In neutral atom quantum computers, readout and preparation of the atomic qubits are usually based on fluorescence imaging and subsequent analysis of the acquired image. For each atom site, the brightness or some comparable metric is estimated and used to predict the presence or absence of an atom. Across different setups, we can see a vast number of different approaches used to analyze these images. Often, the choice of detection algorithm is either not mentioned at all or it is not justified. We investigate several different algorithms and compare their performance in terms of both precision and execution run time. To do so, we rely on a set of synthetic images across different simulated exposure times with known occupancy states. Since the use of simulation provides us with the ground truth of atom site occupancy, we can easily state precise error rates and variances of the reconstructed property. To also rule out the possibility of better algorithms existing, we calculated the Cram\'er-Rao bound in order to establish an upper limit that even a perfect estimator cannot outperform. As the metric of choice, we used the number of photonelectrons that can be contributed to a specific atom site. Since the bound depends on the occupancy of neighboring sites, we provide the best and worst cases, as well as a half filled one. Our comparison shows that of our tested algorithms, a global non-linear least-squares solver that uses the optical system's PSF to return a each sites' number of photoelectrons performed the best, on average crossing the worst-case bound for longer exposure times. Its main drawback is its huge computational complexity and, thus, required calculation time. We manage to somewhat reduce this problem, suggesting that its use may be viable. However, our study also shows that for cases where utmost speed is required, simple algorithms may be preferable.

翻译：在中性原子量子计算机中，原子量子比特的读出与制备通常基于荧光成像及对获取图像的后继分析。针对每个原子位点，需估算其亮度或某种可比拟的度量指标，并据此预测原子存在与否。在不同实验装置中，我们观察到用于分析此类图像的方法存在显著差异。检测算法的选择往往未被提及，或缺乏合理依据。本研究系统考察了多种不同算法，并从精度与执行运行时间两个维度比较其性能。为此，我们采用一组在不同模拟曝光时间下生成、且原子占据状态已知的合成图像。由于模拟方法提供了原子位点占据情况的真实基准，我们能够准确计算重构属性的误差率与方差。为排除存在更优算法的可能性，我们计算了克拉默-拉奥界，以建立即使理想估计器也无法超越的性能上限。选择以可归因于特定原子位点的光电子数量作为核心度量指标。鉴于该界限受相邻位点占据状态影响，我们提供了最佳情况、最坏情况及半填充状态下的计算结果。对比研究表明，在测试算法中，采用光学系统点扩散函数并返回各点位光电子数量的全局非线性最小二乘求解器表现最优，其在较长曝光时间下平均性能超越最坏情况界限。该算法主要缺陷在于极高的计算复杂度及相应的计算耗时需求。我们通过优化部分缓解了该问题，表明其实际应用具备可行性。然而，本研究同时表明，在对计算速度有极端要求的场景中，简单算法可能更具优势。