Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation
China plans to launch a probe (Tianwen-2) around 2025, mainly to explore the near-Earth asteroid 2016 HO3 (469219, Kamo’oalewa). The mission involves close-range exploration, landing, and mining operations that require three-dimensional modeling of the asteroid, which requires prior knowledge of its...
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| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | The Astronomical Journal |
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| Online Access: | https://doi.org/10.3847/1538-3881/adb710 |
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| author | Yijun Tang Yunxiao Jiang Yuxiang Feng Xiaoming Zhang Xiaojun Jiang |
| author_facet | Yijun Tang Yunxiao Jiang Yuxiang Feng Xiaoming Zhang Xiaojun Jiang |
| author_sort | Yijun Tang |
| collection | DOAJ |
| description | China plans to launch a probe (Tianwen-2) around 2025, mainly to explore the near-Earth asteroid 2016 HO3 (469219, Kamo’oalewa). The mission involves close-range exploration, landing, and mining operations that require three-dimensional modeling of the asteroid, which requires prior knowledge of its material composition and uniformity. This information is crucial in progressive or ground exploration processes. Our research focuses on high-precision intelligent inversion of complex physical properties of asteroids based on spectral data, providing support for further analysis of asteroid materials, density, and structure. We have developed a platform for asteroid spectral classification, albedo estimation, and composition analysis, which includes three types of neural networks based on the Transformer attention mechanism: one for spectral classification, achieving a four-class classification accuracy of 94.58% and an 11-class classification accuracy of 95.69%, a second one for albedo estimation, with an average absolute error of 0.0308 in S-type asteroid albedo estimation, and the third one for composition analysis, with a predicted spectral angular distance of only 0.0340 and an rms error of 0.1759 for the abundance of endmembers. These results indicate that our network can provide high-precision asteroid spectral classification, albedo estimation, and composition analysis results. In addition, we utilized the platform to analyze and provide results for six asteroids. |
| format | Article |
| id | doaj-art-3ae36aedab6c4fe597f67b148b2627be |
| institution | OA Journals |
| issn | 1538-3881 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astronomical Journal |
| spelling | doaj-art-3ae36aedab6c4fe597f67b148b2627be2025-08-20T01:57:21ZengIOP PublishingThe Astronomical Journal1538-38812025-01-01169420110.3847/1538-3881/adb710Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo EstimationYijun Tang0https://orcid.org/0000-0001-9291-4368Yunxiao Jiang1Yuxiang Feng2Xiaoming Zhang3Xiaojun Jiang4School of Physics, Zhejiang University of Technology , Hangzhou 310023, People’s Republic of China; Collaborative Innovation Center for Bio-Med Physics Information Technology of ZJUT, Zhejiang University of Technology , Hangzhou 310023, People’s Republic of ChinaSchool of Physics, Zhejiang University of Technology , Hangzhou 310023, People’s Republic of China; Collaborative Innovation Center for Bio-Med Physics Information Technology of ZJUT, Zhejiang University of Technology , Hangzhou 310023, People’s Republic of ChinaSchool of Physics, Zhejiang University of Technology , Hangzhou 310023, People’s Republic of China; Collaborative Innovation Center for Bio-Med Physics Information Technology of ZJUT, Zhejiang University of Technology , Hangzhou 310023, People’s Republic of ChinaCAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaCAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences , Beijing 100101, People’s Republic of ChinaChina plans to launch a probe (Tianwen-2) around 2025, mainly to explore the near-Earth asteroid 2016 HO3 (469219, Kamo’oalewa). The mission involves close-range exploration, landing, and mining operations that require three-dimensional modeling of the asteroid, which requires prior knowledge of its material composition and uniformity. This information is crucial in progressive or ground exploration processes. Our research focuses on high-precision intelligent inversion of complex physical properties of asteroids based on spectral data, providing support for further analysis of asteroid materials, density, and structure. We have developed a platform for asteroid spectral classification, albedo estimation, and composition analysis, which includes three types of neural networks based on the Transformer attention mechanism: one for spectral classification, achieving a four-class classification accuracy of 94.58% and an 11-class classification accuracy of 95.69%, a second one for albedo estimation, with an average absolute error of 0.0308 in S-type asteroid albedo estimation, and the third one for composition analysis, with a predicted spectral angular distance of only 0.0340 and an rms error of 0.1759 for the abundance of endmembers. These results indicate that our network can provide high-precision asteroid spectral classification, albedo estimation, and composition analysis results. In addition, we utilized the platform to analyze and provide results for six asteroids.https://doi.org/10.3847/1538-3881/adb710AsteroidsMain belt asteroidsSpectroscopy |
| spellingShingle | Yijun Tang Yunxiao Jiang Yuxiang Feng Xiaoming Zhang Xiaojun Jiang Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation The Astronomical Journal Asteroids Main belt asteroids Spectroscopy |
| title | Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation |
| title_full | Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation |
| title_fullStr | Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation |
| title_full_unstemmed | Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation |
| title_short | Transformer-based Approach for Accurate Asteroid Spectra Taxonomy and Albedo Estimation |
| title_sort | transformer based approach for accurate asteroid spectra taxonomy and albedo estimation |
| topic | Asteroids Main belt asteroids Spectroscopy |
| url | https://doi.org/10.3847/1538-3881/adb710 |
| work_keys_str_mv | AT yijuntang transformerbasedapproachforaccurateasteroidspectrataxonomyandalbedoestimation AT yunxiaojiang transformerbasedapproachforaccurateasteroidspectrataxonomyandalbedoestimation AT yuxiangfeng transformerbasedapproachforaccurateasteroidspectrataxonomyandalbedoestimation AT xiaomingzhang transformerbasedapproachforaccurateasteroidspectrataxonomyandalbedoestimation AT xiaojunjiang transformerbasedapproachforaccurateasteroidspectrataxonomyandalbedoestimation |