X-ray Absorption Fine Structure (XAFS) spectroscopy is an analytical technique of chemical insight. Improvements to this technique are continuously carried out for reduction of the acquisition time and increasing the resolution, especially for studying operando processes. The accurate reconstruction of XAFS signals requires that the collected data are noise-free to extract elemental structure information in post-processing. A novel approach to rapid sampling (encoded measurement) is validated conceptually. The technique relies on sparse signal recovery, i.e. using compressed sensing to reconstruct under-sampled signals. The proof of concept is demonstrated by using a python code to reconstruct under-sampled XAFS spectra. A case study of transition metal samples and their oxides is considered for this purpose. The results demonstrate a robust recovery of chemical information from a 30% sampled signal for the near-edge region analysis and from a 45% sampled signal for extended-edge region analysis. The application of this procedure is important for demonstrating the feasibility of tabletop operation using laboratory X-ray sources which are not continuously tunable.

中文翻译：

---

用于快速桌面 X 射线吸收光谱的压缩传感

X 射线吸收精细结构 (XAFS) 光谱是一种化学洞察分析技术。该技术不断得到改进，以减少采集时间并提高分辨率，特别是在研究操作过程方面。 XAFS信号的精确重建要求采集的数据是无噪声的，以便在后处理中提取元素结构信息。一种新颖的快速采样方法（编码测量）在概念上得到了验证。该技术依赖于稀疏信号恢复，即使用压缩感知来重建欠采样信号。通过使用 python 代码重建欠采样 XAFS 光谱来演示概念验证。为此目的，考虑了过渡金属样品及其氧化物的案例研究。结果表明，从用于近边缘区域分析的 30% 采样信号和用于扩展边缘区域分析的 45% 采样信号中可以稳健地恢复化学信息。该程序的应用对于证明使用不可连续调谐的实验室 X 射线源进行桌面操作的可行性非常重要。