pith. machine review for the scientific record. sign in

arxiv: 2604.05907 · v1 · submitted 2026-04-07 · 🌌 astro-ph.EP

Recognition: 2 theorem links

· Lean Theorem

The Transit Timing and Transmission Spectrum of Hot Jupiter WASP-43 b from a decade of Multi-band Transit Follow-up Observations

Napaporn A-thano , Supachai Awiphan , Eamonn Kerins , Akshay Priyadarshi , Iain McDonald , Ing-Guey Jiang , Yogesh C. Joshi , Fan Yang
show 16 more authors
Ida Janiak Patcharawee Munsaket Yasir Abdul Qadir Ronnakrit Rattanamala Orarik Tasuya Ekburus Boonsoy Nuanwan Sanguansak Rattiyakorn Rattanasai Thammasorn Padjaroen Siramas Komonjinda Sawatkamol Pichadee Ananpol Sudsap Smanchan Chandaiam Boonyarit Choonhakit Suwanit Wutsang Vik S Dhillon
Authors on Pith no claims yet

Pith reviewed 2026-05-10 18:54 UTC · model grok-4.3

classification 🌌 astro-ph.EP
keywords WASP-43 bhot Jupitertransit timing variationsorbital decaytransmission spectroscopyatmospheric retrievalmulti-instrument observations
0
0 comments X

The pith

Observations of hot Jupiter WASP-43 b over a decade show no significant orbital decay while revealing modeling difficulties when combining atmospheric spectra from multiple instruments.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper combines 35 new ground-based transit light curves of WASP-43 b with existing ground, TESS, HST, and JWST data to update the planet's parameters and search for timing changes. Analysis of 188 mid-transit times finds no clear signs that the orbit is decaying. Atmospheric retrievals on the HST transmission spectrum alone link higher temperatures to higher water abundances, but adding data from other instruments creates wavelength-dependent complexities that prevent firm atmospheric conclusions. The work shows that consistent high-precision observations across instruments will be required to resolve these issues for this planet.

Core claim

Transit timing variations measured from 188 mid-transit times spanning a decade exhibit no significant evidence of orbital decay. Atmospheric retrievals applied to HST/WFC3 G141 transmission spectra indicate that solutions with higher temperatures are associated with higher water abundances, but combining these spectra with ground-based, TESS, and JWST observations across a wide wavelength range introduces substantial modeling challenges that limit atmospheric characterization.

What carries the argument

Collection and joint analysis of 188 mid-transit times from multi-band observations, together with atmospheric retrieval modeling performed on HST spectra and then extended to broader wavelength datasets.

If this is right

  • The orbit of WASP-43 b remains stable with no detectable decay over the ten-year baseline.
  • Higher-temperature atmospheric models for this planet correspond to higher water abundances when using HST data alone.
  • Broad-wavelength datasets increase the number of free parameters and degeneracies in atmospheric retrievals.
  • High-precision, multi-instrument observations will be needed to break current degeneracies in the atmosphere of this target.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar timing analyses on other short-period hot Jupiters could test whether the lack of decay seen here is typical or exceptional.
  • Unquantified instrument-to-instrument differences may affect retrieval results for many exoplanets observed with mixed ground and space facilities.
  • Future work could test whether restricting retrievals to narrow, well-calibrated wavelength windows yields more stable abundance estimates before attempting full-spectrum fits.
  • Repeated observations with a single stable instrument over time could isolate whether the temperature-water correlation persists independently of dataset combination.

Load-bearing premise

Standard transit-fitting software and atmospheric retrieval models can be applied to observations from different instruments without introducing large unaccounted systematics that alter the combined results.

What would settle it

A new set of transit times collected over the next several years that either shows a clear, steady decrease in orbital period or yields consistent water abundance and temperature values when retrievals are run on uniformly calibrated spectra from all instruments.

