通过地震反演估算恒星平均密度
Estimating stellar mean density through seismic inversions
摘要：
确定恒星的质量对于改进恒星演化理论和描述系外行星系统都是至关重要的。星震学提供了一种估计恒星平均密度的有希望的方法。当结合精确的半径测定，如预期从盖亚，这产生准确的恒星质量。主要的困难是找到最好的方法来提取平均密度从一组观察到的频率。我们试图建立一个新的方法来估计恒星的平均密度，它结合了简单的标度律，同时提供反演技术的准确性。我们提供了一个框架，在其中构建和评估基于核的线性反演直接产生的平均密度的一颗星。然后，我们描述了三种不同的反演技术（SOLA和两个标度律），并将其应用到太阳，几个测试案例和三颗恒星。SOLA方法和基于Kjeldsen等人（2008年）描述的表面校正技术的标度律产生可比较的结果，其可以达到0.5%的精度，并且优于标度大频率分离。其原因在于，来自前两种方法的平均核在质量上是相当的，并且比用大频率分离获得的平均核更好。研究还表明，缩放大频率间隔对近表面效应更敏感，但受不正确模式识别的影响要小得多。因此，人们可以通过寻找l和n分配来识别脉动模式，该分配提供了来自大频率分离的结果与来自两种其他方法之一的结果之间的最佳一致性。非线性效应也被讨论，是混合模式的影响。特别是，它表明，混合模式带来的改善不大，由于他们的适应性差的内核。
英文摘要：
Determining the mass of stars is crucial both to improving stellar evolution theory and to characterising exoplanetary systems. Asteroseismology offers a promising way to estimate stellar mean density. When combined with accurate radii determinations, such as is expected from GAIA, this yields accurate stellar masses. The main difficulty is finding the best way to extract the mean density from a set of observed frequencies. We seek to establish a new method for estimating stellar mean density, which combines the simplicity of a scaling law while providing the accuracy of an inversion technique. We provide a framework in which to construct and evaluate kernel-based linear inversions which yield directly the mean density of a star. We then describe three different inversion techniques (SOLA and two scaling laws) and apply them to the sun, several test cases and three stars. The SOLA approach and the scaling law based on the surface correcting technique described by Kjeldsen et al. (2008) yield comparable results which can reach an accuracy of 0.5 % and are better than scaling the large frequency separation. The reason for this is that the averaging kernels from the two first methods are comparable in quality and are better than what is obtained with the large frequency separation. It is also shown that scaling the large frequency separation is more sensitive to near-surface effects, but is much less affected by an incorrect mode identification. As a result, one can identify pulsation modes by looking for an l and n assignment which provides the best agreement between the results from the large frequency separation and those from one of the two other methods. Non-linear effects are also discussed as is the effects of mixed modes. In particular, it is shown that mixed modes bring little improvement as a result of their poorly adapted kernels.
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