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arxiv: 2605.08770 · v1 · submitted 2026-05-09 · 🌌 astro-ph.SR

Recognition: 1 theorem link

· Lean Theorem

The Stellar Abundances and Galactic Evolution Survey (SAGES). V. The First Data Release of the DDO51 Band

Qiqian Zhang , Zhou Fan , Gang Zhao , Kai Xiao , Wei Wang , Hongrui Gu , Jie Zheng , Jingkun Zhao , Chun Li , Yuqin Chen , Haibo Yuan , Haining Li , Kefeng Tan , Yihan Song , Ali Luo , Nan Song , Yujuan Liu , Yaqian Wu , Ali Esamdin , Hubiao Niu , Jinzhong Liu , Guojie Feng , Yu Zhang

Authors on Pith no claims yet

Pith reviewed 2026-05-12 02:16 UTC · model grok-4.3

classification 🌌 astro-ph.SR
keywords SAGES surveyDDO51 bandstellar photometrysurface gravityMilky Way substructuredata releaseGaia photometrylate-type stars
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The pith

The SAGES survey's first DDO51-band data release covers 2500 square degrees and separates late-type dwarf and giant stars via surface-gravity sensitivity.

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

The paper releases the initial public DDO51 photometry from the Stellar Abundances and Galactic Evolution Survey, based on observations with the Nanshan One-meter Wide-field Telescope. The dataset spans roughly 2500 square degrees of the northern sky and contains more than 10 million sources, reaching a depth of about 18.9 magnitudes at S/N of 10 with internal precision of 6-7 millimagnitudes at the bright end. A color-color analysis that combines the new DDO51 measurements with Gaia broadband photometry shows a clear separation between dwarf and giant sequences for late-type stars, confirming the band's expected response to surface gravity. When merged with the survey's other photometric bands, the release supplies a practical tool for mapping Milky Way substructures.

Core claim

This paper presents the first public data release of the DDO51 band from the SAGES survey, covering approximately 2500 square degrees with over 10 million sources and achieving a point-source depth of ~18.9 mag at S/N~10 with internal photometric precision of 6-7 mmag. The DDO51 filter, centered near the Mg I b triplet and MgH feature, is shown through preliminary color-color diagrams with Gaia photometry to produce a clear photometric separation between dwarf and giant sequences for late-type stars, thereby confirming its sensitivity to stellar surface gravity.

What carries the argument

The DDO51 filter centered near the Mg I b triplet and adjacent MgH feature, which supplies photometric sensitivity to stellar surface gravity and enables dwarf-giant separation in color-color space.

If this is right

  • The new DDO51 photometry, when combined with the survey's existing bands, supplies a tool for disentangling Milky Way substructures.
  • The dataset enables photometric identification of late-type dwarfs and giants across a wide northern-sky area.
  • Public availability of the catalog supports immediate use in studies of stellar populations and galactic evolution.

Where Pith is reading between the lines

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

  • Combining these DDO51 measurements with Gaia astrometry could refine photometric distances for faint late-type stars without spectroscopy.
  • The demonstrated separation suggests the band may help isolate metal-poor halo stars from disk populations in future wide-field analyses.
  • Extending the same filter to southern-sky telescopes would create an all-sky gravity-sensitive photometric layer.

Load-bearing premise

The photometric calibration that ties DDO51 magnitudes to synthetic photometry from Gaia XP spectra introduces no large systematic offsets capable of erasing the reported dwarf-giant separation.

What would settle it

An independent set of DDO51 observations that shows either no dwarf-giant split in color-color space or large systematic differences from the Gaia-XP-based synthetic magnitudes.

Figures

Figures reproduced from arXiv: 2605.08770 by Ali Esamdin, Ali Luo, Chun Li, Gang Zhao, Guojie Feng, Haibo Yuan, Haining Li, Hongrui Gu, Hubiao Niu, Jie Zheng, Jingkun Zhao, Jinzhong Liu, Kai Xiao, Kefeng Tan, Nan Song, Qiqian Zhang, Wei Wang, Yaqian Wu, Yihan Song, Yujuan Liu, Yuqin Chen, Yu Zhang, Zhou Fan.

