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REVIEW 4 major objections 4 minor 54 references

This paper claims to deliver a laboratory-grounded, uniformly validated set of near-infrared atomic lines (Y, J, H bands) for stellar abundance determinations, selected by a quantitative four-stage filter applied to six benchmark stars span

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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2026-08-02 23:15 UTC pith:QPEYQE6X

load-bearing objection Good method, broken table: the printed line lists contradict the summary counts, so the central data product isn't usable until fixed. the 4 major comments →

arxiv 2602.14294 v1 pith:QPEYQE6X submitted 2026-02-15 astro-ph.SR astro-ph.GA

Gaia FGK Benchmark Stars: Selecting Infrared Lines for Abundance Determination

Scarlet Elgueta , Paula Jofr\'e , Claudia Aguilera-G\'omez , Ditte Slumstrup , \'Alvaro Rojas-Arriagada , Ulrike Heiter , Laia Casamiquela , Manuela Zoccali
show 2 more authors
Clare Worley Caroline Soubiran
This is my paper
classification astro-ph.SR astro-ph.GA
keywords infrared spectroscopystellar abundancesline selectionatomic databenchmark starsspectral synthesisline blendinggoodness of fit
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.

The paper aims to solve a practical problem: infrared abundance measurements are less reliable than optical ones because line lists and models are less well validated. It proposes a reproducible, purely quantitative selection pipeline that takes atomic transitions in the Y, J, and H bands, tests each against depth, saturation, blending, and spectral-fit criteria, and keeps only lines that pass in all six benchmark stars. The result is a line list anchored to laboratory data rather than empirical calibration, with accepted lines dominated by Mg I, Si I, Ca I, and Fe I, plus Sr II as the only neutron-capture species. A sympathetic reader would care because this provides a community-usable reference and a template for re-validation as atomic data and instruments improve.

Core claim

The central claim is that a set of atomic transitions in the near-infrared can be identified that behave consistently across a wide range of stellar parameters, so that they can be used for abundance determinations without object-dependent fine-tuning. The paper demonstrates this by applying a sequence of quantitative filters—line depth >=0.03, non-saturation via curve-of-growth slope and core-flux response, purity measured as the ratio of equivalent widths in two velocity windows, and goodness-of-fit statistics with band-specific thresholds—to synthetic spectra computed for six benchmark stars. The accepted lines are tabulated per spectral type in the appendices. The method is designed to b

What carries the argument

The key mechanism is a four-stage flagging decision tree. Each candidate transition is evaluated for depth (minimum central absorption 0.03), saturation (local curve-of-growth slope below 0.5 plus negligible core-flux change flags the line), purity (P = equivalent width in a 30 km/s window divided by that in a 60 km/s window; P>=0.75 accepted, 0.5–0.75 flagged undecided, <0.5 rejected), and goodness of fit (reduced chi-square, RMSE, and MAD against observed spectra, with relaxed thresholds in J and H bands to account for telluric residuals). Only lines that earn 'YYYY' in all four stages are included in the robust list.

Load-bearing premise

The entire selection rests on the assumption that the 1D-LTE synthetic spectra computed with benchmark parameters and scaled abundances are accurate enough that a line's failure to match the observed profile is due to the line itself, not to the model or assumed abundance.

What would settle it

Take a star not in the sample (or one with independently known elemental abundances) and measure abundances from the paper's robust lines in two different bands; if the results disagree by more than the internal scatter, or if a line accepted as robust gives an abundance offset larger than the stated NLTE corrections (about 0.2 dex) when compared against an independent reference, the claim of cross-band and cross-stellar robustness is refuted.

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

If this is right

  • NIR abundance analyses can adopt the tabulated lines as a library of reliable diagnostics across spectral types from F dwarfs to M giants.
  • The quantitative framework can be re-executed automatically as new laboratory atomic data, atmosphere models, or instruments become available.
  • The approach provides a way to detect problematic lines without empirical recalibration, isolating the atomic data or model as the source of disagreement.
  • The result that only Sr II among n-capture elements passes the tests implies that systematic searches for heavier-element lines in the NIR need further work.
  • The line list can serve as a cross-check for survey pipelines that rely on astrophysically calibrated lists.

