2022 Fiscal Year Final Research Report
Study of Distant Galaxy Morphology Using Subaru Telescope Wide-Area Survey Data
| Project/Area Number |
20K14508
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 16010:Astronomy-related
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| Research Institution | Kitami Institute of Technology |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | 銀河形態 / 遠方銀河 / すばる望遠鏡 |
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| Outline of Final Research Achievements |
In this study, we have investigated morphological properties of distant and rare galaxies using multiple image processing techniques to enhance the spatial resolution of images taken by the Hyper Suprime-Cam (HSC), a wide-field camera on the Subaru Telescope. We have established procedures for enhancing low-spatial resolution HSC images in three image processing methods: the point spread function (PSF) deconvolution method (a classical approach), sparse modeling that incorporates sparsity and smoothness constraints into the classical approach, and the generative adversarial network. By leveraging the high-spatial resolution HSC images obtained through these processes and the wide survey coverage of the HSC survey data, we have revealed impacts of galaxy mergers on the formation and evolution of distant and rare galaxies.
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| Free Research Field |
天文学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で，画像高解像度化の技術と広領域探査データを組み合わせ，遠方希少銀河の形態を調べる手法を確立できた．本手法はジェームズウェッブ宇宙望遠鏡のデータに応用可能であり，赤方偏移z>7の宇宙最初期の銀河形態研究を展開できると期待される．また，機械学習による銀河形態研究の一環として，HSC画像から銀河の半光度半径などの銀河形態パラメータを推定する，機械学習ソフトウェアを開発した．本ソフトウェアは，将来の地上広領域探査で得られる，大規模銀河サンプルの銀河形態パラメータを高速に推定するための有用なツールになると考えられる．
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