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用于X射线散斑可见度光谱学的精确对比度测定。

Accurate contrast determination for X-ray speckle visibility spectroscopy.

作者信息

Sun Yanwen, Montana-Lopez Jordi, Fuoss Paul, Sutton Mark, Zhu Diling

机构信息

Linac Coherent Light Source, SLAC National Accelerator Laboratory, USA.

Physics Department, Stanford University, USA.

出版信息

J Synchrotron Radiat. 2020 Jul 1;27(Pt 4):999-1007. doi: 10.1107/S1600577520006773. Epub 2020 Jun 19.

DOI:10.1107/S1600577520006773
PMID:33566009
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7336177/
Abstract

X-ray speckle visibility spectroscopy using X-ray free-electron lasers has long been proposed as a probe of fast dynamics in noncrystalline materials. In this paper, numerical modeling is presented to show how the data interpretation of visibility spectroscopy can be impacted by the nonidealities of real-life X-ray detectors. Using simulated detector data, this work provides a detailed analysis of the systematic errors of several contrast extraction algorithms in the context of low-count-rate X-ray speckle visibility spectroscopy and their origins are discussed. Here, it was found that the finite detector charge cloud and pixel size lead to an unavoidable `degeneracy' in photon position determination, and that the contrasts extracted using different algorithms can all be corrected by a simple linear model. The results suggest that experimental calibration of the correction coefficient at the count rate of interest is possible and essential. This allows computationally lightweight algorithms to be implemented for on-the-fly analysis.

摘要

长期以来,利用X射线自由电子激光的X射线散斑可见度光谱法一直被提议作为探测非晶材料快速动力学的一种手段。本文通过数值模拟展示了实际X射线探测器的非理想特性如何影响可见度光谱的数据解读。利用模拟探测器数据,这项工作详细分析了低计数率X射线散斑可见度光谱中几种对比度提取算法的系统误差,并讨论了其来源。在此发现,探测器有限的电荷云及像素尺寸导致光子位置确定中不可避免地存在“简并”现象,并且使用不同算法提取的对比度均可通过一个简单的线性模型进行校正。结果表明,在感兴趣的计数率下对校正系数进行实验校准是可行且必不可少的。这使得可以实施计算量小的算法进行实时分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/29177a42e5e5/s-27-00999-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/789994bdae35/s-27-00999-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/af95ed73e718/s-27-00999-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/3480590c1765/s-27-00999-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/d450447a51e8/s-27-00999-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/670da81d690b/s-27-00999-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/24ddee48f516/s-27-00999-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/5e9824c47dc4/s-27-00999-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/29177a42e5e5/s-27-00999-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/789994bdae35/s-27-00999-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/af95ed73e718/s-27-00999-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/3480590c1765/s-27-00999-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/d450447a51e8/s-27-00999-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/670da81d690b/s-27-00999-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/24ddee48f516/s-27-00999-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/5e9824c47dc4/s-27-00999-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/7336177/29177a42e5e5/s-27-00999-fig8.jpg

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