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The HUSTLE Program: The UV to Near-IR Transmission Spectrum of the Hot Jupiter KELT-7b

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read KELT-7b's atmosphere is flooded with H- ions, seven orders beyond equilibrium.

desk verdict A careful dual-pipeline, dual-retrieval paper whose new G280 spectrum is solid but whose headline H- abundance is heavily model-dependent, and the abstract overstates a water feature the retrievals do not detect. read the letter →

arxiv 2506.19193 v1 pith:ATBKETD5 submitted 2025-06-23 astro-ph.EP

Carlos Gascón , Mercedes López-Morales , Ryan J. MacDonald , Joanna K. Barstow , Victoria A. Boehm , Hannah R. Wakeford , Munazza K. Alam , Lili Alderson
show 9 more authors
Natasha E. Batalha Charlotte E. Fairman David Grant Nikole K. Lewis Mark S. Marley Sarah E. Moran Kazumasa Ohno Guillem Anglada-Escudé Ignasi Ribas
This is my paper · ORCID
classification astro-ph.EP
keywords ExoplanetatmospheresTransmissionspectroscopyHotJupitersKELT-7bH-opacityUV-opticalHSTWFC3/UVISG280Atmosphericretrieval
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

The paper presents a new 0.2-0.8 micron transmission spectrum of the hot Jupiter KELT-7b from HST WFC3/UVIS, combined with previously published near-infrared G141 data and Spitzer photometry. The central claim is that the combined spectrum is best explained by a very high abundance of the negative hydrogen ion H-, around log10 H- = -5, about seven orders of magnitude above the equilibrium chemistry prediction near $10^{-12}$. Two independent retrieval codes agree on this result with Bayesian detection significances above 4.5 $\sigma$, and the excess H- is attributed to photochemical disequilibrium in the upper atmosphere. The paper also finds that the UV-optical data are needed to constrain H- and to reveal bright stellar surface inhomogeneities that infrared data alone would miss.

What carries the argument

The load-bearing object is the H- bound-free continuum, the continuous absorption of the negative hydrogen ion across UV-optical wavelengths, which both retrieval codes need to fit the slight blue slope. The second piece of machinery is the 3-parameter stellar contamination model from Rathcke et al. (2021), which represents unocculted bright regions on the stellar disk by a temperature offset and a covering fraction; the paper calls these 'stellar inhomogeneities' rather than faculae because the fast-rotating host star makes true faculae physically infeasible. Retrievals compare models with and without each opacity source via Bayesian evidence, which converts the Bayes factors into the reported detection significances.

What would settle it

A JWST NIRSpec G395H spectrum from 2.9 to 5.1 microns would settle the claim: if the retrieved H- abundance is correct, the continuum should show the corresponding H- opacity and the 4.3 micron CO2 feature should appear as retrieved; if the blue slope was caused by unmodeled stellar heterogeneity instead, the infrared spectrum would not require H- at that level. Independent Doppler imaging or spot-modulation photometry that finds no bright regions at the retrieved covering fraction would also refute the stellar contamination part and call the H- abundance into question.

Watch

Extended reading notes

Core claim

On its own terms, the paper claims that KELT-7b's transmission spectrum from 0.2 to 5.4 microns is dominated by H- bound-free opacity rather than by molecular bands or clouds. Both retrieval codes, NEMESISPY and POSEIDON, return H- abundances of log H- = -4.94 (+0.89/-1.10) and -5.32 (+0.75/-0.94), with Bayes factors of 17,000 (4.8 sigma) and 6,000 (4.6 sigma) relative to models without H-. The spectrum is otherwise featureless longward of 0.4 microns, shows an asymmetric water feature in the G141 bandpass that is not required, and a tentative CO2 signal driven solely by the two Spitzer points. The same retrievals find bright stellar inhomogeneities covering about 9% of the stellar disk at roughly 300 K above the photosphere, a 2.7-sigma detection. Equilibrium chemistry forward models cannot reproduce the observed H- abundance, so the paper interprets the excess as evidence for photochemistry producing atomic H and free electrons in KELT-7b's upper atmosphere.

Load-bearing premise

The retrieved H- abundance depends on the assumption that the star's surface can be represented as a single uniform photosphere plus single-temperature bright patches; if the real stellar heterogeneity is more complex, the H- abundance needed to fit the blue slope could be biased.

Editorial extensions

If this is right

  • KELT-7b joins HAT-P-41b and WASP-79b as hot Jupiters around F-type stars with H- enriched upper atmospheres, suggesting EUV-driven photochemistry may be common in this population.
  • Observations with JWST redward of 1 micron, such as NIRISS SOSS and NIRSpec G395H, should further constrain the H- abundance and confirm or refute the tentative CO2 detection.
  • The cloudy-to-clear transition in hot Jupiter atmospheres may occur at lower temperatures than previously thought if H-, rather than a cloud deck, is what flattens the UV-optical spectra of these planets.
  • Including UV-optical coverage in transmission retrievals is necessary to break the degeneracy between clouds and H- and to detect bright stellar inhomogeneities that are invisible in infrared data alone.

