Quantum Limits and Optimal Receivers for Passive Sub-Diffraction Imaging
Does quantum mechanics have anything useful to contribute to technology development in high-precision classical sensing? For quantitative sensing tasks in many application spaces, modeling the light collected by an optical sensor as a quantum state is a powerful theoretical avenue for evaluating how precisely the task could be carried out if the sensor is allowed to make any measurements that obey the laws of physics. Focusing on far-field super-resolution imaging, I will discuss how such a quantum information-theoretic framework has led us at the University of Arizona and others to develop “quantum-inspired” techniques that provably approach or achieve the upper limits on imaging precision that nature allows (such as the quantum Cramer-Rao bound on parameter estimation or the quantum Chernoff bound on object discrimination) while yielding large fundamental improvements over conventional resolution limits. I will highlight our theoretical and experimental progress in pushing these insights beyond toy problems and into the realm of useful real-world imaging needs, with applications in super-resolution microscopy, astronomy, and remote sensing.