Figure 1
Figure 1. Figure 1: Total system throughput curves of the SAGES passbands, including the filter transmission and CCD quantum efficiency. The Hαn filters are shown using the design transmission profiles, while the other filters are based on laboratory measurements. 2. OBSERVATIONS 2.1. SAGES Survey Design and Overview SAGES targets the northern sky with δ > −5 ◦ , explicitly excluding the crowded, high-extinction Galactic plan… view at source ↗
Figure 2
Figure 2. Figure 2: Sky coverage of the SAGES DDO51 data released in this work. The gray region shows the full SAGES survey footprint, while the colored pixels mark the area included in this release, with color indicating the surface density of detected sources (sources per deg−2 ). Balancing the constraints of the telescope aperture, exposure time limits, and system efficiencies, we set design target depths of S/N ≈ 100 at u… view at source ↗
Figure 3
Figure 3. Figure 3: Example of the SAGES pointing pattern in equatorial coordinates. Red dashed rectangles outline the individual image footprints, with shaded regions indicating the effective image area and their mutual overlaps, while blue stars mark the image centers labeled by field ID. 2.4. Observing Strategy The survey footprint is partitioned into declination-fixed strips. Adjacent field centers are separated by 1◦ , p… view at source ↗
Figure 4
Figure 4. Figure 4: Long-term stability of image quality, astrometry, and photometry. All panels show image-level quantities as a function of exposure index, which follows the chronological observing sequence. (a) Median FWHM for each exposure, tracing the temporal behavior of the seeing; vertical dashed lines mark the boundaries between observing nights. (b) External astrometric RMS from SCAMP, both for all matched sources a… view at source ↗
Figure 5
Figure 5. Figure 5: Two-dimensional distribution of astrometric residuals (∆RA vs. ∆Dec) for one typical image, with points color-coded by DDO51 magnitude. The top and right panels show the one-dimensional histograms of ∆RA and ∆Dec, with the quoted σ values marking the dispersion of each component. derived. We can synthesize highly accurate DDO51-band magnitudes, which serve as a dense and precise grid of standard stars. The… view at source ↗
Figure 6
Figure 6. Figure 6: Visualization of the 2D spatial photometric calibration for a representative single exposure. (a) The distribution of the reference standard sources (synthesized from Gaia DR3 XP spectra) across the detector pixel coordinates (X, Y), color-coded by their intrinsic Gaia BP − RP colors. (b) The spatial distribution of the photometric residuals (∆m = mcalibrated − mXP) after applying the full 2D spatial calib… view at source ↗
Figure 7
Figure 7. Figure 7: Calibrated DDO51 magnitude versus photometric uncertainty (MAGERR AUTO from Source Extractor) from the full single-epoch catalog (without catalog merging) after photometric calibration. local linear correction (a sliding linear kernel) as a function of detector position, enabling the precise removal of these medium-scale patterns. To visualize the effectiveness of this spatially resolved photometric calibr… view at source ↗
Figure 8
Figure 8. Figure 8: Left: example science exposure showing multiple linear streaks across the field. Right: sources that fail to match Gaia in the same image, plotted in pixel coordinates; colored segments mark spurious linear features identified as artifacts by the RANSAC-based detection algorithm [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Color–magnitude diagrams in the (BPgaia − DDO51) versus DDO51 plane. (a): Full sources with good quality and well matched with gaia. (b): Subsample of sources matched to the REGALADE galaxy catalog, with galaxy=True illustrating the locus occupied by galaxies. (c): Stellar sample obtained after removing the REGALADE–identified galaxies from the full catalog, yielding a cleaned stellar sequence. In all pane… view at source ↗
Figure 10
Figure 10. Figure 10: DDO51 photometric depth and precision of the merged catalog. (a) Histogram of DDO51 magnitudes for all sources and ”clean” subsample in the final catalogue, showing the number of objects per 0.1-mag bin. (b) Photometric uncertainty (σ) as a function of DDO51 magnitude for individual sources. The background is a two-dimensional histogram color–coded by the logarithmic number of sources per bin, while the r… view at source ↗
Figure 11
Figure 11. Figure 11: Astrometric accuracy of the merged catalog relative to Gaia DR3. (a) Histogram of the angular separation between the merged source positions and the proper–motion–corrected Gaia coordinates, in arcseconds. (b) Angular separation as a function of magnitude; the color scale shows the (logarithmic) number of sources per bin and the red curve traces the running median separation. (c) Right-ascension residuals… view at source ↗
Figure 12
Figure 12. Figure 12: Internal photometric precision of SAGES DDO51 derived from 5.26 million pairs of repeated observations. Top: Distribution of magnitude differences (∆m) for calibrated stars. The red lines mark the ±1σ envelope, and the blue dashed line shows the median bias. Bottom: Single-measurement precision (σint) as a function of magnitude. Dotted lines indicate 1% (10 mmag) and 10% precision levels. 0.4 0.2 0.0 0.2 … view at source ↗
Figure 13
Figure 13. Figure 13: External photometric validation of the SAGES DDO51 calibration. Symbols and color coding follow those in [PITH_FULL_IMAGE:figures/full_fig_p018_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: Performance of SAGES DDO51 photometry in separating dwarfs and giants. The sample is using ”clean” filtered to exclude galaxies and non-isolated sources. (a) Distribution of sources in the observed (uncorrected for extinction) (GBP − DDO51) versus (GBP − GRP ) plane. The color scale represents the logarithmic number density. (b) Variation of the color index (GBP − DDO51) with DDO51 magnitude for stars in … view at source ↗
read the original abstract

