David Dahlbüdding | Searcharxiv

arXiv2026

Habitability of Tidally Heated H$_2$-Dominated Exomoons around Free-Floating Planets

Exomoons around free-floating planets (FFPs) can survive their host planet's ejection. Such ejections can increase their orbital eccentricity, providing significant tidal heating in the absence of any stellar energy source. Previous studies suggested that liquid water could exist on such moons under thick CO$_2$-dominated atmospheres, but these models faced challenges with CO$_2$ condensation and atmospheric collapse, particularly in the high-pressure regimes that favoured long-term habitability. To address this, we employ a self-consistent model, including radiative transfer and equilibrium chemistry with condensation, to simulate a more stable hydrogen-dominated atmosphere for a range of initial chemical compositions, including C, O, and N. We find that such atmospheres can effectively trap heat via collision-induced absorption of H$_2$, maintaining surface temperatures suitable for liquid water for time-scales of up to 4.3 Gyr, depending on the surface pressure, while not prone to condensation-induced collapse. Wet-dry cycling caused by the strong tides together with the alkalinity of dissolved NH$_3$ could create favourable conditions for RNA polymerisation and thus support the emergence of life.

astro-ph.EP↗

arXiv2024

Approximating Rayleigh Scattering in Exoplanetary Atmospheres using Physics-informed Neural Networks (PINNs)

This research introduces an innovative application of physics-informed neural networks (PINNs) to tackle the intricate challenges of radiative transfer (RT) modeling in exoplanetary atmospheres, with a special focus on efficiently handling scattering phenomena. Traditional RT models often simplify scattering as absorption, leading to inaccuracies. Our approach utilizes PINNs, noted for their ability to incorporate the governing differential equations of RT directly into their loss function, thus offering a more precise yet potentially fast modeling technique. The core of our method involves the development of a parameterized PINN tailored for a modified RT equation, enhancing its adaptability to various atmospheric scenarios. We focus on RT in transiting exoplanet atmospheres using a simplified 1D isothermal model with pressure-dependent coefficients for absorption and Rayleigh scattering. In scenarios of pure absorption, the PINN demonstrates its effectiveness in predicting transmission spectra for diverse absorption profiles. For Rayleigh scattering, the network successfully computes the RT equation, addressing both direct and diffuse stellar light components. While our preliminary results with simplified models are promising, indicating the potential of PINNs in improving RT calculations, we acknowledge the errors stemming from our approximations as well as the challenges in applying this technique to more complex atmospheric conditions. Specifically, extending our approach to atmospheres with intricate temperature-pressure profiles and varying scattering properties, such as those introduced by clouds and hazes, remains a significant area for future development.

astro-ph.EP↗