REVIEW 5 major objections 5 minor 95 references
Mind the Gap II: the near-UV fluxes of M dwarfs
T0 review · 5 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash
Pith's one-line read M dwarfs split into two distinct near-ultraviolet populations on the $M_{\rm NUV}$–$M_G$ diagram, with the lower branch's excess flux dominated by Fe II line forests.
desk verdict A credible two-branch NUV split for M dwarfs, with the Fe II mechanism overreaching; binarity is a real, untested confounder. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The key machinery is the $M_{\rm NUV}$ vs. $M_G$ diagram, where Gaia absolute $G$ magnitude serves as a mass proxy, combined with the GALEX NUV bandpass. Two-dimensional Gaussian mixture clustering assigns stars to upper and lower branch fits, and paired HST/STIS spectra convolved with the GALEX NUV filter curve identify which emission lines carry the flux difference. The paper also uses the known kink in the mass-luminosity relation at M2, attributed to H2 formation and improved convective energy transport, as the proposed physical trigger for the NUV anomaly.
What would settle it
Take new HST/STIS spectra of a lower-branch early-M dwarf (M0–M2) outside the Hyades that has the same $M_G$ as an upper-branch star, and check whether Fe II forests still dominate the flux difference; if the excess instead comes from Mg II, continuum, or other lines, the Fe II mechanism fails. A second test: if a deeper NUV survey such as UVEX fills the gap between the two branches for late M dwarfs, the two-population claim would be an artifact of GALEX sensitivity limits rather than a physical split.
Extended reading notes
Core claim
The central discovery is that the near-ultraviolet main sequence of M dwarfs is not a single sequence. In a sample of 10,234 GALEX/Gaia stars, the authors find two well-separated populations on the $M_{\rm NUV}$ vs. $M_G$ diagram: an upper branch whose NUV fluxes match PARSEC photospheric model isochrones, and a lower branch whose members are brighter in NUV by factors of 3 to 25, with the ratio increasing for later, lower-mass M dwarfs. The number of stars on the lower branch rises sharply near M2 ($M_G \sim 9.4$), coincident with the main-sequence gap and with atmospheric H2 formation. Archival HST/STIS spectra of two matched pairs show that the lower-branch stars have additional emission from Fe II line forests near 2400 and 2600 Å, which after convolution with the GALEX NUV bandpass account for most of the accumulated excess flux; the Mg II doublet contributes less than 20%. The authors further show that most young moving-group members and fast rotators fall on the lower branch, though many lower-branch stars are neither young nor fast-rotating, and they find evidence that NUV flaring stars may form a third, even brighter population.
Load-bearing premise
The claim that Fe II line forests cause the excess NUV flux rests on just two pairs of HST spectra, and the lower-branch stars with full NUV spectra are almost all mid-M dwarfs and Hyades members because of HST bright-object restrictions; if those few stars are not representative of the entire lower branch, the mechanism does not generalize.
Editorial extensions
If this is right
- A single polynomial mass-luminosity or color-magnitude relation cannot describe M dwarfs in the NUV; models and surveys that treat NUV flux as a smooth function of mass will mis-estimate UV output for a large fraction of stars.
- Because the same-mass M dwarf can differ by factors of 3 to 25 in NUV flux, the ultraviolet radiation environment, and therefore photochemistry and potential surface habitability, of exoplanets around M dwarfs depends on which branch the host star occupies.
- The excess flux grows toward later types, so lower-mass M dwarfs on the lower branch are relatively the most NUV-bright, which must be accounted for when interpreting GALEX-based activity surveys.
- Mg II emission is present in essentially all M dwarfs, yet it is not the driver of the branch separation; future UV studies should target Fe II-rich wavelength regions rather than only the traditional Mg II diagnostic.
Reading between the lines
- If the Fe II dominance holds across all masses, then NUV band definitions matter: a filter centered near 2400–2800 Å strongly selects for the lower-branch population, and comparisons between GALEX and Swift NUV measurements could systematically differ because of their different bandpasses.
- The proposed link between H2 formation at M2 and enhanced NUV emission is suggestive but untested; a model that couples H2-driven convection with chromospheric heating could predict where the lower branch should appear as a function of metallicity, offering a testable extension.
