论文标题
一种遗传算法方法，用于从过滤的X射线二极管阵列光谱仪重建光谱含量
A genetic algorithm approach to reconstructing spectral content from filtered x-ray diode array spectrometers
论文作者
论文摘要
通常使用过滤后的二极管阵列光谱仪来推断X射线源的光谱功率的时间演变，但是在这些不确定的系统中，从有限的宽阔，频谱重叠的通道频谱敏感性中唯一地提取频谱含量。我们介绍了遗传算法来重建概率光谱强度分布，并与文献中最常见的传统方法相比。与许多先前发表的模型不同，这种方法的光谱重建既不受基础功能形式的限制，也不需要先验的光谱知识。虽然这种测量的最初目的是诊断出光谱辐射源的光谱功率的时间演变，其中光谱内容的确切细节被认为不是至关重要的，但我们证明，这种新技术可以通过为更多的物理光谱和更高的物理配置提供强大的不合格，从而可以大大增强诊断的实用性。
Filtered diode array spectrometers are routinely employed to infer the temporal evolution of spectral power from x-ray sources, but uniquely extracting spectral content from a finite set of broad, spectrally overlapping channel spectral sensitivities is decidedly nontrivial in these underdetermined systems. We present the use of genetic algorithms to reconstruct a probabilistic spectral intensity distribution and compare to the traditional approach most commonly found in literature. Unlike many of the previously published models, spectral reconstructions from this approach are neither limited by basis functional forms, nor do they require a priori spectral knowledge. While the original intent of such measurements was to diagnose the temporal evolution of spectral power from quasi-blackbody radiation sources, where the exact details of spectral content was not thought to be crucial, we demonstrate that this new technique can greatly enhance the utility of the diagnostic by providing more physical spectra and improved robustness to hardware configuration for even strongly non-Planckian distributions.
