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Abundance analysis of benchmark M dwarfs

T0 review · 4 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read A Sun-differential near-infrared line-by-line analysis gives benchmark Fe, Ti, and Ca abundances for nine M dwarfs that agree with previous studies mostly within uncertainties.

desk verdict Solid, honest differential abundance analysis of nine M dwarfs, but the GJ 725 binary offset implies a ~0.15 dex systematic floor not captured by the quoted uncertainties—benchmark claim needs qualification. read the letter →

arxiv 2505.07116 v1 pith:NXHXBLEQ submitted 2025-05-11 astro-ph.SR astro-ph.GA

T. Olander (1) , U. Heiter (1) , N. Piskunov (1) , J. Köhler (2) , O. Kochukhov (1) ((1) Department of Physics , Astronomy , Uppsala University , Sweden
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(2) Thüringer Landessternwarte Tautenburg Germany)
This is my paper · ORCID
classification astro-ph.SRastro-ph.GA
keywords Mdwarfsstellarabundancesirontitaniumcalciumdifferentialabundanceanalysisnear-infraredspectroscopybenchmarkstars
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

M dwarfs are the most common stars in the Galaxy and frequent exoplanet hosts, but their molecular-blanketed atmospheres make abundance work difficult. This paper obtains iron, titanium, and calcium abundances for nine well-studied M dwarfs whose effective temperatures and surface gravities were fixed by interferometry, so that the stars can serve as calibration anchors for large surveys. Using high-resolution near-infrared spectra and synthetic fits with MARCS model atmospheres, the authors subtract the Sun's abundance line by line and take the median as the final value. The resulting [Fe/H], [Ti/H], and [Ca/H] values mostly agree with earlier studies within their quoted uncertainties, with the weakest agreement for calcium and a few individual stars.

What carries the argument

The load-bearing mechanism is the line-by-line differential abundance analysis: each Fe I, Ti I, and Ca I line in the M dwarf is fitted with a synthetic spectrum computed from a 1D LTE model-atmosphere grid in a spectral synthesis code, and then the abundance derived from the same line in a high-resolution solar spectrum is subtracted. Taking the median of the line-by-line differences removes, to first order, shared errors in oscillator strengths, damping, and model structure; the median absolute difference of those line values is quoted as the uncertainty. The analysis is anchored to interferometric effective temperatures and gravities, and the fitted lines were visually screened and iterated over Fe, Ti, and Ca to break abundance degeneracies.

What would settle it

Analyse GJ 699 through an intermediate K-type star in a stepwise differential chain; if the inferred [Fe/H] departs from the directly subtracted value by more than the reported ~0.18 dex uncertainty, the direct Sun-to-M-dwarf cancellation assumption fails.

Watch

Extended reading notes

Core claim

The central claim is that a differential, line-by-line spectral synthesis of the 1.03–1.31 μm region yields benchmark Fe, Ti, and Ca abundances for nine M dwarfs with interferometric stellar parameters. Abundances are computed for each fitted Fe I, Ti I, or Ca I line, and the same line's solar abundance is subtracted to cancel shared errors in the model and atomic data; the median of the accepted lines is the final [X/H], and the median absolute deviation is the uncertainty. The paper reports agreement with earlier work mostly within uncertainties for [Fe/H] and [Ti/H], while [Ca/H] comes out systematically lower by about 0.2 dex than one comparison set and shows larger scatter. It also finds a 0.15 dex difference in [Fe/H] between the two components of the GJ 725 binary, which it reads as a warning about the true precision. The intended product is a small benchmark sample for calibrating abundance tools applied to large M-dwarf surveys.

Load-bearing premise

The results depend on the assumption that a one-dimensional model atmosphere in local thermodynamic equilibrium, with a generic atomic line list, predicts the shape of each Fe, Ti, and Ca line well enough that subtracting the Sun from the same calculation removes the main systematic errors, even though the Sun and an M dwarf are very different stars.