Figures

Figures reproduced from arXiv: 2604.05907 by Akshay Priyadarshi, Ananpol Sudsap, Boonyarit Choonhakit, Eamonn Kerins, Ekburus Boonsoy, Fan Yang, Iain McDonald, Ida Janiak, Ing-Guey Jiang, Napaporn A-thano, Nuanwan Sanguansak, Orarik Tasuya, Patcharawee Munsaket, Rattiyakorn Rattanasai, Ronnakrit Rattanamala, Sawatkamol Pichadee, Siramas Komonjinda, Smanchan Chandaiam, Supachai Awiphan, Suwanit Wutsang, Thammasorn Padjaroen, Vik S Dhillon, Yasir Abdul Qadir, Yogesh C. Joshi.

Figure 1
Figure 1. Figure 1: Left panels: The normalized, phase-folded transit light curves of WASP-43 b from the 2.4-m and 1-m TNT observa￾tions in the SPEARNET telescope network, shown as grey dots. The best-fitting model from TransitFit is displayed as a solid line. Right panels: Residuals of the light curves after model subtraction. Both the light curves and residuals are vertically offset for clarity. The corresponding residuals … view at source ↗
Figure 2
Figure 2. Figure 2: The normalized, phase-folded transit light curves of WASP-43 b are shown for HST/WFC3 G141 observations on November 15, 2013 (upper left), TESS observations within Sector 9 (upper right), and JWST/MIRI (bottom). The observational data are presented as dots, and the best-fitting model from TransitFit is shown as solid lines. Both the light curves and the corresponding residuals (right panels) are vertically… view at source ↗
Figure 3
Figure 3. Figure 3: The O − C diagram and best-fitting timing models for WASP-43 b, including data from the literature (grey circles), HST (pink circles), TESS (blue circles), JWST (green circles), and this study (red circles), are shown. The orange line represents the timing residuals of the orbital decay model. 10−3 10−2 10−1 Frequency [cycle/period] 0.0 0.1 0.2 0.3 0.4 Power FAP = 9 x 10−7 % FAP = 0.1 % FAP = 0.5 % [PITH_… view at source ↗
Figure 4
Figure 4. Figure 4: The GLS periodograms were calculated for the timing residuals of a total of 188 epochs. The dashed line indicates the FAP levels. The highest power peak was found at a frequency of 0.01657 ± 0.00001 cycles/day, with a FAP of 9 × 10−7%. that the lowest ∆χ 2 red values are close to the upper mass limit corresponding to a TTV amplitude of 15 seconds. In the unstable orbit region with an orbital period rang￾in… view at source ↗
Figure 5
Figure 5. Figure 5: The O − C diagram for the TESS data sets. (a) The O − C data from observations in TESS three sectors over a five-year interval. (b)-(e) The O − C data plotted by individual sectors for clearer visibility. work TauREx3 (Al-Refaie et al. 2021) 9 , which uses the nested sampling routines from MultiNest (Feroz et al. 2009) with 1000 live points to determine the atmospheric parameters. For the transmission spec… view at source ↗
Figure 6
Figure 6. Figure 6: The GLS periodograms of the timing residuals for TESS data show that the highest power peak was found at a frequency of 0.33017 ± 0.00005 cycles/day with a False Alarm Probability (FAP) of 29.7% [PITH_FULL_IMAGE:figures/full_fig_p014_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Upper mass limit of the perturbing planet in the WASP-43 system. The best ∆χ 2 red values, binned with a period ratio of 0.05, are shown as the black dotted line. The upper mass limits for TTV amplitudes of 5, 15, and 25 seconds are represented by the blue dash-dotted, green dashed, and red solid lines, respectively. The white vertical line represents the orbital period of WASP-43 b. The black vertical lin… view at source ↗
Figure 8
Figure 8. Figure 8: The HST transmission spectrum of WASP-43 b, reduced using Iraclis (pink) and TransitFit (dark-red). STScI is operated by the AURA, Inc., under NASA con￾tract NAS 5–26555. The specific observations analyzed can be accessed via https://doi.org/10.17909/T97P46 and https://doi.org/10.17909/t9-nmc8-f686, respec￾tively. This work also used the data based on obser￾vations made with the NASA/ESA/CSA James Webb Spa… view at source ↗
Figure 9
Figure 9. Figure 9: The best-fit transmission spectrum model of WASP-43 b derived from HST data. The synthetic model generated by TauREx is shown as a solid blue line, with the corresponding 1σ confidence region indicated by the blue shading. The binned best-fit model values are shown as blue squares. The transit depths computed with Iraclis and TransitFit are shown as pink and dark-red dots, respectively [PITH_FULL_IMAGE:fi… view at source ↗
Figure 10
Figure 10. Figure 10: The best-fit transmission spectrum model of WASP-43 b, calculated for the combined dataset including ground￾based observations (grey dots), TESS (light-blue dots), HST processed with Iraclis (pink dots), HST processed with TransitFit (dark-red dots), and JWST (green dots). The synthetic model generated by TauREx is shown as a solid blue line, with the corresponding 1σ confidence region indicated by the bl… view at source ↗
read the original abstract

