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arXiv 1805.04519astro-ph.SR
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从亮度变化推断恒星参数

Inference of stellar parameters from brightness variations

Melissa K. Ness, Victor Silva Aguirre, Mikkel N. Lund, Matteo Cantiello, Daniel Foreman-Mackey, David W. Hogg, Ruth Angus

摘要:

已经证明,恒星亮度在不同频率下的时间变化可以用来推断其表面重力、半径、质量和年龄。随着开普勒和K2的大量光变曲线样本以及即将到来的TESS调查,我们希望量化这些数据的整体信息内容并确定信息所在的位置。作为对这个问题的第一次研究,我们问我们可以从红巨星数据中的亮度变化预测哪些恒星参数,以及使用数据驱动模型的精度。我们证明了2000颗红巨星的长节奏(30分钟)开普勒光变曲线可以用来预测它们的$T_{\rm eff}$和$\log g$。我们的推断利用了光变曲线的自相关函数(ACF)的一部分的数据驱动模型,在那里我们将恒星参数和ACF像素值之间的多项式关系进行了建模。我们发现,这个模型,使用1000颗恒星训练,可以用来恢复温度$T_{\rm eff}$ $<$ 100 K,表面重力$<$ 0.1 dex,和星震功率谱参数$\rm ν_{max}$和$\rm Δν$ $<11$ $μ$ Hz和$<0.9$ $μ$ Hz($\lesssim$ 15\%)。我们从0.045 $<$ $T_{\rm lag}$ $<$ 370天的时滞范围恢复$T_{\rm eff}$,从0.045 $<$ $T_{\rm lag}$ $<$ 35天的时滞范围恢复$\log g$、$\rm ν_{max}$和$\rm Δν$。我们没有发现任何有关恒星金属丰度的信息。关于每个参数的数据的信息内容是经验性地量化使用这种方法,使对流造粒的理论预期的比较。

英文摘要:

It has been demonstrated that the time variability of a star's brightness at different frequencies can be used to infer its surface gravity, radius, mass, and age. With large samples of light curves now available from Kepler and K2, and upcoming surveys like TESS, we wish to quantify the overall information content of this data and identify where the information resides. As a first look into this question we ask which stellar parameters we can predict from the brightness variations in red-giant stars data and to what precision, using a data-driven model. We demonstrate that the long-cadence (30-minute) Kepler light curves for 2000 red-giant stars can be used to predict their $T_{\rm eff}$ and $\log g$. Our inference makes use of a data-driven model of a part of the autocorrelation function (ACF) of the light curve, where we posit a polynomial relationship between stellar parameters and the ACF pixel values. We find that this model, trained using 1000 stars, can be used to recover the temperature $T_{\rm eff}$ to $<$100 K, the surface gravity to $<$ 0.1 dex, and the asteroseismic power-spectrum parameters $\rm ν_{max}$ and $\rm Δν$ to $<11$ $μ$Hz and $<0.9$ $μ$Hz ($\lesssim$ 15\%). We recover $T_{\rm eff}$ from range of time-lags 0.045 $<$ $T_{\rm lag}$ $<$ 370 days and the $\log g$, $\rm ν_{max}$ and $\rm Δν$ from the range 0.045 $<$ $T_{\rm lag}$ $<$ 35 days. We do not discover any information about stellar metallicity. The information content of the data about each parameter is empirically quantified using this method, enabling comparisons to theoretical expectations about convective granulation.

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