论文标题
通过Lorentz传输电子显微镜和可区分编程的高分辨率功能成像
High resolution functional imaging through Lorentz transmission electron microscopy and differentiable programming
论文作者
论文摘要
Lorentz透射电子显微镜是一种独特的特征技术，可以同时对高空间分辨率的材料的显微结构和功能特性进行成像。磁化和电势等定量信息是通过电子波的相携带的，并且在成像过程中丢失。为了理解局部相互作用并发展结构 - 特性关系，有必要检索电子波的完整波函数，这需要求解电子的相移（相检索）。在这里，我们开发了一种基于可区分编程的方法，以使用一系列悬缝显微镜图像来解决相位检索的反问题。我们表明，就相同的电子剂量条件下，根据空间分辨率和所检索相的准确性，我们的方法是强大的，并且可以胜过广泛使用的\ textit {强度方程式}。此外，我们的方法具有与高级机器学习算法相同的基本结构，并且很容易适应电子显微镜中各种其他形式的相位检索。
Lorentz transmission electron microscopy is a unique characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials at high spatial resolution. The quantitative information such as magnetization and electric potentials is carried by the phase of the electron wave, and is lost during imaging. In order to understand the local interactions and develop structure-property relationships, it is necessary to retrieve the complete wavefunction of the electron wave, which requires solving for the phase shift of the electrons (phase retrieval). Here we have developed a method based on differentiable programming to solve the inverse problem of phase retrieval, using a series of defocused microscope images. We show that our method is robust and can outperform widely used \textit{transport of intensity equation} in terms of spatial resolution and accuracy of the retrieved phase under same electron dose conditions. Furthermore, our method shares the same basic structure as advanced machine learning algorithms, and is easily adaptable to various other forms of phase retrieval in electron microscopy.
