Pith. sign in

REVIEW 4 major objections 4 minor 74 references

Phase II of the LAMOST-Kepler/K2 Survey. II. Time Domain of Medium-resolution Spectroscopic Observations from 2018 to 2023

T0 review · 4 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read This paper releases a five-year, 36,588-star catalog of stellar parameters from repeated medium-resolution LAMOST spectra of the Kepler and K2 fields, with internal uncertainties calibrated by epoch scatter and external checks against…

desk verdict A useful five-year time-domain catalog for Kepler/K2 stellar science, but the abstract overstates the external agreement and the quoted error bars omit known systematics in [Fe/H] and [alpha/M]. read the letter →

arxiv 2507.19751 v2 pith:SES7D32C submitted 2025-07-26 astro-ph.SR

classification astro-ph.SR
keywords catalogsspectroscopystellarparameterstime-domainsurveysKepler/K2fieldsradialvelocityvariabilitymetal-poorstarsvariable
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper reports the completion of the first five-year phase of the LAMOST-Kepler/K2 Medium-Resolution Spectroscopic Survey, a time-domain campaign that repeatedly observed 20 plates in the Kepler and K2 fields. From 3.5 million spectra of 49,310 stars, the survey releases a catalog of weighted-mean effective temperature, surface gravity, metallicity, alpha-element abundance, radial velocity, and projected rotation for 36,588 stars. The paper argues these parameters are reliable for temperature, gravity, and radial velocity on the strength of comparisons with APOGEE and GALAH, while metallicity and especially alpha abundance show systematic offsets that users should treat cautiously. It also uses the multi-epoch spectra to identify metal-poor and high-velocity candidates, 2,333 radial-velocity variable candidates, and 371 photometrically confirmed periodic variables. A sympathetic reader would care because this turns the Kepler/K2 light-curve archive into a multi-epoch spectroscopic archive, enabling studies of stellar variability, binaries, and stellar populations with known photometric context.

What carries the argument

The load-bearing mechanism is the repeated-observation design combined with the LAMOST Stellar Parameter Pipeline (LASP), which fits each coadded medium-resolution spectrum to template libraries and reports effective temperature, surface gravity, metallicity, radial velocity, projected rotation, and $\alpha$-element abundance. Multiple epochs of the same star are combined into a signal-to-noise-weighted mean, and the internal uncertainty is calibrated from the scatter of individual measurements about that mean, modeled as $\sigma = a\,(\mathrm{S/N})^b + c$ after iteratively clipping 3-$\sigma$ outliers. External validation then checks these internal errors against independent high-resolution surveys, which is what supports the claim that the catalog is reliable outside its own pipeline.

What would settle it

Restrict the LK-MRS-I stars in common with APOGEE to S/N > 50 and refit the alpha-abundance regression: if the slope stays near 0.42 instead of moving toward 1, the compression is a pipeline systematic that the internal uncertainties miss; if the slope rises to unity, the low-S/N spectra were the cause.

Watch

Extended reading notes

Core claim

The central claim is that five years of repeated medium-resolution spectroscopy with LAMOST can produce homogeneous stellar parameters for 36,588 stars in the Kepler and K2 fields, with per-observation uncertainties of 120 K in effective temperature, 0.18 dex in surface gravity, 0.13 dex in metallicity, 0.08 dex in alpha-element abundance, 1.9 km/s in radial velocity, and 4.0 km/s in projected rotation at S/N = 10, validated against independent high-resolution surveys. The release includes weighted averages over all epochs, and the survey demonstrates its time-domain value by finding 2,333 stars whose radial velocity varies beyond three times its uncertainty; combining these with Kepler/K2 and TESS photometry yields 371 periodic variable stars of classified types. The paper also presents 764 metal-poor and 174 very metal-poor candidates plus 30 high-velocity candidates, including one star whose measured velocities exceed the Galactic escape velocity. The external comparisons show good agreement for radial velocity, effective temperature, and surface gravity but systematic offsets for metallicity and alpha abundance, with regression slopes of about 0.75 and 0.42, so the paper presents the latter quantities as useful but in need of caution.

Load-bearing premise

The quoted uncertainties are the scatter of repeated observations about a signal-to-noise-weighted mean after iterative 3-sigma clipping, and the paper assumes that internal scatter captures the full error budget even though external comparison shows a systematic compression in alpha-element abundance that these error bars do not include.

Editorial extensions

If this is right

  • A reader can pull homogeneous effective temperature, surface gravity, metallicity, alpha abundance, radial velocity, and projected rotation for 36,588 stars in the Kepler/K2 footprints, 18,892 of them in the Kepler/K2 input catalogs, with uncertainties quoted as a function of signal-to-noise ratio.
  • Stars with at least three valid coadded spectra, numbering 17,996, can be used for variability and rotation studies directly from the catalog's multi-epoch measurements.
  • The 2,333 radial-velocity-variable candidates, of which 1,088 have Kepler/K2 photometry and 1,709 have TESS photometry, provide a ready target list for binary and pulsation follow-up.
  • The 371 confirmed periodic variables, 194 newly reported, add classified delta Scuti, gamma Doradus, hybrid, RR Lyrae, eclipsing, RS Canum Venaticorum, and rotating variables to the known stellar populations in these fields.
  • The catalog's external comparisons imply that effective temperature, surface gravity, and radial velocity can be used at face value across the sample, while metallicity and especially alpha abundance require calibration or caution.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the reported alpha-abundance compression is real, the survey's alpha abundances should be treated as relative indices rather than absolute abundances; anchoring them to the roughly 4,500 APOGEE cross-matches could produce a calibrated abundance scale for the full 36,588-star sample.
  • The multi-epoch radial velocities, not just the 371 photometrically confirmed variables, are themselves a resource: combining them with Gaia astrometric orbits could reveal long-period binaries that the 3-sigma radial-velocity threshold misses.
  • The 371 confirmed variables are likely a lower bound on the true variable population, because only about half the radial-velocity-variable candidates have Kepler/K2 or TESS light curves and the periodogram threshold of S/N = 5.6 is conservative.
  • The unbound high-velocity candidate KIC 7881304, with five of seven epochs above the escape velocity, is a strong target for immediate high-resolution follow-up to rule out binary motion or template mismatch.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 4 minor

Summary. The paper presents the LK-MRS-I catalog, derived from five years (2018–2023) of time-domain medium-resolution LAMOST spectroscopy of 20 plates in the Kepler and K2 fields. It releases stellar parameters (Teff, log g, [Fe/H], [α/M], radial velocity, v sin i) for 36,588 unique stars, with per-observation uncertainties quoted at S/N = 10, and validates the parameters against APOGEE, GALAH, and Gaia. It also identifies candidate metal-poor stars, very metal-poor stars, high-velocity stars, and radial-velocity variable stars, and uses Kepler/K2 or TESS photometry to confirm and classify 371 periodic variables.

Significance. If the catalog is reliable, it is a valuable community resource: it provides repeated-epoch, medium-resolution spectra in the Kepler/K2 fields, is processed with the updated LASP pipeline, and includes machine-readable tables. The external validation of Teff, log g, and radial velocity against APOGEE, GALAH, and Gaia is a genuine strength, and the photometric confirmation of variable-star candidates is a useful addition. However, the quoted uncertainties are derived only from internal scatter, and the paper's own external comparison shows substantial scale compressions for [Fe/H] and [α/M]. Because the catalog's headline uncertainties and the metal-poor candidate counts depend on these quantities, the uncertainty budget and the consistency of the text need revision before the catalog can be used as published.