- The existence of lower-branch stars that are neither young nor fast-rotating, plus the paper's third, flaring population, suggests unresolved binarity or non-linear wave heating may be important; high-contrast imaging of such outliers would separate these alternatives.
- If the same two-branch structure appears for K dwarfs, as the paper's cursory FUV check hints, then the phenomenon is not specific to fully convective M dwarfs and the M2/H2 coincidence may be accidental; the authors leave this as future work.
Signed reviews
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper analyzes a GALEX/Gaia cross-matched sample of 10,234 nearby M dwarfs and claims that M dwarfs form two distinct populations in the near-ultraviolet, visible as upper and lower branches on the M_NUV versus M_G diagram. The authors report that the split begins near spectral type M2/M_G~9.4, that the flux gap between branches grows from roughly a factor of 3 to a factor of 25 toward lower masses, and that archival HST/STIS spectra of two branch-matched pairs show the excess is dominated by Fe II line forests near 2400 and 2800 Angstroms rather than by the Mg II doublet. They further show that H-alpha-active stars, fast rotators, and young moving-group candidates preferentially fall on the lower branch, while not all lower-branch stars are young or fast rotators. The paper concludes that standard smooth polynomial main-sequence relations do not hold in the NUV band.
Significance. If the two-branch interpretation is correct, the result is significant for M dwarf characterization and exoplanet UV-environment studies, because it implies that single M dwarfs of the same mass can differ by factors of 3 to 25 in NUV output and that smooth relations calibrated on optical and near-IR bands cannot be extrapolated to GALEX NUV. The paper has genuine strengths: it uses a large, well-defined all-sky sample; it anchors the branch interpretation with independent external samples (H-alpha surveys, rotation periods, BANYAN young-star candidates); it compares the upper branch to a PARSEC photosphere and finds consistency; and it explicitly states the limitations of its spectroscopic sample in Section 11. The central photometric bimodality is visible in the data, and the H-alpha and rotation comparisons provide independent supporting evidence. The main weaknesses are the unquantified role of unresolved binaries and the very limited spectroscopic basis for the Fe II mechanism.
major comments (5)
- [Section 2 and Section 4] The sample selection does not exclude equal-mass or close unresolved binaries: RUWE<1.4 and the 15-arcsecond neighbor cut with dGRP<4.0 remove only wide, unequal-flux companions, while Section 4 explicitly lists 'equal mass short-period binaries' as a candidate explanation for lower-branch stars and Section 11 says unresolved binaries 'could be the main reason' for relatively inactive lower-branch stars. Because unresolved binaries elevate NUV flux without any chromospheric Fe II enhancement, the paper needs to quantify the binary fraction on each branch or test whether lower-branch excess correlates with radial-velocity variability, astrometric signatures, or high-resolution imaging before concluding that the two populations are a stellar activity dichotomy rather than partly a binarity effect.
- [Section 10 and Section 11] The claim that Fe II line forests dominate the excess NUV flux rests on only two spectral pairs, GJ163/2MA0417+1454 and GJ699/2MA0358+1237, and the authors acknowledge in Section 11 that lower-branch stars with full NUV coverage are almost exclusively mid-M dwarfs and Hyades members because of HST bright-object restrictions. This selection bias limits both the mass range and the age/activity range over which the Fe II mechanism is established, so the statement that Fe II forests dominate the excess 'at a given mass' is not yet demonstrated across the full M dwarf branch. The authors should either present additional lower-branch spectra (including early M dwarfs and non-Hyades stars) or explicitly restrict the mechanistic conclusion to the mid-M/Hyades regime where data exist.
- [Section 7 and Table 2] The fitted branch slopes, intercepts, and the resulting excess ratios 3x, 13x, and 25x in Figure 7 and the 7x/36x FUV values are presented without uncertainties. Table 2 gives coefficients without errors, the 0.4-magnitude branch classification cutoff in Section 7.1 is set by inspection, and the FUV upper-branch line is fitted by eye. Since the excess ratios are derived from these fitted lines via Equation (5), the paper should provide bootstrap or covariance-based uncertainties on the branch parameters, check the sensitivity of the derived excess ratios to the classification offset, and report error bars on the magnitude differences and flux ratios. Without this, the central quantitative claims cannot be evaluated for significance.