Where Pith is reading between the lines

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

  • Applying the same four-stage filter to other spectral bands (e.g., K or L bands) or to a larger sample of benchmark stars could extend the validated line library and test the thresholds' generality.
  • The purity criterion could be combined with 3D and NLTE synthetic spectra, since the paper itself notes IR NLTE corrections up to 0.2 dex; such tests might revise which lines survive.
  • The reproducibility of the pipeline means a community-driven effort could maintain a living line list, updating flags whenever atomic data are revised.
  • For elements lacking optical abundances, the practice of scaling to metallicity is a clear limitation; a dedicated star with independently determined abundances for those elements would make a sharper test.

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 quantitative, multi-criteria pipeline for selecting robust atomic absorption lines in the near-infrared Y, J, and H bands (9800–18000 Å) for abundance analyses of FGK stars. Six Gaia FGK Benchmark Stars observed with CRIRES+ are analyzed using 1D-LTE MARCS/MOOG synthetic spectra computed from VALD3 laboratory atomic data and benchmark stellar parameters. Each candidate transition is evaluated for line depth, saturation, purity (blending), and goodness of fit against observed profiles. Lines that pass all four criteria in a given band are labeled YYYY and compiled as 'robust' lists per spectral type in Appendices A.1–A.6, with input–output counts summarized in Table B.1. The robust lists are cross-matched against APOGEE, Şentürk et al. (2024), and Marfil et al. (2020), showing partial overlap. The paper claims to provide a reproducible, laboratory-grounded line list useful across a wide range of stellar parameters.

Significance. If the reported lists were internally consistent, the paper would offer a valuable community resource: a homogeneous NIR line selection based on a transparent, deterministic decision tree, with genuinely external validation through cross-matching (33 transitions in common with APOGEE for the Sun, 24 for Arcturus, 22 with Şentürk, and 15 Fe I with Marfil). The pipeline is described in sufficient detail to be rerun as atomic data improve, and the authors explicitly recognize several modeling limitations (LTE-only synthesis, missing molecular data for the coolest star, approximate abundance scaling). However, the central data product is compromised as printed: the robust line lists in Appendices A.1–A.6 and the summary counts in Table B.1 contradict each other by large factors for many spectral classes and bands. A user cannot determine which transitions are actually recommended. In addition, the GoF step tests consistency with abundance assumptions that are not independently constrained for alpha-elements in metal-poor stars. These issues are load-bearing for the paper's main claim, though they appear fixable by re-running the pipeline and performing targeted sensitivity tests.

