Information Rich Sampling via Adaptive Modal Imaging for Quantum-Limited Resolution (IRIS)

Spatial mode sorting has recently become the subject of numerous theoretical explorations demonstrating impressive performance enhancements over direct imaging for passive and active sub-diffraction imaging tasks. These tasks include discriminating objects below the diffraction limit, super-localizing constellations of point emitters, and resolving sub-diffraction extended objects. While these theoretical studies suggest a readily apparent opportunity for new technologies, most experimental follow-on research consists principally of proof-of-concept demonstrations that have limited prospects of becoming a robust technology. In contrast, our team has endeavored to explore real-world operational regimes in which mode sorting solutions may offer practical benefits over direct imaging. Biologists, clinicians, and pharmaceutical drug researchers use super-resolution microscopy to obtain images of biological samples below the Rayleigh limit of classical imaging systems. Current super-resolution techniques, like STORM, STED, and PALM rely on clever spatio-temporal illumination methods to single out a small number of point-emitters that are never closer-spaced than the Rayleigh limit at any given time. These techniques have allowed biological samples to be imaged at length scales of tens of nanometers but suffer from long integration times that prevent live imaging applications. The primary aim of super resolution imaging is to gather data on the biological function of imaged structures which requires resolving events in time.  Our proposal is to insert an adaptive spatial mode sorter between the entrance pupil of the receiver—either of a microscope (for bio-imaging) or a telescope (for space-domain awareness, or SDA)—and the detector(s), to linearly preprocess multimode information-bearing light, to maximally extract task specific information, allowing for shorter integration times and higher spatial resolution. Doing so while resolving emitters in the sub-Rayleigh regime will enable SDA applications such as quickest change detection in GEO objects, identifying and tracking orbits of LEO objects, astronomical-imaging applications such as exo-planet detection and astrometry, and many in bio-imaging, e.g., live cell imaging that will elucidate functions in cancer, drug interaction, nanotechnology, and viral research. We bring together a group of experts with backgrounds spanning quantum estimation theory, computational imaging, and optical instrumentation for telescopes, to propose Information Rich Sampling via Adaptive Modal Imaging for Quantum-Limited Resolution (IRIS),  to: develop and demonstrate–in lab and in on-sky setups–algorithms for adaptively varying spatial-mode measurement bases in response to continual recording of measurement data from detectors, to achieve the most efficient estimation of a subRayleigh stellar scene in the presence of various system noise and imperfections.