Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example
Decadal changes in a nearby supernova remnant (SNR) were analyzed using a multiepoch maximum likelihood estimation (MLE) approach. To achieve greater accuracy in capturing the dynamics of SNRs, kinematic features and point-spread function effects were integrated into the MLE framework. Using Cassiop...
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IOP Publishing
2024-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/ad739f |
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| author | Yusuke Sakai Shinya Yamada Toshiki Sato Ryota Hayakawa Nao Kominato |
| author_facet | Yusuke Sakai Shinya Yamada Toshiki Sato Ryota Hayakawa Nao Kominato |
| author_sort | Yusuke Sakai |
| collection | DOAJ |
| description | Decadal changes in a nearby supernova remnant (SNR) were analyzed using a multiepoch maximum likelihood estimation (MLE) approach. To achieve greater accuracy in capturing the dynamics of SNRs, kinematic features and point-spread function effects were integrated into the MLE framework. Using Cassiopeia A as a representative example, data obtained by the Chandra X-ray Observatory in 2000, 2009, and 2019 were utilized. The proposed multiepoch MLE was qualitatively and quantitatively demonstrated to provide accurate estimates of various motions, including shock waves and faint features, across all regions. To investigate asymmetric structures, such as singular components that deviate from the direction of expansion, the MLE method was extended to combine multiple computational domains and classify kinematic properties using the k -means algorithm. This approach allowed for the mapping of different physical states onto the image, and one classified component was suggested to interact with circumstellar material by comparison with infrared observations from the James Webb Space Telescope. Thus, this technique will help quantify the dynamics of SNRs and discover their unique evolution. |
| format | Article |
| id | doaj-art-ba020fb5f2354ee19d0129dcab74b74b |
| institution | OA Journals |
| issn | 1538-4357 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
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| series | The Astrophysical Journal |
| spelling | doaj-art-ba020fb5f2354ee19d0129dcab74b74b2025-08-20T01:47:38ZengIOP PublishingThe Astrophysical Journal1538-43572024-01-01974224510.3847/1538-4357/ad739fKinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an ExampleYusuke Sakai0https://orcid.org/0000-0002-5809-3516Shinya Yamada1https://orcid.org/0000-0003-4808-893XToshiki Sato2https://orcid.org/0000-0001-9267-1693Ryota Hayakawa3https://orcid.org/0000-0002-3752-0048Nao Kominato4https://orcid.org/0000-0001-8335-1057Department of Physics, Rikkyo University , Toshima-Ku, Tokyo, 171-8501, JapanDepartment of Physics, Rikkyo University , Toshima-Ku, Tokyo, 171-8501, JapanDepartment of Physics, School of Science and Technology, Meiji University , 1-1-1 Higashi Mita, Tama-ku, Kawasaki, Kanagawa 214-8571, JapanInternational Center for Quantum-field Measurement Systems for Studies of the Universe and Particles (QUP) , KEK, 1-1 Oho, Tsukuba, Ibaraki 305-0801, JapanDepartment of Physics, Rikkyo University , Toshima-Ku, Tokyo, 171-8501, JapanDecadal changes in a nearby supernova remnant (SNR) were analyzed using a multiepoch maximum likelihood estimation (MLE) approach. To achieve greater accuracy in capturing the dynamics of SNRs, kinematic features and point-spread function effects were integrated into the MLE framework. Using Cassiopeia A as a representative example, data obtained by the Chandra X-ray Observatory in 2000, 2009, and 2019 were utilized. The proposed multiepoch MLE was qualitatively and quantitatively demonstrated to provide accurate estimates of various motions, including shock waves and faint features, across all regions. To investigate asymmetric structures, such as singular components that deviate from the direction of expansion, the MLE method was extended to combine multiple computational domains and classify kinematic properties using the k -means algorithm. This approach allowed for the mapping of different physical states onto the image, and one classified component was suggested to interact with circumstellar material by comparison with infrared observations from the James Webb Space Telescope. Thus, this technique will help quantify the dynamics of SNRs and discover their unique evolution.https://doi.org/10.3847/1538-4357/ad739fSupernova remnantsAstronomy data analysisAstronomy image processingProper motionsX-ray astronomy |
| spellingShingle | Yusuke Sakai Shinya Yamada Toshiki Sato Ryota Hayakawa Nao Kominato Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example The Astrophysical Journal Supernova remnants Astronomy data analysis Astronomy image processing Proper motions X-ray astronomy |
| title | Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example |
| title_full | Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example |
| title_fullStr | Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example |
| title_full_unstemmed | Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example |
| title_short | Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example |
| title_sort | kinematics of supernova remnants using multiepoch maximum likelihood estimation chandra observation of cassiopeia a as an example |
| topic | Supernova remnants Astronomy data analysis Astronomy image processing Proper motions X-ray astronomy |
| url | https://doi.org/10.3847/1538-4357/ad739f |
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