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REVIEW 4 major objections 4 minor 300 references

A sample of 10,236 blue horizontal-branch stars, identified with 80–90% recovery and ≤10% contamination, receives atmospheric parameters from a color-augmented data-driven model.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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2026-08-01 13:13 UTC pith:R3RJ5OOV

load-bearing objection A solid, standard BHB catalog paper with an unspecified reddening step in the color inputs—addressable, not fatal. the 4 major comments →

arxiv 2607.19175 v1 pith:R3RJ5OOV submitted 2026-07-21 astro-ph.SR

Identifying and Determining Atmospheric Parameters of BHB Stars Based on LAMOST DR11

Xiao-Long Wang , Wen-Yuan Cui , Jie Ju , Guo-Zhen Hu , Min Fang , Shuai Zhang , Jia-Ming Liu This is my paper
classification astro-ph.SR
keywords blue horizontal-branch starsatmospheric parametersLAMOST DR11SLAMsupport vector regressionBalmer linesGalactic haloblue straggler stars
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

Blue horizontal-branch (BHB) stars are old, helium-burning giants whose nearly fixed luminosities make them useful tracers of the Milky Way's halo. The paper systematically searches a large spectroscopic survey (LAMOST DR11) for BHB stars using Balmer-line profile diagnostics, identifying 13,988 BHB spectra belonging to 10,236 unique stars, with an estimated identification rate of ~80–90% and contamination below ~10%. It then applies the data-driven Stellar LAbel Machine (SLAM), trained on synthetic spectra, to estimate effective temperature, surface gravity, and metallicity for each star. A key step is appending Gaia and 2MASS color indices to the spectral flux before training; the paper shows this breaks the degeneracy between temperature and surface gravity, improving parameter recovery especially at low signal-to-noise. The resulting catalog reveals a bump in [Fe/H] around −0.5, and the metal-rich BHB stars are shown to be mostly disk members, providing a new window on the disk–halo interface.

Core claim

The central discovery is that combining photometric colors with spectral fluxes in a support-vector-regression-based labeler yields reliable atmospheric parameters for BHB stars, overcoming the well-known Teff–logg degeneracy that makes hot giants and cool dwarfs mimic each other in hydrogen-line profiles. Applied to 13,988 BHB spectra from LAMOST DR11, the method yields median parameters (Teff ≈ 8270 K, logg ≈ 3.41, [Fe/H] ≈ −2.16) consistent with literature BHB values. The paper also reports a secondary bump in the [Fe/H] distribution around −0.5, and shows through kinematics and spatial distribution that most of these metal-rich BHB stars are likely disk members, rather than halo contamin

What carries the argument

The key machinery is the combination of two established Balmer-line diagnostics—the D0.2 method (line width at 20% below the continuum) and the scale width-shape method (Sérsic-profile fit yielding width b and shape c) applied to Hβ, Hγ, and Hδ—for identification, and the Stellar LAbel Machine (SLAM), a support vector regression trained on a synthetic spectral grid, for parameter estimation. The crucial novelty is that SLAM is fed both normalized spectral fluxes and four appended color indices (BP−G, G−RP, BP−RP, J−H); these colors act as an independent temperature indicator that breaks the degeneracy between effective temperature and surface gravity. The identification step uses the Balmer

Load-bearing premise

The parameter catalog assumes that the observed Gaia and 2MASS colors fed into the model are extinction-free; if reddening is not corrected, the color inputs are systematically too red, which would shift the predicted temperatures and gravities.