We present a new set of 35 transit light curves of the hot Jupiter WASP-43~b, obtained through the SPEARNET network. These datasets were analyzed together with previously published ground-based observations, as well as space-based data from \emph{TESS}, \emph{HST}, and \emph{JWST}, to refine the planetary parameters of WASP-43~b. A total of 188 mid-transit times, measured with \texttt{TransitFit}, were analyzed for potential timing variations. The transit timing variations do not show any significant evidence of orbital decay. Atmospheric retrievals using \emph{HST}/WFC3 G141 transmission spectra suggest that higher-temperature solutions are associated with higher water abundances. However, when these data are combined with observations from ground-based telescopes, \emph{TESS}, and \emph{JWST}, the increased modeling complexity across the broad wavelength baseline presents significant challenges for atmospheric characterization. These results highlight that high-precision, multi-instrument datasets will be necessary to break existing degeneracies in the atmospheric modeling of this target in the future.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. This paper reports 35 new multi-band transit light curves of hot Jupiter WASP-43 b from the SPEARNET network, combined with archival ground-based, TESS, HST, and JWST observations. A total of 188 mid-transit times measured with TransitFit are analyzed for timing variations, yielding no significant evidence of orbital decay. Atmospheric retrievals on HST/WFC3 G141 transmission spectra indicate that higher-temperature solutions correlate with higher water abundances, while noting that combining data across instruments introduces substantial modeling challenges and degeneracies.

Significance. If the results hold, the decade-long timing baseline supplies a clear null detection on orbital decay for this well-studied hot Jupiter, adding to constraints on tidal evolution. The atmospheric section usefully illustrates degeneracies in retrievals and the limits of current multi-instrument datasets. Credit is due for the large homogeneous timing sample, use of standard software (TransitFit) for reproducibility, and the appropriately cautious framing of the HST-only retrieval result rather than overclaiming a multi-instrument solution.

minor comments (3)
  1. [Abstract] Abstract: the statement that 'higher-temperature solutions are associated with higher water abundances' would be strengthened by a brief parenthetical note on the retrieval code or free parameters used (e.g., whether clouds or metallicity were fixed).
  2. [TTV analysis] TTV analysis section: while the null result on decay is stated, the manuscript should report the quantitative upper limit on any period derivative (e.g., dP/dt < X s/yr at 3σ) or the likelihood ratio between constant-period and decaying-orbit models to make the 'no significant evidence' claim more precise.
  3. [Atmospheric retrieval] Atmospheric retrieval section: an explicit statement of how the reported temperature-water correlation was quantified (e.g., Spearman coefficient or marginalized posterior) would help readers evaluate its robustness given the acknowledged degeneracies.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their positive assessment of the manuscript, including recognition of the homogeneous timing sample, use of TransitFit for reproducibility, and the appropriately cautious framing of the HST-only retrieval results. We appreciate the recommendation for minor revision.

