利用MDI观测精确描述高阶模
Accurate Characterization of High-Degree Modes Using MDI Observations
摘要：
我们提出了第一个准确的表征高度模式，来自使用最好的MDI全磁盘全分辨率数据集。2001年获得了一个90天长的时间序列的全磁盘每像素分辨率为2弧秒的多普勒。利用我们对图像尺度的最佳估计和MDI图像失真的已知分量，对这些多普勒图进行空间分解。使用多锥度功率谱估计器来生成高达l = 1000的功率谱，具有大量锥度以减少实现噪声，而在高程度上的混合否定了对高谱分辨率的需要。这些功率谱适用于l = 100和l = 1000之间的所有度数和所有方位阶。这种拟合产生了超过6x10^6个脊频率、线宽、振幅和不对称性（单峰：l，n，m）的个体估计值，对应于大约6，000个多重峰（l，n）。以高度数拟合产生脊特征，该特征不对应于底层模式特征。我们使用了一个复杂的前向建模，以恢复潜在的模式特性（模式频率，以及线宽，幅度和不对称性）的最佳可能的估计。我们详细描述了这种建模及其验证。模型已被广泛审查和完善，包括一个迭代过程，以改善其输入参数，以更好地匹配观察。此外，泄漏矩阵对程序准确性的贡献也得到了仔细评估。我们提出了导出的一组校正模式特性，讨论其不确定性和精度的脊模式校正计划。在我们的结论中，我们讨论了如何进一步改善这些估计，以及对其他数据集的影响，如GONG+和HMI。
英文摘要：
We present the first accurate characterization of high-degree modes, derived using the best MDI full-disk full-resolution data set available. A ninety day long time series of full-disk two arc-second per pixel resolution dopplergrams was acquired in 2001. These dopplergrams were spatially decomposed using our best estimate of the image scale and the known components of MDI's image distortion. A multi-taper power spectrum estimator was used to generate power spectra up to l = 1000, with a large number of tapers to reduce the realization noise, while the blending at high degrees negates the need for high spectral resolution. These power spectra were fitted for all degrees and all azimuthal orders, between l = 100 and l = 1000. This fitting generated in excess of 6x10^6 individual estimates of ridge frequencies, line-widths, amplitudes and asymmetries (singlets: l,n,m), corresponding to some 6,000 multiplets (l,n). Fitting at high degrees generates ridge characteristics, characteristics that do not correspond to the underlying mode characteristics. We used a sophisticated forward modeling to recover the best possible estimate of the underlying mode characteristics (mode frequencies, as well as line-widths, amplitudes and asymmetries). We describe in detail this modeling and its validation. The modeling has been extensively reviewed and refined, by including an iterative process to improve its input parameters to better match the observations. Also, the contribution of the leakage matrix on the accuracy of the procedure has been carefully assessed. We present the derived set of corrected mode characteristics, discuss their uncertainties and the precision of the ridge to mode correction schemes. In our conclusions, we address how to further improve these estimates, and the implications for other data sets, like GONG+ and HMI.
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