We present the first public data release of DDO51 band from the Stellar Abundances and Galactic Evolution Survey (SAGES), based on Nanshan One-meter Wide-field Telescope (NOWT) observations obtained between 2023 September and 2024 January. This release initiates the DDO51-band component of the survey, covering $\sim$ 2,500 deg$^2$ of the northern sky and including more than 10 million sources. The DDO51 filter is centered near the \ion{Mg}{1}~$b$ triplet and the adjacent MgH feature, offering sensitivity to stellar surface gravity. The data reduction pipeline incorporates an improved astrometric solution anchored to Gaia DR3 and a photometric calibration strategy tied to synthetic photometry from Gaia XP spectra. These procedures yield a point-source depth of $\sim$18.9 mag at S/N$\sim$10 and an internal photometric precision $\approx$6-7 mmag at the bright end. A preliminary color--color analysis using Gaia broadband photometry confirms the expected sensitivity of the DDO51 band to stellar surface gravity, demonstrating a clear photometric separation between dwarf and giant sequences for late-type stars. This dataset, when combined with existing SAGES photometry in other bands, provides a crucial tool for disentangling the substructures of the Milky Way. All data products from this release upon publication will be available.

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.

Referee Report

2 major / 1 minor

Summary. The paper presents the first data release of the DDO51 band photometry from the SAGES survey. Based on observations with the Nanshan One-meter Wide-field Telescope from September 2023 to January 2024, it covers about 2500 square degrees of the northern sky with over 10 million sources. The pipeline uses Gaia DR3 for astrometry and synthetic photometry from Gaia XP spectra for calibration, achieving a depth of 18.9 mag and precision of 6-7 mmag. A preliminary color-color analysis demonstrates the DDO51 band's sensitivity to surface gravity through separation of dwarf and giant sequences in late-type stars.

Significance. This data release offers a large photometric catalog with gravity-sensitive measurements that can aid in dissecting the Milky Way's stellar populations and substructures when integrated with other SAGES data. The public availability enhances its value for the astronomical community. The initial validation of the filter's utility supports its use in future galactic evolution studies.

major comments (2)
  1. [Data reduction pipeline] The photometric calibration tied to synthetic photometry from Gaia XP spectra (described in the data reduction pipeline) may suffer from systematic offsets because XP spectra have insufficient resolution to accurately model the narrow DDO51 filter transmission centered on the Mg I b triplet and MgH feature. The paper provides no quantitative tests, such as magnitude residuals versus independent DDO51 observations or versus spectroscopic log g, to show that these offsets do not affect the claimed separation in the color-color diagram.
  2. [Preliminary color-color analysis] The abstract reports a clear photometric separation between dwarf and giant sequences, but lacks supporting details including the size of the separation, the stellar sample size, or any statistical measures. Furthermore, no completeness or purity metrics are given for the separation, which is important for assessing its robustness.
minor comments (1)
  1. [Abstract] The internal photometric precision is given as ≈6-7 mmag; clarifying whether this is the rms or median error and over what magnitude range would improve precision.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed review of our manuscript on the first DDO51 data release from the SAGES survey. We have carefully considered the major comments and provide point-by-point responses below, outlining specific revisions that will be incorporated to address the concerns raised.

read point-by-point responses
  1. Referee: The photometric calibration tied to synthetic photometry from Gaia XP spectra (described in the data reduction pipeline) may suffer from systematic offsets because XP spectra have insufficient resolution to accurately model the narrow DDO51 filter transmission centered on the Mg I b triplet and MgH feature. The paper provides no quantitative tests, such as magnitude residuals versus independent DDO51 observations or versus spectroscopic log g, to show that these offsets do not affect the claimed separation in the color-color diagram.

    Authors: We acknowledge that the limited spectral resolution of Gaia XP spectra could introduce systematic uncertainties when generating synthetic DDO51 photometry for the narrow filter. In the revised manuscript, we will add quantitative validation by cross-matching a subset of our sources with spectroscopic catalogs (e.g., LAMOST or APOGEE) to examine DDO51 magnitude residuals as a function of spectroscopic log g. We will also report any trends or offsets observed and discuss their potential impact on the dwarf-giant separation. This will provide the requested evidence that calibration systematics do not undermine the preliminary results. revision: yes

  2. Referee: The abstract reports a clear photometric separation between dwarf and giant sequences, but lacks supporting details including the size of the separation, the stellar sample size, or any statistical measures. Furthermore, no completeness or purity metrics are given for the separation, which is important for assessing its robustness.

    Authors: We agree that the abstract and the preliminary color-color analysis section would benefit from additional quantitative details. In the revision, we will expand this section to specify the sample size (number of late-type stars selected via Gaia colors), the typical separation between dwarf and giant sequences in the relevant color index (e.g., in magnitudes), and basic statistical measures such as the standard deviation within each sequence. We will further include estimates of completeness and purity for the separation, derived from cross-matching with spectroscopic surveys for a representative subsample. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical calibration and separation rest on external Gaia references

full rationale

The paper is a data-release description whose central demonstration is an empirical color-color diagram showing dwarf/giant separation in DDO51 vs. Gaia colors. The photometric zero-points and color terms are derived from synthetic photometry on external Gaia XP spectra and positions; the separation is then measured directly in the calibrated data against independent Gaia broadband photometry. No equations, fitted parameters, or self-citations are invoked to define the separation in terms of itself, nor is any internal model prediction reduced to the calibration inputs by construction. The chain is therefore self-contained against external benchmarks and receives the default non-circularity finding.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

As a data-release paper the central claims rest on standard photometric reduction techniques and external Gaia catalogs rather than new free parameters or entities.

axioms (1)
  • domain assumption Gaia DR3 positions and XP spectra provide an accurate external reference for astrometry and synthetic photometry.
    Invoked for the improved astrometric solution and photometric calibration strategy.

pith-pipeline@v0.9.0 · 5636 in / 1183 out tokens · 57253 ms · 2026-05-12T02:16:12.582230+00:00 · methodology

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    Relation between the paper passage and the cited Recognition theorem.

    A preliminary color-color analysis using Gaia broadband photometry confirms the expected sensitivity of the DDO51 band to stellar surface gravity, demonstrating a clear photometric separation between dwarf and giant sequences for late-type stars.

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Works this paper leans on

46 extracted references · 46 canonical work pages · 1 internal anchor

  1. [1]

    P., Tollerud, E

    Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, ApJ, 935, 167, doi: 10.3847/1538-4357/ac7c74

  2. [2]

    2020, Research in Astronomy and Astrophysics, 20, 211 21

    Bai, C.-H., Feng, G.-J., Zhang, X., et al. 2020, Research in Astronomy and Astrophysics, 20, 211 21

  3. [3]

    L., Oelkers, R

    Beaton, R. L., Oelkers, R. J., Hayes, C. R., et al. 2021, The Astronomical Journal, 162, 302

  4. [4]

    2006, in Astronomical Data Analysis Software and Systems XV, Vol

    Bertin, E. 2006, in Astronomical Data Analysis Software and Systems XV, Vol. 351, 112

  5. [5]