major comments (4)
  1. [Section 3.3 and Section 5] The abstract and Section 3.3 describe the [Fe/H] and [α/M] comparisons as showing 'minor discrepancies' and 'generally good consistency,' yet Section 5 reports regression slopes of approximately 0.75 for [Fe/H] and 0.42 for [α/M] against APOGEE/GALAH. A slope of 0.75 is a 25% compression of the metallicity scale and 0.42 is a major compression of the α-element scale; these are calibration-level systematics, not random noise. Because the uncertainties quoted in Table 3 and the abstract (0.13 dex for [Fe/H], 0.08 dex for [α/M] at S/N = 10) are derived solely from internal scatter in Section 3.2, they do not include these external systematics. This is load-bearing because Section 4.1 selects metal-poor and very metal-poor candidates using [Fe/H] thresholds, and [α/M] is a headline catalog parameter. Please add explicit systematic uncertainty terms for [Fe/H] and [α/M], or substantially soften the abstract and Summary claims and add warnings to the catalog documentation.
  2. [Section 4.1, Abstract, Section 5] The number of metal-poor candidates is internally inconsistent: the abstract and Section 5 state 764 metal-poor stars, while Section 4.1 states 746 metal-poor stars (plus 174 very metal-poor stars). The abstract's total of 938 (764 + 174) also differs from the Section 4.1 total of 920 (746 + 174). Please correct the count and ensure the tables and text agree, because this is a headline result of the paper.
  3. [Table 3, Equation (4)] The v sin i uncertainty fit does not reproduce the tabulated values and is unphysical. With a = 41.52, b = -0.02, c = -36.0 in Equation (4), the predicted uncertainties are 3.65, 3.11, and 2.35 km/s at S/N = 10, 20, and 50, respectively, not the 4.0, 3.5, and 2.9 km/s listed in Table 3. Moreover, as S/N tends to infinity, the fitted curve approaches c = -36 km/s, so the relation becomes negative at sufficiently high S/N. This suggests an error in either the coefficients or the tabulated values. In addition, v sin i receives no external validation in Section 3.3, and Section 3.1 notes that values below 8 km/s are only upper limits; the quoted 4.0 km/s uncertainty therefore needs to be qualified.
  4. [Section 4.3] The radial-velocity variability selection uses the criterion that the standard deviation of RVs exceeds three times the mean RV uncertainty, but no minimum number of epochs is stated. For a star with only two visits, a single discrepant pair can satisfy this criterion, and Equation (2) gives large weight to such cases because of the N/(N-1) factor. The reported 2,333 RV-variable candidates therefore need either a minimum-epoch requirement (e.g., N >= 3 or 5), a demonstration that the false-positive rate is negligible, or a quantitative statement of the epoch distribution used.
minor comments (4)
  1. [Section 3.1 and Section 3.3] The cross-match radius is given as 3.75 arcsec in Section 3.1 and as 3.7 arcsec in Section 3.3 and Footnote 5; please unify the notation.
  2. [Appendix A heading] The heading 'PARAMETERS OF MELTA-POOR STAR CANDIDATES' contains a typo; it should read 'METAL-POOR'.
  3. [Section 2.2] The sentence 'This work presents a statistical analysis of LK-MRS based on the LAMOST DR11 3 Therefore, the current release...' appears garbled, with an orphaned footnote marker and missing punctuation; please rephrase.
  4. [Throughout] The notation for radial velocity is used inconsistently as 'R V', 'RV', and 'radial velocity'; please define a single notation and use it consistently.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the catalog is produced from spectra by an independent pipeline, the quoted uncertainties are calibrated internal scatter, and the key validations use external APOGEE/GALAH/Gaia data.

full rationale

The paper is an observational catalog release, not a derivation of a theory from first principles. The stellar parameters are produced by the LASP template-matching pipeline from individual coadded spectra (Section 3.1), so they are not defined in terms of the paper's own fitted outputs. The internal uncertainty relation, sigma_P = a*x^b + c (Eq. 4), is fitted to the scatter of repeated measurements about the weighted mean (Section 3.2); this is a calibration of repeatability rather than a prediction that is forced by construction. The external validation in Section 3.3 is genuinely external, using APOGEE, GALAH, and Gaia, and the paper openly reports regression slopes below unity for [Fe/H] (~0.75) and [alpha/M] (~0.42), with explicit caution about interpreting [alpha/M]; an incomplete error budget is an accuracy limitation, not circularity. The candidate samples (metal-poor, high-velocity, RV-variable) are threshold selections described as candidates with recommended follow-up, and the RV-variability criterion is a signal-to-noise cut relative to per-epoch uncertainties rather than a self-referential fit. Citations of Paper I for observing strategy and weighting equations are methodological continuity; the load-bearing content (pipeline parameters, external comparisons) does not reduce to those self-citations. No step was found in which an output equals an input by construction, so the circularity score is 0.

Assumptions & free parameters 1 free parameters · 4 assumptions · 0 invented entities

The paper introduces no new entities. It relies on the established LASP pipeline, external survey calibrations, and standard Galactic models. The main fitted quantities are the uncertainty relation coefficients in Table 3, which are used to characterize the catalog's internal precision.

