Pith. sign in

REVIEW 3 major objections 5 minor 2 cited by

JWST COMPASS: NIRSpec/G395H Transmission Observations of the Super-Earth TOI-776b

T0 review · 3 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash

Pith's one-line read The paper reports that two JWST transits of the super-Earth TOI-776b rule out any clear, low-metallicity hydrogen atmosphere at the 1-millibar level.

desk verdict New TOI-776b spectrum with careful dual-reduction analysis, but the abstract reverses the visit limits and the Visit 2 detector offset is fit to the same data, leaving the headline 3σ bound a bit softer than the prose claims. read the letter →

arxiv 2501.14596 v1 pith:FY3ZTTZQ submitted 2025-01-24 astro-ph.EP

classification astro-ph.EP
keywords ExoplanetatmosphericcompositionatmospheresExoplanetsInfraredspectroscopysuper-EarthtransmissionJWSTNIRSpecG395HTOI-776b
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

Using two independent reductions of two NIRSpec/G395H transit visits, the authors measure TOI-776b's 2.8–5.2 µm transmission spectrum at a median precision of 34 ppm per 0.02 µm bin. They find no reliable molecular features: Visit 1 is best described by a flat line, and Visit 2 by a flat line plus a ~65 ppm offset between the NRS1 and NRS2 detectors, which they treat as instrumental. Comparing the spectra to PICASO forward models, they conclude that at an opaque pressure of $10^{-3}$ bar any atmosphere below 100× solar metallicity is excluded at ≥3σ in every visit and every reduction; at 1 bar, 10× solar and below are excluded by more than 8σ. The exact lower limit moves between visits and reductions, from ~100× solar in Visit 2 to ~350–470× solar in Visit 1, so the paper cautions against over-interpreting any single metallicity number. The result bears on what kind of atmosphere, if any, this 1.85 Earth-radius planet can retain, favouring a very thin, heavily clouded, or highly metal-enriched atmosphere over a clear hydrogen-dominated one.

What carries the argument

The central machinery is a grid of PICASO forward transmission models spanning 1–1000× solar metallicity in 20 logarithmically spaced steps and opaque pressure levels from 1 to $10^{-4}$ bar, where the opaque pressure plays the role of an agnostic, wavelength-independent cloud deck or the planetary surface. PICASO is a radiative-transfer code that computes transmission spectra from chemical-equilibrium abundances supplied by photochem, on temperature-pressure profiles parameterized following Guillot (2010), using the Resampled Opacities database (Batalha et al. 2022) with CH4, CO, CO2, H2O, NH3, Na, K, and dozens of minor species. Each model is rebinned to the data resolution and scored by reduced chi-squared, and the 3σ exclusion contours are obtained by 2D cubic interpolation in the metallicity–opaque-pressure plane. A second piece of machinery is the set of non-physical fits (zero-slope, sloped, step offset between NRS1 and NRS2, and Gaussian features) that establishes the spectral shape preferred by each visit and supplies the offset applied before the physical-model comparison.

What would settle it

A decisive check would be a third transit of TOI-776b observed at a different telescope roll angle, or with NIRSpec PRISM, so that no NRS1/NRS2 step correction is needed; if a methane band at ~3.3 µm or a CO2 band at ~4.3 µm then appears with an amplitude consistent with a <100× solar atmosphere, the paper's exclusion is wrong. A cheaper test is available now: re-fit the Visit 2 spectrum allowing the NRS1/NRS2 offset to be wavelength-dependent and see whether the 3σ excluded-metallicity boundary shifts by more than the stated visit-to-visit spread.

Watch

Extended reading notes

Core claim

TOI-776b's transmission spectrum is featureless at the achieved precision, and the paper's central claim is a conservative exclusion: using chemical-equilibrium PICASO forward models in which an opaque pressure level represents either a cloud deck or the surface, the authors rule out atmospheres below 100× solar metallicity at $10^{-3}$ bar to ≥3σ across both visits and both reductions. At 1 bar, the exclusion is much stronger, with 10× solar and below rejected by more than 8σ and 100× solar rejected at 7σ for Visit 1. After subtracting the NRS1/NRS2 offset in Visit 2, the 3σ boundary at $10^{-3}$ bar spans ~350× solar (ExoTiC-JEDI) and ~470× solar (Eureka!) for Visit 1, and ~100× and ~130× solar for Visit 2. The atmospheres that survive are a very thin layer (opaque pressure at or below $10^{-4}$ bar), a high-metallicity atmosphere near ~1000× solar at 1 bar, or any of these with a wavelength-independent cloud deck; a bare rock is disfavoured because the planet's density and radius-valley position require some low-density material.

