Five Key Exoplanet Questions Answered via the Analysis of 25 Hot-Jupiter Atmospheres in Eclipse

Changeat, Quentin; Edwards, Billy; Al-Refaie, Ahmed; Tsiaras, Angelos; Skinner, J. W.; Cho, James Y-K.; Yip, Kai Hou; Anisman, Lara; Ikoma, Masahiro; Bieger, Michelle Fabienne; Venot, Olivia; Shibata, Sho; Waldmann, I. P.; Tinetti, Giovanna

doi:10.3847/1538-4365/ac5cc2

Cited by 49 publications

(51 citation statements)

References 298 publications

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“…It is thought that VO also plays an important role in determining the structure of and driving temperature inversion in the atmospheres of hot Jupiter exoplanets [19][20][21][22][23]. Studies have looked to confirm these effects in the hot Jupiters WASP-121b [24][25][26][27] and HD 209458b but evidence has been tentative [20,28,29].…”

Section: Introductionmentioning

confidence: 99%

Fine and hyperfine resolved empirical energy levels of VO

Bowesman

Akbari²,

Hopkins³

et al. 2022

Journal of Quantitative Spectroscopy and Radiative Transfer

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Section: Introductionmentioning

confidence: 99%

Fine and hyperfine resolved empirical energy levels of VO

Bowesman

Akbari²,

Hopkins³

et al. 2022

Journal of Quantitative Spectroscopy and Radiative Transfer

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“…Irwin et al 2008;Madhusudhan & Seager 2009;Line et al 2013;Lavie et al 2017;Gandhi et al 2019;Lothringer & Barman 2020;Min et al 2020;Cubillos & Blecic 2021;Al-Refaie et al 2021b). As the number of spectroscopic observations slowly increases, the community has started to look at planetary characterisation on a population level (Sing et al 2016;Barstow et al 2017;Tsiaras et al 2019;Pinhas et al 2019;Mansfield et al 2021;Roudier et al 2021;Changeat et al 2022).…”

Section: Introductionmentioning

confidence: 99%

To Sample or Not To Sample: Retrieving Exoplanetary Spectra with Variational Inference and Normalising Flows

Yip¹,

Changeat²,

Al-Refaie³

et al. 2022

Preprint

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Current endeavours in exoplanet characterisation rely on atmospheric retrieval to quantify crucial physical properties of remote exoplanets from observations. However, the scalability and efficiency of the technique are under strain with increasing spectroscopic resolution and forward model complexity. The situation becomes more acute with the recent launch of the James Webb Space Telescope and other upcoming missions. Recent advances in Machine Learning provide optimisation-based Variational Inference as an alternative approach to perform approximate Bayesian Posterior Inference. In this investigation we combined Normalising Flow-based neural network with our newly developed differentiable forward model, Diff-τ , to perform Bayesian Inference in the context of atmospheric retrieval. Using examples from real and simulated spectroscopic data, we demonstrated the superiority of our proposed framework: 1) Training Our neural network only requires a single observation; 2) It produces high-fidelity posterior distributions similar to sampling-based retrieval and; 3) It requires 75% less forward model computation to converge. 4.) We performed, for the first time, Bayesian model selection on our trained neural network. Our proposed framework contribute towards the latest development of a neural-powered atmospheric retrieval. Its flexibility and speed hold the potential to complement sampling-based approaches in large and complex data sets in the future.

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“…With the continuous developments of transit spectrophotometry, direct spectroscopy, and high-resolution Doppler spectroscopy, abundant spectral features induced by atoms and molecules have been detected in dozens of exoplanets . The ultrahot gas giants are generally found to be dominated by ionized or neutral atoms with inverted thermal profiles, while the cooler ones by molecules without inversions (Stangret et al 2022;Changeat et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Detection of Na and K in the atmosphere of the hot Jupiter HAT-P-1b with P200/DBSP

Chen¹,

Wang²,

Boekel³

et al. 2022

Preprint

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We present a new optical transmission spectrum of the hot Jupiter HAT-P-1b based on two transits observed with the Double Spectrograph (DBSP) on the Palomar 200-inch (P200) telescope. The DBSP transmission spectrum, covering a wavelength range from 325 to 1001 nm, is consistent with that observed with the Hubble Space Telescope (HST), but the former has a finer spectral resolution. The DBSP spectrum alone reveals the presence of a pressure broadened line wing for Na, the line cores for both Na and K, and tentative evidence for H 2 O. We obtain consistent results from the spectral retrieval analyses performed on the DBSP-only dataset and the DBSP, HST, and Spitzer combined dataset. Our retrievals suggest a mostly clear atmosphere for HAT-P-1b, with a cloud coverage of 22 +5 −3 % that is dominated by enhanced haze. We derive subsolar abundances for Na, K, and C, and subsolar-to-solar for O. Future observations with James Webb Space Telescope and ground-based high-resolution spectrographs should be able to not only confirm the presence of these species but also stringently constrain the formation and migration pathways for HAT-P-1b.

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Five Key Exoplanet Questions Answered via the Analysis of 25 Hot-Jupiter Atmospheres in Eclipse

Cited by 49 publications

References 298 publications

Fine and hyperfine resolved empirical energy levels of VO

Fine and hyperfine resolved empirical energy levels of VO

To Sample or Not To Sample: Retrieving Exoplanetary Spectra with Variational Inference and Normalising Flows

Detection of Na and K in the atmosphere of the hot Jupiter HAT-P-1b with P200/DBSP

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