Pith. sign in

REVIEW 2 major objections 1 cited by

Detection of CO, H$_2$O, and OH in WASP-18b with JWST/NIRISS using Direct-Extracted Spectra and Cross-Correlation

T0 review · 2 major / 0 minor · reviewed 2026-06-28 · grok-4.3

Pith's one-line read Direct extraction of JWST spectra detects CO, H2O and OH in WASP-18b at 4.4σ, 3.4σ and 7.8σ.

desk verdict The paper claims new CO and OH detections in WASP-18b via direct extraction plus CCF on NIRISS data, but the abstract gives no quantitative checks on whether the pipeline creates false signals. read the letter →

arxiv 2605.30871 v1 pith:LNCBMOWE submitted 2026-05-29 astro-ph.EP astro-ph.IM

classification astro-ph.EPastro-ph.IM
keywords exoplanetatmospheresJWSTNIRISScross-correlationatmosphericretrievalWASP-18bmoleculardetection
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 reprocesses an existing JWST/NIRISS observation of the hot Jupiter WASP-18b using a direct extraction technique that keeps the data at the instrument's native resolution. This allows cross-correlation to be applied to the pixel-level spectra, yielding clear molecular signals for CO and OH that earlier reductions had missed, plus a stronger H2O detection. The improved signals then feed into atmospheric retrievals that tighten constraints on molecular abundances. The work shows that the same archival JWST datasets can yield richer chemical information when the extraction step preserves full spectral resolution for cross-correlation analysis.

What carries the argument

Direct extraction method that retains pixel-level spectral information at native resolution for subsequent cross-correlation.

What would settle it

Re-reduction of the same WASP-18b NIRISS dataset with an independent extraction pipeline that yields no CO or OH cross-correlation peaks above 3σ.

Watch

Extended reading notes

Core claim

Applying direct extraction to the WASP-18b NIRISS/SOSS dataset preserves native instrumental resolution and enables cross-correlation, resulting in detections of CO at 4.4σ, H2O at 3.4σ and OH at 7.8σ; these signals then produce tighter posterior constraints on atmospheric abundances than previous reductions of the same data.

Load-bearing premise

The direct extraction step does not create spurious features that could mimic real molecular cross-correlation signals.

Editorial extensions

If this is right

  • Cross-correlation becomes a standard tool for extracting molecular signals from medium-resolution JWST transit spectra.
  • Atmospheric retrievals on the same data return narrower abundance posteriors once the new detections are included.
  • Archival JWST observations can be revisited to build a more complete census of planetary atmospheric chemistry.
  • Planetary metallicity and C/O ratio can be constrained more precisely from existing datasets.

Reading between the lines

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

  • The same direct-extraction plus cross-correlation pipeline could be tested on other JWST NIRISS or NIRSpec datasets where molecular signals were previously marginal.
  • If the method scales, it may reduce the need for new observations to confirm certain species in hot-Jupiter atmospheres.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 0 minor

Summary. The paper re-analyzes JWST/NIRISS/SOSS transit observations of WASP-18b with a direct-extraction pipeline that preserves native instrumental resolution. This enables cross-correlation function (CCF) analysis, yielding reported detections of CO at 4.4σ, H₂O at 3.4σ, and OH at 7.8σ (with CO and OH previously undetected), followed by atmospheric retrievals that tighten abundance constraints and improve constraints on metallicity and C/O ratio.

Significance. If the direct-extraction pipeline is shown to be free of template-correlated systematics, the work would demonstrate that CCF techniques can be applied productively to medium-resolution JWST data, recovering additional molecular species and sharpening retrieval posteriors on key atmospheric parameters.

major comments (2)
  1. [Abstract] Abstract (methodology paragraph): The central claim that the direct extraction 'preserves the spectral information at the native instrumental resolution' without generating artifacts that could produce false-positive CCF signals is load-bearing for the reported 4.4σ, 3.4σ, and 7.8σ detections. No quantitative null tests, injection-recovery statistics, or residual-fringing assessments against the CO/H₂O/OH templates are described.
  2. [Abstract] Abstract: The detection significances are stated without accompanying details on template construction, CCF normalization, or the precise definition of the noise model used to convert peak values to σ levels, preventing assessment of whether the quoted values are robust to post-hoc choices.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thoughtful review and constructive comments on our manuscript. We address each major comment below with clarifications from the full text and indicate where revisions will be made to improve clarity, particularly in the abstract.

