Abstract

Information transfer rates in optical communications may be dramatically increased by making use of spatially non-Gaussian states of light. Here, we demonstrate the ability of deep neural networks to classify numerically generated, noisy Laguerre–Gauss modes of up to 100 quanta of orbital angular momentum with near-unity fidelity. The scheme relies only on the intensity profile of the detected modes, allowing for considerable simplification of current measurement schemes required to sort the states containing increasing degrees of orbital angular momentum. We also present results that show the strength of deep neural networks in the classification of experimental superpositions of Laguerre–Gauss modes when the networks are trained solely using simulated images. It is anticipated that these results will allow for an enhancement of current optical communications technologies.

© 2018 Optical Society of America

Full Article  |  PDF Article
More Like This
Transport-based pattern recognition versus deep neural networks in underwater OAM communications

Patrick L. Neary, Jonathan M. Nichols, Abbie T. Watnik, K. Peter Judd, Gustavo K. Rohde, James R. Lindle, and Nicholas S. Flann
J. Opt. Soc. Am. A 38(7) 954-962 (2021)

768-ary Laguerre-Gaussian-mode shift keying free-space optical communication based on convolutional neural networks

Haitao Luan, Dajun Lin, Keyao Li, Weijia Meng, Min Gu, and Xinyuan Fang
Opt. Express 29(13) 19807-19818 (2021)

Joint atmospheric turbulence detection and adaptive demodulation technique using the CNN for the OAM-FSO communication

Jin Li, Min Zhang, Danshi Wang, Shaojun Wu, and Yueying Zhan
Opt. Express 26(8) 10494-10508 (2018)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (15)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (2)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (5)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription