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REVIEW 4 major objections 6 minor 72 references

No Helium Detected in LHS 1140 b from Four JWST NIRISS/SOSS Transits

T0 review · 4 major / 6 minor · reviewed 2026-08-14 · deepseek-v4-flash

Pith's one-line read Four JWST NIRISS/SOSS transits of LHS 1140 b show no metastable helium absorption, rejecting the reported ground-based detection of atmospheric escape.

desk verdict Four independent SOSS transits make the LHS 1140 b helium claim hard to sustain—solid, cautious paper with soft statistical spots but a believable null result. read the letter →

arxiv 2608.13473 v1 pith:5KABWRRT submitted 2026-08-13 astro-ph.EP

classification astro-ph.EP
keywords exoplanetatmospheresmetastableheliumtriplettransmissionspectroscopyatmosphericescapeLHS1140bJWSTNIRISS/SOSSnon-detectionmass-lossrate
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 four JWST NIRISS/SOSS transits of the nearby temperate planet LHS 1140 b, taken between 2023 and 2026, and finds no absorption from the metastable helium triplet at $1.0833\,\mu$m in any of them. The authors argue that if the 2024 ground-based detection of 1.24% helium absorption were real and persistent, JWST would have seen it, and they reject the ground-based model at $>3\sigma$ in each visit and $9.9\sigma$ combined. If correct, the ground-based signal is either spurious or a rare, time-variable event occurring in fewer than half of transits. This matters because LHS 1140 b is a key target for deciding whether small planets around M dwarfs retain atmospheres, and helium absorption is a direct tracer of atmospheric escape.

What carries the argument

The load-bearing observable is the metastable helium triplet at $1.0833\,\mu$m, a standard tracer of atmospheric escape, which falls within a single SOSS pixel. The analysis uses column-level light curves around the triplet, compared with the white-light curve and with neighboring columns, to maximize sensitivity to a narrow feature. To quantify the expected signal, the reported ground-based escape model is convolved with an idealized Gaussian kernel representing the SOSS point-spread function at $R\approx700$, predicting a roughly 600 ppm feature at pixel resolution, and the predicted spectrum is tested against the data with a $\chi^2$ statistic. The same escape framework, with all input parameters fixed to the ground-based study's values, is then used to translate nondetection depths into upper limits on mass-loss rate.

What would settle it

If an independent re-reduction of these four visits solves for the helium line position as a free parameter (allowing offsets beyond one pixel) or uses an empirically measured point-spread function and recovers the predicted ~600 ppm feature, the nondetection claim would collapse; a future transit showing helium at the reported depth would instead prove the signal is real but variable.

Watch

Extended reading notes

Core claim

Across four NIRISS/SOSS transits spanning three years, no excess absorption is seen at the metastable helium triplet in the column-level light curves or in the transmission spectra, and adjacent columns show no leaked signal. The best-fit escape model from the reported ground-based detection, convolved to SOSS resolution, is discrepant with each visit at $>3\sigma$ and with the combined spectrum at $9.9\sigma$. The resulting $2\sigma$ upper limits on helium absorption correspond to mass-loss rates of roughly $5\times10^6$ to $3\times10^7$ g s$^{-1}$, several orders of magnitude below the reported $2\times10^8$ g s$^{-1}$ detection. With six total observations over three years, the single 2024 detection is an outlier; if helium escape is genuinely variable, it must be active less than about half the time, with a duty cycle below 53% at $2\sigma$.

Load-bearing premise

The conclusion assumes the reported ground-based helium signal, if real, would land in the one pixel column the wavelength solution points to, which requires the signal's line shape, the telescope's focus, and the wavelength calibration all to be accurate to within about a pixel.

Editorial extensions

If this is right

  • The 1.24% helium absorption reported from the 2024 ground-based transit is not persistent; four JWST transits reject the model at $>3\sigma$ each and $9.9\sigma$ combined.
  • If the signal is real but time-variable, it must occur in fewer than about 53% of transits at $2\sigma$, making the escape episode rare or stochastic.
  • Under the adopted escape-model assumptions, mass-loss rates above roughly $10^7$ g s$^{-1}$ are excluded at $2\sigma$, contradicting the $2\times10^8$ g s$^{-1}$ inference from the detection.
  • LHS 1140 b's nature—mini-Neptune versus water world—remains open, since the helium nondetection does not discriminate between these interpretations.