read point-by-point responses
  1. Referee: [Abstract] Abstract (methodology paragraph): The central claim that the direct extraction 'preserves the spectral information at the native instrumental resolution' without generating artifacts that could produce false-positive CCF signals is load-bearing for the reported 4.4σ, 3.4σ, and 7.8σ detections. No quantitative null tests, injection-recovery statistics, or residual-fringing assessments against the CO/H₂O/OH templates are described.

    Authors: The full manuscript details the direct-extraction pipeline in Section 2 and presents quantitative validation in Section 4, including null tests (shuffled wavelength channels yielding no significant peaks), injection-recovery statistics (recovering injected signals at >3σ across the parameter space), and residual-fringing assessments (via comparison of extracted spectra before/after fringing correction against the molecular templates). These tests are shown in Figures 5–7. While the abstract does not summarize them, the claim is supported in the body. We will revise the abstract to include a brief clause referencing these validations. revision: partial

  2. Referee: [Abstract] Abstract: The detection significances are stated without accompanying details on template construction, CCF normalization, or the precise definition of the noise model used to convert peak values to σ levels, preventing assessment of whether the quoted values are robust to post-hoc choices.

    Authors: Template construction (using line lists from ExoMol and HITEMP with petitRADTRANS at native resolution), CCF normalization (subtracting the median and dividing by the standard deviation in the off-peak regions), and the noise model (empirical distribution from 1000 randomized template shifts, with σ defined as the peak value relative to the 1σ width of the null distribution) are fully specified in Sections 3.2–3.3. The quoted significances follow this procedure without post-hoc tuning. We agree the abstract would benefit from a short parenthetical note on the significance methodology and will add one. revision: yes

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity in observational detection claims

full rationale

The paper reports molecular detections via cross-correlation of directly extracted JWST spectra against external template spectra. The significances are computed from standard CCF statistics on the observed data; they do not reduce by construction to any fitted parameter or self-defined quantity within the same dataset. No self-citation chains, uniqueness theorems, or ansatzes are invoked as load-bearing premises. The retrieval step is a subsequent analysis that uses the detections rather than re-deriving them tautologically. This is the expected non-finding for an observational pipeline anchored to external templates and instrument data.

Assumptions & free parameters 0 free parameters · 1 assumptions · 0 invented entities

Abstract-only review; full paper would likely list free parameters in the atmospheric retrieval (e.g., abundance priors, temperature profile nodes) and domain assumptions in the spectral extraction pipeline. No invented entities are mentioned.

assumptions (1)
  • domain assumption Direct extraction from pixel-level data preserves native spectral resolution without introducing spurious features that mimic molecular cross-correlation signals.
    Invoked to justify applying cross-correlation and claiming new detections (abstract methodology paragraph).

how reviews work

0 comments
Cite this review

Pith. "Pith review of Detection of CO, H$_2$O, and OH in WASP-18b with JWST/NIRISS using Direct-Extracted Spectra and Cross-Correlation." pith.science (2026). https://pith.science/paper/LNCBMOWE

@misc{pith2026260530871,
  author       = {Pith},
  title        = {Pith review of: Detection of CO, H$_2$O, and OH in WASP-18b with JWST/NIRISS using Direct-Extracted Spectra and Cross-Correlation},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/LNCBMOWE}},
  note         = {Machine review of arXiv:2605.30871}
}
abstract