What would settle it

Check whether the predicted Teff of BHB stars correlates with their reddening (EBV): if the observed colors are not dereddened, de reddened stars should show systematically lower Teff than unreddened stars of the same true temperature, a signature that would contradict the derived parameter scale.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • The catalog of 10,236 BHB stars with atmospheric parameters enables studies of the Galactic halo's substructure, kinematics, and mass distribution out to distances where BHB stars serve as standard candles.
  • The demonstration that color indices break the Teff–logg degeneracy suggests that similar color-augmented labelers could improve atmospheric parameter estimates for other spectral types where Balmer lines are degenerate, especially in low-signal-to-noise data.
  • The metal-rich BHB population with [Fe/H] > −1, shown to be mostly disk members, implies that BHB stars are not exclusively halo objects; this may complicate distance-based halo studies but also opens a path to studying disk stellar populations via BHB stars.
  • The published list of 4,282 blue straggler stars with parameters provides a ready-made negative sample for refining future BHB selections and for studying blue straggler formation channels.
  • The identification rate of ~80–90% and contamination ≲10% quantify the reliability of the combined D0.2 and scale width-shape approach, giving future surveys a benchmark for spectroscopic BHB selection.

Where Pith is reading between the lines

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

  • The same color-index augmentation could be extended to hotter BHB subcategories (HBB and EHB stars) if the synthetic training grid were expanded above 12,000 K; the method's success in the 7000–12,000 K range suggests it would generalize.
  • If the metal-rich bump at [Fe/H] ≈ −0.5 is a genuine disk BHB population, it may imply a formation pathway for BHB stars at near-solar metallicity, possibly related to helium enrichment in massive globular clusters or a separate field population; this hypothesis could be tested with high-resolution follow-up spectroscopy.
  • The lack of an explicit dereddening step for the observed colors in the SLAM input is a potential systematic: if reddening is uncorrected, the color inputs would be shifted redward, biasing Teff estimates for reddened stars. A testable extension would be to apply the catalog to a sample with known extinctions and check whether Teff correlates with EBV.
  • The systematic ~250 K offset between SLAM and SED-based Teff, attributed to differences between model atmospheres, suggests that the absolute temperature scale of the catalog carries an unknown model-dependent zero-point; cross-calibration with asteroseismic or interferometric temperatures could anchor it.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The paper presents a systematic search for blue horizontal-branch (BHB) stars in LAMOST DR11, using equivalent-width cuts on Hγ and G4300, the D0.2 Balmer-line width method, and the Sérsic scale width-shape method on Hβ, Hγ, and Hδ. It reports 13,988 BHB spectra, corresponding to 10,236 unique stars, and also provides 4,282 blue straggler (BS) stars. Atmospheric parameters (Teff, logg, [Fe/H]) are derived with the data-driven SLAM method, trained on synthetic ATLAS9 spectra, with and without appended Gaia/2MASS color indices. The authors estimate an identification rate of ~80–90% and contamination of ≲10%, and discuss a metal-rich [Fe/H]~−0.5 bump whose members are primarily kinematically disk-like. The manuscript includes comparisons with previous BHB catalogs, globular-cluster tests, and a comparison of SLAM parameters with the SED-based catalog of Culpan et al. (2024).

Significance. If the catalog is reliable, it would be one of the largest spectroscopically selected, parameterized samples of BHB and BS stars in the LAMOST era, useful for halo kinematics, substructure studies, and tests of horizontal-branch evolution. The study also re-emphasizes, with synthetic tests, that including color indices helps break the Teff–logg degeneracy for low-SNR spectra. The comparison with Culpan et al. (2024) provides an external anchor, and the globular-cluster CMD checks are a useful, albeit small, independent validation. However, the reliability of the identification rate and the atmospheric parameters depends on resolving the issues below.

