{"title":"利用多历元最大似然估计超新星残留物的运动学:以仙后座 A 的钱德拉观测为例","authors":"Yusuke Sakai, Shinya Yamada, Toshiki Sato, Ryota Hayakawa and Nao Kominato","doi":"10.3847/1538-4357/ad739f","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":501813,"journal":{"name":"The Astrophysical Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example\",\"authors\":\"Yusuke Sakai, Shinya Yamada, Toshiki Sato, Ryota Hayakawa and Nao Kominato\",\"doi\":\"10.3847/1538-4357/ad739f\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":501813,\"journal\":{\"name\":\"The Astrophysical Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Astrophysical Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3847/1538-4357/ad739f\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Astrophysical Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3847/1538-4357/ad739f","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
利用多历元最大似然估计(MLE)方法分析了附近一颗超新星遗迹(SNR)的十年变化。为了更准确地捕捉 SNR 的动态变化,将运动学特征和点展函数效应纳入了 MLE 框架。以仙后座 A 为代表,利用了钱德拉 X 射线天文台在 2000 年、2009 年和 2019 年获得的数据。从定性和定量的角度证明了所提出的多历元 MLE 能够准确估计所有区域的各种运动,包括冲击波和微弱特征。为了研究非对称结构,如偏离扩展方向的奇异成分,对 MLE 方法进行了扩展,以结合多个计算域,并使用 k-means 算法对运动特性进行分类。这种方法可以将不同的物理状态映射到图像上,通过与詹姆斯-韦伯太空望远镜的红外观测数据进行比较,发现一个被分类的成分与周星体物质相互作用。因此,这项技术将有助于量化SNR的动态,发现其独特的演化过程。
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 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.