    1996, Astronomy and astrophysics supplement series, 117, 393

    Bertin, E., & Arnouts, S. 1996, Astronomy and astrophysics supplement series, 117, 393

  6. [6]

    Bessell, M. S. 2005, Annu. Rev. Astron. Astrophys., 43, 293

  7. [7]

    2024, PyGaia: Python toolkit for Gaia science performance simulation and astrometric catalogue data manipulation., https://github.com/agabrown/PyGaia

    Brown, A., et al. 2024, PyGaia: Python toolkit for Gaia science performance simulation and astrometric catalogue data manipulation., https://github.com/agabrown/PyGaia

  8. [8]

    Casagrande, L., & VandenBerg, D. A. 2014, Monthly Notices of the Royal Astronomical Society, 444, 392

  9. [9]

    Schlaufman, K. C. 2018, Monthly Notices of the Royal Astronomical Society, 478, 2812

  10. [10]

    e., Moles, M., Crist´ obal-Hornillos, D., et al

    Cenarro, A. e., Moles, M., Crist´ obal-Hornillos, D., et al. 2019, Astronomy & Astrophysics, 622, A176

  11. [11]

    The Pan-STARRS1 Surveys

    Chambers, K. C., Magnier, E., Metcalfe, N., et al. 2016, arXiv preprint arXiv:1612.05560

  12. [12]

    Clark, J. P. A., & McClure, R. D. 1979, PASP, 91, 507, doi: 10.1086/130529

  13. [13]

    2018, Progress In Astronomy, 36, 101

    Fan, Z., Zhao, G., Wang, W., et al. 2018, Progress In Astronomy, 36, 101

  14. [14]

    2023, The Astrophysical Journal Supplement Series, 268, 9

    Fan, Z., Zhao, G., Wang, W., et al. 2023, The Astrophysical Journal Supplement Series, 268, 9

  15. [15]

    Summary of the content and survey properties

    Fischler, M. A., & Bolles, R. C. 1981, Communications of the ACM, 24, 381 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023a, A&A, 674, A1, doi: 10.1051/0004-6361/202243940 Gaia Collaboration, Montegriffo, P., Bellazzini, M., et al. 2023b, A&A, 674, A33, doi: 10.1051/0004-6361/202243709

  16. [16]

    1984, Publications of the Astronomical Society of the Pacific, 96, 723

    Geisler, D. 1984, Publications of the Astronomical Society of the Pacific, 96, 723

  17. [17]

    1990, Publications of the Astronomical Society of the Pacific, 102, 344

    Geisler, D. 1990, Publications of the Astronomical Society of the Pacific, 102, 344

  18. [18]

    M., Guhathakurta, P., Beaton, R

    Gilbert, K. M., Guhathakurta, P., Beaton, R. L., et al. 2012, The Astrophysical Journal, 760, 76

  19. [19]

    2025, The Astrophysical Journal Supplement Series, 277, 19

    Gu, H., Fan, Z., Zhao, G., et al. 2025, The Astrophysical Journal Supplement Series, 277, 19

  20. [20]

    C., Lee, Y

    Hong, J., Beers, T. C., Lee, Y. S., et al. 2024, The Astrophysical Journal Supplement Series, 273, 12

  21. [21]

    2022, SCIENTIA SINICA

    Huang, B., Xiao, K., & Yuan, H. 2022, SCIENTIA SINICA

  22. [22]

    2024, The Astrophysical Journal Supplement Series, 271, 13

    Huang, B., Yuan, H., Xiang, M., et al. 2024, The Astrophysical Journal Supplement Series, 271, 13

  23. [23]

    C., Yuan, H., et al

    Huang, Y., Beers, T. C., Yuan, H., et al. 2023, The Astrophysical Journal, 957, 65 Ivezi´ c,ˇZ., Beers, T. C., & Juri´ c, M. 2012, Annual Review of Astronomy and Astrophysics, 50, 251 Ivezi´ c,ˇZ., Sesar, B., Juri´ c, M., et al. 2008, The Astrophysical Journal, 684, 287

  24. [24]

    E., et al

    Kaiser, N., Aussel, H., Burke, B. E., et al. 2002, in Survey and Other Telescope Technologies and Discoveries, Vol. 4836, SPIE, 154–164

