动力模态分解反演扭转Alfvén波
Dynamic mode decomposition to retrieve torsional Alfvén waves
摘要：
动态模式分解（DMD）被用来识别行星内部产生的内在信号。专注于轴对称准地转磁流体动力学（MHD）波-称为扭转阿尔文波（TW）-我们研究DMD的效用在两种类型的MHD直接数值模拟：Boussinesq磁对流和滞弹性对流驱动发电机在快速旋转的球壳，其中模型的动态地球的核心和木星，分别。我们表明，DMD是能够区分内部模式和边界/界面相关的模式的内部速度的时间序列。这些内部模式可以实现为自由TW，在其正常模式的解决方案的本征值和本征函数。同时，为了更好地考虑这些细节，球壳的整体TW特征值问题还需要进一步研究。
英文摘要：
Dynamic mode decomposition (DMD) is utilised to identify the intrinsic signals arising from planetary interiors. Focusing on an axisymmetric quasi-geostrophic magnetohydrodynamic (MHD) wave -called torsional Alfvén waves (TW) - we examine the utility of DMD in two types of MHD direct numerical simulations: Boussinesq magnetoconvection and anelastic convection-driven dynamos in rapidly rotating spherical shells, which model the dynamics in Earth's core and in Jupiter, respectively. We demonstrate that DMD is capable of distinguishing internal modes and boundary/interface-related modes from the timeseries of the internal velocity. Those internal modes may be realised as free TW, in terms of eigenvalues and eigenfunctions of their normal mode solutions. Meanwhile it turns out that, in order to account for the details, the global TW eigenvalue problems in spherical shells need to be further addressed.
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