Load-bearing premise

The argument assumes that the ~65 ppm offset between the NRS1 and NRS2 detectors in Visit 2 is a fixed instrumental artifact that a single step function can remove before comparing the spectrum to physical models: if this offset actually changes with wavelength or time, the derived metallicity exclusion contours would be biased.

Editorial extensions

If this is right

  • If the central claim is correct, TOI-776b cannot host a clear, hydrogen-dominated, low-metallicity atmosphere down to the 1-millibar level, so any atmosphere it retains must be metal-rich, very thin, or hidden by an opaque cloud or haze deck.
  • The conservative 100× solar exclusion at 10^-3 bar extends the COMPASS sample's growing pattern that JWST super-Earth transmission spectra are featureless and point to high mean molecular weights or clouds rather than detectable molecular bands.
  • Visit- and reduction-dependent limits (roughly 100× to 470× solar at 10^-3 bar) imply that comparing single quoted metallicities across planets or programs without accounting for these systematics could produce misleading population-level conclusions.
  • The paper's identification of allowed low-metallicity, low-pressure parameter space shows that a non-detection of molecular features does not by itself distinguish a bare rock from an extremely thin atmosphere, since a 10^-10 mass-fraction hydrogen layer is photoevaporation-equivalent to a bare rock.

Reading between the lines

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

  • An implication the authors leave implicit is that the unexcluded 1× solar, 10^-4 bar corner is unlikely to be a physically persistent atmosphere, so future observing time is better spent distinguishing a bare rock from a thin but stable high-metallicity or cloudy atmosphere than refining the high-metallicity boundary.
  • If the Visit 2 NRS1/NRS2 offset is actually wavelength-dependent or time-varying, a scalar step correction could be hiding real spectral structure; a third transit at a different roll angle or with NIRSpec PRISM would test whether the 100× solar exclusion survives without the offset correction.
  • A joint analysis of both visits with a shared systematic model for the detector offset might either sharpen the combined 3σ contour or reveal that the visit-to-visit spread is larger than the photon noise, which would argue for treating multi-visit super-Earth spectra as correlated measurements rather than independent confirmations.
  • Applying the same metallicity-pressure grid approach to other COMPASS targets could separate cloudy high-metallicity atmospheres from genuinely bare-rock planets, a distinction that density and radius-valley arguments alone cannot make.
Share X Bluesky LinkedIn Reddit HN

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 two JWST NIRSpec/G395H transit observations of the super-Earth TOI-776b, reduced independently with the ExoTiC-JEDI and Eureka! pipelines. The resulting 2.8–5.2 micron transmission spectra have a median precision of 34 ppm per 0.02 micron bin. The two reductions agree well for each visit, but the two visits show different overall structure: Visit 1 is consistent with a flat line, while Visit 2 requires a step offset between NRS1 and NRS2. After correcting for that offset, the authors compare the spectra to PICASO forward models over a grid of metallicity and opaque pressure. They conclude that atmospheres below 100x solar metallicity at an opaque pressure of 10^-3 bar are ruled out at >=3 sigma in all visits and reductions, with stronger visit- and reduction-dependent limits reaching 350–470x solar for Visit 1 and 100–130x solar for Visit 2.

Significance. If the central claim holds, this is a useful addition to the growing JWST sample of super-Earth atmospheric constraints, and it strengthens the COMPASS program's statistical approach. The paper's strengths include the use of two independent reduction pipelines, the public release of data products on Zenodo, the explicit discussion of visit-to-visit and reduction-to-reduction differences, and the framing of a conservative lower metallicity limit rather than a claimed detection. The conclusion that TOI-776b likely has a very thin, very cloudy, or highly metal-rich atmosphere is credible and informative for future population-level interpretations.