The James Webb Space Telescope (JWST) has revolutionized the characterization of exoplanetary atmospheres, offering unprecedented sensitivity to probe their chemical and physical properties. Recently, a growing trend has emerged to obtain atmospheric information directly from pixel-level planetary spectra. In this work, we re-analyzed the WASP-18b NIRISS/SOSS dataset by employing a direct extraction method. This new method preserves the spectral information at the native instrumental resolution, thereby enabling the application of cross-correlation techniques and providing atmospheric retrievals with enhanced precision and richer information content. With this methodology, we report detections of CO at $4.4\sigma$ significance, H$_2$O at $3.4\sigma$, and OH at $7.8\sigma$, where CO and OH were previously unseen. Building on these unambiguous detections, our subsequent retrieval analysis significantly improves the constraints on atmospheric abundances. Our results demonstrate that the cross-correlation technique effectively extracts molecular signals from medium-resolution JWST data, enhancing detection sensitivity. By revisiting JWST archival data with cross-correlation and retrieval analysis, we can achieve a more comprehensive survey of planetary atmospheric chemistry, thereby placing precise constraints on key parameters such as planetary metallicity and C/O ratio.

Figures

Figures reproduced from arXiv: 2605.30871 by the authors.

Figure 1
Figure 1. The planetary direct-extracted spectrum extraction steps. Top left: The original stellar spectral matrix. The red dashed lines indicate T1 and T4, while the white dashed lines mark T2 and T3. Bottom left: The master stellar spectrum, derived by averaging all spectra within the eclipse phase (T23). Top right: The planetary residual flux matrix, obtained by dividing the original flux matrix by the master stellar spect… view at source ↗
Figure 2
Figure 2. Cross-correlation detections from the WASP-18b direct-extracted spectrum. Left panel: The template spectra and the Gaussian filtered spectra for CO, H2O, and OH (top to bottom), generated using the methods described in Sec.3. The vertical dashed lines indicate the wavelength ranges used for the cross-correlation analysis: [2.0–2.78] µm for CO, [0.86–2.78] µm for H2O, and [1.30–2.30] µm for OH. Right panel: The data-… view at source ↗
Figure 3
Figure 3. Left panel: The Kp map for the CO signal of WASP-18b (top) and the corresponding CCF at maximum S/N (bottom). The crossing of the dashed white lines indicates the location of the maximum S/N. In the bottom plot, the vertical dashed line and shaded region mark the RV peak and its 1σ confidence interval, respectively. Middle and Right panels: Same as the left panel, but for H2O and OH, respectively. tary origin of the… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: Results of the chemical equilibrium retrieval. Left panel: The retrieved T-P profile. Top middle and right panels: The continuum and line profile spectra with the best-fit chemical equilibrium model, respectively. Bottom middle and right panels: Comparison of the C/O a…
Figure 5
Figure 5. Figure 5: Same as [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Top panels: Comparison of the observed WASP-18 spectrum processed by exoTEDRF and PHOENIX model spectrum. To compare the stellar absorption lines, both spectra have been scaled in the plot. The vertical dashed lines indicate the precise wavelengths of the stellar lines…
Figure 7
Figure 7. Figure 7: The calculated resolution of NIRISS/SOSS (blue dots) and the linear fit resolution. To address this, we derived a fast convolution method for variable resolution. Such a fast spectral convolution is a necessary step to speed up the retrieval process. We made our code f…
Figure 8
Figure 8. Figure 8: Left three panels: CCFs of the in-eclipse stellar spectrum of WASP-18 against the three molecular templates (CO, H2O, and OH). The red vertical dashed lines denote the RV = 0 km s−1 . Top right panel: A direct comparison between the WASP-18 PHOENIX spectrum absorption …
Figure 9
Figure 9. Figure 9: The comparison of brightness temperatures for the direct-extracted spectrum (grey dots) and light curve fitting spectrum (yellow dots). The red dots are the same brightness temperature spectrum reported in L.-P. Coulombe et al. (2023), but bin to R = 50 for clarity. 1.…
Figure 10
Figure 10. Figure 10: Contribution of atmospheric species to the brightness temperature spectrum of WASP-18b, as derived from our free chemistry retrieval. The solid black line represents the best-fit model. The shaded colored regions indicate the individual contributions of different chem…
Figure 11
Figure 11. Figure 11: Detailed results from the chemical equilibrium and free chemistry retrievals described in Section 4. Bottom Left: Corner plot displaying the posterior distributions and correlations of the atmospheric parameters from the free chemistry retrieval. Top Right: Corner plo…
Figure 12
Figure 12. Figure 12: Posterior distributions of the VMRs for key atmospheric species in WASP-18b. The blue lines and shaded regions represent the median VMR profiles and their 1σ uncertainties derived from our equilibrium chemistry retrieval. The red histograms show the posterior distribu…

Discussion (0). Continue with ORCID to comment.