major comments (4)
  1. [Section 4.4, Figures 10 and 12, Table 1] The SLAM training uses intrinsic synthetic colors (Section 4.2), but the inference on observed spectra in Section 4.4 is described only as applying the machine to ‘observed spectra’ and ‘observed color’ (Figure 10). The text never states whether the observed Gaia/2MASS colors are dereddened before being passed to SLAM. The catalog lists EBV, and CMD analyses elsewhere use Schlegel et al. (1998) with Wang & Chen (2019), so this omission is conspicuous. If reddened colors are used, the input distribution at inference differs systematically from the training distribution. Since BP−RP and J−H are monotonic Teff indicators and strongly influence the SLAM outputs, this can bias Teff and, through the degeneracy, logg for a large fraction of the catalog. The synthetic CV tests (Section 4.3) add Gaussian noise but not reddening, so they do not probe this effect. The +250 K offset versus Culpan et
  2. [Section 5.1 vs. Section 3.2] The claimed identification rate of ~80–90% is partly circular. The selection boxes in Equations (2) and (6) were drawn using ‘known BHB stars’ from Xue et al. (2008; 2011) and Ju et al. (2024) as references. Section 5.1 then measures recovery against Ju et al. (2024), Xue et al. (2011), and Vickers et al. (2021); the latter used Xue et al. (2008; 2011) as its training set. Thus these recovery fractions are not fully independent. The globular-cluster test is more independent, but it rests on only 18 BHB stars in 8 clusters (and 16 outside two clusters), yielding an identification rate of 13/16 ≈ 81%. That is consistent with the stated range, but the statistical weight is small. The authors should explicitly acknowledge this circularity and present the GC result as the primary independent completeness estimate, or add an independent validation sample with a larger number of stars.
  3. [Equation (2) and Equation (3)] The notation in the selection cuts appears inconsistent: the second line of Equation (2) reads ‘20.0 ≤ D0.2,γ ≤ 28.5, and 0.15 ≤ fm,β ≤ 0.33’ and the third line reads ‘20.0 ≤ D0.2,δ ≤ 28.0, and 0.15 ≤ fm,γ ≤ 0.33’ – i.e., the fm variable does not match the Balmer line being used. The same pattern appears in Equation (3). If these are typographical errors and the actual analysis used the matching fm values, the text should be corrected. If the analysis actually used the printed conditions, the selection is not the one described in the prose and the numbers in Section 3.2.3 could change. Because these cuts are the core of the BHB/BS classification, the correct conditions must be stated unambiguously.
  4. [Section 4.4, Figure 12] The paper knowingly retains a clump of ~7500–8000 K stars with logg > 4.0 that deviates significantly from the ZAHB and is described as having potentially higher contamination, with more than half having [Fe/H] ≥ −1. These stars are included in the published BHB catalog for completeness. This is transparent, but it complicates the claim of a ≲10% contamination rate, since that estimate is based on GC stars falling in the selection boxes and does not directly account for the known parameter-based contamination in this clump. The authors should either quantify the fraction of the catalog in this clump and its likely contamination, or state more carefully how the ≲10% figure relates to the full catalog.
minor comments (4)
  1. [Section 5.1, globular clusters] The text reports both ‘16 BHB stars in the other 6 clusters’ with 13 identified, and ‘we identify 18 BHB stars in the 8 GCs, 15 of them are within the selection boxes’. The relationship between these numbers, and how the 18 were selected, should be clarified so that the denominator of the contamination estimate is transparent.
  2. [Section 3.2.1, paragraph after Eq. (2)] The sentence listing the numbers of BHB candidates after the D0.2 cuts gives 15,197, 13,713, and 19,470 for Hβ, Hγ, and Hδ. The prose should indicate whether these are after the fm-cuts in Eq. (2) or after the initial A-type selection, since the logical flow is otherwise ambiguous.
  3. [Section 4.3, Figure 8] The rightmost point in each panel is defined as representing SNRg = ∞, but the x-axis extends to 100. The label should be explicit that this is the noise-free case, and the axis tick should probably be annotated separately to avoid implying a real SNR.
  4. [Table 1] The table lists EBV from Schlegel et al. (1998) but no dereddened photometry or extinction-law column. If dereddened colors are used in Section 4.4, the catalog should either include the dereddened colors or state the procedure clearly in the table description.