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper reports direct measurements of 188 mid-transit times from multi-instrument data using the standard TransitFit package, yielding a null result on orbital decay with no claimed detection or tight constraint. Atmospheric retrievals on HST/WFC3 G141 spectra are presented as empirical associations (higher T with higher H2O) accompanied by explicit caveats on degeneracies when combining with ground-based/TESS/JWST data. No steps reduce by construction to fitted inputs, no uniqueness theorems or ansatzes are imported via self-citation, and no predictions are statistically forced from subsets of the same data. All claims derive from external observations and established analysis methods without internal redefinition or load-bearing self-references.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work rests on standard domain assumptions in transit photometry and atmospheric retrieval; no novel entities are introduced. Specific free parameters typical of light-curve fitting (limb darkening, baseline trends) are implied but not enumerated in the abstract.

axioms (1)
  • domain assumption Standard assumptions in transit photometry and atmospheric retrieval hold across instruments
    The analysis assumes no significant unaccounted instrumental systematics when combining ground-based, TESS, HST, and JWST data.

pith-pipeline@v0.9.0 · 5648 in / 1102 out tokens · 64655 ms · 2026-05-10T18:54:17.998484+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

71 extracted references · 66 canonical work pages

  1. [1]

    2022, AJ, 163, 77, doi: 10.3847/1538-3881/ac416d

    A-thano, N., Jiang, I.-G., Awiphan, S., et al. 2022, AJ, 163, 77, doi: 10.3847/1538-3881/ac416d

    work page doi:10.3847/1538-3881/ac416d 2022

  2. [2]

    Abel, M., Frommhold, L., Li, X., & Hunt, K. L. C. 2011, Journal of Physical Chemistry A, 115, 6805, doi: 10.1021/jp109441f —. 2012, JChPh, 136, 044319, doi: 10.1063/1.3676405

    work page doi:10.1021/jp109441f 2011

  3. [3]

    , keywords =

    Al-Refaie, A. F., Changeat, Q., Waldmann, I. P., & Tinetti, G. 2021, ApJ, 917, 37, doi: 10.3847/1538-4357/ac0252

    work page doi:10.3847/1538-4357/ac0252 2021

  4. [4]

    2016, MNRAS, 463, 2574, doi: 10.1093/mnras/stw2148

    Awiphan, S., Kerins, E., Pichadee, S., et al. 2016, MNRAS, 463, 2574, doi: 10.1093/mnras/stw2148

    work page doi:10.1093/mnras/stw2148 2016

  5. [5]

    W., Line, M

    Bartelt, D., Mansfield, M. W., Line, M. R., et al. 2025, AJ, 169, 101, doi: 10.3847/1538-3881/ad9b95

    work page doi:10.3847/1538-3881/ad9b95 2025

  6. [6]

    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

    work page doi:10.21105/joss.04503 2022

  7. [7]

    J.et al.A First Look at the JWST MIRI/LRS Phase Curve of WASP- 43b.arXiv e-printsarXiv:2301.06350 (2023)

    Bell, T. J., Kreidberg, L., Kendrew, S., et al. 2023, arXiv e-prints, arXiv:2301.06350, doi: 10.48550/arXiv.2301.06350

    work page doi:10.48550/arxiv.2301.06350 2023

  8. [8]

    J., Crouzet, N., Cubillos, P

    Bell, T. J., Crouzet, N., Cubillos, P. E., et al. 2024, Nature Astronomy, doi: 10.1038/s41550-024-02230-x

    work page doi:10.1038/s41550-024-02230-x 2024

  9. [9]

    , keywords =

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    work page doi:10.1051/aas:1996164 1996

  10. [10]

    Blecic, J., Harrington, J., Madhusudhan, N., et al. 2014, ApJ, 781, 116, doi: 10.1088/0004-637X/781/2/116 21 −0.10 −0.05 0.00 0.05 0.10 Phase 0.5 0.6 0.7 0.8 0.9 1.0 Normalized Flux 20190209:0.7-TRT-SBO - I 20190213:0.7-TRT-SBO - I 20190307:0.7-TRT-SBO - I 20190416:0.7-TRT-SBO - I 20200211:0.7-TRT-SBO - R 20210119:0.7-TRT-SBO - R 20210210:0.7-TRT-SBO - R ...

    work page doi:10.1088/0004-637x/781/2/116 2014

  11. [11]