- [Section 7.2 and Figure 7] The FUV analysis is considerably less rigorous than the NUV analysis: the upper branch is fitted by eye, the lower branch is fitted after excluding the by-eye upper branch, and the assumption of two populations in FUV is justified only by a cursory examination of K dwarfs. Given that the FUV sample is sparse and that the claimed FUV excess ratios are even larger than the NUV ones, the FUV two-branch decomposition and excess ratios should be presented as provisional or supported by a reproducible fitting procedure with uncertainties, rather than as results of comparable standing to the NUV fits.
- [Section 3 and Section 11] The abstract and Section 3 present the H2-formation/M2-anomaly connection as a suggested mechanism, but Section 11 correctly states that the connection between H2 formation and excess NUV flux 'is yet to be studied.' This is a reasonable framing, but the paper should apply the same caution to the Fe II mechanism: the spectra in Figure 10 show that Fe II lines are strong in the two Hyades lower-branch stars, but no synthetic or empirical demonstration is given that Fe II opacity alone can produce the observed photometric excess across the branch. A quantitative estimate of the Fe II contribution using the two available pairs, including the uncertainty from the nonzero Delta M_G in the second pair, would strengthen the mechanistic claim.
minor comments (5)
- [Abstract and Introduction] The abstract contains several typographical and grammatical issues, including 'In this study of utilizing a catalog' and the broken 'MN U V' formatting; these should be corrected in a final language pass.
- [Section 3] The claim that 'the improved energy transport may carry extra energy into the atmosphere' is speculative and is not directly tested; consider moving it more explicitly into the discussion of possible mechanisms rather than presenting it near the primary results.
- [Section 7.2, footnotes] The reference to Pedregosa et al. 2020 is cited in the text as 2020, but the bibliography lists Pedregosa et al. 2011; the citation year should be checked.
- [Figure 9 and Table 4] The three highlighted mid-M dwarfs have very different metallicities and rotation periods, so the statement that 'the Mg II line strength increases... the absolute NUV magnitudes continue to decrease' should explicitly note the small sample size and the potential confounding role of metallicity, as the text partially does but the figure caption does not.
- [Section 10] In the second spectral pair, GJ699 and 2MA0358+1237 have Delta M_G = 0.09 mag, which is larger than the first pair's Delta M_G and could imply a small mass difference; the text acknowledges this, but the comparison would be clearer if the mass difference were propagated into the cumulative excess-flux calculation.
Circularity Check
No significant circularity: branch fits are descriptive summaries, not predictions, and the Fe II mechanism is supported by independent spectra.
full rationale
The derivation chain is self-contained. The two-population structure is inferred directly from GALEX/Gaia photometry via a Gaussian mixture, and the branch lines in Table 2 are descriptive fits to the same data. The excess ratios in Section 7.2 are arithmetic transformations of those fitted lines, not predictions validated against held-out data, so no fitted parameter is renamed as a prediction. External anchors support the interpretation: the PARSEC/BT-Settl isochrone matches the upper branch, H-alpha absorption/emission samples from MEarth, CARMENES, and LAMOST map onto the branches, rotation samples from K2 and Newton et al. (2017) place fast rotators on the lower branch, and BANYAN young-star candidates preferentially fall on the lower branch. The Fe II dominance conclusion rests on two HST/STIS pairs, but the paper explicitly acknowledges the Hyades/mid-M selection bias in Section 11; that is a generalization risk, not a circular step. Self-citations to Jao et al. (2018, 2023) supply main-sequence gap boundaries and rotation classification conventions, but those are context and do not carry the central NUV claim. The binary-contamination concern raised in the skeptical reading is a correctness and sample-bias issue, not a circularity issue.
Assumptions & free parameters
free parameters (9)
- NUV upper branch slope a =
0.65035
- NUV upper branch intercept b =
-3.32947
- NUV lower branch slope a =
1.15668
- NUV lower branch intercept b =
-10.38865
- FUV upper branch slope a =
6.28459
- FUV upper branch intercept b =
-103.02273
- FUV lower branch slope a =
0.98846
- FUV lower branch intercept b =
-11.65192
- branch classification offset =
0.4 mag
assumptions (4)
- domain assumption The GUVmatch AISxGaiaDR2 catalog cross-match is reliable for selecting M dwarfs with GALEX NUV photometry.