Circularity Check

1 steps flagged

Identification rate is partly in-sample: Eqs. 2/6 boxes drawn on known BHB stars (Xue 2008/2011, Ju 2024) and §5.1 recovery measured against the same families; external checks keep overall circularity moderate.

specific steps
  1. fitted input called prediction [Sec. 3.2.1 (Eq. 2), Sec. 3.2.2 (Eq. 6), and Sec. 5.1]
    "Based on the distribution in theD0.2 versus fm planes, and using the known BHB stars as references, we flag a spectrum as a BHB candidate ... Of the 5250 matches in LAMOST DR11, 4593 (∼90%) are identified as BHB stars in this work as well."

    The selection boxes (Eq. 2, D0.2–fm; Eq. 6, b–c) are drawn using 'the known BHB stars as references' — 'compiled from Xue et al. 2008, 2011; Ju et al. 2024' (Sec. 3.2.1). Sec. 5.1 then measures the headline 'identification rate ∼80%–90%' against these same families: 90% of Ju et al. 2024 and 80% of Xue et al. 2011 are recovered. Since the cuts were placed on the locus of these reference stars, high recovery is partly guaranteed by construction — the rate is a box-to-calibration-sample goodness-of-fit. Vickers et al. (2021) is also not independent (its ML training set was Xue et al. 2008). Culpan, GCs, and CaMD provide external support but do not remove the in-sample component of the headline rate.

full rationale

The paper's central new products are (i) the 13,988-spectrum BHB/BS catalog from LAMOST DR11, selected by the D0.2 and scale width-shape cuts, and (ii) the SLAM atmospheric-parameter estimates trained on the external ATLAS9 synthetic grid of Allende Prieto et al. (2018). Neither product reduces to its inputs by construction: the catalog counts are the plain outcome of the cuts, and the SLAM labels are a learned inversion of an independent physical model grid, with held-out synthetic CV tests. The conspicuous methodological weak point identified in review — observed, possibly reddened Gaia/2MASS colors fed to a machine trained on synthetic intrinsic colors (§4.2 vs §4.4, Figure 10), with no stated dereddening before inference — is a distribution-shift/systematics risk (potentially biasing Teff/logg, and interacting with the +250 K offset vs Culpan et al. 2024), not a circularity: the color-to-label mapping is still inferred from external synthetic physics rather than from the observed labels themselves. The one genuine circular component is the headline identification rate: the Eq. 2 and Eq. 6 selection boxes were drawn 'using the known BHB stars as references' (compiled from Xue et al. 2008/2011 and Ju et al. 2024, the latter co-authored here), and §5.1 then reports recovery of those same families (90% Ju, 80% Xue, 80% Vickers — Vickers itself trained on Xue et al. 2008) as 'an identification rate ∼80%–90%.' That rate is partly in-sample by construction. The paper does provide independent evidence — 81% recovery in 6 GCs using external Vickers et al. 2012 boxes, CaMD placement, and ~90% recovery of the external Culpan et al. (2024) sample — so the central claim retains independent content. No load-bearing uniqueness theorem, ansatz-smuggling citation, or renamed known result was found. Overall: moderate partial circularity, confined to the in-sample component of the selection-validation loop.

Axiom & Free-Parameter Ledger

5 free parameters · 5 axioms · 0 invented entities

All new content is catalog construction: multi-stage cuts whose boundaries are hand-tuned to reference samples, plus an SVR trained on a published synthetic grid. The method introduces no new physical objects; the effective free parameters are the cut boundaries, SVR hyperparameters, and the disk/halo velocity threshold. The deepest unproven inputs are the fidelity of the ATLAS9 grid and the comparability of observed and synthetic colors.