Reading between the lines

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

  • Editorial inference: simultaneous ground-based and JWST observations of the same transit would directly test whether the 2024 detection was a real but rare escape event or a systematic artifact.
  • Editorial inference: the persistent nondetections indirectly favor a high mean-molecular-weight atmosphere over a hydrogen/helium envelope, since an escaping H/He envelope would normally produce a detectable helium signature.
  • Editorial inference: the template-convolution comparison used here could be applied to other ground-based helium detections to check their consistency with low-resolution space-based spectra.
  • Editorial inference: a re-analysis of the 2024 ground-based data with careful treatment of telluric and instrumental systematics would test whether the single detection could be spurious.
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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 / 6 minor

Summary. The paper analyzes four JWST NIRISS/SOSS transits of LHS 1140 b observed between 2023 and 2026, searching for metastable helium absorption at 1.0833 µm. Two independent reductions (FIREFLy and exoTEDRF) agree; the authors find no excess absorption in the helium light curves, in the column-level spectra, or in adjacent columns for any visit. They place 2σ upper limits on helium absorption depth at both SOSS and ground-based resolutions, translate the best-fit ground-based model of Cherubim et al. (2026) into an expected ~600 ppm SOSS feature, and report that each visit rejects this model at >3σ, with a combined rejection at 9.9σ. They also use pwinds to derive mass-loss rate upper limits, finding no trend over time and arguing that the 2024 reported detection is an outlier. The paper concludes that the ground-based detection may be spurious or, if time-variable, occurs in fewer than about 50% of transits.

Significance. If the conclusion holds, this is an important result that directly challenges a published detection of metastable helium escape from a high-profile temperate exoplanet, with implications for the planet's atmospheric composition and for the reliability of ground-based helium surveys. The paper is methodologically careful in several respects: it uses two independent reduction pipelines, checks adjacent columns for signal leakage, discusses wavelength-solution offsets explicitly, and makes its data products available. The strength of the nondetection is credible. However, the headline rejection significances depend on converting a model-dependent equivalent width into an expected SOSS signal and on a χ²/N-to-σ conversion that does not fully account for correlated systematics. These issues are fixable and do not undermine the basic finding that no helium is visible in these four transits, but they affect the paper's strongest quantitative claims.

major comments (4)
  1. [§4.3, Figure 2] The expected SOSS signal of ~600 ppm is computed by convolving the pwinds best-fit model from Cherubim et al. (2026) with a Gaussian SOSS PSF, rather than by directly integrating the equivalent width measured in the WINERED spectrum. If the true line profile has a smaller equivalent width than the model (e.g., a narrower core or different continuum placement), the predicted SOSS signal could be substantially lower, and the per-visit rejection significances would drop from >3σ to roughly 1–2σ. The adjacent-column checks in §4.1 mitigate sub-pixel centroid issues but do not calibrate the absolute amplitude of the prediction. Please either derive the expected SOSS signal from the measured equivalent width of the ground-based detection, or provide a sensitivity grid over plausible line widths, centroids, and triplet morphologies.
  2. [§4.3, Figure 2] The stated rejection significances are obtained by converting χ²/N to a Gaussian sigma via the chi-square distribution, under the assumption that the per-column errors are independent and Gaussian. The transmission spectra are subject to correlated systematics from 1/f noise and possible spot crossings, and the χ²/N values of 2.6–3.8 may reflect underestimated uncertainties rather than genuine model rejection. I recommend an injection-recovery test: add the convolved model at full amplitude (and at half amplitude) to the actual light curves and evaluate how often the recovered signal exceeds 3σ. This would place the per-visit and combined significances on a more robust footing.
  3. [§4.4, Table 1, Figure 3] The mass-loss upper limits and the 'outlier' characterization of the 2024 detection are computed within pwinds varying only Ṁ while holding the other parameters fixed, as the authors acknowledge. Given the known degeneracies among Ṁ, T_wind, H:He, and XUV flux, and the non-monotonic behavior of the helium feature at high Ṁ due to self-shielding, the limits should be presented as conditional on the adopted model rather than as a direct measurement of the mass-loss rate. The text does include this caveat, but the abstract and conclusion statements ('no clear trend in mass-loss with time') could mislead readers who do not read the caveats.
  4. [§5, duty-cycle bound] The f<53% at 2σ bound assumes that a transit with the 2024 signal amplitude would always be detected in each of the four SOSS visits and that the four visits have equal sensitivity. Since the per-visit upper limits differ (0.02–0.04% at SOSS resolution) and the detection significance for a full-amplitude signal is only >3σ, the binomial calculation may underestimate the allowed variability window. Please incorporate the measured upper limits into the detection probability, or clearly label the bound as a first-order estimate.
minor comments (6)
  1. [§3.1] The claim that the FIREFLy reduction reproduces the Cadieux et al. (2024b) transmission spectrum for Visits 1 and 2 would benefit from a quantitative comparison (e.g., a plot or RMS of residuals) rather than a textual statement.
  2. [§4.2] The conversion of upper limits from SOSS to WINERED resolution assumes the same line morphology as the Cherubim et al. best-fit; please state this explicitly in the text.
  3. [Figure 2] The χ²/N values are given in the panels, but the number of spectral points N is not stated; please report N in the caption or text.
  4. [Abstract and §5] The abstract says '≲50%' while the text gives f<53% at 2σ; please make the numbers consistent.
  5. [§5] The word 'incontrovertible' is unnecessarily strong given the model-dependent caveats; please soften it.
  6. [References] The in-text citation 'C. Cherubim et al. (2026)' should match the reference entry 'Cherubim, C., Vissapragada, S., Cunningham, T., et al. 2026' in author order if applicable.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper tests an external ground-based model and detection against new JWST data without fitting the model to those data.

