arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.05799astro-ph.IMastro-ph.EPastro-ph.SRphysics.data-an
收藏

A Fast, 2D Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization

Tyler Gordon, Eric Agol, Daniel Foreman-Mackey

英文摘要:

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 datapoints 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 datapoints 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