Reading between the lines

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

  • If the H- super-abundance is real, higher-resolution UV spectroscopy of KELT-7b's terminator should show the bound-free continuum with a distinctive wavelength dependence that aligns with the retrieved abundance, while stellar contamination models would predict a steeper blue slope tied to photospheric structure.
  • A testable extension is to check the stellar inhomogeneity interpretation against independent stellar activity diagnostics: if time-series photometry or Doppler imaging finds no bright regions at the retrieved temperature and covering fraction, the H- abundance required by the retrievals would be biased.
  • The failure of equilibrium chemistry by seven orders of magnitude suggests that photochemical models of KELT-7b's upper atmosphere should predict a specific departure of H- abundance with altitude; comparing the retrieved column to such a profile would test the disequilibrium mechanism.
  • Since the paper excludes the TESS point from its preferred solution due to baseline uncertainty, a dedicated joint analysis of the TESS transits with a free baseline offset could test whether the stellar inhomogeneity constraints are robust.
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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

3 major / 5 minor

Summary. This paper presents the first UV-optical transmission spectrum of the hot Jupiter KELT-7b, obtained with HST WFC3/UVIS G280 from 0.2 to 0.8 micron, and combines it with previously published WFC3/IR G141 and Spitzer photometry to form a 0.2-5.4 micron dataset. Two independent reduction pipelines (lluvia and hazelnut) produce broadly consistent spectra. Atmospheric retrievals with two independent codes, NEMESISPY and POSEIDON, find that the spectrum is best explained by H- bound-free opacity with log10 H- abundances of -4.94 and -5.32, respectively, with Bayesian evidences of 17,000 and 6,000, together with bright stellar inhomogeneities covering about 9% of the stellar disk at roughly 300 K above the photosphere. The retrievals do not detect H2O, find tentative CO2 driven entirely by the two Spitzer points, and forward equilibrium chemistry models cannot reproduce the retrieved H- abundance, which the authors interpret as evidence for disequilibrium. The paper also tests the impact of including a TESS photometric point and finds that it shifts the H- abundance, but the authors exclude that point because of a suspected baseline offset.

Significance. If the H- detection holds, this paper would add KELT-7b to the small set of hot Jupiters with strong evidence for H- opacity and would strengthen the case that UV-optical observations are essential for revealing disequilibrium chemistry in the upper atmospheres of hot Jupiters around F-type stars. The study has clear strengths: two independent reduction pipelines, two independent retrieval codes, explicit Bayesian model comparison, a forward equilibrium chemistry check, and a transparent appendix showing the impact of removing the UVIS data. The two codes agree on the H- abundance and on the stellar contamination parameters, and the forward models provide an independent falsifiable test. However, the central claim is conditional on the adopted three-parameter stellar contamination model, which the authors themselves describe as a phenomenological catch-all because true faculae are physically infeasible for the fast-rotating, radiative-envelope host star KELT-7. The sensitivity of the H- abundance to the TESS point and to the presence or absence of UVIS data means that the quoted abundance is not yet robust at the level implied by the abstract.

major comments (3)
  1. [Section 4.3, Table 1, and Section 4.4] The central H- abundance is highly sensitive to the treatment of the TESS photometric point. Including TESS shifts the NEMESISPY log H- from -4.94 to -6.20 and the POSEIDON log H- from -5.32 to -5.79 (Table 1), while the text in Section 4.4 reports -5.50 for POSEIDON, a discrepancy that should be reconciled. The authors exclude TESS because of a possible baseline offset, but this exclusion is itself a modeling choice. Because the TESS point directly samples the optical continuum where H- and stellar contamination are degenerate, the paper should treat the TESS/no-TESS difference as a systematic uncertainty, report a combined abundance range, or explicitly present a retrieval with a free TESS offset as a sensitivity test even if it weakens the constraint.
  2. [Section 4.1, 4.2, and 4.5] Both retrieval codes adopt the same three-parameter stellar contamination prescription (photosphere temperature, heterogeneity temperature difference, and covering fraction, from Rathcke et al. 2021), and Section 4.5 states that true stellar faculae are physically infeasible for the fast-rotating star KELT-7. The bright inhomogeneities are therefore a phenomenological catch-all. Since the blue-UV slope can be absorbed either by H- continuum opacity or by the stellar contamination parameters, the agreement between NEMESISPY and POSEIDON does not validate the separation between these two contributions. The authors should test an alternative parameterization of the stellar contamination, for example a different spectral template for the inhomogeneities or a prior allowing both cooler and hotter regions simultaneously, and show whether the H- posterior and the claimed Bayes factors are stable under such changes.
  3. [Section 4.3, forward equilibrium models] The forward equilibrium chemistry comparison is a useful falsifiable test, but it inherits the stellar contamination and cloud assumptions from the free retrieval. The forward models are not fit to the data, and they are anchored to the maximum-likelihood retrieved T-P profile and to the retrieved stellar contamination parameters. The conclusion that the H- abundance is enhanced by disequilibrium processes is therefore conditional on the phenomenological stellar inhomogeneity model being correct. The paper should state this limitation explicitly, or run the forward models across a range of stellar contamination parameters, to quantify how much of the inferred disequilibrium could be absorbed by an unmodeled stellar surface component.
minor comments (5)
  1. [Abstract] The abstract says the spectrum shows 'an asymmetric water feature in the 1.1-1.7 micron band,' but Section 4.3 concludes 'We do not detect H2O in KELT-7b's atmosphere.' Please rephrase the abstract so that it does not claim a water feature when the retrievals attribute the G141 shape primarily to H- and do not confidently detect H2O.
  2. [Section 3.2] There is a stray 'red' in the sentence 'which agrees within 4.5 sigma with the T0 obtained with lluvia. red The difference...' that should be removed.
  3. [Table 1 and Section 4.4] The POSEIDON log H- value with TESS is given as -5.50 +/- 0.63 in Section 4.4 but as -5.79 +0.83/-0.71 in Table 1. Please make these consistent.
  4. [Figure 5 caption] The caption refers to 'NEMESIS' while the text uses 'NEMESISPY'; please unify the naming.
  5. [Abstract] There is a typo: 'a asymmetric water feature' should be 'an asymmetric water feature.'