Editorial extensions

If this is right

  • The nine stars can serve as calibration anchors for machine-learned abundance estimators trained on large near-infrared M-dwarf surveys.
  • The reported [Fe/H], [Ti/H], and [Ca/H] values provide cross-checks for earlier photometric and spectroscopic calibrations of the same stars.
  • The abundances supply the refractory-element ratios needed to connect M-dwarf host stars to the inferred compositions of their terrestrial planets.
  • Calcium results should be treated with caution until non-LTE and line-list effects are addressed, because the paper finds a systematic offset against one literature set and larger scatter.
  • The GJ 725 binary discrepancy gives a concrete internal consistency target: stars born from the same cloud should match, so reducing that 0.15 dex difference would raise confidence in the whole method.

Reading between the lines

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

  • Adding an intermediate K-type star to the differential chain, an idea the paper raises in its discussion, would likely bring weaker lines such as Si I into reach, letting the same benchmark stars carry more elements than Fe, Ti, and Ca.
  • The 0.15 dex [Fe/H] difference between the GJ 725 components sets an internal consistency test: if one component's spectrum is re-reduced with a continuum treatment that removes fringing, a smaller binary difference would indicate that part of the quoted uncertainties is still systematic.
  • Because the paper finds literature abundances often disagree outside their quoted errors, running several pipelines on the same GIANO-B spectra would expose whether the spread is a shared model dependence in M-dwarf abundance work.
  • For cool, low-metallicity stars like GJ 699, combining atomic Fe I lines with FeH molecular lines could lower the [Fe/H] uncertainty, provided the two independent iron indicators agree once the molecular data are included.
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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 a differential abundance analysis of near-infrared GIANO-B spectra of nine M dwarfs with interferometrically determined effective temperatures and surface gravities. Using Turbospectrum/TSFitPy with MARCS model atmospheres and a VALD line list, the authors fit Fe I, Ti I, and Ca I lines line-by-line, subtract solar abundances derived with the same procedure, and take the median as the final abundance. They report [Fe/H], [Ti/Fe], and [Ca/Fe] with MAD uncertainties, compare with literature values, and propose the sample as benchmarks for future large-scale surveys. The paper includes the full line list and per-star line usage in the appendix.

Significance. The sample fills a gap: there are few abundance benchmarks for M dwarfs with interferometric parameters, and the study uses a consistent differential procedure with careful visual line inspection. The authors are transparent about limitations (fringing, line-list quality, non-LTE, the solar-to-M-dwarf spectral-type gap), and they provide the fitted line sets in Tables A.2-A.4, which is useful for reproducibility. However, the central benchmark claim is not yet fully supported: the GJ 725 binary shows a 0.15 dex internal [Fe/H] discrepancy, the quoted MAD uncertainties reflect only line scatter after post-hoc rejection, and systematic errors from the 1D LTE/MARCS/VALD setup are not quantified. These issues are addressable in revision.

major comments (4)
  1. [§4, Table 3, Fig. 5] The coeval binary GJ 725A/B yields [Fe/H] = -0.477 ± 0.259 and -0.329 ± 0.202, a difference of ~0.15 dex, plus ~0.10 dex in [Ca/Fe], whereas Maldonado et al. (2020) and Souto et al. (2022) find component differences of 0.01-0.05 dex. The authors attribute this to lower SNR and different selected line subsets, but they do not propagate this discrepancy into the quoted uncertainties or into the 'mostly agree within uncertainties' conclusion. Since the aim is to provide benchmark abundances, this internal systematic floor must be either reduced (e.g., by forcing a common line list) or explicitly added to the error budget; otherwise the benchmark claim is not supported.
  2. [§3, 'Metallicity and abundances'] The description of the solar reference analysis is ambiguous. The sentence 'we did not alter the Ti and Ca abundances' can be read as saying that Ti and Ca were not fitted in the solar spectrum. If that is the case, there is no line-by-line solar Ti and Ca abundance to subtract, and the differential correction for these elements would not remove line-dependent systematics, contrary to the stated method. Please clarify whether the Sun was fitted for Ti and Ca and, if not, state the resulting limitation for [Ti/H] and [Ca/H].
  3. [§3.2] Lines were rejected when the derived abundance fell outside 1-2 standard deviations from the median and after visual inspection of the fit quality. The final MAD is computed from the accepted lines only. This post-hoc rejection biases the scatter low and makes the quoted uncertainties optimistic. The authors should report the number of rejected lines per star and element, and test the sensitivity of the median abundances to the rejection threshold (e.g., 3 sigma or no clipping).
  4. [§5 and §3] The uncertainties in Table 3 are purely line-to-line MAD values and do not include systematic errors from the 1D LTE MARCS assumption, the generic VALD line list without astrophysical gf corrections, or the large spectral-type gap between the Sun and the M dwarfs in the differential analysis. The paper acknowledges these effects in the discussion but does not quantify them. Because the central claim is that these stars are benchmarks whose abundances 'agree within uncertainties', a quantitative or at least bounding estimate of these systematic errors is needed.
minor comments (4)
  1. [Table 2 and §3] '3 sin i' should be 'v sin i' (the projected equatorial rotational velocity).
  2. [§2] 'Stephan-Boltzmann law' should be 'Stefan-Boltzmann law'.
  3. [§5] 'An example ca be seen' should be 'can be seen'.
  4. [§4, Fig. 5] The comparison with Souto et al. (2022) and Melo et al. (2024) shows a clear ~0.2 dex offset in [Ca/H]; the abstract's 'mostly within uncertainties' should be qualified to account for this element-specific offset.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the abundances are measured via an externally calibrated differential analysis, not derived from their own inputs.

