论文标题
在微量瓦解度数据中对重叠脉冲的最佳过滤
Optimal Filtering of Overlapped Pulses in Microcalorimeter Data
论文作者
论文摘要
在这里，我们提出了一种用于处理微量滤过数据的一般算法，该数据具有特殊适用于高光子计数速率的数据。传统的最佳滤波在微量瓦尔（微量升温器数据处理中已变得无处不在，它都无法在不牺牲光谱分辨率的情况下恢复重叠的脉冲。这里提出的技术是为了解决这一特定的缺点，并且在不施加的任何假设之外的任何假设之外进行的任何假设。我们使用大约满足这些假设的数据集证明了该算法的性能，并且代表了广泛的微氧计应用程序。我们还将技术应用于高度非线性数据集，从而在这些假设分解的极限中检查了对性能的影响。
Here we present a general algorithm for processing microcalorimeter data with special applicability to data with high photon count rates. Conventional optimal filtering, which has become ubiquitous in microcalorimeter data processing, suffers from its inability to recover overlapped pulses without sacrificing spectral resolution. The technique presented here was developed to address this particular shortcoming, and does so without imposing any assumptions beyond those made by the conventional technique. We demonstrate the algorithm's performance with a data set that approximately satisfies these assumptions, and which is representative of a wide range of microcalorimeter applications. We also apply the technique to a highly non-linear data set, examining the impact on performance in the limit that these assumptions break down.