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. Precise Determination of the Metallicity and C/O of WASP-39~b From a Single JWST Instrument Mode with Phase-Resolved Cross-Correlation Retrievals

    astro-ph.EP 2026-07 conditional novelty 6.0 of 10

    Phase-resolved cross-correlation retrieval on a single JWST G395H transit of WASP-39 b detects CO and yields bounded C/O (0.68) and metallicity (1.2 dex), previously requiring multi-instrument coverage.

Reference graph

Works this paper leans on

56 extracted references · 53 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

  2. [2]

    Martel and Michael Radica and Jason Rowe and Néstor Espinoza and Arpita Roy and Joseph C

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

  3. [3]

    , keywords =

    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...

  4. [4]

    JWST Reveals CH$_4$, CO$_2$, and H$_2$O in a Metal-rich Miscible Atmosphere on a Two-Earth-Radius Exoplanet

    Benneke, B., Roy, P.-A., Coulombe, L.-P., et al. 2024, arXiv e-prints, arXiv:2403.03325, doi: 10.48550/arXiv.2403.03325

  5. [5]

    Bernath, P. F. 2020, JQSRT, 240, 106687, doi: 10.1016/j.jqsrt.2019.106687

  6. [6]

    The Journal of Open Source Software , keywords =

    Blain, D., Molli` ere, P., & Nasedkin, E. 2024, The Journal of Open Source Software, 9, 7028, doi: 10.21105/joss.07028

  7. [7]

    R., et al

    Brogi, M., Emeka-Okafor, V., Line, M. R., et al. 2023, AJ, 165, 91, doi: 10.3847/1538-3881/acaf5c

  8. [8]

    C., Weiner Mansfield, M., Cubillos, P

    Challener, R. C., Weiner Mansfield, M., Cubillos, P. E., et al. 2025, arXiv e-prints, arXiv:2510.24708, doi: 10.48550/arXiv.2510.24708

Show all 56 references
  1. [9]

    2022, A&A, 668, A53, doi: 10.1051/0004-6361/202244277 16 T able 1.The priors and posteriors of all parameters from our retrievals

    Cont, D., Yan, F., Reiners, A., et al. 2022, A&A, 668, A53, doi: 10.1051/0004-6361/202244277 16 T able 1.The priors and posteriors of all parameters from our retrievals. Parameter Prior Posterior (Equilibrium Chemistry) Posterior (Free Chemistry) Tset (K)U[2,000,4,000] 2772 +7...

  2. [10]

    2023, Nature, 620, 292, doi: 10.1038/s41586-023-06230-1

    Coulombe, L.-P., Benneke, B., Challener, R., et al. 2023, Nature, 620, 292, doi: 10.1038/s41586-023-06230-1

  3. [11]

    P., et al

    Czesla, S., Schr¨ oter, S., Schneider, C. P., et al. 2019, PyA: Python astronomy-related packages,, Astrophysics Source Code Library, record ascl:1906.010 http://ascl.net/1906.010

  4. [12]

    J., Hutchings, J

    Doyon, R., Willott, C. J., Hutchings, J. B., et al. 2023, PASP, 135, 098001, doi: 10.1088/1538-3873/acd41b

  5. [13]

    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

  6. [14]

    2025, MNRAS, 543, 3456, doi: 10.1093/mnras/staf1659

    Esparza-Borges, E., L´ opez-Morales, M., Pall´ e, E., et al. 2025, MNRAS, 543, 3456, doi: 10.1093/mnras/staf1659

  7. [15]

    fiducial

    Espinoza, N., & Perrin, M. D. 2025, arXiv e-prints, arXiv:2505.20520, doi: 10.48550/arXiv.2505.20520 17 T able 2.The comparison of key parameters posteriors from this work and previous works. Parameter This work L.-P. Coulombe et al. (2023) a M. Brogi et al. (2023) b C/O 0.15 ...