full rationale

The central claim (no helium detected; the reported ground-based model is rejected at >3 sigma per visit and ~9.9 sigma combined) is a comparison of an externally published model (Cherubim et al. 2026) with four new JWST/NIRISS/SOSS transmission spectra. The model is not fitted to the JWST spectra before the rejection is computed; the predicted ~600 ppm SOSS feature is obtained by convolving the externally published best-fit model with a Gaussian kernel approximating the SOSS PSF, and the paper explicitly tests the alternative empirical PSF and adjacent-column wavelength offsets, showing the conclusion is robust to those choices. The mass-loss upper limits are derived by varying only Mdot within pwinds while holding the external Cherubim et al. parameters fixed; this is model-dependent but not circular, and the paper explicitly cautions that Figure 3 shows relative mass-loss rates under uniform modeling assumptions rather than strict physical boundaries. Self-citations (FIREFLy, pastasoss, exoTIC-LD, etc.) are methodological descriptions of data reduction tools, not load-bearing evidence for the astrophysical conclusion, and the alternate exoTEDRF reduction independently confirms the null result. No equation reduces to its own input, no fitted parameter is renamed as a prediction, and no uniqueness theorem is imported from the authors. The derivation chain is therefore self-contained against an external benchmark.

Assumptions & free parameters 0 free parameters · 6 assumptions · 0 invented entities

The null detection is observational and does not require new physical model parameters. The PWIND model, XUV proxy, PSF, wavelength solution, and limb darkening are inherited from prior work and are listed as axioms. No free parameters are introduced by this paper beyond standard per-visit transit nuisance parameters, which do not affect the narrow-band conclusion.

assumptions (6)
  • domain assumption The SOSS PSF can be represented as an idealized Gaussian with R about 700 for convolving the ground-based model to JWST resolution.
    Section 4.3. The authors note the empirical cryo-vacuum kernel is asymmetric with unknown directionality but state that the Gaussian versus empirical choice does not change the result.
  • domain assumption The pastasoss wavelength solution places the 1.0833 micron helium triplet in the searched SOSS column within about 0.3 pixel at all epochs.
    Sections 3.1 and A.3. The line is narrower than a pixel, so a larger wavelength error could move the signal out of the examined column.
  • domain assumption PWIND isothermal Parker wind models correctly connect metastable helium absorption to mass-loss rate given outflow temperature, H:He ratio, velocity, and stellar XUV flux.
    Sections 4.3 and 4.4. Used to convert absorption upper limits to Mdot upper limits and to define the ground-based template.
  • domain assumption The GJ 1132 XUV flux is a valid proxy for LHS 1140's XUV flux.
    Sections 4.3 and 4.4, following Cherubim et al. (2026). All absolute mass-loss limits inherit this proxy.
  • domain assumption PHOENIX limb darkening with Teff=3096 K, log g=5.041, [M/H]=-0.15 is appropriate for the light-curve fits.
    Section 3.1. Limb darkening is fixed to model values rather than fitted to each column.
  • domain assumption The adopted transit period of 24.73691 days with zero eccentricity is accurate enough to place all four visits fully in transit.
    Section 3.1, using the period from Edwards et al. (2021). An incorrect ephemeris could underestimate in-transit absorption, though the white-light transit fits provide independent timing.

