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A rapid inversion and resolution analysis of magnetic microscope data by the subtractive optimally localized averages method

机译:磁极显微镜数据的快速反演和分辨率分析

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摘要

Modern scanning magnetic microscopes have the potential for fine-scale magnetic investigations of rocks. Observations at high spatial resolution produce large volumes of data, and the interpretation of these data is a nontrivial task. We have developed software using an efficient magnetic inversion technique that explicitly constructs the spatially localized Backus-Gilbert averaging kernel. Our approach, using the subtractive optimally localized averages (SOLA) method (Pijpers, R.P., Thompson, M.J., 1992. Faster formulations of the optimally localized averages method for helioseismic inversions. Astronomy and Astrophysics 262, L33-L36), yield a unidirectional magnetization. The averaging kernel expresses the spatial resolution of the inversion and is valuable for paleomagnetic application of the scanning magnetic microscope. Inversion examples for numerical magnetization patterns are provided to exhibit the performance of the method. Examples of actual magnetic field data collected from thin sections of natural rocks measured with a magnetoimpedance (MI) magnetic microscope are also provided. Numerical tests suggest that the data-independent averaging kernel is desirable for a point-to-point comparison among multiple data. Contamination by vector magnetization components can be estimated by the averaging kernel. We conclude that the SOLA method is a useful technique for paleomagnetic and rock magnetic investigations using scanning magnetic microscopy.
机译:现代扫描磁显微镜具有对岩石进行精细磁性研究的潜力。以高空间分辨率进行的观测会产生大量数据,对这些数据的解释是一项艰巨的任务。我们使用有效的磁反演技术开发了软件,该技术可显式构造空间局部的Backus-Gilbert平均内核。我们的方法是使用减法最佳局部平均数(SOLA)方法(Pijpers,RP,Thompson,MJ,1992.对日震反演的最佳局部平均法的更快公式化。天文学和天体物理262,L33-L36)产生单向磁化强度。平均内核表示反演的空间分辨率,对于扫描磁显微镜的古磁性应用具有重要意义。提供了数值磁化模式的反演示例,以展示该方法的性能。还提供了从自然岩石的薄壁部分收集的实际磁场数据的示例,这些岩石是用磁阻(MI)磁显微镜测量的。数值测试表明,对于多个数据之间的点对点比较,需要独立于数据的平均内核。矢量磁化分量的污染可以通过平均内核来估算。我们得出结论,SOLA方法是使用扫描磁显微镜对古磁和岩磁研究有用的技术。

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