论文标题
拥挤的苔丝光度法中的可变性来源
Localizing Sources of Variability in Crowded TESS Photometry
论文作者
论文摘要
过渡外行外运动卫星（TESS）具有非常大的21英寸/px板尺度，使大多数苔丝光曲线记录了多颗恒星的混合光。这造成了苔丝观察到的变异性错误的危险，使得对错误的来源进行了错误的差异，这将使任何频繁地分析。观察到的可变性（例如，从周期图分析中，我们表明，从每个像素中提取的原始光曲线的最佳拟合正弦幅度与此方法的主要假设相同，因此附近的其他恒星的主要频率是相同频率的限制。 python软件包，苔丝（github.com/higgins00/tess-localize），确定了给定苔丝像素数据的可变源的位置，以及一组观察到的频率，我们的方法利用了苔丝像素响应模型。验证观察到的可变性的来源应该是苔丝分析的标准步骤。
The Transiting Exoplanet Survey Satellite (TESS) has an exceptionally large plate scale of 21"/px, causing most TESS light curves to record the blended light of multiple stars. This creates a danger of misattributing variability observed by TESS to the wrong source, which would invalidate any analysis. We develop a method that can localize the origin of variability on the sky to better than one fifth of a pixel. Given measured frequencies of observed variability (e.g., from periodogram analysis), we show that the corresponding best-fit sinusoid amplitudes to raw light curves extracted from each pixel are distributed the same as light from the variable source. The primary assumption of this method is that other nearby stars are not variable at the same frequencies. Essentially, we are using the high frequency resolution of TESS to overcome limitations from its low spatial resolution. We have implemented our method in an open source Python package, TESS Localize (github.com/Higgins00/TESS-Localize), that determines the location of a variable source on the sky given TESS pixel data and a set of observed frequencies of variability. Our method utilizes the TESS Pixel Response Function models, and we characterize systematics in the residuals of fitting these models to data. Given the ubiquity of source blending in TESS light curves, verifying the source of observed variability should be a standard step in TESS analyses.
