Improved detection of small atom numbers through image processing

TL;DR

This paper presents advanced image processing techniques, including fringe removal and maximum-likelihood estimation, to significantly enhance the detection sensitivity of small atomic ensembles in absorption imaging.

Contribution

It introduces a fringe removal algorithm and an optimal atom-number estimator, achieving near fundamental detection limits for small atom populations.

Findings

Noise reduced to photon-shot-noise level

Signal-to-noise improved by a factor of 3

Minimum resolvable population difference of 17 atoms

Abstract

We demonstrate improved detection of small trapped atomic ensembles through advanced post-processing and optimal analysis of absorption images. A fringe removal algorithm reduces imaging noise to the fundamental photon-shot-noise level and proves beneficial even in the absence of fringes. A maximum-likelihood estimator is then derived for optimal atom-number estimation and is applied to real experimental data to measure the population differences and intrinsic atom shot-noise between spatially separated ensembles each comprising between 10 and 2000 atoms. The combined techniques improve our signal-to-noise by a factor of 3, to a minimum resolvable population difference of 17 atoms, close to our ultimate detection limit.