Approaching quantum-limited imaging resolution without prior knowledge of the object location

Area of Science:

• Optical physics
• Quantum imaging
• Signal processing

Background:

• Passive imaging receivers can overcome classical diffraction limits.
• Mode-sorting receivers face challenges with unknown object parameters like centroids.
• Limited prior information in real-world scenarios hinders performance.

Purpose of the Study:

• To develop a robust imaging strategy for enhanced spatial resolution.
• To address the limitations of mode-sorting receivers in realistic conditions.
• To achieve near quantum-optimal imaging performance with minimal prior information.

Main Methods:

• Proposed a multistage detection strategy by segmenting recording time.
• Implemented an adaptive two-stage scheme dynamically allocating measurement time.
• Utilized Monte Carlo simulations to validate the proposed method.

Main Results:

• The adaptive two-stage scheme significantly outperforms direct detection without prior centroid knowledge.
• Achieved one to two orders of magnitude improvement in mean squared error for estimation tasks.
• Demonstrated enhanced performance at sub-Rayleigh length scales.

Conclusions:

• The proposed multistage detection strategy enhances imaging performance in scenarios with limited prior information.
• The adaptive scheme offers a practical solution for overcoming limitations of current mode-sorting receivers.
• The method is generalizable for complex imaging tasks and multiple parameters.