    S., Desidera, S., Benatti, S., et al

    Bonomo, A. S., Desidera, S., Benatti, S., et al. 2017, A&A, 602, A107, doi: 10.1051/0004-6361/201629882

    work page doi:10.1051/0004-6361/201629882 2017

  12. [12]

    2021, The Exoplanet Characterization Toolkit (ExoCTK), Zenodo, doi:10.5281/zenodo.4556063

    Bourque, M., Espinoza, N., Filippazzo, J., et al. 2021, The Exoplanet Characterization Toolkit (ExoCTK), 1.0.0, Zenodo, doi: 10.5281/zenodo.4556063

    work page doi:10.5281/zenodo.4556063 2021

  13. [13]

    2014, A&A, 563, A40, doi: 10.1051/0004-6361/201322740

    Chen, G., van Boekel, R., Wang, H., et al. 2014, A&A, 563, A40, doi: 10.1051/0004-6361/201322740

    work page doi:10.1051/0004-6361/201322740 2014

  14. [14]

    2020, A&A, 639, A3, doi: 10.1051/0004-6361/201937267

    Waldmann, I. 2020, A&A, 639, A3, doi: 10.1051/0004-6361/201937267

    work page doi:10.1051/0004-6361/201937267 2020

  15. [15]

    and Rocchetto, Marco and Yurchenko, Sergei N

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

    work page doi:10.1051/0004-6361/202038350 2021

  16. [16]

    2000, A&A, 363, 1081

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

    2000

  17. [17]

    P., et al

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

    2019

  18. [18]

    2021, AJ, 162, 210, doi: 10.3847/1538-3881/ac1baf

    Safari, H. 2021, AJ, 162, 210, doi: 10.3847/1538-3881/ac1baf

    work page doi:10.3847/1538-3881/ac1baf 2021

  19. [19]

    M., & Agol, E

    Deck, K. M., & Agol, E. 2016, ApJ, 821, 96, doi: 10.3847/0004-637X/821/2/96

    work page doi:10.3847/0004-637x/821/2/96 2016

  20. [20]

    S., Marsh, T

    Dhillon, V. S., Marsh, T. R., Atkinson, D. C., et al. 2014, MNRAS, 444, 4009, doi: 10.1093/mnras/stu1660

    work page doi:10.1093/mnras/stu1660 2014

  21. [21]

    , keywords =

    Edwards, B., Changeat, Q., Tsiaras, A., et al. 2023, ApJS, 269, 31, doi: 10.3847/1538-4365/ac9f1a

    work page doi:10.3847/1538-4365/ac9f1a 2023

  22. [22]

    Esposito, M., Covino, E., Desidera, S., et al. 2017, A&A, 601, A53, doi: 10.1051/0004-6361/201629720 22 −0.1 0.0 0.1 Phase 0.80 0.85 0.90 0.95 1.00 Normalized Flux 2013110420131104201311042013110420131104201311042013110420131104201311042013110420131104201311042013110420131104201311042013110420131104201311042013110420131104201311042013110420131104201311042...

    work page doi:10.1051/0004-6361/201629720 2017

  23. [23]

    C., Ford , E

    Fabrycky, D. C., Ford, E. B., Steffen, J. H., et al. 2012, ApJ, 750, 114, doi: 10.1088/0004-637X/750/2/114

    work page doi:10.1088/0004-637x/750/2/114 2012

  24. [24]

    doi:10.1111/j.1365-2966.2009.15598.x , archivePrefix =

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

    work page doi:10.1111/j.1365-2966.2009.14548.x 2009

  25. [25]

    N., Gustafsson, M., & Orton, G

    Fletcher, L. N., Gustafsson, M., & Orton, G. S. 2018, ApJS, 235, 24, doi: 10.3847/1538-4365/aaa07a

    work page doi:10.3847/1538-4365/aaa07a 2018

  26. [26]

    and Lang, Dustin and Goodman, Jonathan , title =

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

    work page doi:10.1086/670067 2013

  27. [27]

    J., Shporer, A., Winn, J

    Fulton, B. J., Shporer, A., Winn, J. N., et al. 2011, The Astronomical Journal, 142, 84, doi: 10.1088/0004-6256/142/3/84

    work page doi:10.1088/0004-6256/142/3/84 2011

  28. [28]

