An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
An inquiry into the lunar interior: A nonlinear inversion of the Apollo lunar seismic data
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DOI：
10.1029/2001je001658
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发表时间：
2002-06
影响因子：
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通讯作者：
Amir Khan;K. Mosegaard
中科院分区：
文献类型：
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作者：
Amir Khan;K. Mosegaard
[1]本文详细讨论了阿波罗月球地震数据的反演以及如何对反演结果进行分析的问题。从一组到达时间估计结构参数（地震速度）和其他对了解行星体至关重要的参数的众所周知的问题是强非线性的。在这里，我们考虑这个问题，从贝叶斯统计的观点，使用马尔可夫链蒙特卡罗方法。一般来说，结果似乎表明，一个稍微薄的地壳厚度约45公里，以及更详细的月球速度结构，特别是在中地幔，比以前的研究。关于月震的位置，浅月震被发现在50-220公里的深度范围内，而大多数深月震集中在850-1000公里的深度范围内，似乎是一个明显的相当尖锐的下边界。为了进一步以统计方式分析特定特征的反演结果，我们使用了可信区间、二维边缘和贝叶斯假设检验。使用这种形式的假设检验，我们能够在给定数据、先验信息和支配模型与数据之间关系的物理定律的情况下，在任何两个假设的相对重要性之间做出决定，例如必须在45公里的薄地壳和一般假设值60公里所暗示的厚地壳之间做出决定。我们得到的贝叶斯因子为4.2，这意味着更薄的地壳是非常有利的。
[1] This study discusses in detail the inversion of the Apollo lunar seismic data and the question of how to analyze the results. The well-known problem of estimating structural parameters (seismic velocities) and other parameters crucial to an understanding of a planetary body from a set of arrival times is strongly nonlinear. Here we consider this problem from the point of view of Bayesian statistics using a Markov chain Monte Carlo method. Generally, the results seem to indicate a somewhat thinner crust with a thickness around 45 km as well as a more detailed lunar velocity structure, especially in the middle mantle, than obtained in earlier studies. Concerning the moonquake locations, the shallow moonquakes are found in the depth range 50–220 km, and the majority of deep moonquakes are concentrated in the depth range 850–1000 km, with what seems to be an apparently rather sharp lower boundary. In wanting to further analyze the outcome of the inversion for specific features in a statistical fashion, we have used credible intervals, two-dimensional marginals, and Bayesian hypothesis testing. Using this form of hypothesis testing, we are able to decide between the relative importance of any two hypotheses given data, prior information, and the physical laws that govern the relationship between model and data, such as having to decide between a thin crust of 45 km and a thick crust as implied by the generally assumed value of 60 km. We obtain a Bayes factor of 4.2, implying that a thinner crust is strongly favored.