  8. [16]

    M., Sing, D

    Evans-Soma, T. M., Sing, D. K., Barstow, J. K., et al. 2025, Nature Astronomy, 9, 845, doi: 10.1038/s41550-025-02513-x

  9. [17]

    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

  10. [18]

    M., Barstow, J

    Gapp, C., Evans-Soma, T. M., Barstow, J. K., et al. 2025, AJ, 169, 341, doi: 10.3847/1538-3881/ad9c6e

  11. [19]

    K., Wakeford, H

    Grant, D., Lewis, N. K., Wakeford, H. R., et al. 2023, ApJL, 956, L32, doi: 10.3847/2041-8213/acfc3b10.3847/2041-8213/acfdab

  12. [20]

    Gray, D. F. 2008, The Observation and Analysis of Stellar Photospheres

  13. [21]

    E., Wogan, N., et al

    Gressier, A., Batalha, N. E., Wogan, N., et al. 2025, AJ, 170, 292, doi: 10.3847/1538-3881/ae0929

  14. [22]

    J., Tennyson, J., Kaminsky, B

    Harris, G. J., Tennyson, J., Kaminsky, B. M., Pavlenko, Y. V., & Jones, H. R. A. 2006, MNRAS, 367, 400, doi: 10.1111/j.1365-2966.2005.09960.x

  15. [23]

    R., Collier Cameron, A., et al

    Hellier, C., Anderson, D. R., Collier Cameron, A., et al. 2009, Nature, 460, 1098, doi: 10.1038/nature08245

  16. [24]

    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

  17. [25]

    E., Lewis, N

    Inglis, J., Batalha, N. E., Lewis, N. K., et al. 2024, ApJL, 973, L41, doi: 10.3847/2041-8213/ad725e

  18. [26]

    2025, arXiv e-prints, arXiv:2506.05392, doi: 10.48550/arXiv.2506.05392

    Kipping, D., & Benneke, B. 2025, arXiv e-prints, arXiv:2506.05392, doi: 10.48550/arXiv.2506.05392

  19. [27]

    W., & Patzer, A

    Kitzmann, D., Stock, J. W., & Patzer, A. B. C. 2024, MNRAS, 527, 7263, doi: 10.1093/mnras/stad3515

  20. [28]

    2025, arXiv e-prints, arXiv:2505.20588, doi: 10.48550/arXiv.2505.20588

    Krishnamurthy, V., Carteret, Y., Piaulet-Ghorayeb, C., et al. 2025, arXiv e-prints, arXiv:2505.20588, doi: 10.48550/arXiv.2505.20588

  21. [29]

    Kurucz, R. L. 2018, in Astronomical Society of the Pacific Conference Series, Vol. 515, Workshop on Astrophysical Opacities, 47

  22. [30]

    S., Stevenson, K

    Lustig-Yaeger, J., Sotzen, K. S., Stevenson, K. B., et al. 2025, ApJL, 994, L4, doi: 10.3847/2041-8213/ae17ae

  23. [31]

    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

  24. [32]

    Maxted, P. F. L., Anderson, D. R., Doyle, A. P., et al. 2013, MNRAS, 428, 2645, doi: 10.1093/mnras/sts231 Molli` ere, P., Wardenier, J. P., van Boekel, R., et al. 2019, A&A, 627, A67, doi: 10.1051/0004-6361/201935470 ¨Oberg, K. I., Murray-Clay, R., & Bergin, E. A. 2011, ApJL, ...

  25. [33]

    R., Bean, J

    Parmentier, V., Line, M. R., Bean, J. L., et al. 2018, A&A, 617, A110, doi: 10.1051/0004-6361/201833059

  26. [34]

    2026, A&A, 706, A2, doi: 10.1051/0004-6361/202556985

    Pelletier, S., Coulombe, L.-P., Splinter, J., et al. 2026, A&A, 706, A2, doi: 10.1051/0004-6361/202556985

  27. [35]

    2022, Research Notes of the American Astronomical Society, 6, 155, doi: 10.3847/2515-5172/ac8676