major comments (3)
  1. [Abstract and Section 6] The abstract reverses the visit-specific metallicity limits. The abstract states "Visit 1 ruling out ≲100× solar while the lower limits for Visit 2 extend beyond ∼350× solar," but Section 6 and Figure 6 report the opposite: at 10^-3 bar, Visit 1 excludes 350× solar (ExoTiC-JEDI) and 470× solar (Eureka!) while Visit 2 excludes only 100× solar (ExoTiC-JEDI) and 130× solar (Eureka!). Since the visit comparison is a key result and the conservative 100× solar floor is the headline, the abstract must be corrected to match the body of the paper.
  2. [Section 5.2, Table 3, Figure 6] The Visit 2 NRS1/NRS2 offset is fitted to the binned transmission spectrum in Section 5.1 and then treated as a fixed correction when computing chi-square/N and sigma for the PICASO models. The offset uncertainties (7.2 ppm for ExoTiC-JEDI, 6.2 ppm for Eureka!) are comparable to the 5–7 ppm differences between adjacent high-metallicity models quoted in Section 6, yet the significance contours in Figure 6 do not propagate this uncertainty or test whether the offset is wavelength-dependent or time-varying. Because the weakest case (ExoTiC-JEDI Visit 2) places the 3-sigma boundary at exactly 100× solar, the headline claim rests on the stability of this single-step correction. Please propagate the offset uncertainty into the model comparison, or demonstrate that a wavelength-dependent or time-varying offset moves the 10^-3 bar exclusion boundary by less than the metallicity grid spacing.
  3. [Section 5.1, Table 3] For Visit 2, the step-offset model and the five-parameter Gaussian-in-NRS1 model have Delta lnZ <= 1 for both reductions, so the step function is not statistically preferred over a narrow spectral feature. The paper argues that the Gaussian is not consistent between visits or reductions, but that does not rule out the possibility that the step offset is partially astrophysical in origin, especially given that the Gaussian central wavelength (3.43–3.45 um) lies in the methane band. If the step subtraction removes a real spectral feature, the flatness of the corrected data would be artificially enhanced and the metallicity exclusion contours biased. Please quantify the amplitude and width of the best-fit Gaussian and re-run the physical model comparison treating the offset as a free parameter (or allowing a wavelength-dependent offset) to verify that the 100× solar exclusion at 10^-3 bar is not an artifact of the chosen step correction.
minor comments (5)
  1. [Section 5.2] The term "reduced-χ2" is an unusual construction; consider using "reduced χ²" or simply "χ²/N" throughout for consistency with standard terminology.
  2. [Table 4] Table 4 reports chi-square/N and sigma values at 1 bar opaque pressure, while the headline claim concerns 10^-3 bar. Since the 100× solar row for Visit 2 ExoTiC-JEDI shows sigma = 2.6 at 1 bar, a footnote clarifying that the table is for 1 bar only would prevent readers from interpreting these entries as contradicting the abstract.
  3. [Figure 6] In the bottom panel of Figure 6, the four 3-sigma contours are hard to distinguish because of small labels and overlapping line styles; direct labels on each contour would improve readability.
  4. [Section 3.1] The sentence describing removal of 15 integrations around the HGA move would benefit from clarifying whether this removal was performed before or after the iterative 4-sigma outlier rejection, and whether the alternative of retaining those integrations was tested.
  5. [Section 1, references] The citation "May & MacDonald et al. 2023" is inconsistent with the author-list style used elsewhere; it should be "May, MacDonald, et al. 2023" (or similar) to match the other multi-author citations.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: metallicity exclusions come from comparing TOI-776b data to pre-computed PICASO forward models, with no atmospheric parameter fitted to the target data.

full rationale

The central claim (Section 6: ruling out atmospheres less than 100x solar metallicity at 10^-3 bar) is produced by comparing each reduction's transmission spectrum to a pre-computed grid of PICASO chemical-equilibrium forward models over metallicity and opaque pressure; none of the atmospheric model parameters are fitted to the TOI-776b data. The only fitted inputs relevant to the physical-model step are standard light-curve/systematics parameters and the Visit 2 NRS1/NRS2 detector offset (Section 5.1), which is used as a nuisance correction and does not by construction determine metallicity. The offset-correction approach cites Moran & Stevenson et al. (2023), a co-authored prior paper, but the present paper independently fits the offset with two pipelines and obtains consistent values, so the self-citation is not load-bearing. Potential limitations, including the unpropagated offset uncertainty, possible wavelength dependence of the offset, and the marginal 3-sigma boundary for Visit 2 ExoTiC-JEDI, are statistical robustness concerns rather than circular reasoning. No equation, fitted parameter, or definition in the paper reduces the metallicity exclusion to its own inputs.