full rationale

The paper's abundance derivation is not circular. The input parameters (Teff, log g, initial [Fe/H]) are adopted from external studies (Boyajian et al. 2012; Mann et al. 2015; Reiners et al. 2018; Fouque et al. 2018), and the reported Fe, Ti, and Ca abundances are fitted quantities that are free to disagree with those inputs. The differential solar subtraction is an external calibration: the same line-by-line pipeline is applied to a solar FTS spectrum and the derived solar abundances are subtracted line-by-line, so the M dwarf abundances are not equal by construction to any input abundance. The paper even reports a case where the derived [Fe/H] differs strongly from the adopted input (GJ 809: +0.221 dex derived vs. -0.06 dex input), demonstrating that the fit is not forced. The acknowledged limitations in Sect. 5 (large Sun-to-M-dwarf spectral-type gap, generic VALD line list without astrophysical log(gf) corrections, possible non-LTE effects, fringing/continuum problems) are disclosed systematic-error concerns rather than self-referential steps. Self-citations (REDUCE, TSFitPy, VALD, earlier Olander papers) are tool or prior-parameter references, not load-bearing uniqueness arguments. The internal GJ 725A/B abundance offset is an accuracy and calibration issue, not a circularity, because the authors do not use the binary identity as an input to force the abundances. No specific equation or claim can be quoted in which a predicted quantity reduces to its own input, so the appropriate finding is no significant circularity.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

This is an observational measurement paper; there are no invented entities. The main assumptions are the validity of the adopted model atmospheres, line list, and stellar parameters, plus the empirical microturbulence relation. These are standard in the field but not independently verified here.

free parameters (2)
  • Microturbulence (Vturb) = Determined from an unpublished empirical relation (Gaia-ESO, via TSFitPy)
    Vturb is computed from Teff, log g, and [Fe/H] using a relation whose coefficients are given only as a private communication; it affects line broadening and derived abundances.
  • Macroturbulence = Fitted per star by TSFitPy
    Macroturbulence is set as free in the fitting (Sect. 3); it changes line profiles and can trade off against abundance.
assumptions (4)
  • domain assumption Adopted stellar parameters (Teff, log g, vsini) from Boyajian et al. (2012), Mann et al. (2015), Reiners et al. (2018), and Fouque et al. (2018) are accurate.
    These parameters fix the model atmospheres; errors in them propagate directly into abundances. Table 2 lists adopted values; the authors note an inconsistency for GJ 725B.
  • domain assumption 1D LTE MARCS models are adequate for NIR M dwarf abundance analysis.
    The entire fitting uses MARCS grids; non-LTE effects for Ca and Ti are discussed but not corrected. Section 5.
  • domain assumption The VALD line list (no astrophysical log gf corrections) is accurate enough for a differential solar-relative analysis.
    Line list from VALD extraction (Sect. 3.1); the authors state bad lines may be due to incorrect atomic data and suggest an astrophysically corrected line list would improve results.
  • domain assumption The solar differential zero-point is set correctly by fixing solar metallicity to zero and using the Reiners et al. (2016) FTS solar spectrum.
    The differential method subtracts line-by-line solar abundances; any error in the solar analysis shifts all M dwarf abundances in the same direction. Section 3.