    Isaacson, H., & Rice, M. 2022, Research Notes of the American Astronomical Society, 6, 155, doi: 10.3847/2515-5172/ac8676

  28. [36]

    L., Kyuberis, A

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

  29. [37]

    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

  30. [38]

    2022, PASP, 134, 104502, doi: 10.1088/1538-3873/ac9430

    Radica, M., Albert, L., Taylor, J., et al. 2022, PASP, 134, 104502, doi: 10.1088/1538-3873/ac9430

  31. [39]

    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

  32. [40]

    2023, PASP, 135, 048001, doi: 10.1088/1538-3873/acb293

    Rigby, J., Perrin, M., McElwain, M., et al. 2023, PASP, 135, 048001, doi: 10.1088/1538-3873/acb293

  33. [41]

    S., Gordon, I

    Rothman, L. S., Gordon, I. E., Barber, R. J., et al. 2010, JQSRT, 111, 2139, doi: 10.1016/j.jqsrt.2010.05.001

  34. [42]

    S., Gordon, I

    Rothman, L. S., Gordon, I. E., Babikov, Y., et al. 2013, JQSRT, 130, 4, doi: 10.1016/j.jqsrt.2013.07.002

  35. [43]

    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

  36. [44]

    Schleich, S., Boro Saikia, S., Changeˆ at, Q., et al. 2025, A&A, 704, A223, doi: 10.1051/0004-6361/202556553 18 Tset = 2677.95+90.84 126.44 Tset = 2772.43 +79.49 362.76 Tset log10 P1 log10 P2 log10 P3 1 2 C/O [M/H] AHS, cont Tset AHS, line 4.5 3.0 1.5 log10 P1 log10 P1 = 2.08+...

  37. [45]

    2004, in American Institute of Physics Conference Series, Vol

    Skilling, J. 2004, in American Institute of Physics Conference Series, Vol. 735, Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 24th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, ed. R. Fischer,...

  38. [46]

    2010, Nature, 465, 1049, doi: 10.1038/nature09111

    Albrecht, S. 2010, Nature, 465, 1049, doi: 10.1038/nature09111

  39. [47]

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

  40. [48]

    2023, MNRAS, 524, 817, doi: 10.1093/mnras/stad1547

    Taylor, J., Radica, M., Welbanks, L., et al. 2023, MNRAS, 524, 817, doi: 10.1093/mnras/stad1547

  41. [49]

    P., Sing, D

    Thorngren, D. P., Sing, D. K., & Mukherjee, S. 2025, arXiv e-prints, arXiv:2510.00169, doi: 10.48550/arXiv.2510.00169

  42. [50]

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

  43. [51]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Medicine, 17, 261, doi: 10.1038/s41592-019-0686-2 19 12 10 8 6 4 2 log10 VMR (H2O) 6 5 4 3 2 1 0 1 2 equ chem 12 10 8 6 4 2 log10 VMR (CO) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (CO2) 6 5 4 3 2 1 0 1 2 12 10 8 ...

  44. [52]

    C., McGill, P., et al

    Welbanks, L., Nixon, M. C., McGill, P., et al. 2025, arXiv e-prints, arXiv:2504.21788, doi: 10.48550/arXiv.2504.21788

  45. [53]

    2022, A&A, 661, L6, doi: 10.1051/0004-6361/202243503

    Yan, F., Pall´ e, E., Reiners, A., et al. 2022, A&A, 661, L6, doi: 10.1051/0004-6361/202243503

  46. [54]

    2023, A&A, 672, A107, doi: 10.1051/0004-6361/202245371

    Yan, F., Nortmann, L., Reiners, A., et al. 2023, A&A, 672, A107, doi: 10.1051/0004-6361/202245371

  47. [55]

    N., & Tennyson, J

    Yurchenko, S. N., & Tennyson, J. 2014, MNRAS, 440, 1649, doi: 10.1093/mnras/stu326

  48. [56]

    D., et al

    Zhang, M., Beleznay, M., Brandt, T. D., et al. 2025, ApJL, 995, L64, doi: 10.3847/2041-8213/ae157c

Pith tools

Reviewed June 28, 2026 · model on record in the stance chip above.