修复：用于Helio和asteroseismic数据的强大插值技术
Inpainting: A powerful interpolation technique for helio- and asteroseismic data
摘要：
在日震学和星震学中，必须有连续、不间断的数据集。然而，地震观测通常包含空白，我们需要考虑到这些空白。特别是，如果间隙不是随机分布的，它们会在周期图中产生峰值和一系列谐波，从而破坏恒星信息。数据的插值可以很好地解决这个问题。在本文中，我们研究了一种插值方法的基础上，所谓的“修复”算法。为了检查算法，我们使用了VIRGO和CoRoT卫星数据，我们应用了一个真实的CoRoT观测运行的真实人工窗口来引入间隙。接下来，我们将结果与原始的非窗口数据进行比较。因此，我们能够通过最小化具有间隙的数据的功率谱密度与完整时间序列之间的差异来优化算法。在一般情况下，我们发现，修复的时间序列的功率谱是非常相似的原始的，未扰动的。内插数据后得到的地震推断与原始情况相同。
英文摘要：
In Helio- and asteroseismology, it is important to have continuous, uninterrupted, data sets. However, seismic observations usually contain gaps and we need to take them into account. In particular, if the gaps are not randomly distributed, they will produce a peak and a series of harmonics in the periodogram that will destroy the stellar information. An interpolation of the data can be good solution for this problem. In this paper we have studied an interpolation method based on the so-called 'inpainting' algorithms. To check the algorithm, we used both VIRGO and CoRoT satellite data to which we applied a realistic artificial window of a real CoRoT observing run to introduce gaps. Next we compared the results with the original, non-windowed data. Therefore, we were able to optimize the algorithm by minimizing the difference between the power spectrum density of the data with gaps and the complete time series. In general, we find that the power spectrum of the inpainted time series is very similar to the original, unperturbed one. Seismic inferences obtained after interpolating the data are the same as in the original case.
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