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

No new particles or physical mechanisms are introduced. All of the paper's exclusion contours are conditional on the assumed thermal structure, chemistry, cloud parameterization, and the step-offset correction. The model grid variables are hypothesis labels rather than fitted constants, but they are nevertheless chosen by hand and control the quoted limits.

free parameters (6)
  • NRS1/NRS2 step offset (Visit 2) = 60-70 ppm depending on reduction (ExoTiC-JEDI: 70.7±7.2, Eureka!: 60.2±6.2)
    Fit to the Visit 2 transmission spectrum and applied as a correction before computing model significance. Its uncertainty is not propagated.
  • Per-point error scaling or jitter = Not stated explicitly; Eureka! fits an additive per-point error term, ExoTiC-JEDI rescales errors with beta.
    These scaling terms affect the reported per-point uncertainties and therefore the sigma levels of the model exclusions.
  • Baseline intercept in non-physical fits = Approximately 915-944 ppm depending on visit and reduction
    Free parameter in the flat, offset, and slope model fits; not central to the physical claim but sets the normalization of the transmission spectrum.
  • Metallicity grid = 1 to 1000x solar in 20 logarithmic steps
    Chosen grid over which PICASO models are computed. The reported lower limits are the minimum grid values reaching 3 sigma, so grid spacing sets the resolution of the constraint.
  • Opaque pressure grid = 1 to 1e-4 bar (with 1e-3 bar emphasized)
    Chosen cloud-top or surface pressure grid. The headline limit is quoted at 1e-3 bar; limits at other pressures differ.
  • C/O ratio = 0.55 (1x solar)
    Fixed for all models. Changing C/O would alter methane and CO2 feature sizes and could shift the metallicity limits.
assumptions (6)
  • domain assumption Guillot (2010) analytic T-P profiles are representative for TOI-776b at Teq=514 K.
    Used to generate all atmospheric models; a different thermal structure would change scale heights and feature amplitudes.
  • domain assumption Chemical equilibrium (photochem) with Asplund solar abundances describes the atmospheric composition.
    No photochemistry or kinetic quenching is included; this determines which molecules are present and their abundances.
  • domain assumption A wavelength-independent opaque deck with tau=10 at a chosen pressure captures possible clouds.
    The cloud treatment is agnostic rather than microphysical, and any wavelength-dependent cloud opacity could change the exclusion contours.
  • domain assumption Stellar and orbital parameters from Luque et al. (2021) are accurate enough to fix P, e, omega, and stellar properties.
    These fixed inputs set the scale of the transmission spectrum and the limb darkening coefficients.
  • ad hoc to paper The Visit 2 NRS1/NRS2 offset is purely instrumental and can be removed with a step function.
    This is the key correction enabling the physical interpretation; there is no independent measurement of the offset's cause or wavelength dependence.
  • domain assumption Limb darkening coefficients from model atmospheres (Phoenix, MPS-ATLAS) are correct and fixed.
    The coefficients are taken from stellar models rather than fit freely; incorrect limb darkening would bias transit depths.

how reviews work

0 comments
Cite this review

Pith. "Pith review of JWST COMPASS: NIRSpec/G395H Transmission Observations of the Super-Earth TOI-776b." pith.science (2026). https://pith.science/paper/FY3ZTTZQ

@misc{pith2026250114596,
  author       = {Pith},
  title        = {Pith review of: JWST COMPASS: NIRSpec/G395H Transmission Observations of the Super-Earth TOI-776b},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FY3ZTTZQ}},
  note         = {Machine review of arXiv:2501.14596}
}
abstract