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Cite this review

Pith. "Pith review of Abundance analysis of benchmark M dwarfs." pith.science (2026). https://pith.science/paper/NXHXBLEQ

@misc{pith2026250507116,
  author       = {Pith},
  title        = {Pith review of: Abundance analysis of benchmark M dwarfs},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/NXHXBLEQ}},
  note         = {Machine review of arXiv:2505.07116}
}
read the original abstract

Abundances of M dwarfs, being the most numerous stellar type in the Galaxy, can enhance our understanding of planet formation processes. They can also be used to study the chemical evolution of the Galaxy, where in particular alpha-capture elements play an important role. We aim to obtain abundances for Fe, Ti, and Ca for a small sample of well-known M dwarfs for which interferometric measurements are available. These stars and their abundances are intended to serve as a benchmark for future large-scale spectroscopic studies. We analysed spectra obtained with the GIANO-B spectrograph. Turbospectrum and the wrapper TSFitPy were used with MARCS atmospheric models in order to fit synthetic spectra to the observed spectra. We performed a differential abundance analysis in which we also analysed a solar spectrum with the same method and then subtracted the derived abundances line-by-line. The median was taken as the final abundance for each element and each star. Our abundances of Fe, Ti, and Ca agree mostly within uncertainties when comparing with other values from the literature. However, there are few studies to compare with.

Figures

Figures reproduced from arXiv: 2505.07116 by the authors.

Figure 1
Figure 1. A fragment of spectra taken at two nodding positions by GIANO-B after combining them. One can see replicated spectral lines corresponding to the same spectral orders, the tilt of the slit image, a couple of strong cosmic ray hits and some detector defects outlined in red. limb-darkened angular diameter with the CHARA array and us￾ing the bolometric flux obtained from Hipparcos parallaxes (van Leeuwen 2007) and photo… view at source ↗
Figure 2
Figure 2. Best-fitted Fe I lines in GJ 436 and the Sun. The observed spectra were only adjusted according to the literature radial velocity and not the RV fit for individual lines. The wavelength range 10 421 Å to 10 425 Å has two Fe lines. In the other subplots the Fe line is in the middle of the plot. and log g-A(O) pairs. They also obtained abundances of various atomic species by fitting individual lines. In [PITH_FULL_IM… view at source ↗
Figure 3
Figure 3. Same as [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: Same as [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: Abundances from this work vs abundances from the literature for stars in overlapping samples. The same star can be found on the same horizontal line with the name of the star to the right in each figure. find a clear offset when comparing with Souto et al. (2022) and M…
Figure 6
Figure 6. Figure 6: Abundances of Ti and Ca vs Fe for stars in the sample overlap￾ping with studies from the literature. [Ca/Fe] we have a large spread and none of the studies we com￾pare with really line up well with each other. However the sam￾ple here is too small to derive any concret…

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Works this paper leans on

81 extracted references · 39 canonical work pages

  1. [1]

    M., Korotin , S

    Abia , C., Tabernero , H. M., Korotin , S. A., et al. 2020, , 642, A227

    2020

  2. [2]

    & Plez , B

    Alvarez , R. & Plez , B. 1998, , 330, 1109

    1998

  3. [3]

    2021, , 508, 2236

    Bergemann , M., Hoppe , R., Semenova , E., et al. 2021, , 508, 2236

    work page 2021

  4. [4]

    2012, , 751, 156

    Bergemann , M., Kudritzki , R.-P., Plez , B., et al. 2012, , 751, 156

    work page 2012

  5. [5]

    H., Gies , D

    Berger , D. H., Gies , D. R., McAlister , H. A., et al. 2006, , 644, 475

    work page 2006

  6. [6]

    W., Mann , A

    Birky , J., Hogg , D. W., Mann , A. W., & Burgasser , A. 2020, , 892, 31

    work page 2020

  7. [7]

    2019, , 486, 2075

    Blanco-Cuaresma , S. 2019, , 486, 2075

    2019

  8. [8]

    2014, , 569, A111

    Blanco-Cuaresma , S., Soubiran , C., Heiter , U., & Jofr \'e , P. 2014, , 569, A111

    2014

Show all 81 references
  1. [9]