- domain assumption The PARSEC isochrone with BT-Settl atmospheres represents photospheric-only NUV fluxes for the upper branch.
- ad hoc to paper The Gaussian mixture model with full covariance is an appropriate unsupervised separation of the two branches.
- domain assumption The line identifications in the HST/STIS spectra are correct.
Cite this review
Pith. "Pith review of Mind the Gap II: the near-UV fluxes of M dwarfs." pith.science (2026). https://pith.science/paper/VKUUQ2UD
@misc{pith2026250104806,
author = {Pith},
title = {Pith review of: Mind the Gap II: the near-UV fluxes of M dwarfs},
year = {2026},
howpublished = {\url{https://pith.science/paper/VKUUQ2UD}},
note = {Machine review of arXiv:2501.04806}
}
abstract
Because of the continuous variations in mass, metallicity, and opacity, dwarf stars are distributed along the main sequence on optical and near-IR color-magnitude diagrams following a smooth polynomial. In this study of utilizing a catalog of cross-matched GALEX and Gaia sources, we identify two distinct populations of M dwarfs in the near-ultraviolet (NUV) band on the $M_{NUV}$ vs. $M_G$ diagram. We also reveal a pronounced increase in the number of stars exhibiting high NUV fluxes near the spectral type M2 or $M_G\sim9.4$, coinciding with the $H_2$ formation in the atmosphere to improve the energy transportation at the surface. This suggests that certain yet-to-be-understood stellar mechanisms drive heightened activity in the NUV band around the effective temperature of M2 and later types of M dwarfs. Through examination of archival Hubble Space Telescope spectra, we show that Fe II line forests at $\sim$2400A and 2800A dominate the spectral features in the GALEX NUV bandpass, contributing to the observed excess fluxes at a given mass between the two populations. Additionally, our investigation indicates that fast rotators and young stars likely increase brightness in the NUV band, but not all stars with bright NUV fluxes are fast rotators or young stars.
Figures
Figures from the paper (7 more)
Reference graph
Works this paper leans on
-
[1]
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-
[3]
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arXiv 2021
-
[4]
doi:10.1051/0004-6361/201527078
Astudillo-Defru, N., Delfosse, X., Bonfils, X., et al.\ 2017, , 600, A13. doi:10.1051/0004-6361/201527078
-
[5]
Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al.\ 2013, , 558, A33. doi:10.1051/0004-6361/201322068
-
[6]
Astropy Collaboration, Price-Whelan, A. M., Sip o cz, B. M., et al.\ 2018, , 156, 123. doi:10.3847/1538-3881/aabc4f
-
[7]
Basri, G.\ 2022, The 21st Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun, 114. doi:10.5281/zenodo.7530476
-
[8]
Benedict, G. F., Henry, T. J., Franz, O. G., et al.\ 2016, , 152, 141. doi:10.3847/0004-6256/152/5/141
Show all 95 references
-
[9]
A., Huber, D., van Saders, J
Berger, T. A., Huber, D., van Saders, J. L., et al.\ 2020, , 159, 280. doi:10.3847/1538-3881/159/6/280
