Identifying Objects at the Quantum Limit for Superresolution Imaging

Michael R. Grace, Saikat Guha

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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.

Original languageEnglish (US)
Article number180502
JournalPhysical review letters
Issue number18
StatePublished - Oct 28 2022

ASJC Scopus subject areas

  • General Physics and Astronomy


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