We present two transit observations of the $\sim$520K, 1.85R$_\oplus$, 4.0M$_\oplus$ super-Earth TOI-776b with JWST NIRSpec/G395H, resulting in a 2.8-5.2$\mu$m transmission spectrum. Producing reductions using the ExoTiC-JEDI and Eureka! pipelines, we obtain a median transit depth precision of 34ppm for both visits and both reductions in spectroscopic channels 30 pixels wide ($\sim$0.02$\mu$m). We find that our independent reductions produce consistent transmission spectra, however, each visit shows differing overall structure. For both reductions, a flat line is preferred for Visit 1 while a flat line with an offset between the NRS1 and NRS2 detectors is preferred for Visit 2; however, we are able to correct for this offset during our modeling analysis following methods outlined in previous literature. Using picaso forward models, we can rule out metallicities up to at least 100$\times$ solar with an opaque pressure of 10$^{-3}$ bar to $\geq$3$\sigma$ in all cases, however, the exact lower limit varies between the visits, with Visit 1 ruling out $\lesssim$100$\times$ solar while the lower limits for Visit 2 extend beyond $\sim$350$\times$ solar. Our results add to the growing list of super-Earth atmospheric constraints by JWST, which provide critical insight into the diversity and challenges of characterizing terrestrial planets.

Figures

Figures reproduced from arXiv: 2501.14596 by the authors.

Figure 1
Figure 1. The ExoTiC-JEDI and Eureka! white light curves for each detector and visit, with best-fit models and the associated residuals. The alternate colors demonstrate binned light curves and residuals, which are plotted for reference. Histograms of the residuals are shown in the rightmost column. model and astrophysical model, we fit for an additional per-point error term that is added in quadrature to the measured errors.… view at source ↗
Figure 2
Figure 2. Top: Transmission spectra produced by the ExoTiC-JEDI (left) and Eureka! (right) reductions, with the difference between the two visits shown by the solid line in the lower panel. Across both pipelines, there is a noticeable difference in the morphology between the two visits, particularly due to the transmission spectra of NRS1 in Visit 2 being offset relative to NRS2. Bottom: Transmission spectra from Visit 1 (upp… view at source ↗
Figure 3
Figure 3. Transit depth precisions achieved by the ExoTiC-JEDI (pink) and Eureka! (blue) reductions com￾pared to predicted values from PandExo simulations for the observation set-up. As seen in other low group number stud￾ies (e.g., Lustig-Yaeger & Fu et al. 2023; Moran & Stevenson et al. 2023; Alderson et al. 2024; Wallack et al. 2024) the ob￾servations do not match the precision expected by PandExo. They are on average 1.3×… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Statistical, non-physical model fits to the data for Visit 1 (top row) and Visit 2 (bottom) for the ExoTiC-JEDI (left column) and Eureka! (right column) data reductions. Here we show the three highest-likelihood models between the two reductions. Data is shown as grey …
Figure 5
Figure 5. Figure 5: Forward model fits to the ExoTiC-JEDI (top, pinks) and Eureka! (bottom, blues) transmission spectra for Visits 1 (left) and 2 (right), accounting for the offset in Visit 2 (see Section 5.1). Note the differing y-axis limits between visits due to differing baselines (se…
Figure 6
Figure 6. Figure 6: Allowed parameter space in terms of opaque pressure level (either a cloud top or surface pressure, bar) versus log metallicity for the ExoTiC-JEDI (top, pinks) and Eureka! (middle, blues) reductions for Visits 1 (left) and 2 (right). In all cases, we are able to rule o…
Figure 7
Figure 7. Figure 7: 2D light curves for ExoTiC-JEDI and Eureka! for Visit 1 and Visit 2. Columns show the data (left), models (middle), and residuals (right) at R ∼ 200, the resolution plotted in [PITH_FULL_IMAGE:figures/full_fig_p017_7.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

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

  1. A parameterised approach to disequilibrium retrievals in the JWST era: Application to NIRCam observations of HD 189733b

    astro-ph.EP 2026-07 conditional novelty 5.0 of 10

    A quench-pressure parameterisation with two free parameters recovers unbiased C/O and [M/H] from synthetic JWST spectra with vertical mixing, and tentatively detects quenching and photochemical H2S depletion in HD 189...

  2. JWST COMPASS: A NIRSpec G395H Transmission Spectrum of the Super-Earth GJ 357 b

    astro-ph.EP 2025-07 conditional novelty 5.0 of 10

    The first NIRSpec G395H transmission spectrum of GJ 357 b is featureless, ruling out low mean molecular weight atmospheres at 3-sigma and pointing to a bare rock or a high molecular weight secondary atmosphere.

