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Application of data science techniques to disentangle of X-ray spectral variation of super-massive black holes
https://doi.org/10.20637/JAXA-RR-16-007/0007
https://doi.org/10.20637/JAXA-RR-16-007/00076f57423a-563f-4b5d-8ad0-7bf968ceeeab
名前 / ファイル | ライセンス | アクション |
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Item type | テクニカルレポート / Technical Report(1) | |||||
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公開日 | 2017-04-20 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Application of data science techniques to disentangle of X-ray spectral variation of super-massive black holes | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||
資源タイプ | technical report | |||||
ID登録 | ||||||
ID登録 | 10.20637/JAXA-RR-16-007/0007 | |||||
ID登録タイプ | JaLC | |||||
著者 |
Pike, Sean
× Pike, Sean× 海老沢, 研× 池田, 思朗× 森井, 幹雄× 水本, 岬希× 楠, 絵莉子× Pike, Sean× Ebisawa, Ken× Ikeda, Shiro× Morii, Mikio× Mizumoto, Misaki× Kusunoki, Eriko |
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著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS) | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS) | ||||||
著者所属 | ||||||
統計数理研究所 | ||||||
著者所属 | ||||||
統計数理研究所 | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS) | ||||||
著者所属 | ||||||
宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Statistical Mathematics, Japan | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Statistical Mathematics, Japan | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
著者所属(英) | ||||||
en | ||||||
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS) | ||||||
出版者 | ||||||
出版者 | 宇宙航空研究開発機構(JAXA) | |||||
出版者(英) | ||||||
出版者 | Japan Aerospace Exploration Agency (JAXA) | |||||
書誌情報 |
宇宙航空研究開発機構研究開発報告: 宇宙科学情報解析論文誌: 第6号 en : JAXA Research and Development Report: Journal of Space Science Informatics Japan: Volume 6 巻 JAXA-RR-16-007, p. 73-87, 発行日 2017-03-17 |
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抄録(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | We apply three data science techniques, Nonnegative Matrix Factorization (NMF), Principal Component Analysis (PCA) and Independent Component Analysis (ICA), to simulated X-ray energy spectra of a particular class of super-massive black holes. Two competing physical models, one whose variable components are additive and the other whose variable components are multiplicative, are known to successfully describe X-ray spectral variation of these super-massive black holes, within accuracy of the contemporary observation. We hope to utilize these techniques to compare the viability of the models by probing the mathematical structure of the observed spectra, while comparing advantages and disadvantages of each technique. We find that PCA is best to determine the dimensionality of a dataset, while NMF is better suited for interpreting spectral components and comparing them in terms of the physical models in question. ICA is able to reconstruct the parameters responsible for spectral variation. In addition, we find that the results of these techniques are sufficiently different that applying them to observed data may be a useful test in comparing the accuracy of the two spectral models. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 形態: カラー図版あり | |||||
内容記述(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | Physical characteristics: Original contains color illustrations | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1349-1113 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA1192675X | |||||
資料番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 資料番号: AA1630049007 | |||||
レポート番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | レポート番号: JAXA-RR-16-007 |