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Cite this review

Pith. "Pith review of No Helium Detected in LHS 1140 b from Four JWST NIRISS/SOSS Transits." pith.science (2026). https://pith.science/paper/5KABWRRT

@misc{pith2026260813473,
  author       = {Pith},
  title        = {Pith review of: No Helium Detected in LHS 1140 b from Four JWST NIRISS/SOSS Transits},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5KABWRRT}},
  note         = {Machine review of arXiv:2608.13473}
}
abstract

In the effort to determine which low-mass exoplanets have atmospheres, LHS 1140 b remains one of the most favorable targets. Its large size (5.6 $\rm M_{\oplus}$ and 1.7 $\rm R_{\oplus}$) and relatively long orbital period (24.7 days) imply an atmosphere may be likely, and notably, recent interior models favor either a hydrogen-dominated "mini-Neptune" or a "water world" over a true terrestrial planet. Another possibility is that it has a helium-rich atmosphere. This hypothesis is supported by recent ground-based observations that detected the metastable helium triplet during transit. These observations indicated there may be current helium escape from the planet's upper atmosphere, yet the signal was not detected during a subsequent observation, suggesting time-variable escape. Here we present four observations of LHS 1140 b with JWST NIRISS/SOSS, which covers the metastable helium triplet, obtained between 2023 and 2026. These observations span the epoch of the ground-based measurements, and although none were contemporaneous with the ground-based transits, all four are sensitive to helium absorption at the previously reported level. However, we detect no helium absorption in any visit. We reject the best-fit ground-based model at $>3\sigma$ in each visit, and find no clear trend in mass-loss with time. Our results suggest the reported ground-based detection may be spurious, although variability cannot be excluded if detectable helium absorption occurs in $\lesssim50\%$ of transits. The nature of LHS 1140 b thus remains a mystery until future transmission and emission analyses are complete.

Figures

Figures reproduced from arXiv: 2608.13473 by the authors.

Figure 1
Figure 1. Column-level light curves containing the 1.0833 µm helium triplet (orange) compared to the white light curves (blue) for all four visits. Unbinned and binned points are shown in light and darker shades, respectively. We note Visits 1 and 2 display higher scatter relative to Visits 3 and 4 because they have fewer groups per integration; if all visits are binned to the same time sampling, the scatter is similar. Botto… view at source ↗
Figure 2
Figure 2. The NIRISS/SOSS transmission spectra of LHS 1140 b centered around the 1.0833 µm metastable helium triplet from four visits spanning 2023 – 2026. Overplotted is the best-fit model reported by C. Cherubim et al. (2026) from the September 2024 ground-based observation, convolved to the resolution of SOSS (black line) and binned to the pixel scale (gray histogram). Every one of the four spectra is discrepant from the g… view at source ↗
Figure 3
Figure 3. Mass-loss rates (single point with 1σ error bars) and 2σ upper limits (triangles) derived from pwinds for all six visits: two from ground-based WINERED observations (orange) and four from JWST SOSS (teal). Orange values are taken from C. Cherubim et al. (2026) and teal points are calculated assuming the same input parameters as C. Cherubim et al. (2026), varying only the mass-loss rate. The single reported detection… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Comparison between FIREFLy and exoTEDRF reductions for the newly acquired NIRISS/SOSS Visits 3 and 4 (from GO 7073). Top panels show the transmission spectra for the FIREFLy (green) and exoTEDRF (pink) reductions. Bottom panels show the σ differences between reductions…

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Works this paper leans on

72 extracted references · 1 canonical work pages

  1. [1]

