Techniques to retrieve the atmospheric properties of exoplanets via direct observation of their reflected light have often been limited in scope owing to computational constraints imposed by the forward-model calculations. We have developed a new set of techniques that significantly decrease the time required to perform a retrieval while maintaining accurate results. We constructed a grid of 1.4 million precomputed geometric albedo spectra valued at discrete sets of parameter points. Spectra from this grid are used to produce models for a fast and efficient nested sampling routine called PSGnest. Beyond the upfront time to construct a spectral grid, the amount of time to complete a full retrieval using PSGnest is on the order of seconds to minutes using a personal computer. An extensive evaluation of the error induced from interpolating intermediate spectra from the grid indicates that this bias is insignificant compared to other retrieval error sources, with an average coefficient of determination between interpolated and true spectra of 0.998. We apply these new retrieval techniques to help constrain the optimal bandpass centers for retrieving various atmospheric and bulk parameters from a LuvEx-type mission observing several planetary archetypes. We show that spectral observations made using a 20% bandpass centered at 0.73 μm can be used alongside our new techniques to make detections of H2O and O2 without the need to increase observing time beyond what is necessary for a signal-to-noise ratio of 10. The methods introduced here will enable robust studies of the capabilities of future observatories to characterize exoplanets.

Grid-based Atmospheric Retrievals for Reflected-light Spectra of Exoplanets Using PSGnest

Liuzzi G.
Supervision
;
2023-01-01

Abstract

Techniques to retrieve the atmospheric properties of exoplanets via direct observation of their reflected light have often been limited in scope owing to computational constraints imposed by the forward-model calculations. We have developed a new set of techniques that significantly decrease the time required to perform a retrieval while maintaining accurate results. We constructed a grid of 1.4 million precomputed geometric albedo spectra valued at discrete sets of parameter points. Spectra from this grid are used to produce models for a fast and efficient nested sampling routine called PSGnest. Beyond the upfront time to construct a spectral grid, the amount of time to complete a full retrieval using PSGnest is on the order of seconds to minutes using a personal computer. An extensive evaluation of the error induced from interpolating intermediate spectra from the grid indicates that this bias is insignificant compared to other retrieval error sources, with an average coefficient of determination between interpolated and true spectra of 0.998. We apply these new retrieval techniques to help constrain the optimal bandpass centers for retrieving various atmospheric and bulk parameters from a LuvEx-type mission observing several planetary archetypes. We show that spectral observations made using a 20% bandpass centered at 0.73 μm can be used alongside our new techniques to make detections of H2O and O2 without the need to increase observing time beyond what is necessary for a signal-to-noise ratio of 10. The methods introduced here will enable robust studies of the capabilities of future observatories to characterize exoplanets.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/173847
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