    S., von Braun , K., van Belle , G., et al

    Boyajian , T. S., von Braun , K., van Belle , G., et al. 2012, , 757, 112

    2012

  2. [10]

    L., Polanski , A

    Brinkman , C. L., Polanski , A. S., Huber , D., et al. 2024, , 168, 281

    2024

  3. [11]

    P., Marcy , G

    Butler , R. P., Marcy , G. W., Williams , E., et al. 1996, , 108, 500

    1996

  4. [12]

    A., Gonz \'a lez- \'A lvarez , E., Brady , M., et al

    Caballero , J. A., Gonz \'a lez- \'A lvarez , E., Brady , M., et al. 2022, , 665, A120

    2022

  5. [13]

    2022, , 164, 96

    Cadieux , C., Doyon , R., Plotnykov , M., et al. 2022, , 164, 96

    2022

  6. [14]

    Dressing , C. D. & Charbonneau , D. 2015, , 807, 45

    2015

  7. [15]

    2022, PhD thesis, LSU

    Ellis , T. 2022, PhD thesis, LSU

    2022

  8. [16]

    2018, , 475, 1960

    Fouqu \'e , P., Moutou , C., Malo , L., et al. 2018, , 475, 1960

    2018

  9. [17]

    M., Magg , E., Plez , B., et al

    Gerber , J. M., Magg , E., Plez , B., et al. 2023, , 669, A43

    2023

  10. [18]

    Gray , R. O. & Corbally , Christopher, J. 2009, Stellar Spectral Classification (Princeton University Press)

    2009

  11. [19]

    1989, , 27, 701

    Gustafsson , B. 1989, , 27, 701

    1989

  12. [20]

    2008, , 486, 951

    Gustafsson , B., Edvardsson , B., Eriksson , K., et al. 2008, , 486, 951

    2008

  13. [21]

    H., Allard , F., Alexander , D

    Hauschildt , P. H., Allard , F., Alexander , D. R., & Baron , E. 1997, , 488, 428

    1997

  14. [22]

    J., Jao , W.-C., Subasavage , J

    Henry , T. J., Jao , W.-C., Subasavage , J. P., et al. 2006, , 132, 2360

    2006

  15. [23]

    Henry , T. J. & McCarthy , Donald W., J. 1993, , 106, 773

    1993

  16. [24]

    T., Aoki , W., Hirano , T., et al

    Ishikawa , H. T., Aoki , W., Hirano , T., et al. 2022, , 163, 72

    2022

  17. [25]

    2025, , 978, 154

    Jahandar , F., Doyon , R., Artigau , \'E ., et al. 2025, , 978, 154

    2025

  18. [26]

    A., Allende Prieto , C., et al

    J \"o nsson , H., Holtzman , J. A., Allende Prieto , C., et al. 2020, , 160, 120

    2020

  19. [27]

    O., & Le Bouquin , J

    Kervella , P., M \'e rand , A., Ledoux , C., Demory , B. O., & Le Bouquin , J. B. 2016, , 593, A127

    2016

  20. [28]

    & viper Pipeline Team

    K \"o hler , J. & viper Pipeline Team . 2024, VIPER Manual, ESO, Garching bei München, Germany, https://mzechmeister.github.io/viper\_RV\_pipeline/

    2024

  21. [29]

    Kurucz , R. L. 2007, Robert L. Kurucz on-line database of observed and predicted atomic transitions, http://kurucz.harvard.edu/atoms/2000/

    2007

  22. [30]

    Kurucz , R. L. 2014, Robert L. Kurucz on-line database of observed and predicted atomic transitions, http://kurucz.harvard.edu/atoms/2600/

    2014

  23. [31]

    Kurucz , R. L. 2016, Robert L. Kurucz on-line database of observed and predicted atomic transitions, http://kurucz.harvard.edu/atoms/2200/

    2016

  24. [32]

    E., Guzman , A., Wood , M

    Lawler , J. E., Guzman , A., Wood , M. P., Sneden , C., & Cowan , J. J. 2013, , 205, 11

    2013

  25. [33]

    & Amarsi , A

    Lind , K. & Amarsi , A. M. 2024, , 62, 475

    2024

  26. [34]

    & Heiter , U

    Lindgren , S. & Heiter , U. 2017, , 604, A97

    2017

  27. [35]

