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Abstract

Holography has been identified as a vital platform for three-dimensional displays, optical encryption, microscopy and artificial intelligence through different physical dimensions. However, unlike the wavelength and polarization divisions, orbital angular momentum (OAM) of light, despite its helical wavefront being an independent physical dimension, has not been implemented as an information carrier for holography due to the lack of helical mode index selectivity in the Bragg diffraction formula. Here, we demonstrate OAM holography by discovering strong OAM selectivity in the spatial-frequency domain without a theoretical helical mode index limit. As such, OAM holography allows the multiplexing of a wide range of OAM-dependent holographic images with a helical mode index spanning from −50 to 50, leading to a 10 bit OAM-encoded hologram for high-security optical encryption. Our results showing up to 210 OAM-dependent distinctive holographic images mark a new path to achieving ultrahigh-capacity holographic information systems harnessing the previously inaccessible OAM division.

The orbital angular momentum degree of freedom is used to demonstrate 10 bit holographic images with a helical mode index spanning from −50 to 50.

Details

Title
Orbital angular momentum holography for high-security encryption
Author
Fang Xinyuan 1   VIAFID ORCID Logo  ; Ren Haoran 2   VIAFID ORCID Logo  ; Gu, Min 3   VIAFID ORCID Logo 

 University of Shanghai for Science and Technology, Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, Shanghai, China (GRID:grid.267139.8) (ISNI:0000 0000 9188 055X); School of Science, RMIT University, Laboratory of Artificial-Intelligence Nanophotonics, Melbourne, Australia (GRID:grid.1017.7) (ISNI:0000 0001 2163 3550); College of Engineering and Applied Sciences, Nanjing University, National Laboratory of Solid State Microstructures, Nanjing, China (GRID:grid.41156.37) (ISNI:0000 0001 2314 964X) 
 School of Science, RMIT University, Laboratory of Artificial-Intelligence Nanophotonics, Melbourne, Australia (GRID:grid.1017.7) (ISNI:0000 0001 2163 3550) 
 University of Shanghai for Science and Technology, Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, Shanghai, China (GRID:grid.267139.8) (ISNI:0000 0000 9188 055X); School of Science, RMIT University, Laboratory of Artificial-Intelligence Nanophotonics, Melbourne, Australia (GRID:grid.1017.7) (ISNI:0000 0001 2163 3550) 
Pages
102-108
Publication year
2020
Publication date
Feb 2020
Publisher
Nature Publishing Group
ISSN
17494885
e-ISSN
17494893
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2348290887
Copyright
2019© The Author(s), under exclusive licence to Springer Nature Limited 2019