The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit, an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.

中文翻译：

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mpfit：一种健壮的方法，用于拟合具有多个高斯峰的原子分辨率图像

从原子分辨率扫描透射电子显微镜图像估计原子位置的子像素的标准技术依赖于具有二维高斯函数的拟合强度最大值或最小值。尽管这是一种广泛的测量方法，但在具有非零像差，相邻原子之间的强度差很大或相邻原子位置接近显微镜分辨率极限的情况下，它可能易于出错。在这里，我们演示mpfit，这是一种原子发现算法，该算法可迭代地计算一系列重叠的二维高斯函数以适合实验数据集，然后随后使用计算出的高斯函数的子集执行原子位置的子像素优化。根据这项工作中提供的模拟和实验数据集，