  25. [25]

    W., Mierle, K., Blanton, M., & Roweis, S

    Lang, D., Hogg, D. W., Mierle, K., Blanton, M., & Roweis, S. 2010, The astronomical journal, 139, 1782

  26. [26]

    2024, arXiv preprint arXiv:2410.10218

    Li, C., Fan, Z., Zhao, G., et al. 2024, arXiv preprint arXiv:2410.10218

  27. [27]

    R., Nidever, D

    Majewski, S. R., Nidever, D. L., Munoz, R. R., et al. 2008, Proceedings of the International Astronomical Union, 4, 51

  28. [28]

    Patterson, R. J. 2000, The Astronomical Journal, 120, 2550

  29. [29]

    Mink, D. J. 2002, in Astronomical Data Analysis Software and Systems XI, Vol. 281, 169

  30. [30]

    L., Olszewski, E

    Morrison, H. L., Olszewski, E. W., Mateo, M., et al. 2001, The Astronomical Journal, 121, 283

  31. [31]

    L., Majewski, S

    Nidever, D. L., Majewski, S. R., Munoz, R. R., et al. 2011, The Astrophysical Journal Letters, 733, L10 ¨Ohman, Y. 1936, Stockholms Observatoriums Annaler, vol. 12, pp. 3.1-3.13, 12, 3

  32. [32]

    2025, arXiv preprint arXiv:2509.10883

    Perryman, M. 2025, arXiv preprint arXiv:2509.10883

  33. [33]

    G., et al

    Prusti, T., De Bruijne, J., Brown, A. G., et al. 2016, Astronomy & astrophysics, 595, A1 R¨ oser, S., Schilbach, E., Schwan, H., et al. 2008, Astronomy & Astrophysics, 488, 401

  34. [34]

    2021, Progress in Astronomy, 39, 118

    Shan, X.-m., Zhong, J., Zhang, Y., et al. 2021, Progress in Astronomy, 39, 118

  35. [35]

    Teig, M. J. 2007, PhD thesis, University of California, Irvine

  36. [36]

    1939, Monthly Notices of the Royal Astronomical Society, Vol

    Thackeray, A. 1939, Monthly Notices of the Royal Astronomical Society, Vol. 99, p. 492, 99, 492

  37. [37]

    J., Beaton, R

    Tollerud, E. J., Beaton, R. L., Geha, M. C., et al. 2012, The Astrophysical Journal, 752, 45

  38. [38]

    A., et al

    Tranin, H., Blagorodnova, N., G´ omez-Mu˜ noz, M. A., et al. 2025, arXiv preprint arXiv:2508.13267

  39. [39]

    2013, Proceedings of the International Astronomical Union, 9, 326

    Wang, W., Zhao, G., Chen, Y., & Liu, Y. 2013, Proceedings of the International Astronomical Union, 9, 326

  40. [40]

    G., Adelman, J., Anderson Jr, J

    York, D. G., Adelman, J., Anderson Jr, J. E., et al. 2000, The Astronomical Journal, 120, 1579

  41. [41]

    2015, The Astrophysical Journal, 799, 133 22

    Yuan, H., Liu, X., Xiang, M., et al. 2015, The Astrophysical Journal, 799, 133 22

  42. [42]

    A., Frinchaboy, P., et al

    Zasowski, G., Johnson, J. A., Frinchaboy, P., et al. 2013, The Astronomical Journal, 146, 81

  43. [43]

    2025, The Astrophysical Journal, 993, 170

    Zhang, Q., Fan, Z., Zhao, G., et al. 2025, The Astrophysical Journal, 993, 170

  44. [44]

    2024, Progress in Astronomy, 42, 698

    ZHENG, J., WANG, W., FAN, Z., LI, C., & ZHAO, G. 2024, Progress in Astronomy, 42, 698

  45. [45]

    2018, Research in Astronomy and Astrophysics, 18, 147

    Zheng, J., Zhao, G., Wang, W., et al. 2018, Research in Astronomy and Astrophysics, 18, 147

  46. [46]

    2019, Astronomical Research and Technology, 16, 93

    Zheng, J., Zhao, G., Wang, W., et al. 2019, Astronomical Research and Technology, 16, 93