    2016, , 586, A100

    Lindgren , S., Heiter , U., & Seifahrt , A. 2016, , 586, A100

    2016

  28. [36]

    2024, in AAS/Division for Extreme Solar Systems Abstracts, Vol

    Loyd , P., Schreyer , E., Owen , J., et al. 2024, in AAS/Division for Extreme Solar Systems Abstracts, Vol. 56, AAS/Division for Extreme Solar Systems Abstracts, 625.22

    2024

  29. [37]

    M., Molaverdikhani , K., et al

    Luque , R., Serrano , L. M., Molaverdikhani , K., et al. 2021, , 645, A41

    2021

  30. [38]

    2022, , 661, A140

    Magg , E., Bergemann , M., Serenelli , A., et al. 2022, , 661, A140

    2022

  31. [39]

    R., Schiavon , R

    Majewski , S. R., Schiavon , R. P., Frinchaboy , P. M., et al. 2017, , 154, 94

    2017

  32. [40]

    2020, , 644, A68

    Maldonado , J., Micela , G., Baratella , M., et al. 2020, , 644, A68

    2020

  33. [41]

    W., Feiden , G

    Mann , A. W., Feiden , G. A., Gaidos , E., Boyajian , T., & von Braun , K. 2015, , 804, 64

    2015

  34. [42]

    2024, , 973, 90

    Melo , E., Souto , D., Cunha , K., et al. 2024, , 973, 90

    2024

  35. [43]

    2020, Three dimensional spectroscopic NLTE abundance corrections of Sodium and Titanium in M-dwarfs, Bachelor thesis, University of Heidelberg

    Nordmeier, N. 2020, Three dimensional spectroscopic NLTE abundance corrections of Sodium and Titanium in M-dwarfs, Bachelor thesis, University of Heidelberg

    2020

  36. [44]

    R., Wickliffe , M

    O'Brian , T. R., Wickliffe , M. E., Lawler , J. E., Whaling , W., & Brault , J. W. 1991, Journal of the Optical Society of America B Optical Physics, 8, 1185, (BWL)

    1991

  37. [45]

    R., Heiter , U., et al

    Olander , T., Gent , M. R., Heiter , U., et al. 2025, , 696, A62

    2025

  38. [46]

    2021, , 649, A103

    Olander , T., Heiter , U., & Kochukhov , O. 2021, , 649, A103

    2021

  39. [47]

    2014, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Origlia , L., Oliva , E., Baffa , C., et al. 2014, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9147, Ground-based and Airborne Instrumentation for Astronomy V, ed. S. K. Ramsay , I. S. McLean , & H. Takami , 91471E

    2014

  40. [48]

    V., Ryabchikova , T

    Pakhomov , Y. V., Ryabchikova , T. A., & Piskunov , N. E. 2019, Astronomy Reports, 63, 1010

    2019

  41. [49]

    M., Bello-Garc \' a , A., Ordieres-Mer \'e , J., et al

    Passegger , V. M., Bello-Garc \' a , A., Ordieres-Mer \'e , J., et al. 2022, , 658, A194

    2022

  42. [50]

    M., Bello-Garc \' a , A., Ordieres-Mer \'e , J., et al

    Passegger , V. M., Bello-Garc \' a , A., Ordieres-Mer \'e , J., et al. 2020, , 642, A22

    2020

  43. [51]

    M., Reiners , A., Jeffers , S

    Passegger , V. M., Reiners , A., Jeffers , S. V., et al. 2018, , 615, A6

    2018

  44. [52]

    M., Schweitzer , A., Shulyak , D., et al

    Passegger , V. M., Schweitzer , A., Shulyak , D., et al. 2019, , 627, A161

    2019

  45. [53]

    2021, , 646, A32

    Piskunov , N., Wehrhahn , A., & Marquart , T. 2021, , 646, A32

    2021

  46. [54]

    E., Kupka , F., Ryabchikova , T

    Piskunov , N. E., Kupka , F., Ryabchikova , T. A., Weiss , W. W., & Jeffery , C. S. 1995, , 112, 525

    1995

  47. [55]

    Piskunov , N. E. & Valenti , J. A. 2002, , 385, 1095

    2002

  48. [56]

    2012, Turbospectrum: Code for spectral synthesis , Astrophysics Source Code Library, record ascl:1205.004