Reference graph

Works this paper leans on

64 extracted references · 3 canonical work pages · cited by 2 Pith papers

  1. [1]

    K., Gao, P., Adams Redai, J., et al

    Alam, M. K., Gao, P., Adams Redai, J., et al. 2024, arXiv e-prints, arXiv:2411.03154, doi: 10.48550/arXiv.2411.03154

  2. [2]

    2022a, Exo-TiC/ExoTiC-JEDI: v0.1-beta-release, v0.1, Zenodo, Zenodo, doi: 10.5281/zenodo.7185855

    Alderson, L., Grant, D., & Wakeford, H. 2022a, Exo-TiC/ExoTiC-JEDI: v0.1-beta-release, v0.1, Zenodo, Zenodo, doi: 10.5281/zenodo.7185855

  3. [3]

    R., MacDonald, R

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

  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

  5. [5]

    E., Wakeford, H

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

  6. [6]

    J., & Scott, P

    Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, ARA&A, 47, 481, doi: 10.1146/annurev.astro.46.060407.145222 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...

  7. [7]

    K., Gressier, A., et al

    Banerjee, A., Barstow, J. K., Gressier, A., et al. 2024, ApJL, 975, L11, doi: 10.3847/2041-8213/ad73d0

  8. [8]

    2022, Resampled Opacity Database for PICASO, 2.0, Zenodo, doi: 10.5281/zenodo.6928501

    Batalha, N., Freedman, R., Gharib-Nezhad, E., & Lupu, R. 2022, Resampled Opacity Database for PICASO, 2.0, Zenodo, doi: 10.5281/zenodo.6928501

Show all 64 references
  1. [9]

    2018, ApJL, 856, L34, doi: 10.3847/2041-8213/aab896

    Stevenson, K. 2018, ApJL, 856, L34, doi: 10.3847/2041-8213/aab896

  2. [10]

    E., Marley, M

    Batalha, N. E., Marley, M. S., Lewis, N. K., & Fortney, J. J. 2019, ApJ, 878, 70, doi: 10.3847/1538-4357/ab1b51

  3. [11]

    E., Wolfgang, A., Teske, J., et al

    Batalha, N. E., Wolfgang, A., Teske, J., et al. 2023, AJ, 165, 14, doi: 10.3847/1538-3881/ac9f45

  4. [12]

    E., Mandell, A., Pontoppidan, K., et al

    Batalha, N. E., Mandell, A., Pontoppidan, K., et al. 2017, PASP, 129, 064501, doi: 10.1088/1538-3873/aa65b0

  5. [13]

    2022, The Journal of Open Source Software, 7, 4503, doi: 10.21105/joss.04503

    Bell, T., Ahrer, E.-M., Brande, J., et al. 2022, The Journal of Open Source Software, 7, 4503, doi: 10.21105/joss.04503

  6. [14]

    2017, ApJ, 850, 93, doi: 10.3847/1538-4357/aa965a

    Brugger, B., Mousis, O., Deleuil, M., & Deschamps, F. 2017, ApJ, 850, 93, doi: 10.3847/1538-4357/aa965a

  7. [15]

    2016, Statistics and Computing, 26, 383, doi: 10.1007/s11222-014-9512-y —

    Buchner, J. 2016, Statistics and Computing, 26, 383, doi: 10.1007/s11222-014-9512-y —. 2019, PASP, 131, 108005, doi: 10.1088/1538-3873/aae7fc —. 2021, The Journal of Open Source Software, 6, 3001, doi: 10.21105/joss.03001

  8. [16]

    2022, JWST Calibration Pipeline, 1.8.2, Zenodo, Zenodo, doi: 10.5281/zenodo.7229890

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2022, JWST Calibration Pipeline, 1.8.2, Zenodo, Zenodo, doi: 10.5281/zenodo.7229890

  9. [17]

    J., et al

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

  10. [18]

    A., Droettboom, M., Hunter, J., et al

    Caswell, T. A., Droettboom, M., Hunter, J., et al. 2019, matplotlib/matplotlib v3.1.0, v3.1.0, Zenodo, doi: 10.5281/zenodo.2893252

  11. [19]

    2000, A&A, 363, 1081

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

  12. [20]

