Abstract. Using the solar-wind-driven magnetosphere–ionosphere–thermosphere system, a methodology is developed to reduce a state-vector description of a time-dependent driven system to a composite scalar picture of the activity in the system. The technique uses canonical correlation analysis to reduce the time-dependent system and driver state vectors to time-dependent system and driver scalars, with the scalars describing the response in the system that is most-closely related to the driver. This reduced description has advantages: low noise, high prediction efficiency, linearity in the described system response to the driver, and compactness. The methodology identifies independent modes of reaction of a system to its driver. The analysis of the magnetospheric system is demonstrated. Using autocorrelation analysis, Jensen–Shannon complexity analysis, and permutation-entropy analysis the properties of the derived aggregate scalars are assessed and a new mode of reaction of the magnetosphere to the solar wind is found. This state-vector-reduction technique may be useful for other multivariable systems driven by multiple inputs.

中文翻译：

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通过减少状态向量以聚合标量来压缩瞬态多变量系统及其多变量驱动器的描述：地球的太阳风驱动的磁层

摘要。使用太阳风驱动的磁层-电离层-热层系统，开发了一种方法来将时间相关驱动系统的状态向量描述简化为系统中活动的复合标量图。该技术使用规范相关分析将依赖于时间的系统和驱动程序状态向量减少为依赖于时间的系统和驱动程序标量，这些标量描述了系统中与驱动程序最密切相关的响应。这种简化的描述具有以下优点：低噪声、高预测效率、所描述的系统对驱动器的响应具有线性和紧凑性。该方法识别系统对其驱动程序的独立反应模式。演示了磁层系统的分析。使用自相关分析，Jensen-Shannon 复杂性分析和置换-熵分析评估了导出的聚合标量的特性，并发现了磁层对太阳风的新反应模式。这种状态向量减少技术可能对由多个输入驱动的其他多变量系统有用。