Digital spiral object identification using random light
Zhe Yang, Omar S. Magana-Loaiza, Mohammad Mirhosseini, Yiyu Zhou,, Boshen Gao, Lu Gao, Seyed Mohammad Hashemi Rafsanjani, Guilu Long, Robert, W. Boyd

TL;DR
This paper presents a classical optical method for identifying the spatial and phase features of objects with rotational symmetry using orbital angular momentum correlations in random light, reducing measurement requirements and enhancing robustness.
Contribution
It introduces a novel classical correlation-based approach for object identification that does not rely on quantum states and is effective at various light levels.
Findings
Successfully identified object signatures using intensity correlations.
Achieved object sensing with fewer measurements than pixel-based imaging.
Demonstrated robustness against environmental noise.
Abstract
Photons that are entangled or correlated in orbital angular momentum have been extensively used for remote sensing, object identification and imaging. It has recently been demonstrated that intensity fluctuations give rise to the formation of correlations in the orbital angular momentum components and angular positions of random light. Here, we demonstrate that the spatial signatures and phase information of an object, with rotational symmetries, can be identified using classical orbital angular momentum correlations in random light. The Fourier components imprinted in the digital spiral spectrum of the object, measured through intensity correlations, unveil its spatial and phase information. Sharing similarities with conventional compressive sensing protocols that exploit sparsity to reduce the number of measurements required to reconstruct a signal, our technique allows sensing of an…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