major comments (4)
  1. [Appendix A vs Appendix B, Table B.1] The manuscript states that Table B.1 reports 'the number of transitions that pass all selection criteria' (i.e., final YYYY outcomes), so its numbers must match the contents of Appendices A.1–A.6. They do not. For example, H-band M giant: Appendix A.6 lists 8 Fe I, 5 Si I, and 1 V I, while Table B.1 gives Fe I=0, Si I=1, and no V I row. G-dwarf H: Appendix A.2 lists 16 Fe I and 9 Si I, but Table B.1 gives Fe I=4 and Si I=16. F-dwarf H: Appendix A.1 lists 4 Si I, but Table B.1 gives 6. J-band M giant: Appendix A.6 lists 7 Fe I, 10 Si I, 3 Cr I, and 7 Ti I, but Table B.1 gives 4, 8, 0, and 5. These are not minor typos in a wavelength entry; the two published summaries of the central deliverable are systematically inconsistent. As printed, the robust list is not reproducible, and the main claim is unsupported. The authors must reconcile these tables, explain the discrepancy (e.g., counting
  2. [Sections 3.1 and 3.2.4, Table 2] The GoF stage evaluates how well a synthesis matches the observed spectrum, but the synthesis uses [X/H] scaled to the star's global [M/H] for elements without individual optical abundances, including Si. For Arcturus ([Fe/H]=−0.55, [α/Fe]∼+0.3), this sets [Si/H]≈−0.55 instead of the likely ≈−0.25. The synthetic Si lines are then too weak, and the GoF may reject a perfectly good Si line because the input abundance is wrong, or accept a line only because the abundance error compensates for atomic-data error. Since the paper's cross-match counts and robust lists emphasize Si I lines, this assumption is load-bearing for the alpha-element conclusions. Please run a sensitivity test: redo the Si I selection for Arcturus with [Si/H] from the literature (or with [Si/Fe]=+0.3) and report whether the YYYY decisions change. If they do, the claim of robustness across the full stellar-parameter range
  3. [Section 3.2.1, Eq. (1), Table 1] The depth threshold is d≥0.03, and the paper states that for S/N∼100, Eq. (1) gives σ≈0.01, so d=0.03 is a ∼3σ detection. However, the H-band spectrum of γ Sge has S/N=37.8 (Table 1), for which σ=1/37.8≈0.026 and d=0.03 is only a ∼1.2σ feature. The M-giant H-band robust list (Appendix A.6) is therefore potentially dominated by noise fluctuations. The selection should either mask this low-S/N band/class, apply an S/N-dependent depth threshold, or provide a quantitative justification for why the fixed 0.03 threshold remains reliable at S/N≈38. Without this, the H-band M-giant conclusions are not supported.
  4. [Sections 3.1 and 3.2.1] The entire selection is based on 1D-LTE synthesis, while the paper itself cites NLTE abundance corrections up to 0.2 dex for IR lines of Si I and Ca II (Section 3.2.1). A line that passes the GoF in LTE may fail when NLTE effects are included, and vice versa. Although the authors frame this as a framework that can be updated, the central claim is that the selected lines are 'robust' for abundance work. The paper should quantify how many of the final YYYY lines have known NLTE corrections exceeding, say, 0.1 dex, and whether any of the rejected lines would be recovered under NLTE. This is a concrete, testable addition that would materially strengthen the robustness claim.
minor comments (4)
  1. [Section 4] The cross-match paragraph states 33 transitions in common with APOGEE for the G dwarf, but the breakdown (12 Fe I + 9 Si I + 4 Mg I + 3 N I + 3 C I + 1 Si + 1 Cr I + 1 K I) sums to 34. Please check the count.
  2. [Section 3.2.2] In the text describing saturation, 'a line is flagged as Unsaturated N when...' should presumably read 'flagged as saturated' (the N flag indicates saturation). The placeholder 'element_id' in the same section is unresolved.
  3. [Appendix A.2, H band] In the G-dwarf H-band list, 'Si15400.077' appears adjacent to 'Sii...' lines; please clarify whether this is Si I (neutral) or a separate species, and ensure consistent notation throughout the appendices.
  4. [Section 2] The nominal resolution is reported as 'R∼90000' in the introduction and '∼100000' in Section 2; Table 2 and the synthesis use R=90000. Please harmonize the values or explain the difference.

Circularity Check

0 steps flagged

No significant circularity: robust-line selection is conditional on external benchmark parameters and is not used to fit the abundances entering the synthesis.

full rationale

The paper's central claim is a line-selection result, not a derivation that folds its conclusion back into its inputs. The synthesis uses stellar parameters from Soubiran et al. (2024) and optical abundances from Casamiquela et al. (2025), both external to the IR line list being vetted; Teff/logg rest on interferometric diameters, bolometric fluxes, and parallaxes, and the abundance inputs come from a different wavelength regime. The four filtering stages (depth, saturation, purity, GoF) apply fixed, a priori thresholds: no threshold is tuned line-by-line to force acceptance, and the accepted lines are never used to recompute the abundances that enter the synthesis. Purity is a synthetic-spectrum property of each candidate, not a quantity derived from the final list. The cross-matches against APOGEE, Şentürk et al., and Marfil et al. are independent external checks, not inputs. The paper honestly discloses model-dependence limitations (LTE assumptions, molecular contamination for γSge, up to 0.2 dex NLTE corrections cited for Si I and Ca II), but those are accuracy risks rather than circular steps. The apparent inconsistency between Appendix A robust-line lists and Table B.1 counts is a reproducibility/correctness issue, not a circularity issue, and therefore does not affect this score.

Axiom & Free-Parameter Ledger

5 free parameters · 5 axioms · 0 invented entities

The central claim rests on five hand-set threshold/parameter groups, the LTE+MARCS+VALD3 modeling stack, and the GBS benchmark inputs. All are stated and mostly disclosed in the text; none are tuned to force specific lines through, but their values materially shape the accepted lists. No new physical entities are introduced.

