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

• URL: http://arxiv.org/abs/2502.08511v2
• Date: Tue, 25 Feb 2025 13:22:16 GMT
• Title: Fast, accurate, and predictive method for atom detection in site-resolved images of microtrap arrays
• Authors: Marc Cheneau, Romaric Journet, Matthieu Boffety, François Goudail, Caroline Kulcsár, Pauline Trouvé-Peloux,
• Abstract summary: We introduce a new method, rooted in estimation theory, to detect the individual atoms in site-resolved images of microtrap arrays.<n>Using simulated images, we demonstrate a ten-fold reduction of the detection error rate compared to the popular method based on Wiener deconvolution.
• Score: 1.1545092788508224
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We introduce a new method, rooted in estimation theory, to detect the individual atoms in site-resolved images of microtrap arrays, such as optical lattices or optical tweezers arrays. Using simulated images, we demonstrate a ten-fold reduction of the detection error rate compared to the popular method based on Wiener deconvolution, under a wide range of experimental conditions. The runtime is fully compatible with real-time applications, even for a very large arrays. Finally, we propose a rigorous definition for the signal-to-noise ratio of an image, and show that it can be used as a predictor for the detection error rate, which opens new prospect for the design of future experiments.

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