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the H- detection is a Bayesian model comparison and the equilibrium comparison uses independent forward models; minor self-citations are present but not load-bearing.

full rationale

The paper's central claim—H- at log10(H-) ~ -5, about seven orders above equilibrium—is not forced by construction. The H- abundance is a free parameter in two independent retrieval codes (NEMESISPY and POSEIDON), and the 'detection' is quantified as a Bayes-factor model comparison between retrievals with and without H- (B = 17,000 and 6,000, respectively), so the significance is not a renamed fit. The equilibrium chemistry comparison is an independent forward calculation (NEMESISPY + Fastchem) that does not contain the retrieved H- value and is not fit to the data; it yields H- ~ 1e-12, defining the discrepancy rather than assuming it. The stellar contamination prescription is adopted from prior work with overlapping authors (Lewis et al. 2020; Rathcke et al. 2021), but the paper tests its significance on its own data (B = 10, 2.7 sigma) and explicitly labels the bright patches as phenomenological (Section 4.5). Sensitivity tests (TESS inclusion shifts log H- to -6.20 in NEMESISPY; removing UVIS shifts POSEIDON to -6.07) show the abundance is uncertain at the ~1 dex level but remains detected, so the central claim does not reduce to a single fitted assumption or to a self-citation chain. The weaknesses flagged by the skeptic—dependence on the stellar contamination model and sensitivity to the TESS point—are model-robustness concerns, not circularity. No self-definitional equation, fitted-input-called-prediction step, or uniqueness-imported-from-authors argument was found. Score 2 reflects minor non-load-bearing self-citations in the stellar contamination and H- chemistry context, not circular derivation.

Assumptions & free parameters 10 free parameters · 5 assumptions · 0 invented entities

The central claim rests on a set of retrieved free parameters (dominated by H- abundance and stellar heterogeneity terms) and on standard domain assumptions about 1D hydrostatic atmospheres, opacity sources, and the stellar contamination parameterization. No new physical entities are introduced. The full set of fitted parameters appears in Table 1.

free parameters (10)
  • log10 H- abundance (NEMESISPY) = -4.94 (+0.89/-1.10)
    Retrieved volume mixing ratio, dominated by the UV and NIR spectral shape.
  • log10 H- abundance (POSEIDON) = -5.32 (+0.75/-0.94)
    Independent retrieval, consistent with NEMESISPY.
  • Bright stellar inhomogeneity covering fraction f_het = 0.09 (+0.05/-0.04)
    Retrieved fraction of visible stellar disk covered by hot regions.
  • Temperature difference of inhomogeneities Delta T_het = 333 (+161/-126) K
    Retrieved temperature contrast; the paper argues true faculae are physically infeasible for KELT-7.
  • Photosphere temperature T_phot = 6848 +- 158 K
    Retrieved with a Gaussian prior centered at 6848 K with 200 K width.
  • Cloud top pressure log10(Pcloud/bar) = -4.0 (+2.15/-1.17)
    Highly degenerate with H- abundance; not unambiguously detected.
  • WFC3/IR offset = -48 +- 38 ppm
    Free offset between UVIS and G141 data.
  • Spitzer offset = -78 +- 61 ppm
    Free offset between UVIS and Spitzer data.
  • log10 CO2 abundance (NEMESISPY) = -2.95 (+0.79/-1.23)
    Tentative, driven by two Spitzer points only.
  • Other Table 1 retrieval parameters (gas VMRs, P-T shape, aerosol indices, radius) = See Table 1
    Fitted but largely unconstrained; not load-bearing for the H- claim.
assumptions (5)
  • domain assumption Atmosphere is H2-He dominated with fixed He/H2 = 0.17
    Invoked in both retrieval setups (Sections 4.1 and 4.2). If the mean molecular weight differs, retrieved abundances shift.
  • domain assumption Transmission spectrum is modeled with a 1D, plane-parallel, hydrostatic atmosphere with uniform terminator coverage
    POSEIDON model description in Section 4.2. Three-dimensional effects such as terminator inhomogeneities are neglected.
  • domain assumption H- bound-free continuum opacity from John (1988) is the correct source of the blue-optical continuum
    The detection significance is computed by switching this opacity on and off; if another continuum source (e.g., haze scattering or an incorrect stellar model) mimics it, the H- abundance would be biased.
  • domain assumption Stellar contamination is representable by a 3-parameter single-temperature hot/cold region model (Rathcke et al. 2021)
    Used in both codes; the paper itself argues true faculae are infeasible for KELT-7 (Section 4.5), making this a phenomenological catch-all.
  • domain assumption Equilibrium chemistry forward models (Fastchem) with an isothermal T-P profile at the retrieved temperature represent the baseline for 'equilibrium'
    Section 4.3; deviations from this T-P profile could change the equilibrium H- abundance, narrowing the claimed disequilibrium gap.

