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Abstract:

We aim at extracting the transmission spectrum of the HI Balmer lines of the ultra-hot Jupiter (UHJ) KELT-20b/MASCARA-2b from observations and to further compare the results with what obtained through forward modelling accounting for non-local thermodynamic equilibrium (NLTE) effects. We extract the line profiles from six transits obtained with the HARPS-N high-resolution spectrograph attached to the Telescopio Nazionale Galileo telescope. We compute the temperature-pressure (TP) profile employing the helios code in the lower atmosphere and the Cloudy NLTE code in the middle and upper atmosphere. We further use Cloudy to compute the theoretical planetary transmission spectrum in LTE and NLTE for comparison with observations. We detected the Halpha (0.79+/-0.03%; 1.25 Rp), Hbeta (0.52+/-0.03%; 1.17 Rp), and Hgamma (0.39+/-0.06%; 1.13 Rp) lines, while we detected the Hdelta line at almost 4 sigma (0.27+/-0.07%; 1.09 Rp). The models predict an isothermal temperature of about2200 K at pressures >10^-2 bar and of about 7700 K at pressures <10^-8 bar, with a roughly linear temperature rise in between. In the middle and upper atmosphere, the NLTE TP profile is up to about 3000 K hotter than in LTE. The synthetic transmission spectrum derived from the NLTE TP profile is in good agreement with the observed HI Balmer line profiles, validating our obtained atmospheric structure. Instead, the synthetic transmission spectrum derived from the LTE TP profile leads to significantly weaker absorption compared to the observations. Metals appear to be the primary agents leading to the temperature inversion in UHJs and the impact of NLTE effects on them increases the magnitude of the inversion. We find that the impact of NLTE effects on the TP profile of KELT-20b/MASCARA-2b is larger than for the hotter UHJ KELT-9b, and thus NLTE effects might be relevant also for planets cooler than KELT-20b/MASCARA-2b.Comment: Accepted for publication in Astronomy and Astrophysic

Abstract:

The past two decades have seen a major expansion in the availability, size, and precision of time-domain data sets in astronomy. Owing to their unique combination of flexibility, mathematical simplicity, and comparative robustness, Gaussian processes (GPs) have emerged recently as the solution of choice to model stochastic signals in such data sets. In this review, we provide a brief introduction to the emergence of GPs in astronomy, present the underlying mathematical theory, and give practical advice considering the key modeling choices involved in GP regression. We then review applications of GPs to time-domain data sets in the astrophysical literature so far, from exoplanets to active galactic nuclei, showcasing the power and flexibility of the method. We provide worked examples using simulated data, with links to the source code; discuss the problem of computational cost and scalability; and give a snapshot of the current ecosystem of open source GP software packages. In summary:
â–ª GP regression is a conceptually simple but statistically principled and powerful tool for the analysis of astronomical time series.
â–ª It is already widely used in some subfields, such as exoplanets, and gaining traction in many others, such as optical transients.
â–ª Driven by further algorithmic and conceptual advances, we expect that GPs will continue to be an important tool for robust and interpretable time domain astronomy for many years to come.