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Fourier Analysis of Gapped Time Series: Improved Estimates of Solar and Stellar Oscillation Parameters

机译:间隙时间序列的傅立叶分析:改进的太阳和恒星振荡参数估计

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摘要

Quantitative helioseismology and asteroseismology require very precise measurements of the frequencies, amplitudes, and lifetimes of the global modes of stellar oscillation. The precision of these measurements depends on the total length (T), quality, and completeness of the observations. Except in a few simple cases, the effect of gaps in the data on measurement precision is poorly understood, in particular in Fourier space where the convolution of the observable with the observation window introduces correlations between different frequencies. Here we describe and implement a rather general method to retrieve maximum likelihood estimates of the oscillation parameters, taking into account the proper statistics of the observations. Our fitting method applies in complex Fourier space and exploits the phase information. We consider both solar-like stochastic oscillations and long-lived harmonic oscillations, plus random noise. Using numerical simulations, we demonstrate the existence of cases for which our improved fitting method is less biased and has a greater precision than when the frequency correlations are ignored. This is especially true of low signal-to-noise solar-like oscillations. For example, we discuss a case where the precision of the mode frequency estimate is increased by a factor of five, for a duty cycle of 15%. In the case of long-lived sinusoidal oscillations, a proper treatment of the frequency correlations does not provide any significant improvement; nevertheless, we confirm that the mode frequency can be measured from gapped data with a much better precision than the 1/T Rayleigh resolution.
机译:定量日震学和星震学要求非常精确地测量恒星振荡整体模态的频率,振幅和寿命。这些测量的精度取决于总长度(T),质量和观测的完整性。除少数简单情况外,人们对数据间隙对测量精度的影响了解甚少,尤其是在傅里叶空间中,可观察物与观察窗的卷积会引入不同频率之间的相关性。在这里,我们描述并实现了一种相当通用的方法,以考虑到观测值的适当统计信息来获取振荡参数的最大似然估计。我们的拟合方法适用于复杂的傅立叶空间并利用相位信息。我们考虑了类似于太阳的随机振荡和长寿命的谐波振荡,以及随机噪声。通过数值模拟,我们证明了与忽略频率相关性的情况相比,改进的拟合方法存在较小偏差且精度更高的情况。对于像太阳一样低的信噪比振荡尤其如此。例如,我们讨论了一种情况,对于15%的占空比,模式频率估计的精度提高了五倍。对于长寿命的正弦振荡,对频率相关性的适当处理不会带来任何明显的改善。但是,我们确认可以从间隙数据中测量模式频率,其精度要比1 / T Rayleigh分辨率好得多。

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