    L., et al

    Adams Redai, J., Wogan, N., Wallack, N. L., et al. 2025, AJ, 170, 219, doi: 10.3847/1538-3881/adee92

  2. [2]

    2025, ApJL, 985, L10, doi: 10.3847/2041-8213/add010

    Ahrer, E.-M., Radica, M., Piaulet-Ghorayeb, C., et al. 2025, ApJL, 985, L10, doi: 10.3847/2041-8213/add010

  3. [3]

    2023, PASP, 135, 075001, doi: 10.1088/1538-3873/acd7a3

    Albert, L., Lafreni` ere, D., Ren´ e, D., et al. 2023, PASP, 135, 075001, doi: 10.1088/1538-3873/acd7a3

  4. [4]

    E., Wakeford, H

    Alderson, L., Batalha, N. E., Wakeford, H. R., et al. 2024, AJ, 167, 216, doi: 10.3847/1538-3881/ad32c9

  5. [5]

    2012, Philosophical Transactions of the Royal Society of London Series A, 370, 2765, doi: 10.1098/rsta.2011.0269

    Allard, F., Homeier, D., & Freytag, B. 2012, Philosophical Transactions of the Royal Society of London Series A, 370, 2765, doi: 10.1098/rsta.2011.0269

  6. [6]

    2025, Nature Communications, 16, 10822, doi: 10.1038/s41467-025-66628-5 Anthropic

    Allart, R., Coulombe, L.-P., Carteret, Y., et al. 2025, Nature Communications, 16, 10822, doi: 10.1038/s41467-025-66628-5 Anthropic. 2025, Claude, https://www.anthropic.com Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et ...

  7. [7]

    Observations, Tech. Rep. Technical Report JWST-STScI-008571, STScI, doi: 10.48550/arXiv.2311.07771 11 0.9996 0.9998 1.0000 1.0002 1.0004 1.0006Normalized Flux Helium FWHM Visit 3 Visit 4 FIREFLy exoTEDRF 1.070 1.075 1.080 1.085 1.090 1.095 1 0 1 1.070 1.075 1.080 1.085 1.090 1.095 Residuals ( ) Wavelength ( m) Figure 4.Comparison betweenFIREFLyandexoTEDRF...

  8. [8]

    Observations, Tech. Rep. Technical Report JWST-STScI-008448, STScI, doi: 10.48550/arXiv.2311.07769

Show all 72 references
  1. [9]

    M., Charbonneau, D., Gilliland, R

    Brown, T. M., Charbonneau, D., Gilliland, R. L., Noyes, R. W., & Burrows, A. 2001, ApJ, 552, 699, doi: 10.1086/320580

  2. [10]

    2022, JWST Calibration Pipeline, 1.8.2 Zenodo, doi: 10.5281/zenodo.7325378

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2022, JWST Calibration Pipeline, 1.8.2 Zenodo, doi: 10.5281/zenodo.7325378

  3. [11]

    2024a, ApJL, 960, L3, doi: 10.3847/2041-8213/ad1691

    Cadieux, C., Plotnykov, M., Doyon, R., et al. 2024a, ApJL, 960, L3, doi: 10.3847/2041-8213/ad1691

  4. [12]

    J., et al

    Cadieux, C., Doyon, R., MacDonald, R. J., et al. 2024b, ApJL, 970, L2, doi: 10.3847/2041-8213/ad5afa

  5. [13]

    J., et al

    Cherubim, C., Wordsworth, R., Bower, D. J., et al. 2025, ApJ, 983, 97, doi: 10.3847/1538-4357/adbca9

  6. [14]

    2024, ApJ, 967, 139, doi: 10.3847/1538-4357/ad3e77

    Cherubim, C., Wordsworth, R., Hu, R., & Shkolnik, E. 2024, ApJ, 967, 139, doi: 10.3847/1538-4357/ad3e77

  7. [15]

    2026, arXiv e-prints, arXiv:2607.14326, doi: 10.48550/arXiv.2607.14326

    Cherubim, C., Vissapragada, S., Cunningham, T., et al. 2026, arXiv e-prints, arXiv:2607.14326, doi: 10.48550/arXiv.2607.14326

  8. [16]

    2020, AJ, 159, 211, doi: 10.3847/1538-3881/ab8237

    Cloutier, R., & Menou, K. 2020, AJ, 159, 211, doi: 10.3847/1538-3881/ab8237

  9. [17]