free parameters (5)
  • Line depth threshold = d = 0.03
    Hand-chosen cutoff (Section 3.2.1), justified as ~3 sigma at S/N=100 but only ~1.2 sigma for gamma Sge in H band (S/N=37.8). Adopted from Casamiquela et al. (2025).
  • Saturation slope and core-flux thresholds = COG local slope < 0.5 and dF_core < 0.005
    The paper states these are empirical: 'These thresholds are empirical but follow directly from the definition' (Section 3.2.2).
  • Purity acceptance thresholds = P<0.5 reject; 0.5-0.75 undecided; P>=0.75 accept
    Compromise thresholds; at P=0.75 contaminating features can contribute ~25% of absorption, equivalent to ~0.12 dex systematic error if unmodeled (Section 3.2.3).
  • Per-band GoF thresholds = Y: RMSE 0.035, MAD 0.02; J: 0.038, 0.024; H: 0.05, 0.05; plus 10% chi-square relaxation
    Hand-set reference limits per band based on estimated telluric noise properties; 'we adopt fixed reference limits' (Section 3.2.4). Set after data inspection rather than a priori.
  • Abundance scaling for unmeasured species = [X/H] = [M/H] (global metallicity)
    For Si, P, and other elements lacking individual optical abundances, the global metallicity is used as the input abundance in the synthesis (Section 3.1), biasing line verdicts for alpha-enhanced stars.
axioms (5)
  • domain assumption 1D LTE MARCS models describe NIR line formation faithfully enough for the filters
    Used for all synthesis (Section 3.1); the paper itself cites IR NLTE corrections up to 0.2 dex for Si I and Ca II (Section 3.2.1), and notes depth cuts may be insufficient.
  • domain assumption VALD3 (version 968) laboratory line data are complete and accurate in the Y, J, and H bands
    All synthesis is anchored to VALD3; no molecular line lists are included (Section 3.1), which is acknowledged to complicate the coolest target, gamma Sge (3904 K).
  • domain assumption GBS benchmark parameters (Soubiran et al. 2024) and optical abundances (Casamiquela et al. 2025) are correct
    Used as fixed synthesis inputs (Table 1, Section 3.1); several co-authors belong to the same GBS program, though the parameters are anchored to interferometry, bolometric fluxes, and Gaia parallaxes.
  • domain assumption Residual telluric contamination below 5% after MOLECFIT correction does not bias GoF and purity metrics
    Claimed in Section 2; the looser J- and H-band thresholds admit that residuals in those bands are non-Gaussian and larger, so the assumption only partially holds.
  • standard math Depth, curve-of-growth, and purity criteria jointly diagnose line suitability
    Classical curve-of-growth framework (Gray 2005; Mihalas 1978; Magain 1984) and the Kondo et al. (2019) purity prescription are adopted as the physical basis of the filters (Sections 3.2.2-3.2.3).

pith-pipeline@v1.3.0-alltime-deepseek · 24578 in / 19112 out tokens · 187130 ms · 2026-08-02T23:15:27.299739+00:00 · methodology

0 comments
read the original abstract

The advent of new and more powerful infrared spectrographs has significantly motivated the advancement of the study of atomic and molecular line lists and stellar atmosphere models. While optical abundance determinations rely on extensively validated line lists and modeling frameworks, infrared measurements still face larger uncertainties, largely driven by the choice of atmospheric models and the quality of the available atomic data. In this work, we aim to deliver a homogeneous and reproducible set of atomic absorption lines in the Y, J, and H bands (9800 - 18000 (Angstrom)), based exclusively on laboratory atomic data. We analyse CRIRES spectra of six Gaia FGK Benchmark Stars spanning a wide range in effective temperature, surface gravity, and chemical composition. Synthetic spectra are computed using the benchmark stellar parameters, and each transition is evaluated independently in every star through a quantitative sequence that examines line depth, saturation, blending (purity), and the agreement between observed and synthetic line profiles. We identify a set of robust atomic transitions in these bands that remain consistent across the full range of stellar parameters represented in our sample. Lines of alpha-elements such as Mg I, Si I, and Ca I, together with several Fe I transitions, satisfy all robustness criteria. Among the neutron-capture species explored, only Sr II provides lines that consistently meet our requirements. Beyond the specific list of accepted transitions, this study demonstrates that a fully quantitative, multi-criteria framework provides a transparent and reproducible foundation for near-infrared line validation as laboratory data, stellar atmosphere models, and instrumentation continue to improve.

Figures

Figures reproduced from arXiv: 2602.14294 by \'Alvaro Rojas-Arriagada, Caroline Soubiran, Clare Worley, Claudia Aguilera-G\'omez, Ditte Slumstrup, Laia Casamiquela, Manuela Zoccali, Paula Jofr\'e, Scarlet Elgueta, Ulrike Heiter.

