Lucky imaging and speckle discrimination for the detection of faint companions with adaptive optics

Lucky imaging and speckle discrimination for the detection of faint companions with adaptive optics
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利用自适应光学器件检测微弱伴星的幸运成像和散斑辨别

DOI:
10.1117/12.788442
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发表时间:
2008
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通讯作者:
Gladysz S
Gladysz S
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作者:
Gladysz S

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我们已经分析了帧选择(“幸运成像”)的应用,自适应光学(AO),短曝光观测微弱的同伴。我们已经使用瞬时Strehl比率作为图像质量度量。该量的概率密度函数(PDF)可用于确定在优化移位相加图像的Strehl比和峰值信噪比方面的帧选择的结果。在存在静态散斑的情况下,帧选择可以导致两种情况:分辨率的提高(由Strehl比量化)以及微弱信号的可检测性(由峰值信噪比给出)。这一理论预测证实了真实的数据从AO观测使用利克天文台的3米谢恩望远镜,和帕洛玛天文台的5米黑尔望远镜。此外,我们提出了一种新的基于几何学的技术,用于从AO校正曝光序列中检测微弱的同伴。该算法,我们称之为随机散斑歧视,利用“统计签名”的点扩散函数(PSF)的中心,以区分微弱的同伴和静态散斑。该技术即使对于在移位和相加图像中不可见的信号也会产生出色的结果。
We have analyzed the application of frame selection ("lucky imaging") to adaptive optics (AO), short-exposure observations of faint companions. We have used the instantaneous Strehl ratio as an image quality metric. The probability density function (PDF) of this quantity can be used to determine the outcome of frame selection in terms of optimizing the Strehl ratio and the peak-signal-to-noise-ratio of the shift-and-add image. In the presence of static speckles, frame selection can lead to both: improvement in resolution--as quantified by the Strehl ratio, as well as faint signal detectability--given by the peak-signal-to-noise-ratio. This theoretical prediction is confirmed with real data from AO observations using Lick Observatory's 3m Shane telescope, and the Palomar Observatory's 5m Hale telescope. In addition, we propose a novel statistics-based technique for the detection of faint companions from a sequence of AO-corrected exposures. The algorithm, which we call stochastic speckle discrimination, utilizes the "statistical signature" of the centre of the point spread function (PSF) to discriminate between faint companions and static speckles. The technique yields excellent results even for signals invisible in the shift-and-add images.
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