2020 doi
-
[10]
doi:10.3847/1538-4365/aa7053
Bianchi, L., Shiao, B., & Thilker, D.\ 2017, , 230, 24. doi:10.3847/1538-4365/aa7053
2017 doi
-
[11]
& Shiao, B.\ 2020, , 250, 36
Bianchi, L. & Shiao, B.\ 2020, , 250, 36. doi:10.3847/1538-4365/aba2d7
2020 doi
-
[12]
C.\ 1976, Ph.D
Boeshaar, P. C.\ 1976, Ph.D. Thesis
1976
-
[13]
doi:10.1051/0004-6361:20053046
Bonfils, X., Delfosse, X., Udry, S., et al.\ 2005, , 442, 635. doi:10.1051/0004-6361:20053046
2005 doi
-
[14]
S., von Braun, K., van Belle, G., et al.\ 2012, , 757, 112
Boyajian, T. S., von Braun, K., van Belle, G., et al.\ 2012, , 757, 112. doi:10.1088/0004-637X/757/2/112
2012 doi
-
[15]
R., Vedantham, H
Callingham, J. R., Vedantham, H. K., Shimwell, T. W., et al.\ 2021, Nature Astronomy, 5, 1233. doi:10.1038/s41550-021-01483-0
2021 doi
-
[16]
Cannon, A. J. & Pickering, E.\ 1918, Annals of the Astronomical Observatory of Harvard College, 1918-1949, Cambridge, Mass.: Astronomical Observatory of Harvard College, 1918
1918
-
[17]
doi:10.1111/j.1365-2966.2008.13573.x
Casagrande, L., Flynn, C., & Bessell, M.\ 2008, , 389, 585. doi:10.1111/j.1365-2966.2008.13573.x
2008
- [18]
-
[19]
& Baraffe, I.\ 2000, , 38, 337
Chabrier, G. & Baraffe, I.\ 2000, , 38, 337. doi:10.1146/annurev.astro.38.1.337
2000 doi
-
[20]
doi:10.1093/mnras/stu1605
Chen, Y., Girardi, L., Bressan, A., et al.\ 2014, , 444, 2525. doi:10.1093/mnras/stu1605
2014 doi
-
[21]
doi:10.1051/0004-6361/202347111
Chevalier, S., Babusiaux, C., Merle, T., et al.\ 2023, , 678, A19. doi:10.1051/0004-6361/202347111
2023 doi
-
[22]
A., Cort \'e s-Contreras, M., et al.\ 2020, , 642, A115
Cifuentes, C., Caballero, J. A., Cort \'e s-Contreras, M., et al.\ 2020, , 642, A115. doi:10.1051/0004-6361/202038295
2020 doi
-
[23]
O., & Jorgensen, H
Copeland, H., Jensen, J. O., & Jorgensen, H. E.\ 1970, , 5, 12
1970
-
[24]
Davenport, J. R. A.\ 2016, , 829, 23. doi:10.3847/0004-637X/829/1/23
2016 doi
-
[25]
Debes, J., Sankrit, R., Fischer, T., et al.\ 2024, Instrument Science Report COS 2024-01, 31 pages
2024
-
[26]
B., Henry, T
Dieterich, S. B., Henry, T. J., Jao, W.-C., et al.\ 2014, , 147, 94. doi:10.1088/0004-6256/147/5/94
2014 doi
-
[27]
A., Montes, D., et al.\ 2019, , 621, A126
D \' ez Alonso, E., Caballero, J. A., Montes, D., et al.\ 2019, , 621, A126. doi:10.1051/0004-6361/201833316
2019 doi
-
[28]
T., Ag \"u eros, M
Douglas, S. T., Ag \"u eros, M. A., Covey, K. R., et al.\ 2016, , 822, 47. doi:10.3847/0004-637X/822/1/47
2016 doi
-
[29]
E., Fossati, L., Koskinen, T., et al.\ 2020, , 159, 111
Cubillos, P. E., Fossati, L., Koskinen, T., et al.\ 2020, , 159, 111. doi:10.3847/1538-3881/ab6a0b
2020 doi
-
[30]
M., Stancil, P
Fontenla, J. M., Stancil, P. C., & Landi, E.\ 2015, , 809, 157. doi:10.1088/0004-637X/809/2/157
2015 doi
-
[31]
M., Linsky, J
Fontenla, J. M., Linsky, J. L., Garrison, J., et al.\ 2016, , 830, 154. doi:10.3847/0004-637X/830/2/154
2016 doi
-