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Cite this review

Pith. "Pith review of The HUSTLE Program: The UV to Near-IR Transmission Spectrum of the Hot Jupiter KELT-7b." pith.science (2026). https://pith.science/paper/ATBKETD5

@misc{pith2026250619193,
  author       = {Pith},
  title        = {Pith review of: The HUSTLE Program: The UV to Near-IR Transmission Spectrum of the Hot Jupiter KELT-7b},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ATBKETD5}},
  note         = {Machine review of arXiv:2506.19193}
}
abstract

The ultraviolet and optical wavelength ranges have proven to be a key addition to infrared observations of exoplanet atmospheres, as they offer unique insights into the properties of clouds and hazes and are sensitive to signatures of disequilibrium chemistry. Here we present the 0.2-0.8 $\mu$m transmission spectrum of the Teq = 2000 K Jupiter KELT-7b, acquired with HST WFC3/UVIS G280 as part of the HUSTLE Treasury program. We combined this new spectrum with the previously published HST WFC3/IR G141 (1.1-1.7 $\mu$m) spectrum and Spitzer photometric points at 3.6$\mu$m and 4.5$\mu$m, to reveal a generally featureless transmission spectrum between 0.2 and 1.7 $\mu$m, with a slight downward slope towards bluer wavelengths, and a asymmetric water feature in the 1.1-1.7 $\mu$m band. Retrieval models conclude that the 0.2 - 1.7$\mu$m spectrum is primarily explained by a high H- abundance ($\sim 10^{-5}$), significantly above the equilibrium chemistry prediction ($\sim 10^{-12}$), suggesting disequilibrium in KELT-7b's upper atmosphere. Our retrievals also suggest the presence of bright inhomogeneities in the stellar surface, and tentative evidence of CO2 at the Spitzer wavelengths. We demonstrate that with the UV-optical coverage provided by WFC3 UVIS/G280, we are able to confirm the presence and constrain the abundance of H-, and obtain evidence for bright stellar inhomogeneities that would have been overlooked using infrared data alone. Observations redward of 1$\mu$m with JWST should be able to further constrain the abundance of H-, as well as confirm the presence of CO2 inferred by the two Spitzer datapoints.

Figures

Figures reproduced from arXiv: 2506.19193 by the authors.

Figure 1
Figure 1. Top: HST WFC3/UVIS G280 exposure showing the order zero image, and the spectra corresponding to positive and negative orders. Two background stars are highlighted by purple circles. The dashed rectangles in the image corners indicate the region used to estimate background on each image. Middle: Raw +1 (left) and -1 (right) order white-light curve obtained with lluvia. Bottom: Systematics corrected +1 (left) and -1 (… view at source ↗
Figure 2
Figure 2. Displacements in the X (left) and Y (right) detector directions, measured by cross-correlation of the spectral trace (red triangles and purple circles), and by tracking the centroid position of several background stars (blue squares). els in the frame. We find that the histograms of pixel values in our frames reveal a bimodal distribution of val￾ues; many pixels were valued between -8 to -5 e-, but a similar number … view at source ↗
Figure 3
Figure 3. Results from the KELT-7b light curve fitting. Top: +1 (blue) and -1 (red) order transmission spectra obtained with the lluvia pipeline (left), and the Hazelnut pipeline (right). Bottom: Combined transmission spectrum obtained with lluvia (purple), and the Hazelnut (gray). The narrow panels below each plot show the differences between the corresponding transmission spectra in units of σ, with the dashed lines and the… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: Atmospheric retrievals of KELT-7b’s transmission spectrum conducted with POSEIDON (left panel, purple) and NEMESIS (right panel, blue). Each panel shows the median retrieved spectrum (solid lines), together with the 1σ (dark shading) and 2σ (light shading) regions. nes…
Figure 5
Figure 5. Figure 5: KELT-7b atmospheric retrieval posterior distributions of a subset of the parameters retrieved with POSEIDON (purple) and NEMESISPY (blue). We show constraints on the CO2 and H− abundance, the cloud top pressure, the temperature and covering fraction of the stellar hete…
Figure 6
Figure 6. Figure 6: Atmospheric retrievals of KELT-7b’s transmission spectrum conducted with NEMESISPY including the TESS data point (gray). For comparison, the results without the TESS data are also plotted (blue). The top panel shows the median retrieved spectrum. The histograms on the …
Figure 7
Figure 7. Figure 7: Transmission spectrum of KELT-7b compared to the WFC3/UVIS G280 UV-optical transmission spectra of WASP￾178b (Lothringer et al. 2022) and HAT-P-41b (Wakeford et al. 2020), and the STIS E230M, G430L and G750L transmission spectra of WASP-79b (Rathcke et al. 2021; Gressi…
Figure 8
Figure 8. Figure 8: Atmospheric retrievals of KELT-7b’s transmission spectrum conducted with POSEIDON without including the WFC3/UVIS G280 data (gray). For comparison, the results with the UVIS data are also plotted (purple). The top panel shows the median retrieved spectrum. The histogra…
Figure 9
Figure 9. Figure 9: Top: Raw +1 (left) and -1 (right) order white-light curve obtained with Hazelnut. Bottom: Systematics corrected +1 (left) and -1 (right) order white-light curve. The narrow panel below shows the transit fit residuals, with the dashed lines indicating the standard devia…
Figure 10
Figure 10. Figure 10: +1 order spectroscopic light curves from 2005 to 3905 ˚A obtained with the lluvia pipeline. The left panel shows the raw light curves, the middle panel shows the systematics corrected and model light curves, and the right panel shows the residuals from the correspondi…
Figure 11
Figure 11. Figure 11: +1 order spectroscopic light curves from 4005 to 7705 ˚A obtained with the lluvia pipeline. The left panel shows the raw light curves, the middle panel shows the systematics corrected and model light curves, and the right panel shows the residuals from the correspondi…
Figure 12
Figure 12. Figure 12: +1 order spectroscopic light curves from 2000 to 7800 ˚A obtained with the Hazelnut pipeline. The first and third columns show the systematics corrected and fitted model light curves, and the second and fourth columns show the corresponding residuals. Light curves are…

