论文标题
测量恒星倾向的自动化方法:通过对红色巨型分支的大规模测量进行验证
Automated approach to measure stellar inclinations: validation through large-scale measurements on the red giant branch
论文作者
论文摘要
测量恒星倾向是了解行星形成和动力学以及恒星形成过程中的身体状况至关重要的。红色巨星的振荡光谱表现出混合模式,这些模式既有来自辐射内部的重力成分,又具有对流包膜的压力成分。通过旋转分裂的重力为主导的(G-M)混合模式在频谱内部良好分开,从而使恒星倾斜的准确测量可能。这项工作旨在开发一种自动化和一般的方法来测量恒星倾斜,可以应用于确定振荡模式的任何太阳能脉动器,并使用开普勒观察到的红色巨型分支恒星对其进行验证。我们使用带有不同方位角订单的偶极子混合模式的平均身高与背景比来测量恒星倾斜。使用恒星倾斜角的概率密度函数以公正的方式回收倾斜的基本统计分布。我们得出了红色巨型分支上1139颗恒星的出色倾斜度测量,Gehan等人为此。 (2018)已经确定了偶极子G-M混合模式的方位角顺序。原始测量的倾斜相对于各向同性表现出强偏差,这对于天空上的随机倾向有望。考虑到不确定性时,倾斜的重建分布实际上遵循旋转轴的预期各向同性分布。这项工作突出了影响倾斜度测量的偏见,并提供了推断其基本统计分布的方法。当看到恒星启动或赤道时,测量值具有挑战性,并导致偏置分布。纠正出现在低和高倾斜度上的偏见使我们能够恢复潜在的倾斜度分布。
Measuring stellar inclinations is fundamental to understand planetary formation and dynamics as well as physical conditions during star formation. Oscillation spectra of red giant stars exhibit mixed modes that have both a gravity component from the radiative interior and a pressure component from the convective envelope. Gravity-dominated (g-m) mixed modes split by rotation are well separated inside frequency spectra, making possible accurate measurements of stellar inclinations. This work aims at developing an automated and general approach to measure stellar inclinations, that can be applied to any solar-type pulsator for which oscillation modes are identified, and at validating it using red giant branch stars observed by Kepler. We use the mean height-to-background ratio of dipole mixed modes with different azimuthal orders to measure stellar inclinations. The underlying statistical distribution of inclinations is recovered in an unbiased way using a probability density function for the stellar inclination angle. We derive stellar inclination measurements for 1139 stars on the red giant branch, for which Gehan et al. (2018) have identified the azimuthal order of dipole g-m mixed modes. Raw measured inclinations exhibit strong deviation with respect to isotropy which is expected for random inclinations over the sky. When taking uncertainties into account, the reconstructed distribution of inclinations actually follows the expected isotropic distribution of the rotational axis. This work highlights the biases that affect inclination measurements and provides the way to infer their underlying statistical distribution. When the star is seen either pole-on or equator-on, measurements are challenging and result in a biased distribution. Correcting biases that appear at the low- and high inclination regimes allows us to recover the underlying inclination distribution.