free parameters (1)
  • Uncertainty model coefficients a, b, c for Teff, log g, [Fe/H], [alpha/M], R V, v sin i = e.g., Teff: a=1593, b=-1.16, c=9.5; v sin i: a=41.52, b=-0.02, c=-36.0
    Fitted to the internal scatter of repeated measurements (Figure 3) to quote uncertainties at S/N=10, 20, 50.
assumptions (4)
  • domain assumption LASP pipeline template matching to ELODIE templates yields accurate parameters for late-A to K stars.
    Section 3.1 states LASP is limited to these spectral types.
  • domain assumption External surveys (APOGEE, GALAH, Gaia) provide accurate reference parameters for validation.
    Section 3.3 uses them as benchmarks for external uncertainty estimation.
  • domain assumption The iterative 3-sigma clipping and the power-law fit (Eq 4) describe true measurement uncertainty.
    Section 3.2 uses this model to quote uncertainties at various S/N.
  • domain assumption The Galactic potential model implemented in Galpy is appropriate for computing escape velocities.
    Section 4.2 uses Galpy to model the escape velocity curve.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Phase II of the LAMOST-Kepler/K2 Survey. II. Time Domain of Medium-resolution Spectroscopic Observations from 2018 to 2023." pith.science (2026). https://pith.science/paper/SES7D32C

@misc{pith2026250719751,
  author       = {Pith},
  title        = {Pith review of: Phase II of the LAMOST-Kepler/K2 Survey. II. Time Domain of Medium-resolution Spectroscopic Observations from 2018 to 2023},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SES7D32C}},
  note         = {Machine review of arXiv:2507.19751}
}
read the original abstract

The LAMOST-Kepler/K2 Medium-Resolution Spectroscopic Survey (LK-MRS) conducted time-domain medium-resolution spectroscopic observations of 20 LAMOST plates in the Kepler and K2 fields from 2018 to 2023, a phase designated as LK-MRS-I. A catalog of stellar parameters for a total of 36,588 stars, derived from the spectra collected during these five years, including the effective temperature, the surface gravity, the metallicity, the {\alpha}-element abundance, the radial velocity, and v sin i of the target stars, is released, together with the weighted averages and uncertainties. At S/N = 10, the measurement uncertainties are 120 K, 0.18 dex, 0.13 dex, 0.08 dex, 1.9 km/s, and 4.0 km/s for the above parameters, respectively. Comparisons with the parameters provided by the APOGEE and GALAH surveys validate the effective temperature and surface gravity measurements, showing minor discrepancies in metallicity and {\alpha}-element abundance values. We identified some peculiar star candidates, including 764 metal-poor stars, 174 very metal-poor stars, and 30 high-velocity stars. Moreover, we found 2,333 stars whose radial velocity seems to be variable. Using Kepler/K2 or TESS photometric data, we confirmed 371 periodic variable stars among the radial velocity variable candidates and classified their variability types. LK-MRS-I provides spectroscopic data being useful for studies of the Kepler and K2 fields. The LK-MRS project will continue collecting time-domain medium-resolution spectra for target stars during the third phase of LAMOST surveys, providing data to support further scientific research.

Figures

Figures reproduced from arXiv: 2507.19751 by the authors.

Figure 1
Figure 1. Spatial distribution of plates of the LK–MRS-I. The yellow dash line represents the ecliptic plane. The inset shows the exposure counts for each plate. Blue bars represent plates that have been observed, while orange bars indicate plates observed during the testing phase. velocity stars, metal-poor stars, and those exhibiting radial velocity variations. Finally, Section 5 summarizes the key findings of this study. 2… view at source ↗
Figure 2
Figure 2. Distribution of exposure times for LK-MRS-I sources in the Kepler (left) and K2 (right) surveys. The histogram (vertical bars) shows stellar counts per exposure bin, while the stepped curve (black) displays the reverse cumulative distribution function (CDF) computed from the maximum exposure time downward (i.e., fraction of stars with exposure time ≥ t). The red dashed line indicates the median exposure (50th percen… view at source ↗
Figure 3
Figure 3. S/N versus internal uncertainties for the five parameters Teff, log g, [α/M], RV, and v sin i. Gray points represent data identified as outliers, while cyan points correspond to data retained after filtering. The black dashed vertical line indicates the zero point on the x-axis, and the black dashed curves on either side represent the fitted relationship between ∆P and S/N, as modeled by Equation 4 [PITH_FULL_IMAGE… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Comparison of stellar parameters between LK-MRS-I and APOGEE for giant stars (top row) and dwarf stars (bottom row). Each panel shows a 2D Gaussian density plot, where the color indicates the density of data points. The linear regression (red line) is fitted only to th…
Figure 5
Figure 5. Figure 5: Same as [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]
Figure 6
Figure 6. Figure 6: Comparison of RVs in the LK–MRS project for giants (top row) and dwarfs (bottom row). Each column corresponds to a survey (from left to right: Gaia, APOGEE, and GALAH). For each panel group, the top-left plot shows the RV comparison between LK-MRS-I and the external re…
Figure 7
Figure 7. Figure 7: The histogram shows the distribution of stellar metallicities [Fe/H] for 35,614 stars measured by LK-MRS-I. The blue bars represent the overall metallicity distribution, while the orange and red bars highlight metal-poor (−2.0 ≤ [Fe/H] ≤ −1.0) and very metal-poor (−2.5…
Figure 8
Figure 8. Figure 8: The figure illustrates the distribution of stars as a function of their galactocentric radial distance (RGC ) and total velocity (VGC ). The blue curve represents the Galactic escape velocity, while the orange curve marks 70% of this threshold. The open circles indicat…
Figure 9
Figure 9. Figure 9: Effective temperature versus absolute magnitude diagram (Teff vs. MG) for variable stars identified in the LK-MRS-I survey. The observational δ Sct IS is shown as a blue dashed line, the theoretical δ Sct IS as a green band, and the γ Dor IS as a blue dotted line. Blac…

