文献类型： 会议论文
第一作者： Katelyn Gan
作者： Katelyn Gan 1 ; Vinesh Maguire Rajpaul 2 ;
作者机构： 1.Sage Hill School, Newport Beach, California, USA
2.Astrophysics Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK
关键词： Computer vision;Frequency-domain analysis;Exoplanet;Robustness;Data mining;Standards
会议名称： IEEE MIT Undergraduate Research Technology Conference
主办单位：
页码： 1-5
摘要： For many decades, cross-correlating spectral data with a template mask has been the standard approach to radial velocity (RV) extraction for exoplanet detection. In this proof-of-concept paper, we present a novel approach that utilizes computer vision (CV) techniques to analyze stellar spectra and accurately extract RVs. We tested our method on four real stellar data sets and found that it yields results comparable to an industry-standard, chunk-by-chunk (CBC) method in both time and frequency domains, with remarkable robustness and speed. This CV technique could enable the detection of exoplanets that are currently difficult to detect due to stellar variability and activity.
分类号： tp3-53
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