利用 VLT/SPHERE 进行多参考星差分成像

IF 5.4 2区 物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS
C. Romero, J. Milli, A.-M. Lagrange, R. De Rosa, S. Ertel, C. del Burgo
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引用次数: 0

摘要

背景。高对比度成像观测主要依靠角差分成像,这是一种成功的探测点源(如行星)的技术。然而,在恒星附近(通常低于 300mas),如果没有足够的场旋转,这种技术就会受到信号自减的影响。从档案数据中建立大型参考恒星库,然后用于优化减去恒星晕,这是一种强大的技术,被称为参考恒星差分成像(RSDI),可以克服这一局限。我们的目的是研究在对 VLT/SPHERE 数据进行参考星差分成像时创建由多颗恒星组成的参考库的新方法。为此,我们使用了 SPHERE 高角分辨率碎片盘巡天(SHARDDS)的数据集,该数据集由 2015-2016 年期间用红外双波段成像仪和摄谱仪(IRDIS)在宽波段 H 波段观测到的 55 个目标组成,共约 20 000 帧。我们将HD 206893作为一个基准科学目标,以展示这种方法所提供的更高灵敏度。我们根据不同的图像相似性指标创建了参考帧库:卷积神经网络创建的描述符之间的余弦距离、皮尔逊相关系数、结构相似性指数、Strehl 比率和原始对比度标准。我们使用主成分分析(PCA)来减去恒星光环,并测试了各种归一化选项。我们使用皮尔逊相关系数(PCC)对 245 至 612 马斯之间的环形区域进行筛选,从而在 HD 206893 B 上获得了最佳信噪比(S/N)。在亚恒星伴星HD 206893 B上信噪比最高的十个参考库都是基于皮尔逊相关系数方法,优于其他相似性指标。虽然施特莱尔比是与对比度最相关的环境变量,但它不足以选出相似的图像。我们还表明,在参考库中拥有多个参考星比使用一个精心挑选的参考星能产生更好的结果。在应用参考星差分成像时,使用在特定感兴趣区域计算的皮尔逊相关性来选择参考帧是提高微弱点源可探测性的一种有前途的替代方法。今后,利用这种技术减少 SPHERE 档案中的所有可用数据,可能会为寻找以前未探测到的行星提供有趣的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple reference star differential imaging with VLT/SPHERE
Context. High-contrast imaging observations mostly rely on angular differential imaging, a successful technique for detecting point-sources, such as planets. However, in the vicinity of the star (typically below 300 mas), this technique suffers from signal self-subtraction when there is not enough field rotation. Building large libraries of reference stars from archival data later used to optimally subtract the stellar halo is a powerful technique known as reference star differential imaging (RSDI) that can overcome this limitation.Aims. We aim at investigating new methods for creating reference libraries composed of multiple stars when applying reference star differential imaging to VLT/SPHERE data. We used for that purpose a data set from the SPHERE High Angular Resolution Debris Disk Survey (SHARDDS), composed of 55 targets observed in broad-band H with the InfraRed Dual-band Imager and Spectrograph (IRDIS) during 2015-2016, with a total of ~20 000 frames. We consider HD 206893, known to host a close-in bound substellar companion HD 206893 B, as a benchmark science target to demonstrate the improved sensitivity provided by this method.Methods. We created libraries of reference frames based on different image similarity metrics: the cosine distance between descriptors created by a convolutional neural network, the Pearson correlation coefficient, the Structural Similarity Index, the Strehl ratio, and raw contrast criteria. We used principal component analysis (PCA) to subtract the stellar halo and tested various normalization options.Results. We obtained the best signal-to-noise ratio (S/N) on HD 206893 B by using the Pearson correlation coefficient (PCC) applied to an annulus between 245 and 612 mas to select reference frames. The ten reference libraries with the highest S/N on the substellar companion HD 206893 B were all based on the PCC method, outperforming other similarity metrics. While the Strehl ratio is the environment variable most correlated to the contrast, it is insufficient to select similar images. We also show that having multiple reference stars in the reference library produces better results than using a single well-chosen reference star.Conclusions. Using the Pearson correlation computed on a specific area of interest to select reference frames is a promising alternative to improve the detectability of faint point-sources when applying reference star differential imaging. In the future, reducing all the data available in the SPHERE archive using this technique might offer interesting results in the search for previously undetected planets.
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来源期刊
Astronomy & Astrophysics
Astronomy & Astrophysics 地学天文-天文与天体物理
CiteScore
10.20
自引率
27.70%
发文量
2105
审稿时长
1-2 weeks
期刊介绍: Astronomy & Astrophysics is an international Journal that publishes papers on all aspects of astronomy and astrophysics (theoretical, observational, and instrumental) independently of the techniques used to obtain the results.
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