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Mitigating Charge Migration in JWST NIRISS Reveals That KELT-7 b is a Metal-enriched Ultra-hot Jupiter Orbiting a Young Metal-rich Star

    astro-ph.EP 2026-07 conditional novelty 7.0 of 10

    Correcting NIRISS charge migration reveals KELT-7 b as a metal-enriched (~92x solar) ultra-hot Jupiter with H2O, CO2 and TiO but no H- or clouds, orbiting a young metal-rich star.

Reference graph

Works this paper leans on

89 extracted references · 6 canonical work pages · cited by 1 Pith paper

  1. [1]

    B., Mansfield, M., et al

    Ahrer, E.-M., Stevenson, K. B., Mansfield, M., et al. 2023, Nature, 614, 653, doi: 10.1038/s41586-022-05590-4

    doi:10.1038/s41586-022-05590-4 2023

  2. [2]

    K., Nikolov, N., L´ opez-Morales, M., et al

    Alam, M. K., Nikolov, N., L´ opez-Morales, M., et al. 2018, AJ, 156, 298, doi: 10.3847/1538-3881/aaee89

    doi:10.3847/1538-3881/aaee89 2018

  3. [3]

    R., MacDonald, R

    Alderson, L., Wakeford, H. R., MacDonald, R. J., et al. 2022, MNRAS, 512, 4185, doi: 10.1093/mnras/stac661

    doi:10.1093/mnras/stac661 2022

  4. [4]

    R., Alam, M

    Alderson, L., Wakeford, H. R., Alam, M. K., et al. 2023, Nature, 614, 664, doi: 10.1038/s41586-022-05591-3 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 al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Coll...

    doi:10.1038/s41586-022-05591-3 2023

  5. [5]

    Barstow, J. K. 2020, MNRAS, 497, 4183, doi: 10.1093/mnras/staa2219

    doi:10.1093/mnras/staa2219 2020

  6. [6]

    J., Yurchenko, S

    Barton, E. J., Yurchenko, S. N., & Tennyson, J. 2013, MNRAS, 434, 1469, doi: 10.1093/mnras/stt1105

    doi:10.1093/mnras/stt1105 2013

  7. [7]

    2021, A&A, 648, A127, doi: 10.1051/0004-6361/202039708

    Baxter, C., D´ esert, J.-M., Tsai, S.-M., et al. 2021, A&A, 648, A127, doi: 10.1051/0004-6361/202039708

    doi:10.1051/0004-6361/202039708 2021

  8. [8]

    J., Welbanks, L., Schlawin, E., et al

    Bell, T. J., Welbanks, L., Schlawin, E., et al. 2023, Nature, 623, 709, doi: 10.1038/s41586-023-06687-0

    doi:10.1038/s41586-023-06687-0 2023

Show all 89 references
  1. [9]

    G., et al

    Bieryla, A., Collins, K., Beatty, T. G., et al. 2015, AJ, 150, 12, doi: 10.1088/0004-6256/150/1/12

    2015 doi

  2. [10]

    A., Lewis, N

    Boehm, V. A., Lewis, N. K., Fairman, C. E., et al. 2024, arXiv e-prints, arXiv:2410.17368, doi: 10.48550/arXiv.2410.17368

    2024 doi arXiv

  3. [11]

    2002, Astronomy and Astrophysics, 390, 779, doi: 10.1051/0004-6361:20020555

    Borysow, A. 2002, Astronomy and Astrophysics, 390, 779, doi: 10.1051/0004-6361:20020555

    2002 doi

  4. [12]

    1989, The Astrophysical Journal, 341, 549, doi: 10.1086/167515 —

    Borysow, A., & Frommhold, L. 1989, The Astrophysical Journal, 341, 549, doi: 10.1086/167515 —. 1990, The Astrophysical Journal Letters, 348, L41, doi: 10.1086/185626

