Imaging arbitrary incoherent source distributions with near quantum-limited resolution

TL;DR

This paper introduces an adaptive spatial mode demultiplexing method that achieves near quantum-limited resolution for imaging arbitrary incoherent sources without prior knowledge, outperforming standard techniques.

Contribution

It develops a novel adaptive approach that optimizes spatial imaging modes to approach the quantum limit for arbitrary source distributions.

Findings

Method outperforms standard imaging techniques in accuracy.

Achieves near quantum-limited resolution within a factor of 2.

Monte Carlo simulations validate the effectiveness of the approach.

Abstract

We demonstrate an approach to obtaining near quantum-limited far-field imaging resolution of incoherent sources with arbitrary distributions. Our method assumes no prior knowledge of the source distribution, but rather uses an adaptive approach to imaging via spatial mode demultiplexing that iteratively updates both the form of the spatial imaging modes and the estimate of the source distribution. The optimal imaging modes are determined by minimizing the estimated Cram\'er-Rao bound over the manifold of all possible sets of orthogonal imaging modes. We have observed through Monte Carlo simulations that the manifold-optimized spatial mode demultiplexing measurement consistently outperforms standard imaging techniques in the accuracy of source reconstructions and comes within a factor of 2 of the absolute quantum limit as set by the quantum Cram\'er-Rao bound. The adaptive framework presented here allows for a consistent approach to achieving near quantum-limited imaging resolution of arbitrarily distributed sources through spatial mode imaging techniques.