free parameters (5)
  • D0.2/fm selection boxes for Hβ/Hγ/Hδ = D0.2 between 20.0–28.5/28.0 Å and fm ranges as in Eq. (2)
    Cut boundaries set by eye around density peaks and reference BHB distributions (Fig. 3).
  • b–c boundary polynomials (Eq. 6) = Quartic coefficients per Balmer line (e.g., bβ ≤ -8.66 cβ^4 + ...)
    Drawn to enclose known BHB stars and exclude BS candidates in the b–c planes.
  • EW cuts EWHγ ≥ 6 Å, EWG4300 ≤ 2 Å = 6 Å, 2 Å
    Empirical cuts in Fig. 1 to isolate A-type stars; no uncertainty or optimization described.
  • SLAM hyperparameters C, γ, ε = not reported
    SVR hyperparameters are free and not specified; chosen values affect label predictions.
  • Vφ threshold for disk membership = 200 km/s
    Used to classify metal-rich BHB stars as disk members (Sec. 5.4); authors note it is a simplified single threshold.
axioms (5)
  • domain assumption Synthetic spectra from Allende Prieto et al. (2018) computed with ATLAS9 accurately represent real BHB and BS spectra over Teff=7000–12000 K, logg=2–5, [Fe/H]=-5 to 1.
    These synthetic spectra are the entire training set for SLAM labels (Sec. 4.2); validation is mostly on synthetic test spectra, and the comparison with Culpan et al. (2024) shows a ~250 K systematic Teff offset attributed to grid differences.
  • domain assumption The Sersic profile (Eq. 5) and the D0.2 width parametrize Balmer lines in a way that separates temperature and gravity for A-type stars.
    The classification relies on these adopted profile/width mappings (Secs. 3.2.1, 3.2.2), following prior work by Clewley, Xue, Sirko.
  • domain assumption The reference BHB samples of Xue et al. (2008, 2011) and Ju et al. (2024) are complete and accurate enough to serve as ground truth for setting selection boundaries.
    Selection boxes in Fig. 3 and Eqs. (2) and (6) are drawn using these 'known BHB stars' as references; the recovery-test in Sec. 5.1 then reuses overlapping samples.
  • domain assumption Observed Gaia/2MASS colors can be compared directly with the intrinsic synthetic colors used to train SLAM (i.e., extinction is either negligible or corrected), although no dereddening step is described in Sec. 4.4.
    Training colors are synthetic and intrinsic (Sec. 4.2); observed colors are used as SLAM inputs in Sec. 4.4 without a stated correction.
  • domain assumption Schlegel et al. (1998) extinction map and Wang & Chen (2019) extinction law are accurate for dereddening in the CMD and spatial analyses.
    Used to deredden photometry in GC and CaMD checks (Secs. 5.1, 5.2).

pith-pipeline@v1.3.0-alltime-deepseek · 27192 in / 15702 out tokens · 159899 ms · 2026-08-01T13:13:38.865310+00:00 · methodology

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read the original abstract

Large catalogs of blue horizontal-branch (BHB) stars are essential for studying substructures and kinematics of the Galactic halo. And accurate determination of atmospheric parameters for BHB stars provides insight into stellar evolution. In this work, we perform a systematic search for BHB stars based on LAMOST DR11, and identify $13\,988$ BHB spectra, corresponding to $10\,236$ unique BHB stars. We estimate an identification rate of $\sim80\%-90\%$, and a contamination rate of $\lesssim10\%$ for our sample. Atmospheric parameters for these BHB stars are estimated via the data-driven method named the Stellar LAbel Machine (SLAM). We demonstrate the necessity of including color indices in the spectral labeling to effectively break the degeneracy between effective temperature and surface gravity. We note a bump in the distribution of [Fe/H], and most of these metal-rich BHB stars belong to the disk population. We also provide a list of 4282 blue straggler (BS) stars with determined atmospheric parameters.

Figures

Figures reproduced from arXiv: 2607.19175 by Guo-Zhen Hu, Jia-Ming Liu, Jie Ju, Min Fang, Shuai Zhang, Wen-Yuan Cui, Xiao-long Wang.