    Plez , B. 2012, Turbospectrum: Code for spectral synthesis , Astrophysics Source Code Library, record ascl:1205.004

    2012

  49. [57]

    2019, , 484, 2674

    Rabus , M., Lachaume , R., Jord \'a n , A., et al. 2019, , 484, 2674

    2019

  50. [58]

    D., Nordlander , T., Monty , S., et al

    Rains , A. D., Nordlander , T., Monty , S., et al. 2024, , 529, 3171

    2024

  51. [59]

    S., Allard , F., Rajpurohit , S., et al

    Rajpurohit , A. S., Allard , F., Rajpurohit , S., et al. 2018, , 620, A180

    2018

  52. [60]

    2024, arXiv e-prints, arXiv:2406.05447

    Rauer , H., Aerts , C., Cabrera , J., et al. 2024, arXiv e-prints, arXiv:2406.05447

    2024 arXiv

  53. [61]

    2014, Experimental Astronomy, 38, 249

    Rauer , H., Catala , C., Aerts , C., et al. 2014, Experimental Astronomy, 38, 249

    2014

  54. [62]

    2016, , 587, A65

    Reiners , A., Mrotzek , N., Lemke , U., Hinrichs , J., & Reinsch , K. 2016, , 587, A65

    2016

  55. [63]

    A., et al

    Reiners , A., Zechmeister , M., Caballero , J. A., et al. 2018, , 612, A49

    2018

  56. [64]

    L., et al

    Ryabchikova , T., Piskunov , N., Kurucz , R. L., et al. 2015, Physica Scripta, 90, 054005

    2015

  57. [65]

    Saloman , E. B. 2012, Journal of Physical and Chemical Reference Data, 41, 013101, sal12a

    2012

  58. [66]

    J., et al

    Santerne , A., Brugger , B., Armstrong , D. J., et al. 2018, Nature Astronomy, 2, 393

    2018

  59. [67]

    2021, , 649, A147

    Sarmento , P., Rojas-Ayala , B., Delgado Mena , E., & Blanco-Cuaresma , S. 2021, , 649, A147

    2021

  60. [68]

    H., White , R

    Schaefer , G. H., White , R. J., Baines , E. K., et al. 2018, , 858, 71

    2018

  61. [69]

    2021, , 654, A118

    Shan , Y., Reiners , A., Fabbian , D., et al. 2021, , 654, A118

    2021

  62. [70]

    2015, , 576, A77

    Smette , A., Sana , H., Noll , S., et al. 2015, , 576, A77

    2015

  63. [71]

    V., et al

    Souto , D., Cunha , K., Smith , V. V., et al. 2020, , 890, 133

    2020

  64. [72]

    V., et al

    Souto , D., Cunha , K., Smith , V. V., et al. 2022, , 927, 123

    2022

  65. [73]

    & Bergemann , M

    Storm , N. & Bergemann , M. 2023, , 525, 3718

    2023

  66. [74]

    2015, , 580, A30

    Thiabaud , A., Marboeuf , U., Alibert , Y., Leya , I., & Mezger , K. 2015, , 580, A30

    2015

  67. [75]

    & Nakajima , T

    Tsuji , T. & Nakajima , T. 2016, , 68, 13

    2016

  68. [76]

    2007, , 474, 653

    van Leeuwen , F. 2007, , 474, 653

    2007

  69. [77]

    S., Kane , S

    von Braun , K., Boyajian , T. S., Kane , S. R., et al. 2011, , 729, L26

    2011

  70. [78]

    S., van Belle , G

    von Braun , K., Boyajian , T. S., van Belle , G. T., et al. 2014, , 438, 2413

    2014

  71. [79]

    S., Liu , F., Ireland , T

    Wang , H. S., Liu , F., Ireland , T. R., et al. 2019, , 482, 2222

    2019

  72. [80]

    Woolf , V. M. & Wallerstein , G. 2005, , 356, 963

    2005

  73. [81]

    2021, viper: Velocity and IP EstimatoR , Astrophysics Source Code Library, record ascl:2108.006

    Zechmeister , M., K \"o hler , J., & Chamarthi , S. 2021, viper: Velocity and IP EstimatoR , Astrophysics Source Code Library, record ascl:2108.006

    2021

Pith tools

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