TY - GEN
T1 - Robust Adaptive Quantum-Limited Super-Resolution Imaging
AU - Tan, Tianrui
AU - Lee, Kwan Kit
AU - Ashok, Amit
AU - Datta, Animesh
AU - Bash, Boulat A.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Inspired by the results from quantum information processing, spatial-mode demultiplexing offers resolution of objects at the quantum limit, below the well-known Rayleigh-Abbe diffraction limit. An intriguing aspect of these results is that, while the analysis leading to the ultimate sub-diffraction limit is quantum, semi-classical devices can be used to build 'super-resolving' sensors that achieve this limit. Therefore, these developments have potential to significantly improve the quality of imaging systems in the near term. However, these quantum-inspired systems are sensitive to fluctuation in nuisance parameters, whether they are natural or adversarial. In this paper we analyze the impact of such fluctuations and provide methods to mitigate it. We focus on a problem of resolving two point sources, which has immediate practical applications in, e.g., space situation awareness.
AB - Inspired by the results from quantum information processing, spatial-mode demultiplexing offers resolution of objects at the quantum limit, below the well-known Rayleigh-Abbe diffraction limit. An intriguing aspect of these results is that, while the analysis leading to the ultimate sub-diffraction limit is quantum, semi-classical devices can be used to build 'super-resolving' sensors that achieve this limit. Therefore, these developments have potential to significantly improve the quality of imaging systems in the near term. However, these quantum-inspired systems are sensitive to fluctuation in nuisance parameters, whether they are natural or adversarial. In this paper we analyze the impact of such fluctuations and provide methods to mitigate it. We focus on a problem of resolving two point sources, which has immediate practical applications in, e.g., space situation awareness.
UR - http://www.scopus.com/inward/record.url?scp=85150194349&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85150194349&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF56349.2022.10052064
DO - 10.1109/IEEECONF56349.2022.10052064
M3 - Conference contribution
AN - SCOPUS:85150194349
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 504
EP - 508
BT - 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Y2 - 31 October 2022 through 2 November 2022
ER -