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

74 extracted references · 25 canonical work pages

  1. [1]

    H """"""

    thebibliography [1] 20pt to REFERENCES 6pt =0pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command Each re...

  2. [2]

    2022, , 259, 35, 10.3847/1538-4365/ac4414

    Abdurro'uf , Accetta , K., Aerts , C., et al. 2022, , 259, 35, 10.3847/1538-4365/ac4414

  3. [3]

    2018, , 238, 36, 10.3847/1538-4365/aadfe9

    Abohalima , A., & Frebel , A. 2018, , 238, 36, 10.3847/1538-4365/aadfe9

  4. [4]

    M., Lim , P

    Astropy Collaboration , Price-Whelan , A. M., Lim , P. L., et al. 2022, , 935, 167, 10.3847/1538-4357/ac7c74

  5. [5]

    Kepler's Discoveries Will Continue: 21 Important Scientific Opportunities with Kepler & K2 Archive Data

    Barentsen , G., Hedges , C., Saunders , N., et al. 2018, arXiv e-prints, arXiv:1810.12554, 10.48550/arXiv.1810.12554

  6. [6]

    C., & Christlieb , N

    Beers , T. C., & Christlieb , N. 2005, , 43, 531, 10.1146/annurev.astro.42.053102.134057

  7. [7]

    J., Koch , D., Basri , G., et al

    Borucki , W. J., Koch , D., Basri , G., et al. 2010, Science, 327, 977, 10.1126/science.1185402

  8. [8]

    2015, , 216, 29, 10.1088/0067-0049/216/2/29

    Bovy , J. 2015, , 216, 29, 10.1088/0067-0049/216/2/29

Show all 74 references
  1. [9]

    2021, , 506, 150, 10.1093/mnras/stab1242

    Buder , S., Sharma , S., Kos , J., et al. 2021, , 506, 150, 10.1093/mnras/stab1242

  2. [10]

    2024, , 690, A367, 10.1051/0004-6361/202349106

    Castro-Tapia , M., Aguilera-G \'o mez , C., & Chanam \'e , J. 2024, , 690, A367, 10.1051/0004-6361/202349106

  3. [11]

    2016, , 823, 102, 10.3847/0004-637X/823/2/102

    Choi , J., Dotter , A., Conroy , C., et al. 2016, , 823, 102, 10.3847/0004-637X/823/2/102

  4. [12]

    N., Ren , A

    De Cat , P., Fu , J. N., Ren , A. B., et al. 2015, , 220, 19, 10.1088/0067-0049/220/1/19

  5. [13]

    2016, , 222, 8, 10.3847/0067-0049/222/1/8

    Dotter , A. 2016, , 222, 8, 10.3847/0067-0049/222/1/8

  6. [14]

    A., Grigahc \`e ne , A., Garrido , R., Gabriel , M., & Scuflaire , R

    Dupret , M. A., Grigahc \`e ne , A., Garrido , R., Gabriel , M., & Scuflaire , R. 2005, , 435, 927, 10.1051/0004-6361:20041817

  7. [15]

    Y., Alonso-Santiago , J., et al

    Frasca , A., Zhang , J. Y., Alonso-Santiago , J., et al. 2025, , 698, A7, 10.1051/0004-6361/202553673

