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

TL;DR

This paper introduces the Mikado strategy, an iterative detection method for atoms in microtrap array images that improves accuracy and robustness without relying on explicit probabilistic models.

Contribution

The paper presents a novel Mikado strategy that alternates estimation and detection steps, enhancing atom detection in high-resolution microtrap images beyond previous methods.

Findings

Improved detection accuracy over previous work.

Enhanced robustness against experimental conditions.

Effective in cases of poor optical resolution.

Abstract

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.