[32]
doi:10.1051/0004-6361/202345839
Fouqu \'e , P., Martioli, E., Donati, J.-F., et al.\ 2023, , 672, A52. doi:10.1051/0004-6361/202345839
2023 doi
-
[33]
France, K., Loyd, R. O. P., Youngblood, A., et al.\ 2016, , 820, 89. doi:10.3847/0004-637X/820/2/89
2016 doi
-
[34]
S., Kowalski, A., France, K., et al.\ 2019, , 871, L26
Froning, C. S., Kowalski, A., France, K., et al.\ 2019, , 871, L26. doi:10.3847/2041-8213/aaffcd
2019 doi
-
[35]
E., Malo, L., et al.\ 2018, , 856, 23
Gagn \'e , J., Mamajek, E. E., Malo, L., et al.\ 2018, , 856, 23. doi:10.3847/1538-4357/aaae09
2018 doi
-
[36]
& Faherty, J
Gagn \'e , J. & Faherty, J. K.\ 2018, , 862, 138. doi:10.3847/1538-4357/aaca2e
2018 doi
-
[37]
Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al.\ 2021, , 649, A1. doi:10.1051/0004-6361/202039657
2021 doi
-
[38]
N., Zhan, Z., Seager, S., et al.\ 2020, , 159, 60
G \"u nther, M. N., Zhan, Z., Seager, S., et al.\ 2020, , 159, 60. doi:10.3847/1538-3881/ab5d3a
2020 doi
-
[39]
L., Gizis, J
Hawley, S. L., Gizis, J. E., & Reid, I. N.\ 1996, , 112, 2799. doi:10.1086/118222
1996 doi
-
[40]
L., Davenport, J
Hawley, S. L., Davenport, J. R. A., Kowalski, A. F., et al.\ 2014, , 797, 121. doi:10.1088/0004-637X/797/2/121
2014 doi
-
[41]
Henry, T. J. & Jao, W.-C.\ 2024, , 62, 593. doi:10.1146/annurev-astro-052722-102740
2024 doi
-
[42]
Hunter, J.D., \ 2007, Computing in Science & Engineering, 9, 90
2007
-
[43]
J., Gies, D
Jao, W.-C., Henry, T. J., Gies, D. R., et al.\ 2018, , 861, L11. doi:10.3847/2041-8213/aacdf6
2018 doi
-
[44]
J., White, R
Jao, W.-C., Henry, T. J., White, R. J., et al.\ 2023, , 166, 63. doi:10.3847/1538-3881/ace2bb
2023 doi
-
[45]
V., Sch \"o fer, P., Lamert, A., et al.\ 2018, , 614, A76
Jeffers, S. V., Sch \"o fer, P., Lamert, A., et al.\ 2018, , 614, A76. doi:10.1051/0004-6361/201629599
2018 doi
-
[46]
D., Henry, T
Kirkpatrick, J. D., Henry, T. J., & McCarthy, D. W.\ 1991, , 77, 417. doi:10.1086/191611
1991 doi
-
[47]
F., Wisniewski, J
Kowalski, A. F., Wisniewski, J. P., Hawley, S. L., et al.\ 2019, , 871, 167. doi:10.3847/1538-4357/aaf058
2019 doi
-
[48]
doi:10.1126/science.1067524
Kroupa, P.\ 2002, Science, 295, 82. doi:10.1126/science.1067524
2002 doi
- [49]
-
[50]
L.\ 2017, , 55, 159
Linsky, J. L.\ 2017, , 55, 159. doi:10.1146/annurev-astro-091916-055327
2017 doi
-
[51]
L., Wood, B
Linsky, J. L., Wood, B. E., Youngblood, A., et al.\ 2020, , 902, 3. doi:10.3847/1538-4357/abb36f
2020 doi
-
[52]
Loyd, R. O. P., France, K., Youngblood, A., et al.\ 2016, , 824, 102. doi:10.3847/0004-637X/824/2/102
2016 doi
-
[53]
Loyd, R. O. P., Shkolnik, E. L., Schneider, A. C., et al.\ 2021, , 907, 91. doi:10.3847/1538-4357/abd0f0
2021 doi
-
[54]
peng ., Zhang, L.-
Lu, H.-. peng ., Zhang, L.-. yun ., Shi, J., et al.\ 2019, , 243, 28. doi:10.3847/1538-4365/ab2f8f
2019 doi
-
[55]
R., et al.\ 2020, , 638, A20
Magaudda, E., Stelzer, B., Covey, K. R., et al.\ 2020, , 638, A20. doi:10.1051/0004-6361/201937408