    1989 doi

  5. [13]

    1989, The Astrophysical Journal, 336, 495, doi: 10.1086/167027

    Borysow, A., Frommhold, L., & Moraldi, M. 1989, The Astrophysical Journal, 336, 495, doi: 10.1086/167027

    1989 doi

  6. [14]

    G., & Fu, Y

    Borysow, A., Jorgensen, U. G., & Fu, Y. 2001, JQSRT, 68, 235, doi: 10.1016/S0022-4073(00)00023-6

    2001 doi

  7. [15]

    G., & Zheng, C

    Borysow, A., Jorgensen, U. G., & Zheng, C. 1997, Astronomy and Astrophysics, 324, 185

    1997

  8. [16]

    2014, Astronomy & Astrophysics, 564, A125, doi: 10.1051/0004-6361/201322971

    Buchner, J., Georgakakis, A., Nandra, K., et al. 2014, Astronomy & Astrophysics, 564, A125, doi: 10.1051/0004-6361/201322971

    2014 doi

  9. [17]

    Castelli, F., & Kurucz, R. L. 2003, in Modelling of Stellar Atmospheres, ed. N. Piskunov, W. W. Weiss, & D. F

    2003

  10. [18]

    210, A20, doi: 10.48550/arXiv.astro-ph/0405087

    Gray, Vol. 210, A20, doi: 10.48550/arXiv.astro-ph/0405087

    doi arXiv

  11. [19]

    L., Rocchetto, M., Yurchenko, S

    Chubb, K. L., Rocchetto, M., Yurchenko, S. N., et al. 2021, A&A, 646, A21, doi: 10.1051/0004-6361/202038350

    2021 doi

  12. [20]

    2000, A&A, 363, 1081

    Claret, A. 2000, A&A, 363, 1081

    2000

  13. [21]

    2013, ApJ, 774, 95, doi: 10.1088/0004-637X/774/2/95

    Deming, D., Wilkins, A., McCullough, P., et al. 2013, ApJ, 774, 95, doi: 10.1088/0004-637X/774/2/95

    2013 doi

  14. [22]

    I., et al

    Esparza-Borges, E., L´ opez-Morales, M., Adams Redai, J. I., et al. 2023, ApJL, 955, L19, doi: 10.3847/2041-8213/acf27b

    2023 doi

  15. [23]

    M., Sing, D

    Evans, T. M., Sing, D. K., Goyal, J. M., et al. 2018, AJ, 156, 283, doi: 10.3847/1538-3881/aaebff

    2018 doi

  16. [24]

    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

    2023 doi

  17. [25]

    Feroz, F., & Hobson, M. P. 2008, MNRAS, 384, 449, doi: 10.1111/j.1365-2966.2007.12353.x

    2008

  18. [26]

    P., & Bridges, M

    Feroz, F., Hobson, M. P., & Bridges, M. 2009, MNRAS, 398, 1601, doi: 10.1111/j.1365-2966.2009.14548.x

    2009

  19. [27]

    P., Cameron, E., & Pettitt, A

    Feroz, F., Hobson, M. P., Cameron, E., & Pettitt, A. N. 2019, The Open Journal of Astrophysics, 2, 10, doi: 10.21105/astro.1306.2144

    2019 arXiv

  20. [28]

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

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

    2013 doi

  21. [29]

    2017, ApJL, 847, L22, doi: 10.3847/2041-8213/aa8e40

    Fu, G., Deming, D., Knutson, H., et al. 2017, ApJL, 847, L22, doi: 10.3847/2041-8213/aa8e40

    2017 doi

  22. [30]

    N., Yurchenko, S

    Gorman, M. N., Yurchenko, S. N., & Tennyson, J. 2019, Monthly Notices of the Royal Astronomical Society, 490, 1652, doi: 10.1093/mnras/stz2517

    2019 doi

  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

    2022 doi

  24. [32]

    D., Wakeford, H

    Grant, D., Lothringer, J. D., Wakeford, H. R., et al. 2023, ApJL, 949, L15, doi: 10.3847/2041-8213/acd544

    2023 doi

  25. [33]

    K., et al

    Gressier, A., Lecavelier des Etangs, A., Sing, D. K., et al. 2023, A&A, 672, A34, doi: 10.1051/0004-6361/202244429

    2023 doi

  26. [34]

    1986, PASP, 98, 609, doi: 10.1086/131801

    Horne, K. 1986, PASP, 98, 609, doi: 10.1086/131801

    1986 doi

  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

    2013 doi

  28. [36]

    Irwin, P. G. J., Teanby, N. A., de Kok, R., et al. 2008, JQSRT, 109, 1136, doi: 10.1016/j.jqsrt.2007.11.006

    2008 doi

  29. [37]

    John, T. L. 1988, A&A, 193, 189

    1988

  30. [38]

    J., Norris, C

    Johnson, L. J., Norris, C. M., Unruh, Y. C., et al. 2021, Monthly Notices of the Royal Astronomical Society, 504, 4751

    2021

  31. [39]

    B., et al

    Kitzmann, D., Heng, K., Rimmer, P. B., et al. 2018, ApJ, 863, 183, doi: 10.3847/1538-4357/aace5a

