Optical quantum super-resolution imaging and hypothesis testing

TL;DR

This paper demonstrates quantum-based super-resolution imaging techniques that significantly improve the accuracy of detecting and discriminating closely spaced incoherent thermal sources, surpassing classical limits.

Contribution

The authors introduce a simple two-mode interferometer setup for quantum state discrimination and super-resolution imaging, achieving quantum-limited accuracy with reduced experimental complexity.

Findings

Reduced error probability in detecting weak secondary sources.

Super-resolved angular separation measurement saturating quantum Cramér-Rao bound.

Achieved 1.7% accuracy in resolving sources 15 μm apart at 1 m distance.

Abstract

Estimating the angular separation between two incoherent thermal sources is a challenging task for direct imaging, especially when it is smaller than or comparable to the Rayleigh length. In addition, the task of discriminating whether there are one or two sources followed by detecting the faint emission of a secondary source in the proximity of a much brighter one is in itself a severe challenge for direct imaging. Here, we experimentally demonstrate two tasks for superresolution imaging based on quantum state discrimination and quantum imaging techniques. We show that one can significantly reduce the probability of error for detecting the presence of a weak secondary source, especially when the two sources have small angular separations. In this work, we reduce the experimental complexity down to a single two-mode interferometer: we show that (1) this simple set-up is sufficient for the state discrimination task, and (2) if the two sources are of equal brightness, then this measurement can super-resolve their angular separation, saturating the quantum Cram\'er-Rao bound. By using a collection baseline of 5.3~mm, we resolve the angular separation of two sources that are placed 15~$\mu$m apart at a distance of 1.0~m with an accuracy of $1.7\%$--this is between 2 to 3 orders of magnitudes more accurate than shot-noise limited direct imaging.