  8. [16]

    2022, , 664, A78, 10.1051/0004-6361/202243268

    Frasca , A., Molenda- \.Z akowicz , J., Alonso-Santiago , J., et al. 2022, , 664, A78, 10.1051/0004-6361/202243268

  9. [17]

    2020, Research in Astronomy and Astrophysics, 20, 167, 10.1088/1674-4527/20/10/167

    Fu , J.-N., De Cat , P., Zong , W., et al. 2020, Research in Astronomy and Astrophysics, 20, 167, 10.1088/1674-4527/20/10/167

  10. [18]

    2022, VizieR Online Data Catalog: Gaia DR3 Part 4

    Gaia Collaboration . 2022, VizieR Online Data Catalog: Gaia DR3 Part 4. Variability (Gaia Collaboration, 2022) , VizieR On-line Data Catalog: I/358. Originally published in: Astron. Astrophys., in prep. (2022)

  11. [19]

    Gaia Collaboration , Prusti , T., de Bruijne , J. H. J., et al. 2016, , 595, A1, 10.1051/0004-6361/201629272

  12. [20]

    Gaia Collaboration , Vallenari , A., Brown , A. G. A., et al. 2023, , 674, A1, 10.1051/0004-6361/202243940

  13. [21]

    Green , G. M. 2018, The Journal of Open Source Software, 3, 695, 10.21105/joss.00695

  14. [22]

    2023, , 264, 12, 10.3847/1538-4365/ac9eac

    Han , H., Wang , S., Bai , Y., et al. 2023, , 264, 12, 10.3847/1538-4365/ac9eac

  15. [23]

    A., et al

    Hocd \'e , V., Moskalik , P., Gorynya , N. A., et al. 2024, , 689, A224, 10.1051/0004-6361/202347798

  16. [24]

    B., Sobeck , C., Haas , M., et al

    Howell , S. B., Sobeck , C., Haas , M., et al. 2014, , 126, 398, 10.1086/676406

  17. [25]

    2024, , 168, 280, 10.3847/1538-3881/ad8913

    Jin , M., Fu , J., Zhang , X., et al. 2024, , 168, 280, 10.3847/1538-3881/ad8913

  18. [26]

    2024, , 966, 69, 10.3847/1538-4357/ad3038

    Li , X., Wang , S., Han , H., et al. 2024, , 966, 69, 10.3847/1538-4357/ad3038

  19. [27]

    2022, , 938, 78, 10.3847/1538-4357/ac8f29

    Li , X., Wang , S., Zhao , X., et al. 2022, , 938, 78, 10.3847/1538-4357/ac8f29

  20. [28]

    L., Lu , Y.-J., et al

    Li , Y.-B., Luo , A. L., Lu , Y.-J., et al. 2021, , 252, 3, 10.3847/1538-4365/abc16e

  21. [29]

    2024, , 167, 76, 10.3847/1538-3881/ad18c4

    Liao , J., Du , C., Deng , M., et al. 2024, , 167, 76, 10.3847/1538-3881/ad18c4

  22. [30]

    2020, arXiv e-prints, arXiv:2005.07210, 10.48550/arXiv.2005.07210

    Liu , C., Fu , J., Shi , J., et al. 2020, arXiv e-prints, arXiv:2005.07210, 10.48550/arXiv.2005.07210

  23. [31]

    2025, , 978, L32, 10.3847/2041-8213/ad93cc

    Lu , H.-P., Tian , H., Zhang , L.-Y., et al. 2025, , 978, L32, 10.3847/2041-8213/ad93cc

  24. [32]

    L., Zhao , Y.-H., Zhao , G., et al

    Luo , A. L., Zhao , Y.-H., Zhao , G., et al. 2015, Research in Astronomy and Astrophysics, 15, 1095, 10.1088/1674-4527/15/8/002

  25. [33]

    Y., Zong , W., Fu , J

    Ma , X. Y., Zong , W., Fu , J. N., et al. 2023, , 680, A11, 10.1051/0004-6361/202347410

  26. [34]

    R., Santos , \^A

    Mathur , S., Claytor , Z. R., Santos , \^A . R. G., et al. 2023, , 952, 131, 10.3847/1538-4357/acd118

  27. [35]

    J., Hey , D., Van Reeth , T., & Bedding , T

    Murphy , S. J., Hey , D., Van Reeth , T., & Bedding , T. R. 2019, , 485, 2380, 10.1093/mnras/stz590

