A comparative study of deconvolution techniques for quantum-gas microscope images

TL;DR

This paper compares three deconvolution techniques to improve image analysis in quantum-gas microscopes, assessing their effectiveness under various experimental conditions to enhance single-atom detection fidelity.

Contribution

It provides a systematic comparison of local iterative, Wiener, and Lucy-Richardson deconvolution methods for quantum-gas microscope images, highlighting their performance limits.

Findings

Wiener deconvolution performs best at high signal-to-noise ratios.

Reconstruction fidelity decreases with lower fluorescence levels.

The study quantifies detection limits for different atomic species and setups.

Abstract

Quantum-gas microscopes are used to study ultracold atoms in optical lattices at the single particle level. In these system atoms are localised on lattice sites with separations close to or below the diffraction limit. To determine the lattice occupation with high fidelity, a deconvolution of the images is often required. We compare three different techniques, a local iterative deconvolution algorithm, Wiener deconvolution and the Lucy-Richardson algorithm, using simulated microscope images. We investigate how the reconstruction fidelity scales with varying signal-to-noise ratio, lattice filling fraction, varying fluorescence levels per atom, and imaging resolution. The results of this study identify the limits of singe-atom detection and provide quantitative fidelities which are applicable for different atomic species and quantum-gas microscope setups.