Title: Fast, accurate, and predictive method for atom detection in site-resolved images of microtrap arrays Show Chinese title

Title: 快速、准确且具有预测性的微陷阱阵列位点分辨图像中的原子检测方法

Abstract: We introduce a new method, rooted in estimation theory, to detect individual atoms in site-resolved images of microtrap arrays, such as optical lattices or optical tweezers arrays. Using labelled test images, we demonstrate drastic improvement of the detection accuracy compared to the popular method based on Wiener deconvolution when the inter-site distance is comparable to the radius of the point spread function. The runtime of our method scales approximately linearly with the number of sites, and remains well below 100 ms for an array of 100 x 100 sites on a desktop computer. It is therefore fully compatible with a real-time usage. Finally, we propose a rigorous definition for the signal-to-noise ratio of the problem, and show that it can be used as a predictor for the detection error rate. Our work opens the prospect for future experiments with increased array sizes, or reduced inter-site distances. Show Chinese abstract

Abstract: 我们引入一种新的方法，基于估计理论，以在微陷阱阵列的位分辨图像中检测单个原子，例如光晶格或光镊阵列。 使用标记的测试图像，我们展示了与基于维纳去卷积的流行方法相比，当相邻位之间的距离与点扩散函数的半径相当时，检测精度有了显著提高。 我们方法的运行时间大约与位数成线性关系，并且在台式计算机上对100 x 100位的阵列，其运行时间始终低于100毫秒。 因此，该方法完全适用于实时使用。 最后，我们提出了一个问题的信噪比的严格定义，并表明它可以作为检测错误率的预测器。 我们的工作为未来更大阵列尺寸或更小相邻位距离的实验开辟了前景。