Identifying Objects at the Quantum Limit for Superresolution Imaging

Michael R. Grace and Saikat Guha
Phys. Rev. Lett. 129, 180502 – Published 25 October 2022
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Abstract

We consider passive imaging tasks involving discrimination between known candidate objects and investigate the best possible accuracy with which the correct object can be identified. We analytically compute quantum-limited error bounds for hypothesis tests on any library of incoherent, quasimonochromatic objects when the imaging system is dominated by optical diffraction. We further show that object-independent linear-optical spatial processing of the collected light exactly achieves these ultimate error rates, exhibiting scaling superior to spatially resolved direct imaging as the scene becomes more severely diffraction limited. We apply our results to example imaging scenarios and find conditions under which superresolution object discrimination can be physically realized.

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  • Received 29 April 2022
  • Revised 4 August 2022
  • Accepted 1 September 2022

DOI:https://doi.org/10.1103/PhysRevLett.129.180502

© 2022 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyAtomic, Molecular & OpticalPhysics of Living SystemsGravitation, Cosmology & Astrophysics

Authors & Affiliations

Michael R. Grace and Saikat Guha

  • James C. Wyant College of Optical Sciences, University of Arizona, Tucson, Arizona 85721, USA

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Issue

Vol. 129, Iss. 18 — 28 October 2022

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