2020 doi
-
[56]
W., Dupuy, T., Kraus, A
Mann, A. W., Dupuy, T., Kraus, A. L., et al.\ 2019, , 871, 63. doi:10.3847/1538-4357/aaf3bc
2019 doi
-
[57]
NAtional Academies of Sciences, Engineering, and Medicine
National Academies of Sciences, E.\ 2021, Pathways to Discovery in Astronomy and Astrophysics for the 2020s, Consenses Study Report. NAtional Academies of Sciences, Engineering, and Medicine. 2021. Washington, DC: The National Academies Press, 2021.. doi:10.17226/26141
2021 doi
-
[58]
R., Irwin, J., Charbonneau, D., et al.\ 2016, , 821, L19
Newton, E. R., Irwin, J., Charbonneau, D., et al.\ 2016, , 821, L19. doi:10.3847/2041-8205/821/1/L19
2016 doi
-
[59]
R., Irwin, J., Charbonneau, D., et al.\ 2017, , 834, 85
Newton, E. R., Irwin, J., Charbonneau, D., et al.\ 2017, , 834, 85. doi:10.3847/1538-4357/834/1/85
2017 doi
-
[60]
T., Costa, G., Girardi, L., et al.\ 2022, , 665, A126
Nguyen, C. T., Costa, G., Girardi, L., et al.\ 2022, , 665, A126. doi:10.1051/0004-6361/202244166
2022 doi
-
[61]
doi:10.3847/1538-4365/accea7
Pal, T., Khan, I., Worthey, G., et al.\ 2023, , 266, 41. doi:10.3847/1538-4365/accea7
2023 doi
-
[62]
G., G \"a nsicke, B
Parsons, S. G., G \"a nsicke, B. T., Marsh, T. R., et al.\ 2018, , 481, 1083. doi:10.1093/mnras/sty2345
2018 doi
-
[63]
R., Barclay, T., Youngblood, A., et al.\ 2024, , 971, 24
Paudel, R. R., Barclay, T., Youngblood, A., et al.\ 2024, , 971, 24. doi:10.3847/1538-4357/ad487d
2024 doi
-
[64]
L., et al.\ 2020, , 895, 5
Peacock, S., Barman, T., Shkolnik, E. L., et al.\ 2020, , 895, 5. doi:10.3847/1538-4357/ab893a
2020 doi
-
[65]
\ 2011, Journal of Machine Learning Research, 12, 2825--2830,
Pedregosa, F., Varoquaux, G., Gramfort, A., et al. \ 2011, Journal of Machine Learning Research, 12, 2825--2830,
2011
-
[66]
& Hekker, S.\ 2020, , 635, A43
Reinhold, T. & Hekker, S.\ 2020, , 635, A43. doi:10.1051/0004-6361/201936887
2020 doi
-
[67]
I., Vieytes, M
Peralta, J. I., Vieytes, M. C., Mendez, A. M. P., et al.\ 2023, , 676, A18. doi:10.1051/0004-6361/202346156
2023 doi
-
[68]
S., Youngblood, A., & France, K.\ 2021, , 918, 40
Pineda, J. S., Youngblood, A., & France, K.\ 2021, , 918, 40. doi:10.3847/1538-4357/ac0aea
2021 doi
-
[69]
doi:10.3847/1538-4357/ace5ac
Rekhi, P., Ben-Ami, S., Perdelwitz, V., et al.\ 2023, , 955, 24. doi:10.3847/1538-4357/ace5ac
2023 doi
-
[70]
M.\ 2014, , 794, 144
Reiners, A., Sch \"u ssler, M., & Passegger, V. M.\ 2014, , 794, 144. doi:10.1088/0004-637X/794/2/144
2014 doi
-
[71]
B., Xu, J., Thompson, S
Rimmer, P. B., Xu, J., Thompson, S. J., et al.\ 2018, Science Advances, 4, eaar3302. doi:10.1126/sciadv.aar3302
2018 doi
-
[72]
doi:10.1088/0004-637X/806/1/137
Rugheimer, S., Segura, A., Kaltenegger, L., et al.\ 2015, , 806, 137. doi:10.1088/0004-637X/806/1/137
2015 doi
-
[73]
doi:10.1088/0004-637X/809/1/57
Rugheimer, S., Kaltenegger, L., Segura, A., et al.\ 2015, , 809, 57. doi:10.1088/0004-637X/809/1/57
2015 doi
-
[74]
doi:10.1051/0004-6361/201118179