Figure 1
Figure 1. Figure 1: The background image and contours display the distribution of all spectra with SNRg ≥ 10 and |b| ≥ 20◦ in the EWG4300 vs. EWHγ plane. The red circles connected with red dotted curve represent the main-sequence track, and the giant track is shown as blue squares connected with blue dashed curve (adopted from Liu et al. 2015a). The orange solid lines denote cuts on EWG4300 and EWHγ for the selection of A-typ… view at source ↗
Figure 2
Figure 2. Figure 2: Top panel: An example LAMOST spectrum of a typical BHB star. The spectrum has been corrected to the rest frame, with bad pixels and outlier measurements removed (see Section 2.3 for details). Some basic information for the spectrum provided in the LAMOST catalog, including the unique spectrum ID number (obsid), the spectral type, the radial velocity and the signal-to-noise ratios in the ugriz-bands, are la… view at source ↗
Figure 3
Figure 3. Figure 3: Top row: Identifying BHB candidates based on the D0.2 method (top left) and the scale width￾shape method (top right) using the Hβ line. In both panels, the red dots represent BHB stars collected from various studies (i.e., Xue et al. 2008, 2011; Ju et al. 2024), and the blue lines show cuts on the parameters for selecting BHB and BS stars. In the top left panel, the background image with overlaid contours … view at source ↗
Figure 4
Figure 4. Figure 4: Corner plot showing the parameter space coverage of the theoretical spectra. The blue circles represent the spectra in the raw grid of Allende Prieto et al. (2018), and the small gray dots are the linearly interpolated spectra employed for training the SLAM. We should mention that while the Balmer lines are sensitive indicators of effective tem￾peratures for A-type stars, they are not mono￾tonic functions … view at source ↗
Figure 5
Figure 5. Figure 5: Intrinsic BP − G, G − RP, BP − RP and J − H colors as functions of effective temperatures for theoretical spectra in the training set. The points are color coded by surface gravity. 4.3. The Performance of the SLAM Before applying SLAM to predict stellar labels of the observed spectra, it is necessary to verify the validity of the machine. To achieve this, we first apply the trained machines to the test se… view at source ↗
Figure 6
Figure 6. Figure 6: Comparison between the predicted labels and the true labels for the test set when SLAM is trained with both flux and colors. The black lines in the upper panels are the line of equality. The bottom panels display the residuals. The CV-scatter and CV-bias values are labeled. 7000 8000 9000 10000 11000 12000 Teff, SLA M (K) with_color = False bias= 1.20K, scatter=63.82K 2.0 2.5 3.0 3.5 4.0 4.5 5.0 lo g gSLA … view at source ↗
Figure 7
Figure 7. Figure 7: Similar as [PITH_FULL_IMAGE:figures/full_fig_p016_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: The distribution of the CV-scatter (top panels) and CV-bias (bottom panels) values for predicted stellar labels of Teff (left panels), log g (middle panels), and [Fe/H] (right panels) as functions of SNRg values. In each panel, blue squares connected with dashed line represent training SLAM with flux only, and red circles connected with solid line represent training SLAM with both flux and colors. The righ… view at source ↗
Figure 9
Figure 9. Figure 9: Top-most panel: An example showing the fits to a noise-free spectrum in the test set. The test spectrum is shown as gray line, and the corresponding BP − G, G − RP, BP − RP, and J − H colors are indicated with gray dots from left to right (see the right y-axis). The blue line is the SLAM predicted spectrum when training SLAM with only flux. The red line and circles represent the SLAM predicted spectrum and… view at source ↗
Figure 10
