论文标题
在深色场X射线显微镜中鉴定超分辨率位错鉴定的分析方法
Analytical Methods for Superresolution Dislocation Identification in Dark-Field X-ray Microscopy
论文作者
论文摘要
在这项工作中，我们开发了几种推理方法，以估计使用深色X射线显微镜（DFXM）产生的图像的位置 - 实现超分辨率准确性和原则上的不确定性定量。使用贝叶斯推断的框架，我们将DFXM对比机制的模型和检测器测量噪声以及初始位置估计值结合到了统计模型耦合DFXM图像中，并具有感兴趣的位置位置。我们激励基于此模型的几个位置估计和不确定性定量算法。然后，我们证明了单晶铝中边缘位错的合成现实DFXM图像的主要估计算法的准确性。最后，我们讨论了我们方法对未来错位研究的影响以及可能的未来研究途径的影响。
In this work, we develop several inference methods to estimate the position of dislocations from images generated using dark-field X-ray microscopy (DFXM) -- achieving superresolution accuracy and principled uncertainty quantification. Using the framework of Bayesian inference, we incorporate models of the DFXM contrast mechanism and detector measurement noise, along with initial position estimates, into a statistical model coupling DFXM images with the dislocation position of interest. We motivate several position estimation and uncertainty quantification algorithms based on this model. We then demonstrate the accuracy of our primary estimation algorithm on synthetic realistic DFXM images of edge dislocations in single crystal aluminum. We conclude with a discussion of our methods' impact on future dislocation studies and possible future research avenues.