Saur, J., Grambusch, T., Duling, S., et al.\ 2013, , 552, A119. doi:10.1051/0004-6361/201118179
2013 doi
-
[75]
& Shibata, K.\ 2021, , 919, 29
Sakaue, T. & Shibata, K.\ 2021, , 919, 29. doi:10.3847/1538-4357/ac0e34
2021 doi
-
[76]
Shkolnik, E. L. & Barman, T. S.\ 2014, , 148, 64. doi:10.1088/0004-6256/148/4/64
2014 doi
-
[77]
J., Hawley, S
Schmidt, S. J., Hawley, S. L., West, A. A., et al.\ 2015, , 149, 158. doi:10.1088/0004-6256/149/5/158
2015 doi
-
[78]
Schneider, A. C. & Shkolnik, E. L.\ 2018, , 155, 122. doi:10.3847/1538-3881/aaaa24
2018 doi
-
[79]
M., Cifuentes, C., et al.\ 2019, , 625, A68
Schweitzer, A., Passegger, V. M., Cifuentes, C., et al.\ 2019, , 625, A68. doi:10.1051/0004-6361/201834965
2019 doi
-
[80]
K., Lavvas, P., Ballester, G
Sing, D. K., Lavvas, P., Ballester, G. E., et al.\ 2019, , 158, 91. doi:10.3847/1538-3881/ab2986
2019 doi
-
[81]
V., Reiners, A., et al.\ 2019, , 623, A44
Sch \"o fer, P., Jeffers, S. V., Reiners, A., et al.\ 2019, , 623, A44. doi:10.1051/0004-6361/201834114
2019 doi
-
[82]
V., et al.\ 2020, , 890, 133
Souto, D., Cunha, K., Smith, V. V., et al.\ 2020, , 890, 133. doi:10.3847/1538-4357/ab6d07
2020 doi
-
[83]
e , S., Boyle, R
Sperauskas, J., Barta s i \= u t \. e , S., Boyle, R. P., et al.\ 2016, , 596, A116. doi:10.1051/0004-6361/201527850
2016 doi
-
[84]
G., Oelkers, R
Stassun, K. G., Oelkers, R. J., Paegert, M., et al.\ 2019, , 158, 138. doi:10.3847/1538-3881/ab3467
2019 doi
-
[85]
C., Backus, P
Tarter, J. C., Backus, P. R., Mancinelli, R. L., et al.\ 2007, Astrobiology, 7, 30. doi:10.1089/ast.2006.0124
2007
-
[86]
B.\ 2005, Astronomical Data Analysis Software and Systems XIV, 347, 29
Taylor, M. B.\ 2005, Astronomical Data Analysis Software and Systems XIV, 347, 29
2005
-
[87]
L., et al.\ 2021, , 909, 61
Tilipman, D., Vieytes, M., Linsky, J. L., et al.\ 2021, , 909, 61. doi:10.3847/1538-4357/abd62f
2021 doi
-
[88]
R., Sperauskas, J., & Boyle, R
Upgren, A. R., Sperauskas, J., & Boyle, R. P.\ 2002, Baltic Astronomy, 11, 91
2002
-
[89]
van der Walt, S., Colbert, S.C., Varoquaux, G., \ 2011, Computing in Science & Engineering, 13, 22
2011
-
[90]
Virtanen, P., Gommers, R., Oliphant, T.E., et al., \ 2020, Nature Methods, 17, 261
2020
-
[91]
A., Morgan, D
West, A. A., Morgan, D. P., Bochanski, J. J., et al.\ 2011, , 141, 97. doi:10.1088/0004-6256/141/3/97
2011 doi
-
[92]
Woolf, V. M. & Wallerstein, G.\ 2005, , 356, 963. doi:10.1111/j.1365-2966.2004.08515.x
2005
-
[93]
J., Newton, E
Wright, N. J., Newton, E. R., Williams, P. K. G., et al.\ 2018, , 479, 2351. doi:10.1093/mnras/sty1670
2018 doi
-
[94]
Youngblood, A., France, K., Loyd, R. O. P., et al.\ 2017, , 843, 31. doi:10.3847/1538-4357/aa76dd
2017 doi
-
[95]
doi:10.3847/1538-4365/abd7a8
Zhang, L.-Y., Meng, G., Long, L., et al.\ 2021, , 253, 19. doi:10.3847/1538-4365/abd7a8
2021 doi
Reviewed August 10, 2026 · model on record in the stance chip above.
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