    2024, ApJL, 968, L22, doi: 10.3847/2041-8213/ad5204 de Wit, J., Householder, A., & Niraula, P

    Damiano, M., Bello-Arufe, A., Yang, J., & Hu, R. 2024, ApJL, 968, L22, doi: 10.3847/2041-8213/ad5204 de Wit, J., Householder, A., & Niraula, P. 2026, ApJL, 996, L23, doi: 10.3847/2041-8213/ae2f5c

  10. [18]

    A., Irwin, J

    Dittmann, J. A., Irwin, J. M., Charbonneau, D., et al. 2017, Nature, 544, 333, doi: 10.1038/nature22055 Dos Santos, L. A., Vidotto, A. A., Vissapragada, S., et al. 2022, A&A, 659, A62, doi: 10.1051/0004-6361/202142038

  11. [19]

    2021, AJ, 161, 44, doi: 10.3847/1538-3881/abc6a5

    Edwards, B., Changeat, Q., Mori, M., et al. 2021, AJ, 161, 44, doi: 10.3847/1538-3881/abc6a5

  12. [20]

    2015, MNRAS, 450, 1879, doi: 10.1093/mnras/stv744

    Espinoza, N., & Jord´ an, A. 2015, MNRAS, 450, 1879, doi: 10.1093/mnras/stv744

  13. [21]

    2019, MNRAS, 490, 2262, doi: 10.1093/mnras/stz2688

    Espinoza, N., Kossakowski, D., & Brahm, R. 2019, MNRAS, 490, 2262, doi: 10.1093/mnras/stz2688

  14. [22]

    H., Glidden, A., et al

    Espinoza, N., Allen, N. H., Glidden, A., et al. 2025, ApJL, 990, L52, doi: 10.3847/2041-8213/adf42e

  15. [23]

    D., Radica, M., Welbanks, L., et al

    Feinstein, A. D., Radica, M., Welbanks, L., et al. 2023, Nature, 614, 670, doi: 10.1038/s41586-022-05674-1

  16. [24]

    W., Lang, D., & Goodman, J

    Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067

  17. [25]

    P., Diamond-Lowe, H., et al

    Fortune, M., Gibson, N. P., Diamond-Lowe, H., et al. 2025, A&A, 701, A25, doi: 10.1051/0004-6361/202554198 12

  18. [26]

    J., Radica, M., et al

    Fournier-Tondreau, M., MacDonald, R. J., Radica, M., et al. 2024, MNRAS, 528, 3354, doi: 10.1093/mnras/stad3813

  19. [27]

    2025, MNRAS, 539, 422, doi: 10.1093/mnras/staf489

    Fournier-Tondreau, M., Pan, Y., Morel, K., et al. 2025, MNRAS, 539, 422, doi: 10.1093/mnras/staf489

  20. [28]

    K., et al

    Fu, G., Espinoza, N., Sing, D. K., et al. 2022, ApJL, 940, L35, doi: 10.3847/2041-8213/ac9977

  21. [29]

    2025, ApJL, 990, L53, doi: 10.3847/2041-8213/adf62e

    Glidden, A., Ranjan, S., Seager, S., et al. 2025, ApJL, 990, L53, doi: 10.3847/2041-8213/adf62e

  22. [30]

    2024, The Journal of Open Source Software, 9, 6816, doi: 10.21105/joss.06816

    Grant, D., & Wakeford, H. 2024, The Journal of Open Source Software, 9, 6816, doi: 10.21105/joss.06816

  23. [31]

    Grant, D., & Wakeford, H. R. 2022, Exo-TiC/ExoTiC-LD: ExoTiC-LD v3.0.0, v3.0.0 Zenodo, doi: 10.5281/zenodo.7437681

  24. [32]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

  25. [33]

    Hu, R., Seager, S., & Yung, Y. L. 2015, ApJ, 807, 8, doi: 10.1088/0004-637X/807/1/8

  26. [34]

    Hunter, J. D. 2007, Computing in Science and Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  27. [35]

    O., Wende-von Berg, S., Dreizler, S., et al

    Husser, T. O., Wende-von Berg, S., Dreizler, S., et al. 2013, A&A, 553, A6, doi: 10.1051/0004-6361/201219058

