Experimental Evidence-Based Sub-Rayleigh Source Discrimination

• URL: http://arxiv.org/abs/2601.13972v1
• Date: Tue, 20 Jan 2026 13:49:34 GMT
• Title: Experimental Evidence-Based Sub-Rayleigh Source Discrimination
• Authors: Saurabh U. Shringarpure, Yong Siah Teo, Hyunseok Jeong, Michael Evans, Luis L. Sanchez-Soto, Antonin Grateau, Alexander Boeschoten, Nicolas Treps,
• Abstract summary: We propose a Bayesian evidence-based inference framework based on relative belief ratios and apply it to discriminating between one and two incoherent optical point sources using spatial-mode demultiplexing (SPADE)<n>Our method avoids ad hoc statistical constructs and relies solely on the information contained in the data, with all assumptions entering only through the likelihood model and prior beliefs.
• Score: 33.683963082460515
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a Bayesian evidence-based inference framework based on relative belief ratios and apply it to discriminating between one and two incoherent optical point sources using spatial-mode demultiplexing (SPADE). Unlike the Helstrom measurement, SPADE require no collective detection and its optimal for asymptotically large samples. Our method avoids ad hoc statistical constructs and relies solely on the information contained in the data, with all assumptions entering only through the likelihood model and prior beliefs. Using experimental evidence, we demonstrate the superior resolving performance of SPADE over direct imaging from a new and extensible perspective; one that naturally generalizes to multiple sources and offers a practical robust approach to analyzing quantum-enhanced superresolution.

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