Data processing on simulated data for SHARK-NIR.

E. Carolo, D. Vassallo, J. Farinato, G. Agapito, M. Bergomi, A. Carlotti, M. D. Pascale, V. D’Orazi, D. Greggio, D. Magrin, L. Marafatto, D. Mesa, E. Pinna, A. Puglisi, M. Stangalini, C. Vérinaud, V. Viotto, F. Biondi, S. Chinellato, M. Dima, S. Esposito, F. Pedichini, E. Portaluri, R. Ragazzoni, G. Umbriaco
{"title":"Data processing on simulated data for SHARK-NIR.","authors":"E. Carolo, D. Vassallo, J. Farinato, G. Agapito, M. Bergomi, A. Carlotti, M. D. Pascale, V. D’Orazi, D. Greggio, D. Magrin, L. Marafatto, D. Mesa, E. Pinna, A. Puglisi, M. Stangalini, C. Vérinaud, V. Viotto, F. Biondi, S. Chinellato, M. Dima, S. Esposito, F. Pedichini, E. Portaluri, R. Ragazzoni, G. Umbriaco","doi":"10.26698/AO4ELT5.0068","DOIUrl":null,"url":null,"abstract":"A robust post processing technique is mandatory to analyse the coronagraphic high contrast imaging data. Angular Differential Imaging (ADI) and Principal Component Analysis (PCA) are the most used approaches to suppress the quasi-static structure in the Point Spread Function (PSF) in order to revealing planets at different separations from the host star. The focus of this work is to apply these two data reduction techniques to obtain the best limit detection for each coronagraphic setting that has been simulated for the SHARK-NIR, a coronagraphic camera that will be implemented at the Large Binocular Telescope (LBT). We investigated different seeing conditions ($0.4\"-1\"$) for stellar magnitude ranging from R=6 to R=14, with particular care in finding the best compromise between quasi-static speckle subtraction and planet detection.","PeriodicalId":8428,"journal":{"name":"arXiv: Earth and Planetary Astrophysics","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv: Earth and Planetary Astrophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26698/AO4ELT5.0068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

A robust post processing technique is mandatory to analyse the coronagraphic high contrast imaging data. Angular Differential Imaging (ADI) and Principal Component Analysis (PCA) are the most used approaches to suppress the quasi-static structure in the Point Spread Function (PSF) in order to revealing planets at different separations from the host star. The focus of this work is to apply these two data reduction techniques to obtain the best limit detection for each coronagraphic setting that has been simulated for the SHARK-NIR, a coronagraphic camera that will be implemented at the Large Binocular Telescope (LBT). We investigated different seeing conditions ($0.4"-1"$) for stellar magnitude ranging from R=6 to R=14, with particular care in finding the best compromise between quasi-static speckle subtraction and planet detection.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
SHARK-NIR模拟数据的数据处理。
一个强大的后处理技术是必要的,以分析日冕的高对比度成像数据。角差成像(ADI)和主成分分析(PCA)是抑制点扩散函数(PSF)中的准静态结构以揭示与主星不同距离的行星的最常用方法。这项工作的重点是应用这两种数据简化技术,以获得每个日冕仪设置的最佳极限检测,这些设置已经为SHARK-NIR模拟,这是一种将在大型双筒望远镜(LBT)上实施的日冕仪相机。我们研究了从R=6到R=14的恒星星等的不同观测条件($0.4"-1"$),特别注意寻找准静态散斑减法和行星探测之间的最佳折衷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Revisiting The Averaged Problem in The Case of Mean-Motion Resonances of The Restricted Three-Body Problem. Global Rigorous Treatment and Application To The Co-Orbital Motion. Automatic planetary defense Deflecting NEOs by missiles shot from L1 and L3 (Earth-Moon). Modeling the nonaxisymmetric structure in the HD 163296 disk with planet-disk interaction Origin and dynamical evolution of the asteroid belt Revised planet brightness temperatures using the Planck/LFI 2018 data release
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1