Figure 1
Figure 1. Figure 1: Spectral cuts for each of the three bands are shown for the representative stars, after telluric correction, RV correction, and normalization. The stars are sorted by temperature, making clear how the line profiles evolve from warmer to cooler GBS. ties persist, especially in spectral regions densely populated by strong telluric bands. A widely adopted strategy to im￾prove correction accuracy is to observe… view at source ↗
Figure 2
Figure 2. Figure 2: Methodology flow chart where the flags for each process are defined. regimes but not comprehensively for the infrared regime, yet some efforts to correct abundances in APOGEE spec￾tra have been made (see, e.g., Osorio et al. 2020). The spectral synthesis is run in two configurations: first, a full synthesis including all elements present in the linelist within the specified wavelength range (hereafter refe… view at source ↗
Figure 3
Figure 3. Figure 3: Synthesis of the Si i absorption line for ϵ Eri (K Dwarf) in the Y band. The line in crimson indicates the synthesis for Si i only. dance generally follows the α-pattern in disk and bulge stars (Caffau et al. 2005; Nissen et al. 2007; Spite et al. 2011). Therefore, the resulting purity estimates (P ≡ EW1/EW2) are expected to remain robust, with the main caveats ap￾plying to the weakest features and to line… view at source ↗
Figure 4
Figure 4. Figure 4: Number of absorption lines with d > 0.03. For both M Giant and F Dwarf. Article number, page 7 of 22 [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Example of a non-saturated line, the absorption feature of the Sr ii line at 10036.65 Å in a M Giant star. Top panel: Syn￾thetic spectra computed for different Sr ii abundances, ranging from [Sr ii/H] = −2.0 to +2.0 dex. Bottom panel: Correspond￾ing curve of growth (COG). Each point represents a synthetic spectrum at a given abundance offset. The red dot marks the reference abundance used for the stellar m… view at source ↗
Figure 6
Figure 6. Figure 6: Distribution of purity values (P) for all lines with purity flags N, U and Y. The dashed horizontal line indicates the high-purity threshold at P = 0.75, whereas the red dotted line indicates the rejection limit.). throughout this work, and a higher P indicates a line less affected by blends. Following the flagging scheme described in Section 3.2 and illustrated in [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Observed (red) versus synthetic (blue) spectra for two representative infrared lines stacked vertically. Each panel shows six stellar targets and reports the reduced chi-square (χ 2 red), RMSE, and MAD used for the GoF evaluation. The different outcomes for α Boo and β Hyi reflect variations in line strength and local blending conditions. isotopic structure, or magnetic broadening). Our aim is to retain li… view at source ↗

discussion (0)

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Reference graph

Works this paper leans on

54 extracted references

  1. [1]

    2016, ApJ, 819, 103

    Afşar, M., Sneden, C., Frebel, A., et al. 2016, ApJ, 819, 103

    2016

  2. [2]

    M., Lind, K., Asplund, M., Barklem, P

    Amarsi, A. M., Lind, K., Asplund, M., Barklem, P. S., & Collet, R. 2016, MNRAS, 463, 1518

    2016

  3. [3]

    M., Lind, K., Osorio, Y., et al

    Amarsi, A. M., Lind, K., Osorio, Y., et al. 2020, A&A, 642, A62

    2020

  4. [4]

    M., et al

    Bergemann, M., Collet, R., Amarsi, A. M., et al. 2017, ApJ, 847, 15

    2017

  5. [5]

    2012, ApJ, 751, 156

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

    2012

  6. [6]

    2014, A&A, 569, A111

    Blanco-Cuaresma, S., Soubiran, C., Heiter, U., & Jofré, P. 2014, A&A, 569, A111

    2014

  7. [7]

    L., Rix, H.-W., et al

    Bovy, J., Nidever, D. L., Rix, H.-W., et al. 2014, ApJ, 790, 127

    2014

  8. [8]

    2005, A&A, 441, 533

    Caffau, E., Bonifacio, P., Faraggiana, R., et al. 2005, A&A, 441, 533

    2005

  9. [9]

    2025, arXiv e-prints, arXiv:2504.19648

    Casamiquela, L., Soubiran, C., Jofré, P., et al. 2025, arXiv e-prints, arXiv:2504.19648

    arXiv 2025

  10. [10]

