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Title: Smart quantum statistical imaging beyond the Abbe-Rayleigh criterion
Abstract The wave nature of light imposes limits on the resolution of optical imaging systems. For over a century, the Abbe-Rayleigh criterion has been utilized to assess the spatial resolution limits of imaging instruments. Recently, there has been interest in using spatial projective measurements to enhance the resolution of imaging systems. Unfortunately, these schemes require a priori information regarding the coherence properties of “unknown” light beams and impose stringent alignment conditions. Here, we introduce a smart quantum camera for superresolving imaging that exploits the self-learning features of artificial intelligence to identify the statistical fluctuations of unknown mixtures of light sources at each pixel. This is achieved through a universal quantum model that enables the design of artificial neural networks for the identification of photon fluctuations. Our protocol overcomes limitations of existing superresolution schemes based on spatial mode projections, and consequently provides alternative methods for microscopy, remote sensing, and astronomy.  more » « less
Award ID(s):
2225986
PAR ID:
10484105
Author(s) / Creator(s):
; ; ; ; ; ;
Corporate Creator(s):
Editor(s):
Mary Francina
Publisher / Repository:
Nature Publishing Group
Date Published:
Journal Name:
npj Quantum Information
Edition / Version:
1
Volume:
8
Issue:
1
ISSN:
2056-6387
Page Range / eLocation ID:
1
Subject(s) / Keyword(s):
Quantum Imaging
Format(s):
Medium: X Size: 8 Other: pdf
Size(s):
8
Sponsoring Org:
National Science Foundation
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