Ideas and Limitations for Improving Imaging Resolution via Quantum-Inspired Superresolution

#superresolution #quantum #diffraction #imaging

Professor Kevin Liang, Adelphi University 

Prof. Kevin Liang is an assistant professor of physics at Adelphi University. His research focuses on mathematical optics, which recently involves the analysis of novel superresolution techniques in which traditional assumptions about imaging are challenged. Prior to his position at Adelphi University, Prof. Liang did his post-doctoral work and received his PhD in Optics from The Institute of Optics at the University of Rochester. 

Abstract: The fundamental task of imaging is to improve one's ability to discern the details in a given object scene. This could range from tasks as simple as measuring the distance between two known point-like sources, or determining the full intensity profile of a complicated, continuous object distribution. Traditional wisdom in the field dictates that the transverse resolution of a linear optical imaging system is limited by the width of the system's diffraction-limited point spread function; a limitation known as Rayleigh's Criterion. Over the past decade, new quantum-inspired superresolution techniques, whose improvement can be measured via well-known statistical metrics such as the Fisher Information, have been shown to possibly circumvent Rayleigh's Criterion. The details of these techniques, and their limitations, are discussed in this talk.