    H., Meadows, V

    Currie, M. H., Meadows, V. S., & Rasmussen, K. C. 2023, PSJ, 4, 83, doi: 10.3847/PSJ/accf86

  13. [21]

    2024, ApJL, 968, L22, doi: 10.3847/2041-8213/ad5204

    Damiano, M., Bello-Arufe, A., Yang, J., & Hu, R. 2024, ApJL, 968, L22, doi: 10.3847/2041-8213/ad5204

  14. [22]

    2015, A&A, 577, A83, doi: 10.1051/0004-6361/201424915

    Dorn, C., Khan, A., Heng, K., et al. 2015, A&A, 577, A83, doi: 10.1051/0004-6361/201424915

  15. [23]

    D., & Charbonneau, D

    Dressing, C. D., & Charbonneau, D. 2015, ApJ, 807, 45, doi: 10.1088/0004-637X/807/1/45

  16. [24]

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

    Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306

  17. [25]

    Y., Bonfanti, A., et al

    Fridlund, M., Georgieva, I. Y., Bonfanti, A., et al. 2024, A&A, 684, A12, doi: 10.1051/0004-6361/202243838

  18. [26]

    P., Lee, G

    Gao, P., Thorngren, D. P., Lee, G. K. H., et al. 2020, Nature Astronomy, 4, 951, doi: 10.1038/s41550-020-1114-3

  19. [27]

    E., & Sari, R

    Ginzburg, S., Schlichting, H. E., & Sari, R. 2018, MNRAS, 476, 759, doi: 10.1093/mnras/sty290

  20. [28]

    Weber, B. W. 2022, Cantera: An Object-oriented Software Toolkit for Chemical Kinetics, Thermodynamics, and Transport Processes, 2.6.0, Zenodo, doi: 10.5281/zenodo.6387882 16

  21. [29]

    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

  22. [30]

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

  23. [31]

    H., et al

    Gressier, A., Espinoza, N., Allen, N. H., et al. 2024, ApJL, 975, L10, doi: 10.3847/2041-8213/ad73d1

  24. [32]

    2010, A&A, 520, A27, doi: 10.1051/0004-6361/200913396

    Guillot, T. 2010, A&A, 520, A27, doi: 10.1051/0004-6361/200913396

  25. [33]

    2012, ApJ, 754, 60, doi: 10.1088/0004-637X/754/1/60

    Heng, K., & Kopparla, P. 2012, ApJ, 754, 60, doi: 10.1088/0004-637X/754/1/60

  26. [34]

    2017, Journal of Open Research Software, 5

    Hoyer, S., & Hamman, J. 2017, Journal of Open Research Software, 5

  27. [35]

    2013, A&A, 553, A6, doi: 10.1051/0004-6361/201219058

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

  28. [36]

    P., Dannert, F., & LIFE Collaboration

    Kammerer, J., Quanz, S. P., Dannert, F., & LIFE Collaboration. 2022, A&A, 668, A52, doi: 10.1051/0004-6361/202243846

  29. [37]

    B., Fu, G., et al

    Kirk, J., Stevenson, K. B., Fu, G., et al. 2024, AJ, 167, 90, doi: 10.3847/1538-3881/ad19df

  30. [38]

    2022, arXiv preprint arXiv:2206.06641

    Kostogryz, N., Witzke, V., Shapiro, A., et al. 2022, arXiv preprint arXiv:2206.06641

  31. [39]

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

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

  32. [40]

    2025, Treatise on Geochemistry, 7, 51, doi: 10.1016/B978-0-323-99762-1.00122-4

    Lichtenberg, T., & Miguel, Y. 2025, Treatise on Geochemistry, 7, 51, doi: 10.1016/B978-0-323-99762-1.00122-4

  33. [41]

    Lodders, K., Palme, H., & Gail, H. P. 2009, Landolt B&ouml;rnstein, 4B, 712, doi: 10.1007/978-3-540-88055-4 34

  34. [42]

    M., Molaverdikhani, K., et al

    Luque, R., Serrano, L. M., Molaverdikhani, K., et al. 2021, A&A, 645, A41, doi: 10.1051/0004-6361/202039455

  35. [43]

    M., et al

    Lustig-Yaeger, J., Fu, G., May, E. M., et al. 2023, arXiv e-prints, arXiv:2301.04191, doi: 10.48550/arXiv.2301.04191

