利用Theseus改进日球天空图估计
Towards Improved Heliosphere Sky Map Estimation with Theseus
摘要：
星际边界探测器（IBEX）卫星自2008年以来一直在轨道上运行，探测来自日光层的能量分辨高能中性原子（ENA）。日光层的不同区域以不同的速率产生ENA。利用IBEX收集的数据，以比以前更高的分辨率估计日光层ENA率的空间图（称为天空图），具有科学意义。这些天空图随后将被用来区分目前不可能的日光层特性的竞争理论。IBEX收集的数据对天空图估计提出了挑战。两个主要的挑战是噪声和不规则间隔的数据收集和IBEX仪器的点扩散函数。从本质上讲，IBEX收集的数据既有噪音，又有偏见，不利于推理感兴趣的基本天空图。在本文中，我们提出了一个两阶段的天空图估计程序称为忒修斯。在第一阶段，Theseus使用集合方法从噪声和不规则间隔的数据中估计模糊的天空图，该方法利用投影追踪回归和广义加法模型。在阶段2中，Theseus通过使用正则化将PSF与模糊地图反卷积来对天空地图进行去模糊。未模糊的天空地图的不确定性计算通过自举。我们比较忒修斯的方法密切相关的一个操作上使用的IBEX科学运营中心（ISOC）的模拟和真实数据。Theseus在模拟数据的几乎每一个考虑的指标上都优于ISOC，这表明Theseus是对当前技术水平的改进。
英文摘要：
The Interstellar Boundary Explorer (IBEX) satellite has been in orbit since 2008 and detects energy-resolved energetic neutral atoms (ENAs) originating from the heliosphere. Different regions of the heliosphere generate ENAs at different rates. It is of scientific interest to take the data collected by IBEX and estimate spatial maps of heliospheric ENA rates (referred to as sky maps) at higher resolutions than before. These sky maps will subsequently be used to discern between competing theories of heliosphere properties that are not currently possible. The data IBEX collects present challenges to sky map estimation. The two primary challenges are noisy and irregularly spaced data collection and the IBEX instrumentation's point spread function. In essence, the data collected by IBEX are both noisy and biased for the underlying sky map of inferential interest. In this paper, we present a two-stage sky map estimation procedure called Theseus. In Stage 1, Theseus estimates a blurred sky map from the noisy and irregularly spaced data using an ensemble approach that leverages projection pursuit regression and generalized additive models. In Stage 2, Theseus deblurs the sky map by deconvolving the PSF with the blurred map using regularization. Unblurred sky map uncertainties are computed via bootstrapping. We compare Theseus to a method closely related to the one operationally used today by the IBEX Science Operation Center (ISOC) on both simulated and real data. Theseus outperforms ISOC in nearly every considered metric on simulated data, indicating that Theseus is an improvement over the current state of the art.
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