REPUBLIC: PLATO 多相机光曲线的可变性保护系统校正算法

Oscar Barrag'an, S. Aigrain, J. McCormac
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引用次数: 0

摘要

天基光度测量任务会产生精美的光曲线,其中包含了大量时间尺度上的恒星变异性。光曲线通常还包含大量的仪器系统学信息,即许多光曲线在不同程度上普遍存在的虚假、非物理趋势。利用光曲线本身的信息进行经验系统性校正的方法非常成功,但往往会抑制天体物理信号,尤其是在较长的时间尺度上。与之前的任务不同,PLATO 任务将使用多台照相机来监测同一颗恒星。我们提出的 REPUBLIC 是一种新颖的系统学校正算法,它利用这种多照相机配置来校正不同照相机之间的系统学差异,同时保留每颗恒星信号中所有照相机(无论时间尺度如何)所共有的部分。通过模拟天体物理信号(星斑和行星凌日)、开普勒类似误差和白噪声,我们证明 REPUBLIC 能够保留通常在标准校正技术中丢失的长期天体物理信号。我们还探讨了 REPUBLIC 在不同相机数量和系统特性下的性能。我们的结论是,应将 REPUBLIC 视为现有多相机巡天系统校正策略的潜在补充,其效用取决于进一步验证和适应 PLATO 任务数据的具体特征。
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REPUBLIC: A variability-preserving systematic-correction algorithm for PLATO’s multi-camera light curves
Space-based photometry missions produce exquisite light curves that contain a wealth of stellar variability on a wide range of timescales. Light curves also typically contain significant instrumental systematics – spurious, non-astrophysical trends that are common, in varying degrees, to many light curves. Empirical systematics-correction approaches using the information in the light curves themselves have been very successful, but tend to suppress astrophysical signals, particularly on longer timescales. Unlike its predecessors, the PLATO mission will use multiple cameras to monitor the same stars. We present REPUBLIC, a novel systematics-correction algorithm which exploits this multi-camera configuration to correct systematics that differ between cameras, while preserving the component of each star’s signal that is common to all cameras, regardless of timescale. Through simulations with astrophysical signals (star spots and planetary transits), Kepler-like errors, and white noise, we demonstrate REPUBLIC’s ability to preserve long-term astrophysical signals usually lost in standard correction techniques. We also explore REPUBLIC’s performance with different number of cameras and systematic properties. We conclude that REPUBLIC should be considered a potential complement to existing strategies for systematic correction in multi-camera surveys, with its utility contingent upon further validation and adaptation to the specific characteristics of the PLATO mission data.
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Classifying LEO satellite platforms with boosted decision trees PyExoCross: a Python program for generating spectra and cross sections from molecular line lists The verification of periodicity with the use of recurrent neural networks REPUBLIC: A variability-preserving systematic-correction algorithm for PLATO’s multi-camera light curves A simple spacecraft – vector intersection methodology and applications
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