    2021, MNRAS, 508, 5514, doi: 10.1093/mnras/stab2929

    Garai, Z., Pribulla, T., Parviainen, H., et al. 2021, MNRAS, 508, 5514, doi: 10.1093/mnras/stab2929

    work page doi:10.1093/mnras/stab2929 2021

  29. [29]

    Gillon, M., Triaud, A. H. M. J., Fortney, J. J., et al. 2012, A&A, 542, A4, doi: 10.1051/0004-6361/201218817

    work page doi:10.1051/0004-6361/201218817 2012

  30. [30]

    S., Wilzewski, J

    Gordon, I., Rothman, L. S., Wilzewski, J. S., et al. 2016, in AAS/Division for Planetary Sciences Meeting Abstracts, Vol. 48, AAS/Division for Planetary Sciences Meeting Abstracts #48, 421.13

    2016

  31. [31]

    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

    work page doi:10.3847/2041-8213/acfc3b10.3847/2041-8213/acfdab 2023

  32. [32]

    Hayes, J. J. C., Priyadarshi, A., Kerins, E., et al. 2024, MNRAS, 527, 4936, doi: 10.1093/mnras/stad3353

    work page doi:10.1093/mnras/stad3353 2024

  33. [33]

    R., Collier Cameron, A., et al

    Hellier, C., Anderson, D. R., Collier Cameron, A., et al. 2011, A&A, 535, L7, doi: 10.1051/0004-6361/201117081

    work page doi:10.1051/0004-6361/201117081 2011

  34. [34]

    2016, AJ, 151, 137, doi: 10.3847/0004-6256/151/6/137

    Hoyer, S., Pall´ e, E., Dragomir, D., & Murgas, F. 2016, AJ, 151, 137, doi: 10.3847/0004-6256/151/6/137

    work page doi:10.3847/0004-6256/151/6/137 2016

  35. [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

    work page doi:10.1051/0004-6361/201219058 2013

  36. [36]

    S., & Winn, J

    Ivshina, E. S., & Winn, J. N. 2022, ApJS, 259, 62, doi: 10.3847/1538-4365/ac545b

    work page doi:10.3847/1538-4365/ac545b 2022

  37. [37]

    M., et al., 2016, in Chiozzi G., Guzman J

    Jenkins, J. M., Twicken, J. D., McCauliff, S., et al. 2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9913, Software and Cyberinfrastructure for Astronomy IV, ed. G. Chiozzi & J. C. Guzman, 99133E, doi: 10.1117/12.2233418

    work page doi:10.1117/12.2233418 2016

  38. [38]

    2016, AJ, 151, 17, doi: 10.3847/0004-6256/151/1/17

    Jiang, I.-G., Lai, C.-Y., Savushkin, A., et al. 2016, AJ, 151, 17, doi: 10.3847/0004-6256/151/1/17

    work page doi:10.3847/0004-6256/151/1/17 2016

  39. [39]

    2018, Research Notes of the AAS, 2, 4, doi: 10.3847/2515-5172/aaa4b7

    Kanodia, S., & Wright, J. 2018, Research Notes of the AAS, 2, 4, doi: 10.3847/2515-5172/aaa4b7

    work page doi:10.3847/2515-5172/aaa4b7 2018

  40. [40]

    2023, ApJS, 265, 4, doi: 10.3847/1538-4365/ac9da4

    Kokori, A., Tsiaras, A., Edwards, B., et al. 2023, ApJS, 265, 4, doi: 10.3847/1538-4365/ac9da4

    work page doi:10.3847/1538-4365/ac9da4 2023

  41. [41]

    2015, Publications of the Astronomical Society of the Pacific, 127, 1161, doi: 10.1086/683602

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

    work page doi:10.1086/683602 2015

  42. [42]

    R., Thorngren, D., Morley, C

    Kreidberg, L., Line, M. R., Thorngren, D., Morley, C. V., & Stevenson, K. B. 2018, ApJL, 858, L6, doi: 10.3847/2041-8213/aabfce

    work page doi:10.3847/2041-8213/aabfce 2018

  43. [43]