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

    Cirasuolo, M., Afonso, J., Carollo, M., 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, 91470N Şentürk, S. A., Şahin, T., Güney, F., Bilir, S., & Marışmak, M. 2024, ApJ, 976, 175

    2014

  11. [11]

    J., Bristow, P., Smoker, J

    Dorn, R. J., Bristow, P., Smoker, J. V., et al. 2023, A&A, 671, A24

    2023

  12. [12]

    S., Matsunaga, N., Jian, M., et al

    Elgueta, S. S., Matsunaga, N., Jian, M., et al. 2024, MNRAS, 532, 3694

    2024

  13. [13]

    M., et al

    Freudling, W., Romaniello, M., Bramich, D. M., et al. 2013, A&A, 559, A96 García Pérez, A. E., Allende Prieto, C., Holtzman, J. A., et al. 2016, AJ, 151, 144

    2013

  14. [14]

    P., Mather, J

    Gardner, J. P., Mather, J. C., Abbott, R., et al. 2023, Publications of the Astronomical Society of the Pacific, 135, 068001

    2023

  15. [15]

    E., Rothman, L

    Gordon, I. E., Rothman, L. S., Hargreaves, R. J., et al. 2022, J. Quant. Spectr. Rad. Transf., 277, 107949

    2022

  16. [16]

    Gray, D. F. 2005, The Observation and Analysis of Stellar Photo- spheres, 3rd edn. (Cambridge University Press)

    2005

  17. [17]

    2014, AJ, 148, 53

    Gullikson, K., Dodson-Robinson, S., & Kraus, A. 2014, AJ, 148, 53

    2014

  18. [18]

    2008, A&A, 486, 951

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

    2008

  19. [19]

    D., et al

    Hahlin, A., Kochukhov, O., Rains, A. D., et al. 2023, A&A, 675, A91

    2023

  20. [20]

    2016, A&A, 592, A70

    Hawkins, K., Jofré, P., Heiter, U., et al. 2016, A&A, 592, A70

    2016

  21. [21]

    R., Bovy, J., Holtzman, J

    Hayden, M. R., Bovy, J., Holtzman, J. A., et al. 2015, ApJ, 808, 132

    2015

  22. [22]

    2015, A&A, 582, A49

    Heiter, U., Jofré, P., Gustafsson, B., et al. 2015, A&A, 582, A49

    2015

  23. [23]

    2021, A&A, 645, A106 Jofré, P., Heiter, U., & Soubiran, C

    Heiter, U., Lind, K., Bergemann, M., et al. 2021, A&A, 645, A106 Jofré, P., Heiter, U., & Soubiran, C. 2019, ARA&A, 57, 571 Jofré, P., Heiter, U., Soubiran, C., et al. 2015, A&A, 582, A81 Jofré, P., Heiter, U., Soubiran, C., et al. 2014, A&A, 564, A133 Kaeufl,H.-U.,Ballester,P.,Biereichel,P.,etal.2004,inGround-based Instrumentation for Astronomy, ed. A. F...

    2021

  24. [24]

    2019, ApJ, 875, 129

    Kondo, S., Fukue, K., Matsunaga, N., et al. 2019, ApJ, 875, 129

    2019

  25. [25]

    2012, MNRAS, 427, 50

    Lind, K., Bergemann, M., & Asplund, M. 2012, MNRAS, 427, 50

    2012

  26. [26]

    1984, Astronomy and Astrophysics, 134, 189

    Magain, P. 1984, Astronomy and Astrophysics, 134, 189

    1984

  27. [27]

    H., & Rieke, M

    Maiolino, R., Rieke, G. H., & Rieke, M. J. 1996, AJ, 111, 537

    1996

  28. [28]

    R., Schiavon, R

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

    2017

  29. [29]

    M., Montes, D., et al

    Marfil, E., Tabernero, H. M., Montes, D., et al. 2020, MNRAS, 492, 5470

    2020

  30. [30]

    R., Korn, A

    Mashonkina, L., Gehren, T., Shi, J. R., Korn, A. J., & Grupp, F. 2011, A&A, 528, A87

    2011

  31. [31]

    2020, ApJS, 246, 10

    Matsunaga, N., Taniguchi, D., Jian, M., et al. 2020, ApJS, 246, 10

    2020

  32. [32]

    1978, Stellar Atmospheres, 2nd edn

    Mihalas, D. 1978, Stellar Atmospheres, 2nd edn. (San Francisco: W. H. Freeman and Company)

