Finding Signs of Life in Transit: High-resolution Transmission Spectra of Earth-like Planets around FGKM Host Stars

Abstract

Thousands of transiting exoplanets have already been detected orbiting a wide range of host stars, including the first planets that could potentially be similar to Earth. The upcoming Extremely Large Telescopes and the James Webb Space Telescope will enable the first searches for signatures of life in transiting exoplanet atmospheres. Here, we quantify the strength of spectral features in transit that could indicate a biosphere similar to the modern Earth on exoplanets orbiting a wide grid of host stars (F0 to M8) with effective temperatures between 2,500 and 7,000K: transit depths vary between about 6,000ppm (M8 host) to 30 ppm (F0 host) due to the different sizes of the host stars. CO2 possesses the strongest spectral features in transit between 0.4 and 20microns. The atmospheric biosignature pairs O2+CH4 and O3+CH4 - which identify Earth as a living planet - are most prominent for Sun-like and cooler host stars in transit spectra of modern Earth analogs. Assessing biosignatures and water on such planets orbiting hotter stars than the Sun will be extremely challenging even for high-resolution observations. All high-resolution transit spectra and model profiles are available online: they provide a tool for observers to prioritize exoplanets for transmission spectroscopy, test atmospheric retrieval algorithms, and optimize observing strategies to find life in the cosmos. In the search for life in the cosmos, transiting planets provide the first opportunity to discover whether or not we are alone, with this database as one of the keys to optimize the search strategies.

ApJL in press, 8 pages, 5 figures

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• In Search of the Edge: A Bayesian Exploration of the Detectability of Red Edges in Exoplanet Reflection Spectra
• Higher Water Loss on Earth-like Exoplanets in Eccentric Orbits
• Purple is the new green: biopigments and spectra of Earth-like purple worlds
• Follow the Water: Finding Water, Snow and Clouds on Terrestrial Exoplanets with Photometry and Machine Learning