  28. [36]

    2024, , 168, 253, 10.3847/1538-3881/ad84f5

    Pan , Y., Frasca , A., Wang , J.-X., Fu , J.-N., & Zhang , X.-B. 2024, , 168, 253, 10.3847/1538-3881/ad84f5

  29. [37]

    2020, , 905, 67, 10.3847/1538-4357/abc250

    Pan , Y., Fu , J.-N., Zong , W., et al. 2020, , 905, 67, 10.3847/1538-4357/abc250

  30. [38]

    G., Moharana , A., et al

    Pawar , T., He miniak , K. G., Moharana , A., et al. 2024, , 691, A101, 10.1051/0004-6361/202451126

  31. [39]

    2011, , 192, 3, 10.1088/0067-0049/192/1/3

    Paxton , B., Bildsten , L., Dotter , A., et al. 2011, , 192, 3, 10.1088/0067-0049/192/1/3

  32. [40]

    2013, , 208, 4, 10.1088/0067-0049/208/1/4

    Paxton , B., Cantiello , M., Arras , P., et al. 2013, , 208, 4, 10.1088/0067-0049/208/1/4

  33. [41]

    2015, , 220, 15, 10.1088/0067-0049/220/1/15

    Paxton , B., Marchant , P., Schwab , J., et al. 2015, , 220, 15, 10.1088/0067-0049/220/1/15

  34. [42]

    H., Elsworth , Y., Epstein , C., et al

    Pinsonneault , M. H., Elsworth , Y., Epstein , C., et al. 2014, , 215, 19, 10.1088/0067-0049/215/2/19

  35. [43]

    H., Elsworth , Y

    Pinsonneault , M. H., Elsworth , Y. P., Tayar , J., et al. 2018, , 239, 32, 10.3847/1538-4365/aaebfd

  36. [44]

    R., Winn , J

    Ricker , G. R., Winn , J. N., Vanderspek , R., et al. 2014, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9143, Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave, ed. J. M. Oschmann , Jr., M. Clampin , G. G...

  37. [45]

    K., Bardalez-Gagliuffi , D., et al

    Rothermich , A., Faherty , J. K., Bardalez-Gagliuffi , D., et al. 2024, , 167, 253, 10.3847/1538-3881/ad324e

  38. [46]

    2017, , 233, 23, 10.3847/1538-4365/aa97df

    Serenelli , A., Johnson , J., Huber , D., et al. 2017, , 233, 23, 10.3847/1538-4365/aa97df

  39. [47]

    2011, Kepler/KIC, STScI/MAST, 10.17909/T9059R

    STScI . 2011, Kepler/KIC, STScI/MAST, 10.17909/T9059R

  40. [48]

    2016 a , Kepler/EPIC, STScI/MAST, 10.17909/T93W28

    ---. 2016 a , Kepler/EPIC, STScI/MAST, 10.17909/T93W28

  41. [49]

    2016 b , Kepler LC+SC, Q0-Q17, STScI/MAST, 10.17909/T98304

    ---. 2016 b , Kepler LC+SC, Q0-Q17, STScI/MAST, 10.17909/T98304

  42. [50]

    2016 c , K2 Light Curves (all), STScI/MAST, 10.17909/T9WS3R

    ---. 2016 c , K2 Light Curves (all), STScI/MAST, 10.17909/T9WS3R

  43. [51]

    2018, TESS Input Catalog and Candidate Target List, STScI/MAST, 10.17909/FWDT-2X66

    ---. 2018, TESS Input Catalog and Candidate Target List, STScI/MAST, 10.17909/FWDT-2X66

  44. [52]

    2021 a , TESS Light Curves - All Sectors, STScI/MAST, 10.17909/T9-NMC8-F686

    Team, M. 2021 a , TESS Light Curves - All Sectors, STScI/MAST, 10.17909/T9-NMC8-F686

  45. [53]

    2021 b , TESS "Fast" Light Curves - All Sectors, STScI/MAST, 10.17909/T9-ST5G-3177

    ---. 2021 b , TESS "Fast" Light Curves - All Sectors, STScI/MAST, 10.17909/T9-ST5G-3177

  46. [54]

    2021, , 506, 6117, 10.1093/mnras/stab1705

    Wang , J., Fu , J.-N., Zong , W., Wang , J., & Zhang , B. 2021, , 506, 6117, 10.1093/mnras/stab1705