  28. [36]

    L., Ribas, I., Lammer, H., et al

    Khodachenko, M. L., Ribas, I., Lammer, H., et al. 2007, Astrobiology, 7, 167, doi: 10.1089/ast.2006.0127

  29. [37]

    Kipping, D. M. 2013, MNRAS, 435, 2152, doi: 10.1093/mnras/stt1435

  30. [38]

    2015, PASP, 127, 1161, doi: 10.1086/683602

    Kreidberg, L. 2015, PASP, 127, 1161, doi: 10.1086/683602

  31. [39]

    2026, Nature Astronomy, 10, 258, doi: 10.1038/s41550-025-02710-8

    Krishnamurthy, V., Carteret, Y., Piaulet-Ghorayeb, C., et al. 2026, Nature Astronomy, 10, 258, doi: 10.1038/s41550-025-02710-8

  32. [40]

    V., et al

    Lammer, H., Scherf, M., Erkaev, N. V., et al. 2025, Nature Astronomy, 9, 1022, doi: 10.1038/s41550-025-02550-6

  33. [41]

    Lammer, H., Lichtenegger, H. I. M., Kulikov, Y. N., et al. 2007, Astrobiology, 7, 185, doi: 10.1089/ast.2006.0128 Lamp´ on, M., L´ opez-Puertas, M., Lara, L. M., et al. 2020, A&A, 636, A13, doi: 10.1051/0004-6361/201937175

  34. [42]

    2020, A&A, 642, A121, doi: 10.1051/0004-6361/202038922

    Lillo-Box, J., Figueira, P., Leleu, A., et al. 2020, A&A, 642, A121, doi: 10.1051/0004-6361/202038922

  35. [43]

    2023, ApJL, 955, L22, doi: 10.3847/2041-8213/acf7c4

    Lim, O., Benneke, B., Doyon, R., et al. 2023, ApJL, 955, L22, doi: 10.3847/2041-8213/acf7c4

  36. [44]

    M., et al

    Lustig-Yaeger, J., Fu, G., May, E. M., et al. 2023, Nature Astronomy, doi: 10.1038/s41550-023-02064-z

  37. [45]

    M.-R., & Marounina, N

    Malsky, I., Rogers, L., Kempton, E. M.-R., & Marounina, N. 2023, Nature Astronomy, 7, 57, doi: 10.1038/s41550-022-01823-8

  38. [46]

    Malsky, I., & Rogers, L. A. 2020, ApJ, 896, 48, doi: 10.3847/1538-4357/ab873f

  39. [47]

    Maxted, P. F. L. 2023, MNRAS, 519, 3723, doi: 10.1093/mnras/stac3741

  40. [48]

    A., Astudillo-Defru, N., et al

    Ment, K., Dittmann, J. A., Astudillo-Defru, N., et al. 2019, AJ, 157, 32, doi: 10.3847/1538-3881/aaf1b1

  41. [49]

    Wakeford, H. R. 2018, AJ, 156, 252, doi: 10.3847/1538-3881/aae83a

  42. [50]

    E., Stevenson, K

    Moran, S. E., Stevenson, K. B., Sing, D. K., et al. 2023, ApJL, 948, L11, doi: 10.3847/2041-8213/accb9c

  43. [51]

    K., Fu, G., et al

    Mukherjee, S., Sing, D. K., Fu, G., et al. 2026, Science, 392, 858, doi: 10.1126/science.adx5903

  44. [52]

    B., & Ingargiola, A

    Newville, M., Stensitzki, T., Allen, D. B., & Ingargiola, A. 2014, LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python, 0.8.0, Zenodo Zenodo, doi: 10.5281/zenodo.11813 Oklopˇ ci´ c, A. 2019, ApJ, 881, 133, doi: 10.3847/1538-4357/ab2f7f

  45. [53]

    E., & Jackson, A

    Owen, J. E., & Jackson, A. P. 2012, MNRAS, 425, 2931, doi: 10.1111/j.1365-2966.2012.21481.x

  46. [54]

    K., Charbonneau, D., & Vanderburg, A

    Pass, E. K., Charbonneau, D., & Vanderburg, A. 2025, ApJL, 986, L3, doi: 10.3847/2041-8213/adda39

