Adaptive Imaging of Arbitrary Thermal Source Distributions with Near Quantum-Limited Resolution
Year: 2021
Type: preprint
Abstract: We demonstrate an approach to obtaining near quantum limited far-field imaging resolution of thermal, 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 Cramer-Rao bound over the manifold of all possible sets of orthogonal modes. We have observed through Monte Carlo simulations that the manifold-optimized spatial mode demultiplexing measurement consistently outperforms standard imaging techniques in the resolution and precision of source reconstructions, and approaches the quantum limits as set by the quantum Cramer-Rao bound. The adaptive framework presented here allows for a consistent approach to achieving near quantum-limited imaging resolution of arbitrarily distributed thermal sources.
Source: arXiv (Cornell University)
Authors: Erik Matlin, Lucas Zipp
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3175732011