    1978

  33. [33]

    E., Akerman, C., Asplund, M., et al

    Nissen, P. E., Akerman, C., Asplund, M., et al. 2007, A&A, 469, 319

    2007

  34. [34]

    2012, A&A, 543, A92

    Noll, S., Kausch, W., Barden, M., et al. 2012, A&A, 543, A92

    2012

  35. [35]

    2020, A&A, 637, A80

    Osorio, Y., Allende Prieto, C., Hubeny, I., Mészáros, S., & Shetrone, M. 2020, A&A, 637, A80

    2020

  36. [36]

    Queiroz, A. B. A., Anders, F., Chiappini, C., et al. 2020, A&A, 638, A76

    2020

  37. [37]

    L., et al

    Ryabchikova, T., Piskunov, N., Kurucz, R. L., et al. 2015, Phys. Scr, 90, 054005

    2015

  38. [38]

    2009, A&A, 496, 701

    Ryde, N., Edvardsson, B., Gustafsson, B., et al. 2009, A&A, 496, 701

    2009

  39. [39]

    Ryde, N., Edvardsson, B., Gustafsson, B., & Käufl, H. U. 2007, in IAU Symposium, Vol. 241, Stellar Populations as Building Blocks of Galaxies, ed. A. Vazdekis & R. Peletier, 260–261

    2007

  40. [40]

    2010, A&A, 509, A20

    Ryde, N., Gustafsson, B., Edvardsson, B., et al. 2010, A&A, 509, A20

    2010

  41. [41]

    2019, A&A, 631, L3

    Ryde, N., Hartman, H., Oliva, E., et al. 2019, A&A, 631, L3

    2019

  42. [42]

    2018, PASP, 130, 074502

    Sameshima, H., Matsunaga, N., Kobayashi, N., et al. 2018, PASP, 130, 074502

    2018

  43. [43]

    2010, AJ, 139, 646

    Sharon, C., Hillenbrand, L., Fischer, W., & Edwards, S. 2010, AJ, 139, 646

    2010

  44. [44]

    E., et al

    Shetrone, M., Bizyaev, D., Lawler, J. E., et al. 2015, ApJS, 221, 24

    2015

  45. [45]

    2015, ApJ, 808, 148

    Sitnova, T., Zhao, G., Mashonkina, L., et al. 2015, ApJ, 808, 148

    2015

  46. [46]

    2015, A&A, 576, A77

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

    2015

  47. [47]

    V., Bizyaev, D., Cunha, K., et al

    Smith, V. V., Bizyaev, D., Cunha, K., et al. 2021, AJ, 161, 254

    2021

  48. [48]

    2012, MOOG: LTE line analysis and spectrum synthesis

    Sneden, C., Bean, J., Ivans, I., Lucatello, S., & Sobeck, J. 2012, MOOG: LTE line analysis and spectrum synthesis

    2012

  49. [49]

    L., Lagarde, N., et al

    Soubiran, C., Creevey, O. L., Lagarde, N., et al. 2024, A&A, 682, A145

    2024

  50. [50]

    M., et al

    Spite, M., Caffau, E., Andrievsky, S. M., et al. 2011, A&A, 528, A9

    2011

  51. [51]

    M., et al

    Thorsbro, B., Ryde, N., Rich, R. M., et al. 2020, ApJ, 894, 26

    2020

  52. [52]

    J., Santos, N

    Ulmer-Moll, S., Figueira, P., Neal, J. J., Santos, N. C., & Bonnefoy, M. 2019, A&A, 621, A79

    2019

  53. [53]

    D., Cushing, M

    Vacca, W. D., Cushing, M. C., & Rayner, J. T. 2003, PASP, 115, 389

    2003

  54. [54]

    2016, ApJ, 833, 137 Article number, page 15 of 22 A&A proofs:manuscript no

    Zhang, J., Shi, J., Pan, K., Allende Prieto, C., & Liu, C. 2016, ApJ, 833, 137 Article number, page 15 of 22 A&A proofs:manuscript no. aanda Appendix A: Robust lines A.1. F Dwarf Table A.1.Robust (YYYY) transitions for F Dwarf in the Y, J, and H bands. Y band (F Dwarf) – 18 lines Ci10123.870, 10541.240, 10729.530 Fei9944.207 Ni10112.481, 10114.640 Nii9898...

    2016