BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN
We deploy a newly generated set of geometric albedo spectral grids to examine the detectability of methane (CH _4 ) in the reflected-light spectrum of an Earth-like exoplanet at visible and near-infrared (NIR) wavelengths with a future exoplanet imaging mission. By quantifying the detectability as a...
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2024-01-01
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| Online Access: | https://doi.org/10.3847/1538-3881/ad9729 |
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| author | Natasha Latouf Michael D. Himes Avi M. Mandell Michael Dane Moore Vincent Kofman Geronimo L. Villanueva Chris Stark |
| author_facet | Natasha Latouf Michael D. Himes Avi M. Mandell Michael Dane Moore Vincent Kofman Geronimo L. Villanueva Chris Stark |
| author_sort | Natasha Latouf |
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| description | We deploy a newly generated set of geometric albedo spectral grids to examine the detectability of methane (CH _4 ) in the reflected-light spectrum of an Earth-like exoplanet at visible and near-infrared (NIR) wavelengths with a future exoplanet imaging mission. By quantifying the detectability as a function of signal-to-noise ratio (SNR) and molecular abundance, we can constrain the best methods of detection with the high-contrast space-based coronagraphy slated for the next-generation telescopes such as the Habitable Worlds Observatory. We used 25 bandpasses between 0.8 and 1.5 μ m. The abundances range from a modern-Earth level to an Archean-Earth level, driven by abundances found in available literature. We constrain the optimal 20%, 30%, and 40% bandpasses based on the effective SNR of the data, and investigate the impact of spectral confusion between CH _4 and H _2 O on the detectability of each one. We find that a modern-Earth level of CH _4 is not detectable, while an Archean-Earth level of CH _4 would be detectable at all SNRs and bandpass widths. Crucially, we find that CH _4 detectability is inversely correlated with H _2 O abundance, with the required SNR increasing as H _2 O abundance increases, while H _2 O detectability depends on CH _4 abundance and the selected observational wavelength, implying that any science requirements for the characterization of Earth-like planet atmospheres in the visible–NIR should consider the abundances of both species in tandem. |
| format | Article |
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| institution | DOAJ |
| issn | 1538-3881 |
| language | English |
| publishDate | 2024-01-01 |
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| series | The Astronomical Journal |
| spelling | doaj-art-4210b05c001640fbbd8b2ca56fd3a4c92025-08-20T02:57:29ZengIOP PublishingThe Astronomical Journal1538-38812024-01-0116915010.3847/1538-3881/ad9729BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KENNatasha Latouf0https://orcid.org/0000-0001-8079-1882Michael D. Himes1https://orcid.org/0000-0002-9338-8600Avi M. Mandell2https://orcid.org/0000-0002-8119-3355Michael Dane Moore3https://orcid.org/0000-0001-7912-6519Vincent Kofman4https://orcid.org/0000-0002-5060-1993Geronimo L. Villanueva5https://orcid.org/0000-0002-2662-5776Chris Stark6Department of Physics and Astronomy, George Mason University , 4400 University Drive MS 3F3, Fairfax, VA 22030, USA ; nlatouf@gmu.edu, natasha.m.latouf@nasa.gov; NASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Sellers Exoplanents Environment Collaboration , 8800 Greenbelt Road, Greenbelt, MD 20771, USANASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; NASA Postdoctoral Program Fellow, NASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Morgan State University , 1700 E Cold Spring Lane, Baltimore, MD 21251, USANASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Sellers Exoplanents Environment Collaboration , 8800 Greenbelt Road, Greenbelt, MD 20771, USANASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Business Integra, Inc. , Bethesda, MD, USA; Sellers Exoplanets Environment Collaboration , 8800 Greenbelt Road, Greenbelt, MD 20771, USANASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Sellers Exoplanents Environment Collaboration , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Integrated Space Science and Technology Institute, Department of Physics, American University , Washington, DC, USANASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Sellers Exoplanents Environment Collaboration , 8800 Greenbelt Road, Greenbelt, MD 20771, USANASA Goddard Space Flight Center , 8800 Greenbelt Road, Greenbelt, MD 20771, USA; Sellers Exoplanents Environment Collaboration , 8800 Greenbelt Road, Greenbelt, MD 20771, USAWe deploy a newly generated set of geometric albedo spectral grids to examine the detectability of methane (CH _4 ) in the reflected-light spectrum of an Earth-like exoplanet at visible and near-infrared (NIR) wavelengths with a future exoplanet imaging mission. By quantifying the detectability as a function of signal-to-noise ratio (SNR) and molecular abundance, we can constrain the best methods of detection with the high-contrast space-based coronagraphy slated for the next-generation telescopes such as the Habitable Worlds Observatory. We used 25 bandpasses between 0.8 and 1.5 μ m. The abundances range from a modern-Earth level to an Archean-Earth level, driven by abundances found in available literature. We constrain the optimal 20%, 30%, and 40% bandpasses based on the effective SNR of the data, and investigate the impact of spectral confusion between CH _4 and H _2 O on the detectability of each one. We find that a modern-Earth level of CH _4 is not detectable, while an Archean-Earth level of CH _4 would be detectable at all SNRs and bandpass widths. Crucially, we find that CH _4 detectability is inversely correlated with H _2 O abundance, with the required SNR increasing as H _2 O abundance increases, while H _2 O detectability depends on CH _4 abundance and the selected observational wavelength, implying that any science requirements for the characterization of Earth-like planet atmospheres in the visible–NIR should consider the abundances of both species in tandem.https://doi.org/10.3847/1538-3881/ad9729AstrobiologyExoplanet atmospheresBiosignatures |
| spellingShingle | Natasha Latouf Michael D. Himes Avi M. Mandell Michael Dane Moore Vincent Kofman Geronimo L. Villanueva Chris Stark BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN The Astronomical Journal Astrobiology Exoplanet atmospheres Biosignatures |
| title | BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN |
| title_full | BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN |
| title_fullStr | BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN |
| title_full_unstemmed | BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN |
| title_short | BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN |
| title_sort | barbie bayesian analysis for remote biosignature identification on exoearths iii introducing the ken |
| topic | Astrobiology Exoplanet atmospheres Biosignatures |
| url | https://doi.org/10.3847/1538-3881/ad9729 |
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