    2018 doi

  32. [40]

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

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

    2015 doi

  33. [41]

    Krissansen-Totton, J., Garland, R., Irwin, P., & Catling, D. C. 2018, AJ, 156, 114, doi: 10.3847/1538-3881/aad564

    2018 doi

  34. [42]

    2020, The Journal of Open Source Software, 5, 2281, doi: 10.21105/joss.02281

    Laginja, I., & Wakeford, H. 2020, The Journal of Open Source Software, 5, 2281, doi: 10.21105/joss.02281

    2020 doi

  35. [43]

    Lavvas, P., Koskinen, T., & Yelle, R. V. 2014, ApJ, 796, 15, doi: 10.1088/0004-637X/796/1/15 24

    2014 doi

  36. [44]

    K., Wakeford, H

    Lewis, N. K., Wakeford, H. R., MacDonald, R. J., et al. 2020, ApJL, 902, L19, doi: 10.3847/2041-8213/abb77f

    2020 doi

  37. [45]

    E., Rothman, L

    Li, G., Gordon, I. E., Rothman, L. S., et al. 2015, Astrophys. J. Suppl., 216, 15, doi: 10.1088/0067-0049/216/1/15

    2015 doi

  38. [46]

    D., Sing, D

    Lothringer, J. D., Sing, D. K., Rustamkulov, Z., et al. 2022, Nature, 604, 49, doi: 10.1038/s41586-022-04453-2

    2022 doi

  39. [47]

    MacDonald, R. J. 2023, The Journal of Open Source Software, 8, 4873, doi: 10.21105/joss.04873

    2023 doi

  40. [48]

    J., & Madhusudhan, N

    MacDonald, R. J., & Madhusudhan, N. 2017, MNRAS, 469, 1979, doi: 10.1093/mnras/stx804

    2017 doi

  41. [49]

    2009, ApJ, 707, 24, doi: 10.1088/0004-637X/707/1/24

    Madhusudhan, N., & Seager, S. 2009, ApJ, 707, 24, doi: 10.1088/0004-637X/707/1/24

    2009 doi

  42. [50]

    2015, A&A, 573, A90, doi: 10.1051/0004-6361/201423804

    Magic, Z., Chiavassa, A., Collet, R., & Asplund, M. 2015, A&A, 573, A90, doi: 10.1051/0004-6361/201423804

    2015 doi

  43. [51]

    Marsh, T. R. 1989, PASP, 101, 1032, doi: 10.1086/132570

    1989 doi

  44. [52]

    K., Masseron, T., Hoeijmakers, H

    McKemmish, L. K., Masseron, T., Hoeijmakers, H. J., et al. 2019, MNRAS, 488, 2836, doi: 10.1093/mnras/stz1818

    2019 doi

  45. [53]

    2020, ApJL, 895, L47, doi: 10.3847/2041-8213/ab93d7

    Ohno, K., & Kawashima, Y. 2020, ApJL, 895, L47, doi: 10.3847/2041-8213/ab93d7

    2020 doi

  46. [54]

    1978, Astrophysical Journal, Part 1, vol

    Parker, E. 1978, Astrophysical Journal, Part 1, vol. 221, Apr. 1, 1978, p. 368-377., 221, 368

    1978

  47. [55]

    T., Yurchenko, S

    Patrascu, A. T., Yurchenko, S. N., & Tennyson, J. 2015, MNRAS, 449, 3613, doi: 10.1093/mnras/stv507

    2015 doi

  48. [56]

    2020, Updated Calibration of the UVIS G280

    Pirzkal, N. 2020, Updated Calibration of the UVIS G280

    2020

  49. [57]

    Grism, Instrument Science Report WFC3 2020-9, 27 pages

    2020

  50. [58]

    2020, AJ, 160, 112, doi: 10.3847/1538-3881/aba000

    Pluriel, W., Whiteford, N., Edwards, B., et al. 2020, AJ, 160, 112, doi: 10.3847/1538-3881/aba000

    2020 doi

  51. [59]

    L., Kyuberis, A

    Polyansky, O. L., Kyuberis, A. A., Zobov, N. F., et al. 2018, MNRAS, 480, 2597, doi: 10.1093/mnras/sty1877

    2018 doi

  52. [60]

    2006, MNRAS, 373, 231, doi: 10.1111/j.1365-2966.2006.11012.x

    Pont, F., Zucker, S., & Queloz, D. 2006, MNRAS, 373, 231, doi: 10.1111/j.1365-2966.2006.11012.x

    2006

  53. [61]

    D., Lee, E

    Powell, D., Feinstein, A. D., Lee, E. K. H., et al. 2024, Nature, 626, 979, doi: 10.1038/s41586-024-07040-9

    2024 doi

  54. [62]

    V., Apai, D., & Giampapa, M

    Rackham, B. V., Apai, D., & Giampapa, M. S. 2018, ApJ, 853, 122, doi: 10.3847/1538-4357/aaa08c

    2018 doi

  55. [63]

    D., MacDonald, R

    Rathcke, A. D., MacDonald, R. J., Barstow, J. K., et al. 2021, AJ, 162, 138, doi: 10.3847/1538-3881/ac0e99