Figure 10. Figure 10: An example demonstrating fitting the observed spectrum with the SLAM trained with both flux and color indices. The observed and the best-fitted spectrum are shown as gray and red lines, respectively. The gray dots and red circles represent the observed and the SLAM predicted colors, respectively. From left to right are BP − G, G − RP, BP − RP, and J − H colors, respectively (see the right y-axis). 6000 80… view at source ↗
Figure 11
Figure 11. Figure 11: Histograms showing the distribution of Teff (left panel), log g (middle panel), and [Fe/H] (right panel) for the BHB (blue solid) and BS (red open) samples. low in the clusters NGC 5024 and NGC 7078, which is mainly due to that the selection box suffer RR Lyrae contamination on the red end (Vickers et al. 2012) 8 . Excluding these two clus￾ters, there are 16 BHB stars in the other 6 clus￾8 There are 7 obj… view at source ↗
Figure 12
Figure 12. Figure 12: Top panel: Distribution of BHB (red and black dots) and BS (blue dots) stars in the log g vs. Teff plane. Also shown are the theoretical zero-age horizontal branches (ZAHBs) with various [Fe/H] from Pietrinferni et al. (2021). BHB stars with [Fe/H] > −1 are shown as black dots. Bottom panel: Distribution of BHB stars in the [Fe/H] vs. Teff plane, and only objects classified as BHB stars based on all the t… view at source ↗
Figure 13
Figure 13. Figure 13: CMDs of 8 Globular clusters in the SDSS footprint (An et al. 2008). In each panel, the background image shows SDSS photometry for the corresponding cluster. The black boxes show the criteria used to select BHB stars in the clusters following Vickers et al. (2012), and the selected BHB stars are shown as gray dots. The blue dots mark sources observed with the LAMOST, and sources identified as BHB stars in … view at source ↗
Figure 14
Figure 14. Figure 14: Left panel: Distribution of BHB stars (red dots) in the Gaia CaMD. The background image shows the distribution of all the LAMOST sources with |b| ≥ 20◦ and SNRg ≥ 10 (see Section 2.1). The extinction correction is performed adopting the extinction map of Schlegel et al. (1998) and the extinction law of Wang & Chen (2019). Middle panel: Zoom-in view of the horizontal-branch (blue box in the left panel). Th… view at source ↗
Figure 15
Figure 15. Figure 15: Histograms showing the distribution of apparent magnitude (left panel) and distance (right panel) of our BHB sample (red filled histograms) and the BHB sample from Xue et al. (2011) (blue hatched histograms). The red and blue dashed lines show the median values of apparent magnitude and distance of the two samples, respectively, and the corresponding values are indicated in the legends. 5 10 15 20 25 R (k… view at source ↗
Figure 16
Figure 16. Figure 16: Corner plot showing the spatial distri￾bution of the BHB stars in the R–Z plane of the cylindrical galactocentric coordinate system. The red, green, and blue dashed lines in the diagonal panels show the 16th, 50th, and 84th percentiles for R and Z, respectively, and the corresponding values are indicated in the legends. disk members11, while only 33 (<15%) of the metal-poor stars belong to the disk popula… view at source ↗
Figure 17
Figure 17. Figure 17: Comparison of Teff (left panel) and log g (right panel) obtained in this work with that from Culpan et al. (2024). In each panel, the solid line is the line of equality. Mean and standard deviation of the parameter differences between our results and that from Culpan et al. (2024) are also shown in the plot. 200 0 200 V (km/s) 0 10 20 30 40 50 N u m b er [Fe/H] > 1 [Fe/H] 1 20° 40° 60° 80° |b| 0 50 100 15… view at source ↗
Figure 18
Figure 18. Figure 18: Histograms showing the distributions of Vϕ (left panel), |b| (middle panel), and Z (right panel) for BHB stars with [Fe/H] > −1 dex (red filled histogram) and [Fe/H] ≤ −1 dex (blue open histogram). The vertical dashed line in the left panel corresponds to Vϕ = 200 km s−1 , and is used to separate the sample into disk (Vϕ ≥ 200 km s−1 ) and halo (Vϕ < 200 km s−1 ) populations. search for BHB stars via the … view at source ↗

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