François Goudail | Searcharxiv

arXiv2026

Mikado strategy for the detection of atoms in images of microtrap arrays

Building on top of our recent work [arXiv:2502.08511], we introduce a new strategy to solve the problem of detecting atoms in high-resolution images of microtrap arrays. By alternating estimation and detection steps, we get rid of the need for an explicit model to compute the posterior occupancy probability of each site given its a priori optimal estimate. As direct benefits, we show an improved detection accuracy compared to our previous work when the sites are not optically well resolved, and we expect a greater robustness against real experimental conditions.

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arXiv2025

Fast, accurate, and predictive method for atom detection in site-resolved images of microtrap arrays

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.

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