通过相位匹配进行的表面层独立模型拟合：理论和对HD49933和HD177153（aka Perky）的应用
Surface layer independent model fitting by phase matching: theory and application to HD49933 an HD177153 (aka Perky)
摘要：
目标。描述通过相位匹配进行表面层独立模型拟合的理论，并将其应用于CoRoT观测的恒星HD 49933和开普勒方法观测的恒星HD 177153（aka Perky）。我们使用理论分析，相移和模型拟合。结果我们定义了模型星的频率集的内、外相移，并证明了外相移（几乎）与度$\ell$无关，并且内相移的函数（相位函数）在外层坍缩为与频率无关的$\ell$函数.然后，我们将展示如何使用这个结果的模型拟合技术，找到一个最适合的模型，以观察到的频率集，通过计算内部相移的模型使用观察到的频率，并确定在何种程度上的相函数崩溃到一个单一的功能，在外层的频率。我们给出了两个例子，应用这种技术的频率集的HD49933观察到的CoRoT和HD177153（又名Perky）观测到的开普勒，并比较我们的结果与以前的研究，并表明它们是兼容的使用不同的技术。我们表明，可以有许多不同的模型，适合误差内的数据，需要更好的精度的频率来区分模型。我们比较了这种技术，使用小到大的分离比，表明在原则上，它是更准确的，避免了相关的分离比拟合误差的问题。
英文摘要：
Aims. To describe the theory of surface layer independent model fitting by phase matching and to apply this to the stars HD49933 observed by CoRoT, and HD177153 (aka Perky), observed by Kepler Methods. We use theoretical analysis, phase shifts, and model fitting. Results. We define the inner and outer phase shifts of a frequency set of a model star and show that the outer phase shifts are (almost) independent of degree $\ell$, and that a function of the inner phase shifts (the phase function) collapses to an $\ell$ independent function of frequency in the outer layers. We then show how to use this result in a model fitting technique to find a best fit model to an observed frequency set by calculating the inner phase shifts of a model using the observed frequencies and determining the extent to which the phase function collapses to a single function of frequency in the outer layers. We give two examples applying this technique to the frequency sets of HD49933 observed by CoRoT and HD177153 (aka Perky) observed by Kepler, and compare our results with those of previous studies and show that they are compatible with those obtained using different techniques. We show that there can be many different models that fit the data within the errors and that better precision on the frequencies is needed to discriminate between the models. We compare this technique to that using the ratios of small to large separations, showing that in principle it is more accurate and avoids the problem of correlated errors in separation ratio fitting.
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