    L., D´ esert, J.-M., et al

    Kreidberg, L., Bean, J. L., D´ esert, J.-M., et al. 2014, ApJL, 793, L27, doi: 10.1088/2041-8205/793/2/L27

    work page doi:10.1088/2041-8205/793/2/l27 2014

  44. [44]

    W., Mierle, K., Blanton, M., & Roweis, S

    Lang, D., Hogg, D. W., Mierle, K., Blanton, M., & Roweis, S. 2010, AJ, 139, 1782, doi: 10.1088/0004-6256/139/5/1782

    work page doi:10.1088/0004-6256/139/5/1782 2010

  45. [45]

    2023, A&A, 678, A23, doi: 10.1051/0004-6361/202347151

    Lesjak, F., Nortmann, L., Yan, F., et al. 2023, A&A, 678, A23, doi: 10.1051/0004-6361/202347151

    work page doi:10.1051/0004-6361/202347151 2023

  46. [46]

    2013, Information Bulletin on Variable Stars, 6082, 1

    Maciejewski, G., Puchalski, D., Saral, G., et al. 2013, Information Bulletin on Variable Stars, 6082, 1

    2013

  47. [47]

    and Wilkinson, M

    McDonald, I., van Loon, J. T., Decin, L., et al. 2009, MNRAS, 394, 831, doi: 10.1111/j.1365-2966.2008.14370.x

    work page doi:10.1111/j.1365-2966.2008.14370.x 2009

  48. [48]

    2012 , month = apr, journal =

    McDonald, I., Zijlstra, A. A., & Boyer, M. L. 2012, MNRAS, 427, 343, doi: 10.1111/j.1365-2966.2012.21873.x

    work page doi:10.1111/j.1365-2966.2012.21873.x 2012

  49. [49]

    A., & Watson, R

    McDonald, I., Zijlstra, A. A., & Watson, R. A. 2017, MNRAS, 471, 770, doi: 10.1093/mnras/stx1433

    work page doi:10.1093/mnras/stx1433 2017

  50. [50]

    K., Masseron, T., Hoeijmakers, H

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

    work page doi:10.1093/mnras/stz1818 2019

  51. [51]

    K., Yurchenko, S

    McKemmish, L. K., Yurchenko, S. N., & Tennyson, J. 2016, MNRAS, 463, 771, doi: 10.1093/mnras/stw1969

    work page doi:10.1093/mnras/stw1969 2016

  52. [52]

    R., et al

    Murgas, F., Pall´ e, E., Zapatero Osorio, M. R., et al. 2014, A&A, 563, A41, doi: 10.1051/0004-6361/201322374

    work page doi:10.1051/0004-6361/201322374 2014

  53. [53]

    J., et al

    Parviainen, H., Tingley, B., Deeg, H. J., et al. 2019, A&A, 630, A89, doi: 10.1051/0004-6361/201935709

    work page doi:10.1051/0004-6361/201935709 2019

  54. [54]

    C., Winn , J

    Patra, K. C., Winn, J. N., Holman, M. J., et al. 2020, AJ, 159, 150, doi: 10.3847/1538-3881/ab7374

    work page doi:10.3847/1538-3881/ab7374 2020

  55. [55]

    T., Hill, C., Tennyson, J., & Yurchenko, S

    Patrascu, A. T., Hill, C., Tennyson, J., & Yurchenko, S. N. 2014, The Journal of Chemical Physics, 141, 144312, doi: 10.1063/1.4897484

    work page doi:10.1063/1.4897484 2014

  56. [56]

    L., Kyuberis, A

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

    work page doi:10.1093/mnras/sty1877 2018

  57. [57]

    G., Ayala-Loera, C., et al

    Ricci, D., Ram´ on-Fox, F. G., Ayala-Loera, C., et al. 2015, PASP, 127, 143, doi: 10.1086/680233

    work page doi:10.1086/680233 2015

  58. [58]