    2021 doi

  56. [64]

    R., Winn, J

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

    2014 doi

  57. [65]

    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

    2023 doi

  58. [66]

    Sing, D. K. 2010, A&A, 510, A21, doi: 10.1051/0004-6361/200913675

    2010 doi

  59. [67]

    K., Wakeford, H

    Sing, D. K., Wakeford, H. R., Showman, A. P., et al. 2015, MNRAS, 446, 2428, doi: 10.1093/mnras/stu2279

    2015 doi

  60. [68]

    K., Fortney, J

    Sing, D. K., Fortney, J. J., Nikolov, N., et al. 2016, Nature, 529, 59, doi: 10.1038/nature16068

    2016 doi

  61. [69]

    K., Lavvas, P., Ballester, G

    Sing, D. K., Lavvas, P., Ballester, G. E., et al. 2019, AJ, 158, 91, doi: 10.3847/1538-3881/ab2986

    2019 doi

  62. [70]

    Solanki, S. K. 1993, Space Science Reviews, 63, 1

    1993

  63. [71]

    1979, Solar Physics, 61, 363

    Spruit, H. 1979, Solar Physics, 61, 363

    1979

  64. [72]

    G., Collins, K

    Stassun, K. G., Collins, K. A., & Gaudi, B. S. 2017, AJ, 153, 136, doi: 10.3847/1538-3881/aa5df3

    2017 doi

  65. [73]

    W., Kitzmann, D., & Patzer, A

    Stock, J. W., Kitzmann, D., & Patzer, A. B. C. 2022, MNRAS, 517, 4070, doi: 10.1093/mnras/stac2623

    2022 doi

  66. [74]

    W., Kitzmann, D., Patzer, A

    Stock, J. W., Kitzmann, D., Patzer, A. B. C., & Sedlmayr, E. 2018, MNRAS, 479, 865, doi: 10.1093/mnras/sty1531 STScI Development Team. 2013, pysynphot: Synthetic photometry software package, Astrophysics Source Code Library, record ascl:1303.023

    2018 doi

  67. [75]

    2023, The Journal of Open Source Software, 8, 4602, doi: 10.21105/joss.04602

    Townsend, R., & Lopez, A. 2023, The Journal of Open Source Software, 8, 4602, doi: 10.21105/joss.04602

    2023 doi

  68. [76]

    2008, Contemporary Physics, 49, 71, doi: 10.1080/00107510802066753

    Trotta, R. 2008, Contemporary Physics, 49, 71, doi: 10.1080/00107510802066753

    2008 doi

  69. [77]

    Tsai, S.-M., Lee, E. K. H., Powell, D., et al. 2023, Nature, 617, 483, doi: 10.1038/s41586-023-05902-2

    2023 doi

  70. [78]

    P., Zingales, T., et al

    Tsiaras, A., Waldmann, I. P., Zingales, T., et al. 2018, AJ, 155, 156, doi: 10.3847/1538-3881/aaaf75

    2018 doi

  71. [79]

    E., et al

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

    2020 doi

  72. [80]

    2010, The Astrophysical Journal, 716, 1060

    Visscher, C., Lodders, K., & Fegley, B. 2010, The Astrophysical Journal, 716, 1060

    2010

  73. [81]

    R., & Sing, D

    Wakeford, H. R., & Sing, D. K. 2015, A&A, 573, A122, doi: 10.1051/0004-6361/201424207

    2015 doi

  74. [82]

    2016, ApJ, 819, 10, doi: 10.3847/0004-637X/819/1/10

    Mandell, A. 2016, ApJ, 819, 10, doi: 10.3847/0004-637X/819/1/10

    2016 doi

  75. [83]

    R., Sing, D

    Wakeford, H. R., Sing, D. K., Deming, D., et al. 2017, The Astronomical Journal, 155, 29

    2017

  76. [84]

    R., Sing, D

    Wakeford, H. R., Sing, D. K., Kataria, T., et al. 2017, Science, 356, 628, doi: 10.1126/science.aah4668

    2017 doi

  77. [85]

    R., Sing, D

    Wakeford, H. R., Sing, D. K., Stevenson, K. B., et al. 2020, AJ, 159, 204, doi: 10.3847/1538-3881/ab7b78

    2020 doi

  78. [86]

    Wende, S., Reiners, A., Seifahrt, A., & Bernath, P. F. 2010, A&A, 523, A58, doi: 10.1051/0004-6361/201015220

    2010 doi

  79. [87]

    2024, The Journal of Open Source Software, 9, 6874, doi: 10.21105/joss.06874

    Yang, J., Alday, J., & Irwin, P. 2024, The Journal of Open Source Software, 9, 6874, doi: 10.21105/joss.06874

    2024 doi

  80. [88]

    N., Bond, W., Gorman, M

    Yurchenko, S. N., Bond, W., Gorman, M. N., et al. 2018, MNRAS, 478, 270, doi: 10.1093/mnras/sty939

    2018 doi

  81. [89]

    2020, MNRAS, 496, 5282, doi: 10.1093/mnras/staa1874

    Tennyson, J. 2020, MNRAS, 496, 5282, doi: 10.1093/mnras/staa1874

    2020 doi

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