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GPI PSF subtraction with TLOCI: the next evolution in exoplanet/disk high-contrast imaging

机译:用TLOCI进行GPI PSF减法:系外行星/磁盘高对比度成像的下一步发展

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To directly image exoplanets and faint circumstellar disks, the noisy stellar halo must be suppressed to a high level. To achieve this feat, the angular differential imaging observing technique and the least-squares Locally Optimized Combination of Images (LOCI) algorithm have now become the standard in single band direct imaging observations and data reduction. With the development and commissioning of new high-order high-contrast adaptive optics equipped with integral field units, the image subtraction algorithm needs to be modified to allow the optimal use of polychromatic images, field-rotated images and archival data. A new algorithm, TLOCI (for Template LOCI), is designed to achieve this task by maximizing a companion signal-to-noise ratio instead of simply minimizing the noise as in the original LOCI algorithm. The TLOCI technique uses an input spectrum and template Point Spread Functions (PSFs, generated from unocculted and unsaturated stellar images) to optimize the reference image least-squares coefficients to minimize the planet self-subtraction, thus maximizing its throughput per wavelength, while simultaneously providing a maximum suppression of the speckle noise. The new algorithm has been developed using on-sky GPI data and has achieved impressive contrast. This paper presents the TLOCI algorithm, on-sky performance, and will discuss the challenges in recovering the planet spectrum with high fidelity.
机译:要直接对系外行星和微弱的星际盘成像,必须将嘈杂的恒星光晕抑制到很高的水平。为了实现这一壮举,角度差分成像观测技术和最小二乘图像局部优化组合(LOCI)算法现在已成为单波段直接成像观察和数据精简的标准。随着新型高阶高对比度自适应光学元件的开发和调试,该光学元件具有集成的场单元,需要对图像减法算法进行修改,以最佳利用多色图像,场旋转图像和档案数据。一种新的算法TLOCI(用于模板LOCI)旨在通过最大化伴随的信噪比而不是像原始LOCI算法那样简单地将噪声最小化来实现此任务。 TLOCI技术使用输入光谱和模板点扩展函数(PSF,由隐匿和非饱和恒星图像生成)来优化参考图像的最小二乘系数,以最小化行星的自减,从而在每个波长下最大化其吞吐量,同时提供最大程度地抑制了斑点噪声。该新算法是使用空中GPI数据开发的,并取得了令人印象深刻的对比度。本文介绍了TLOCI算法的天空性能,并将讨论以高保真度恢复行星光谱的挑战。

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