Reading Between the Rainbows: Comparative Exoplanet Characterisation through Molecule Agnostic Spectral Clustering

Fuente: arXiv
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Main Authors: Guez, Ilyana A., Claire, Mark
Format: Preprint
Published: 2024
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author Guez, Ilyana A.
Claire, Mark
author_facet Guez, Ilyana A.
Claire, Mark
contents Rocky exoplanets are faint and difficult to observe due to their small size and low brightness compared to their host star. Despite this, the James Webb Space Telescope (JWST) has allowed us new methods and opportunities to study them. Accurately characterising exoplanet atmospheres could offer insights not only into the planetary demographics of rocky worlds in the universe, but also how our own Earth compares. Previous work simulating the observational spectra of planets with various models of atmospheric composition has constrained conditions under which specific molecules would be observable. We seek a different approach that does not depend on specific molecular features, but rather on correlating "agnostic" spectral characteristics to each other. This study uses 42 synthetic transit transmission spectra in a range matching that of JWST's MIRI instrument. Spectra were de-noised, normalised and split into bands for which the enclosed areas were calculated. Using the HDBSCAN clustering algorithm, separation patterns and clusters were found across these bands, which correlated to various a priori planet characteristics, such as relative gas concentration. Using 0.7 $μ$m bands between 7 and 12 $μ$m, we are able to separate reducing vs. oxic atmospheres and constrain CO$_2$ and O$_2$ mixing ratios accurate to within two orders of magnitude in an unknown sample. Through this, we have demonstrated that it is possible to differentiate and analyse exoplanet atmosphere type from agnostic interrogation of their transit spectra with a method we call "Molecule Agnostic Spectral Clustering".
format Preprint
id arxiv_https___arxiv_org_abs_2410_16986
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reading Between the Rainbows: Comparative Exoplanet Characterisation through Molecule Agnostic Spectral Clustering
Guez, Ilyana A.
Claire, Mark
Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
Rocky exoplanets are faint and difficult to observe due to their small size and low brightness compared to their host star. Despite this, the James Webb Space Telescope (JWST) has allowed us new methods and opportunities to study them. Accurately characterising exoplanet atmospheres could offer insights not only into the planetary demographics of rocky worlds in the universe, but also how our own Earth compares. Previous work simulating the observational spectra of planets with various models of atmospheric composition has constrained conditions under which specific molecules would be observable. We seek a different approach that does not depend on specific molecular features, but rather on correlating "agnostic" spectral characteristics to each other. This study uses 42 synthetic transit transmission spectra in a range matching that of JWST's MIRI instrument. Spectra were de-noised, normalised and split into bands for which the enclosed areas were calculated. Using the HDBSCAN clustering algorithm, separation patterns and clusters were found across these bands, which correlated to various a priori planet characteristics, such as relative gas concentration. Using 0.7 $μ$m bands between 7 and 12 $μ$m, we are able to separate reducing vs. oxic atmospheres and constrain CO$_2$ and O$_2$ mixing ratios accurate to within two orders of magnitude in an unknown sample. Through this, we have demonstrated that it is possible to differentiate and analyse exoplanet atmosphere type from agnostic interrogation of their transit spectra with a method we call "Molecule Agnostic Spectral Clustering".
title Reading Between the Rainbows: Comparative Exoplanet Characterisation through Molecule Agnostic Spectral Clustering
topic Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2410.16986