Global Mapping of an Exo-Earth using Sparse Modeling
We develop a new retrieval scheme for obtaining two-dimensional surface maps of exoplanets from scattered light curves. In our scheme, the combination of the L1-norm and Total Squared Variation, which is one of the techniques used in sparse modeling, is adopted to find the optimal map. We apply the...
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ftdatacite:10.48550/arxiv.2004.03941 2023-05-15T13:59:00+02:00 Global Mapping of an Exo-Earth using Sparse Modeling Aizawa, Masataka Kawahara, Hajime Fan, Siteng 2020 https://dx.doi.org/10.48550/arxiv.2004.03941 https://arxiv.org/abs/2004.03941 unknown arXiv https://dx.doi.org/10.3847/1538-4357/ab8d30 arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Earth and Planetary Astrophysics astro-ph.EP Instrumentation and Methods for Astrophysics astro-ph.IM FOS Physical sciences article-journal Article ScholarlyArticle Text 2020 ftdatacite https://doi.org/10.48550/arxiv.2004.03941 https://doi.org/10.3847/1538-4357/ab8d30 2022-03-10T15:47:48Z We develop a new retrieval scheme for obtaining two-dimensional surface maps of exoplanets from scattered light curves. In our scheme, the combination of the L1-norm and Total Squared Variation, which is one of the techniques used in sparse modeling, is adopted to find the optimal map. We apply the new method to simulated scattered light curves of the Earth, and find that the new method provides a better spatial resolution of the reconstructed map than those using Tikhonov regularization. We also apply the new method to observed scattered light curves of the Earth obtained during the two-year DSCOVR/EPIC observations presented by Fan et al. (2019). The method with Tikhonov regularization enables us to resolve North America, Africa, Eurasia, and Antarctica. In addition to that, the sparse modeling identifies South America and Australia, although it fails to find the Antarctica maybe due to low observational weights on the poles. Besides, the proposed method is capable of retrieving maps from noise injected light curves of a hypothetical Earth-like exoplanet at 5 pc with noise level expected from coronagraphic images from a 8-m telescope. We find that the sparse modeling resolves Australia, Afro-Eurasia, North America, and South America using 2-year observation with a time interval of one month. Our study shows that the combination of sparse modeling and multi-epoch observation with 1 day or 5 days per month can be used to identify main features of an Earth analog in future direct imaging missions such as the Large UV/Optical/IR Surveyor (LUVOIR). : 17 pages, 9 figures; revised assumptions of distance to a planet and telescope size in section 5; accepted for publication in the Astrophysical Journal Article in Journal/Newspaper Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) |
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DataCite Metadata Store (German National Library of Science and Technology) |
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language |
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topic |
Earth and Planetary Astrophysics astro-ph.EP Instrumentation and Methods for Astrophysics astro-ph.IM FOS Physical sciences |
spellingShingle |
Earth and Planetary Astrophysics astro-ph.EP Instrumentation and Methods for Astrophysics astro-ph.IM FOS Physical sciences Aizawa, Masataka Kawahara, Hajime Fan, Siteng Global Mapping of an Exo-Earth using Sparse Modeling |
topic_facet |
Earth and Planetary Astrophysics astro-ph.EP Instrumentation and Methods for Astrophysics astro-ph.IM FOS Physical sciences |
description |
We develop a new retrieval scheme for obtaining two-dimensional surface maps of exoplanets from scattered light curves. In our scheme, the combination of the L1-norm and Total Squared Variation, which is one of the techniques used in sparse modeling, is adopted to find the optimal map. We apply the new method to simulated scattered light curves of the Earth, and find that the new method provides a better spatial resolution of the reconstructed map than those using Tikhonov regularization. We also apply the new method to observed scattered light curves of the Earth obtained during the two-year DSCOVR/EPIC observations presented by Fan et al. (2019). The method with Tikhonov regularization enables us to resolve North America, Africa, Eurasia, and Antarctica. In addition to that, the sparse modeling identifies South America and Australia, although it fails to find the Antarctica maybe due to low observational weights on the poles. Besides, the proposed method is capable of retrieving maps from noise injected light curves of a hypothetical Earth-like exoplanet at 5 pc with noise level expected from coronagraphic images from a 8-m telescope. We find that the sparse modeling resolves Australia, Afro-Eurasia, North America, and South America using 2-year observation with a time interval of one month. Our study shows that the combination of sparse modeling and multi-epoch observation with 1 day or 5 days per month can be used to identify main features of an Earth analog in future direct imaging missions such as the Large UV/Optical/IR Surveyor (LUVOIR). : 17 pages, 9 figures; revised assumptions of distance to a planet and telescope size in section 5; accepted for publication in the Astrophysical Journal |
format |
Article in Journal/Newspaper |
author |
Aizawa, Masataka Kawahara, Hajime Fan, Siteng |
author_facet |
Aizawa, Masataka Kawahara, Hajime Fan, Siteng |
author_sort |
Aizawa, Masataka |
title |
Global Mapping of an Exo-Earth using Sparse Modeling |
title_short |
Global Mapping of an Exo-Earth using Sparse Modeling |
title_full |
Global Mapping of an Exo-Earth using Sparse Modeling |
title_fullStr |
Global Mapping of an Exo-Earth using Sparse Modeling |
title_full_unstemmed |
Global Mapping of an Exo-Earth using Sparse Modeling |
title_sort |
global mapping of an exo-earth using sparse modeling |
publisher |
arXiv |
publishDate |
2020 |
url |
https://dx.doi.org/10.48550/arxiv.2004.03941 https://arxiv.org/abs/2004.03941 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://dx.doi.org/10.3847/1538-4357/ab8d30 |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.2004.03941 https://doi.org/10.3847/1538-4357/ab8d30 |
_version_ |
1766267367357153280 |