The upcoming NASA mission HelioSwarm will use nine spacecraft to make the first simultaneous multi-point measurements of space plasmas spanning multiple scales. Using the wave-telescope technique, HelioSwarm's measurements will allow for both the calculation of the power in wavevector-and-frequency space and the characterization of the associated dispersion relations of waves present in the plasma at MHD and ion-kinetic scales. This technique has been applied to the four-spacecraft missions of CLUSTER and MMS and its effectiveness has previously been characterized in a handful of case studies. We expand this uncertainty quantification analysis to arbitrary configurations of four through nine spacecraft for three-dimensional plane waves. We use Bayesian inference to learn equations that approximate the error in reconstructing the wavevector as a function of relative wavevector magnitude, spacecraft configuration shape, and number of spacecraft. We demonstrate the application of these equations to data drawn from a nine-spacecraft configuration to both improve the accuracy of the technique, as well as expand the magnitudes of wavevectors that can be characterized.

翻译：即将到来的NASA任务HelioSwarm将使用九个航天器同时进行跨多个尺度的空间等离子体的多点测量 。利用波望远镜技术，HelioSwarm的测量将允许计算波矢和频率空间中的功率，并对存在于MHD和离子动力学尺度的等离子体中的波的相关色散关系进行表征。这种技术已经应用于CLUSTER和MMS的四个航天器任务，并且其有效性在少数几个案例研究中已经被确定。我们将此不确定性量化分析扩展到四到九个航天器的任意配置的三维平面波。我们使用贝叶斯推断来学习方程，该方程近似于重构波矢的误差，其函数是相对波矢大小、航天器配置形状和航天器数量的函数。我们演示了这些方程的应用，以从九个航天器的配置中提取数据，以改善该技术的精度，并扩大可以表征的波矢的大小。