  47. [55]

    2024, , 690, A201, 10.1051/0004-6361/202449484

    Wang , J., Pan , Y., Fu , J., et al. 2024, , 690, A201, 10.1051/0004-6361/202449484

  48. [56]

    2020, , 251, 27, 10.3847/1538-4365/abc1ed

    Wang , J., Fu , J.-N., Zong , W., et al. 2020, , 251, 27, 10.3847/1538-4365/abc1ed

  49. [57]

    L., Zhang , S., et al

    Wang , R., Luo , A. L., Zhang , S., et al. 2023, , 266, 40, 10.3847/1538-4365/acce36

  50. [58]

    L., Chen , J

    Wang , R., Luo , A. L., Chen , J. J., et al. 2019, , 244, 27, 10.3847/1538-4365/ab3cc0

  51. [59]

    L., Henden , A

    Watson , C. L., Henden , A. A., & Price , A. 2006, Society for Astronomical Sciences Annual Symposium, 25, 47

  52. [60]

    2000, , 143, 9, 10.1051/aas:2000332

    Wenger , M., Ochsenbein , F., Egret , D., et al. 2000, , 143, 9, 10.1051/aas:2000332

  53. [61]

    C., Hearty , F

    Wilson , J. C., Hearty , F. R., Skrutskie , M. F., et al. 2019, , 131, 055001, 10.1088/1538-3873/ab0075

  54. [62]

    A., Sharma , S., Stello , D., et al

    Wittenmyer , R. A., Sharma , S., Stello , D., et al. 2018, , 155, 84, 10.3847/1538-3881/aaa3e4

  55. [63]

    C., Jofr \'e , P., Rendle , B., et al

    Worley , C. C., Jofr \'e , P., Rendle , B., et al. 2020, , 643, A83, 10.1051/0004-6361/201936726

  56. [64]

    2022, The Innovation, 3, 100224, 10.1016/j.xinn.2022.100224

    Yan , H., Li , H., Wang , S., et al. 2022, The Innovation, 3, 100224, 10.1016/j.xinn.2022.100224

  57. [65]

    R., Stello , D., et al

    Yu , J., Bedding , T. R., Stello , D., et al. 2020, , 493, 1388, 10.1093/mnras/staa300

  58. [66]

    2021, , 256, 14, 10.3847/1538-4365/ac0834

    Zhang , B., Li , J., Yang , F., et al. 2021, , 256, 14, 10.3847/1538-4365/ac0834

  59. [67]

    2022, , 258, 26, 10.3847/1538-4365/ac42d1

    Zhang , B., Jing , Y.-J., Yang , F., et al. 2022, , 258, 26, 10.3847/1538-4365/ac42d1

  60. [68]

    2012, Research in Astronomy and Astrophysics, 12, 723, 10.1088/1674-4527/12/7/002

    Zhao , G., Zhao , Y.-H., Chu , Y.-Q., Jing , Y.-P., & Deng , L.-C. 2012, Research in Astronomy and Astrophysics, 12, 723, 10.1088/1674-4527/12/7/002

  61. [69]

    2024, , 167, 227, 10.3847/1538-3881/ad3357

    Zong , P., Fu , J.-N., Su , J., et al. 2024, , 167, 227, 10.3847/1538-3881/ad3357

  62. [70]

    2016, , 585, A22, 10.1051/0004-6361/201526300

    Zong , W., Charpinet , S., Vauclair , G., Giammichele , N., & Van Grootel , V. 2016, , 585, A22, 10.1051/0004-6361/201526300

  63. [71]

    2018, , 238, 30, 10.3847/1538-4365/aadf81

    Zong , W., Fu , J.-N., De Cat , P., et al. 2018, , 238, 30, 10.3847/1538-4365/aadf81

  64. [72]

    2020, , 251, 15, 10.3847/1538-4365/abbb2d

    ---. 2020, , 251, 15, 10.3847/1538-4365/abbb2d

  65. [73]

    L., Du , B., et al

    Zuo , F., Luo , A. L., Du , B., et al. 2024, , 271, 4, 10.3847/1538-4365/ad1eeb

  66. [74]

    - [1] #1 = = ^ ^ ^ .\!\!^ d .\!\!^ h .\!\!^ m .\!\!^ s .\!\!^ @mss

    thebibliography [1] 20pt to REFERENCES 6pt =0pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environm...

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.