Planet cartography with neural learned regularization

Abstract

Finding potential life harboring exo-Earths is one of the aims of exoplanetary science. Detecting signatures of life in exoplanets will likely first be accomplished by determining the bulk composition of the planetary atmosphere via reflected/transmitted spectroscopy. However, a complete understanding of the habitability conditions will surely require mapping the presence of liquid water, continents and/or clouds. Spin-orbit tomography is a technique that allows us to obtain maps of the surface of exoplanets around other stars using the light scattered by the planetary surface. We leverage the potential of deep learning and propose a mapping technique for exo-Earths in which the regularization is learned from mock surfaces. The solution of the inverse mapping problem is posed as a deep neural network that can be trained end-to-end with suitable training data. We propose in this work to use methods based on the procedural generation of planets, inspired by what we found on Earth. We also consider mapping the recovery of surfaces and the presence of persistent cloud in cloudy planets. We show that the a reliable mapping can be carried out with our approach, producing very compact continents, even when using single passband observations. More importantly, if exoplanets are partially cloudy like the Earth is, we show that one can potentially map the distribution of persistent clouds that always occur on the same position on the surface (associated to orography and sea surface temperatures) together with non-persistent clouds that move across the surface. This will become the first test one can perform on an exoplanet for the detection of an active climate system. For small rocky planets in the habitable zone of their stars, this weather system will be driven by water, and the detection can be considered as a strong proxy for truly habitable conditions.

12 pages, 9 figures, accepted for publication in A&A, code on https://github.com/aasensio/neural_exocartography

References in corpus (22)

• Array Programming with NumPy
• Planck 2018 results. I. Overview and the cosmological legacy of Planck
• Extreme Water Loss and Abiotic O${}_2$ Buildup On Planets Throughout the Habitable Zones of M Dwarfs
• A Re-appraisal of the Habitability of Planets Around M Dwarf Stars
• STARRY: Analytic Occultation Light Curves
• Exoplanet Biosignatures: Understanding Oxygen as a Biosignature in the Context of Its Environment
• Finding extraterrestrial life using ground-based high-resolution spectroscopy
• Alien Maps of an Ocean-Bearing World
• Characterization of extrasolar terrestrial planets from diurnal photometric variability
• DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications
• The transmission spectrum of Earth through lunar eclipse observations
• Kepler Planet Occurrence Rates for Mid-Type M Dwarfs as a Function of Spectral Type
• Identifying the rotation rate and the presence of dynamic weather on extrasolar Earth-like planets from photometric observations
• Mapping Earth Analogs from Photometric Variability: Spin-Orbit Tomography for Planets in Inclined Orbits
• Global Mapping of Earth-like Exoplanets from Scattered Light Curves
• Mapping Clouds and Terrain of Earth-like Planets from Photometric Variability: Demonstration with Planets in Face-on Orbits
• Convolutional Neural Networks on the HEALPix sphere: a pixel-based algorithm and its application to CMB data analysis
• exocartographer: A Bayesian Framework for Mapping Exoplanets in Reflected Light
• Global Mapping of an Exo-Earth using Sparse Modeling
• Characterizing the atmospheres of transiting rocky planets around late type dwarfs
• Global Mapping of the Surface Composition on an Exo-Earth using Color Variability
• Bayesian Dynamic Mapping of an Exo-Earth from Photometric Variability

Cited by in corpus (6)

• The Atmospheres of Rocky Exoplanets II. Influence of surface composition on the diversity of cloud condensates
• Analytic Light Curves in Reflected Light: Phase Curves, Occultations, and Non-Lambertian Scattering for Spherical Planets and Moons
• Exploring spectropolarimetric inversions using neural fields. Solar chromospheric magnetic field under the weak-field approximation
• Water versus land on temperate rocky planets
• Global Mapping of Surface Composition on an Exo-Earth Using Sparse Modeling
• Exoplanet Cartography using Convolutional Neural Networks