    S., & Gordon, I

    Rothman, L. S., & Gordon, I. E. 2014, in 13th International HITRAN Conference, 49, doi: 10.5281/zenodo.11207

    work page doi:10.5281/zenodo.11207 2014

  59. [59]

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

    work page doi:10.1093/mnras/staa278 2020

  60. [60]

    B., Line, M

    Stevenson, K. B., Line, M. R., Bean, J. L., et al. 2017, AJ, 153, 68, doi: 10.3847/1538-3881/153/2/68

    work page doi:10.3847/1538-3881/153/2/68 2017

  61. [61]

    Yurchenko and Ahmed F

    Tennyson, J., Yurchenko, S. N., Al-Refaie, A. F., et al. 2016, Journal of Molecular Spectroscopy, 327, 73, doi: 10.1016/j.jms.2016.05.002

    work page doi:10.1016/j.jms.2016.05.002 2016

  62. [62]

    Instrumentation in astronomy VI , year = 1986, editor =

    Tody, D. 1986, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 627, Instrumentation in astronomy VI, ed. D. L. Crawford, 733, doi: 10.1117/12.968154

    work page doi:10.1117/12.968154 1986

  63. [63]

    1993, in Astronomical Society of the Pacific Conference Series, Vol

    Tody, D. 1993, in Astronomical Society of the Pacific Conference Series, Vol. 52, Astronomical Data Analysis Software and Systems II, ed. R. J. Hanisch, R. J. V. Brissenden, & J. Barnes, 173

    1993

  64. [64]

    P., Rocchetto, M., et al

    Tsiaras, A., Waldmann, I. P., Rocchetto, M., et al. 2016a, ApJ, 832, 202, doi: 10.3847/0004-637X/832/2/202 24 −0.05 0.00 0.05 Phase −0.2 0.0 0.2 0.4 0.6 0.8 1.0 Normalized Flux TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 TESS Sector 35 ...

    work page doi:10.3847/0004-637x/832/2/202

  65. [65]

    P., et al

    Tsiaras, A., Rocchetto, M., Waldmann, I. P., et al. 2016c, ApJ, 820, 99, doi: 10.3847/0004-637X/820/2/99

    work page doi:10.3847/0004-637x/820/2/99

  66. [66]

    P., Zingales, T., et al

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

    work page doi:10.3847/1538-3881/aaaf75 2018

  67. [67]

    C., L´ opez-Morales, M., Espinoza, N., et al

    Weaver, I. C., L´ opez-Morales, M., Espinoza, N., et al. 2020, AJ, 159, 13, doi: 10.3847/1538-3881/ab55da

    work page doi:10.3847/1538-3881/ab55da 2020

  68. [68]

    2020, AJ, 160, 155, doi: 10.3847/1538-3881/ababad

    Wong, I., Shporer, A., Daylan, T., et al. 2020, AJ, 160, 155, doi: 10.3847/1538-3881/ababad

    work page doi:10.3847/1538-3881/ababad 2020

  69. [69]

    ExoMol line lists – XXXIX

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

    work page doi:10.1093/mnras/staa1874 2020

  70. [70]

    N., Owens, A., Kefala, K., & Tennyson, J

    Yurchenko, S. N., Owens, A., Kefala, K., & Tennyson, J. 2024, MNRAS, 528, 3719, doi: 10.1093/mnras/stae148

    work page doi:10.1093/mnras/stae148 2024

  71. [71]

    Zechmeister, M., & K¨ urster, M. 2009, A&A, 496, 577, doi: 10.1051/0004-6361:200811296 26 −4.5 −3.0 −1.5 log10(H2O) −8 −6 −4 −2 log10(CH4) −8 −6 −4 −2 log10(CO) −8 −6 −4 −2 log10(CO2) −8 −6 −4 −2 log10(TiO) −8 −6 −4 −2 log10(VO) −8 −6 −4 −2 log10(AlO) 400 800120016002000 Tp 2 3 4 5 6 log10(P c) −4.5 −3.0 −1.5 log10(H2O) −8 −6 −4 −2 log10(CH4) −8 −6 −4 −2 ...

    work page doi:10.1051/0004-6361:200811296 2009