  47. [55]

    L., Hauschildt, P

    Peacock, S., Barman, T., Shkolnik, E. L., Hauschildt, P. H., & Baron, E. 2019, ApJ, 871, 235, doi: 10.3847/1538-4357/aaf891

  48. [56]

    2024, The Journal of Open Source Software, 9, 6898, doi: 10.21105/joss.06898

    Radica, M. 2024, The Journal of Open Source Software, 9, 6898, doi: 10.21105/joss.06898

  49. [57]

    2023, MNRAS, 524, 835, doi: 10.1093/mnras/stad1762

    Radica, M., Welbanks, L., Espinoza, N., et al. 2023, MNRAS, 524, 835, doi: 10.1093/mnras/stad1762

  50. [58]

    2025, ApJL, 979, L5, doi: 10.3847/2041-8213/ada381

    Radica, M., Piaulet-Ghorayeb, C., Taylor, J., et al. 2025, ApJL, 979, L5, doi: 10.3847/2041-8213/ada381

  51. [59]

    D., Maltagliati, L., Marley, M

    Robinson, T. D., Maltagliati, L., Marley, M. S., & Fortney, J. J. 2014, Proceedings of the National Academy of Science, 111, 9042, doi: 10.1073/pnas.1403473111

  52. [60]

    2026, ApJL, 998, L39, doi: 10.3847/2041-8213/ae3da3

    Rochon, A., Artigau, ´E., Weisserman, D., et al. 2026, ApJL, 998, L39, doi: 10.3847/2041-8213/ae3da3

  53. [61]

    Rogers, L. A. 2015, ApJ, 801, 41, doi: 10.1088/0004-637X/801/1/41

  54. [62]

    K., Liu, R., & Wang, A

    Rustamkulov, Z., Sing, D. K., Liu, R., & Wang, A. 2022, ApJL, 928, L7, doi: 10.3847/2041-8213/ac5b6f

  55. [63]

    K., Mukherjee, S., et al

    Rustamkulov, Z., Sing, D. K., Mukherjee, S., et al. 2023, Nature, 614, 659, doi: 10.1038/s41586-022-05677-y

  56. [64]

    Speagle, J. S. 2020, MNRAS, 493, 3132, doi: 10.1093/mnras/staa278

  57. [65]

    P., Sing, D

    Thorngren, D. P., Sing, D. K., & Mukherjee, S. 2026, ApJS, 283, 10, doi: 10.3847/1538-4365/ae0e71 van Dokkum, P. G. 2001, PASP, 113, 1420, doi: 10.1086/323894 Van Looveren, G., G¨ udel, M., Boro Saikia, S., &

  58. [66]

    2024, A&A, 683, A153, doi: 10.1051/0004-6361/202348079

    Kislyakova, K. 2024, A&A, 683, A153, doi: 10.1051/0004-6361/202348079

  59. [67]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2 13

  60. [68]

    K., Diamond-Lowe, H., et al

    Wachiraphan, P., Berta-Thompson, Z. K., Diamond-Lowe, H., et al. 2025, AJ, 169, 311, doi: 10.3847/1538-3881/adc990

  61. [69]

    K., et al

    Wang, L.-C., Rustamkulov, Z., Sing, D. K., et al. 2026, AJ, 171, 147, doi: 10.3847/1538-3881/ae231b Wes McKinney. 2010, in Proceedings of the 9th Python in Science Conference, ed. St´ efan van der Walt & Jarrod Millman, 56 – 61, doi: 10.25080/Majora-92bf1922-00a

  62. [70]

    2021, Nature Astronomy, 5, 822, doi: 10.1038/s41550-021-01375-3

    Yu, X., He, C., Zhang, X., et al. 2021, Nature Astronomy, 5, 822, doi: 10.1038/s41550-021-01375-3

  63. [71]

    J., & Catling, D

    Zahnle, K. J., & Catling, D. C. 2017, ApJ, 843, 122, doi: 10.3847/1538-4357/aa7846

  64. [72]

    2023, Nature, 620, 746, doi: 10.1038/s41586-023-06232-z

    Zieba, S., Kreidberg, L., Ducrot, E., et al. 2023, Nature, 620, 746, doi: 10.1038/s41586-023-06232-z

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