A Fast, Two-dimensional Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization
A Fast, Two-dimensional Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization
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DOI：
10.3847/1538-3881/abbc16
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发表时间：
2020-07
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通讯作者：
Tyler A. Gordon;E. Agol;D. Foreman-Mackey
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作者：
Tyler A. Gordon;E. Agol;D. Foreman-Mackey
高斯过程是天体物理时间序列中常用的随机变率模型。特别是，GPS经常被用来解释行星凌日光变曲线中的相关恒星变化。GP方法的最新进展（包括celerite方法）使GP在含有数千至数万个数据点的光变曲线中的有效应用成为可能。在这里，我们提出了一个扩展的celerite方法的两个输入尺寸，通常情况下，第二维度是小的。当每个大维度中的噪声与相同的celerite内核成比例并且仅相关噪声的幅度在第二维度中变化时，该方法与数据点的总数线性缩放。我们证明了这种方法的应用，从多波长光变曲线测量精确的过境参数的问题，并表明它有可能提高过境参数测量的数量级。这种方法的应用包括凌日光谱学和系外卫星探测，以及更广泛的天文问题。
Gaussian processes (GPs) are commonly used as a model of stochastic variability in astrophysical time series. In particular, GPs are frequently employed to account for correlated stellar variability in planetary transit light curves. The efficient application of GPs to light curves containing thousands to tens of thousands of data points has been made possible by recent advances in GP methods, including the celerite method. Here we present an extension of the celerite method to two input dimensions where, typically, the second dimension is small. This method scales linearly with the total number of data points when the noise in each large dimension is proportional to the same celerite kernel and only the amplitude of the correlated noise varies in the second dimension. We demonstrate the application of this method to the problem of measuring precise transit parameters from multiwavelength light curves and show that it has the potential to improve transit parameters measurements by orders of magnitude. Applications of this method include transit spectroscopy and exomoon detection, as well a broader set of astronomical problems.