Confocal super-resolution microscopy based on a spatial mode sorter

TL;DR

This paper introduces a generalized deconvolution algorithm combined with a spatial mode sorter to significantly improve resolution in confocal microscopy, surpassing conventional methods by over 30% in simulated tests.

Contribution

It extends the Richardson-Lucy deconvolution to incorporate spatial mode sorting, enabling enhanced resolution for complex incoherent objects in confocal microscopy.

Findings

Resolution improved by over 30% compared to conventional confocal microscopy.

The method is effective for objects of arbitrary geometry.

Potential applications include fluorescence microscopy and astronomical imaging.

Abstract

Spatial resolution is one of the most important specifications of an imaging system. Recent results in quantum parameter estimation theory reveal that an arbitrarily small distance between two incoherent point sources can always be efficiently determined through the use of a spatial mode sorter. However, extending this procedure to a general object consisting of many incoherent point sources remains challenging, due to the intrinsic complexity of multi-parameter estimation problems. Here, we generalize the Richardson-Lucy (RL) deconvolution algorithm to address this challenge. We simulate its application to an incoherent confocal microscope, with a Zernike spatial mode sorter replacing the pinhole used in a conventional confocal microscope. We test different spatially incoherent objects of arbitrary geometry, and we find that the resolution enhancement of sorter-based microscopy is on average over 30% higher than that of a conventional confocal microscope using the standard RL deconvolution algorithm. Our method could potentially be used in diverse applications such as fluorescence microscopy and astronomical imaging.