Adaptive Information Mining from Faint Photons for Sub-Rayleigh Object Localization and Tracking on a Large Telescope

The open problem is to demonstrate a quantum-inspired advantage on a large telescope for sub-Rayleigh, photon starved, high contrast imaging of point/extended objects. Even though there is preliminary research in the optics community showing the feasibility of such an enhancement, the technology readiness level is low for any meaningful interpolation to real world performance. As the Rayleigh limit has been the crucial roadblock for remote sensing systems, this challenge also presents a unique opportunity for lasting impact and value creation. We plan to overcome this challenge by bringing together state-of-the-art custom built hardware and rigorous mathematical principles from modal imaging, quantum optics, information theory, optimal design, edge computing, wavefront sensing, coronagraphy and computational imaging.