  36. [44]

    M., MacDonald, R

    May, E. M., MacDonald, R. J., Bennett, K. A., et al. 2023, arXiv e-prints, arXiv:2310.10711, doi: 10.48550/arXiv.2310.10711

  37. [45]

    2011, Python for high performance and scientific computing, 14, 1

    McKinney, W., et al. 2011, Python for high performance and scientific computing, 14, 1

  38. [46]

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

  39. [47]

    E., Stevenson, K

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

  40. [48]

    E., Fortney, J

    Mukherjee, S., Batalha, N. E., Fortney, J. J., & Marley, M. S. 2023, ApJ, 942, 71, doi: 10.3847/1538-4357/ac9f48

  41. [49]

    2006, NumPy: A guide to NumPy, USA: Trelgol Publishing

    Oliphant, T. 2006, NumPy: A guide to NumPy, USA: Trelgol Publishing. http://www.numpy.org/

  42. [50]

    E., & Schlichting, H

    Owen, J. E., & Schlichting, H. E. 2023, arXiv e-prints, arXiv:2308.00020, doi: 10.48550/arXiv.2308.00020

  43. [51]

    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

  44. [52]

    2024, arXiv e-prints, arXiv:2404.02932, doi: 10.48550/arXiv.2404.02932

    Redfield, S., Batalha, N., Benneke, B., et al. 2024, arXiv e-prints, arXiv:2404.02932, doi: 10.48550/arXiv.2404.02932

  45. [53]

    G., & Owen, J

    Rogers, J. G., & Owen, J. E. 2021a, MNRAS, 503, 1526, doi: 10.1093/mnras/stab529 —. 2021b, MNRAS, 503, 1526, doi: 10.1093/mnras/stab529

  46. [54]

    R., et al

    Scarsdale, N., Wogan, N., Wakeford, H. R., et al. 2024, arXiv e-prints, arXiv:2409.07552, doi: 10.48550/arXiv.2409.07552

  47. [55]

    W., et al

    Schlawin, E., Leisenring, J., McElwain, M. W., et al. 2021, AJ, 161, 115, doi: 10.3847/1538-3881/abd8d4

  48. [56]

    L., St¨ urmer, J., et al

    Seifahrt, A., Bean, J. L., St¨ urmer, J., et al. 2020, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 11447, Ground-based and Airborne Instrumentation for Astronomy VIII, ed. C. J

  49. [57]

    Evans, J. J. Bryant, & K. Motohara, 114471F, doi: 10.1117/12.2561564

  50. [58]

    X., Wolfgang, A., et al

    Teske, J., Wang, S. X., Wolfgang, A., et al. 2021, ApJS, 256, 33, doi: 10.3847/1538-4365/ac0f0a

  51. [59]

    2019, scipy/scipy: SciPy 1.2.1, v1.2.1, Zenodo, doi: 10.5281/zenodo.2560881

    Virtanen, P., Gommers, R., Burovski, E., et al. 2019, scipy/scipy: SciPy 1.2.1, v1.2.1, Zenodo, doi: 10.5281/zenodo.2560881

  52. [60]

    L., Batalha, N

    Wallack, N. L., Batalha, N. E., Alderson, L., et al. 2024, AJ, 168, 77, doi: 10.3847/1538-3881/ad3917

  53. [61]

    F., Catling, D

    Wogan, N. F., Catling, D. C., Zahnle, K. J., & Lupu, R. 2023, PSJ, 4, 169, doi: 10.3847/PSJ/aced83

  54. [62]

    J., & Catling, D

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

  55. [63]

    Zeng, L., & Jacobsen, S. B. 2016, ApJ, 829, 18, doi: 10.3847/0004-637X/829/1/18

  56. [64]

    Zhang, H., Wang, J., & Plummer, M. K. 2024, AJ, 167, 37, doi: 10.3847/1538-3881/ad109e 17 APPENDIX 3.0 3.5 4.0 4.5 5.0ExoTiC-JEDI Visit 1 3 2 1 0 1 2 3.0 3.5 4.0 4.5 5.0ExoTiC-JEDI Visit 2 3 2 1 0 1 2 3 2 1 0 1 2 0.9990 0.9995 1.0000 1.0005 1.0010 Relative Flux 0.2 0.1 0.0 0.1...

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.