photometric and spectroscopic cut In this appendix, we conducted a test by applying only photometric cuts, only spectroscopic cuts, ...
2023
Reviewed August 5, 2026 · model on record in the stance chip above.
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