Researching | OAM-based diffractive all-optical classification

Advanced Photonics, Volume. 6, Issue 1, 010501(2024)

OAM-based diffractive all-optical classification

Md Sadman Sakib Rahman^1,2,3 and Aydogan Ozcan^1,2,3、*

Author Affiliations

¹University of California, Electrical and Computer Engineering Department, Los Angeles, California, United States

²University of California, Bioengineering Department, Los Angeles, California, United States

³University of California, California NanoSystems Institute (CNSI), Los Angeles, California, United States

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$OAM-based all-optical classification schemes with diffractive deep neural networks (D2NNs). (a) A single classification task with a single detector OAM-encoded D2NN. (b) Multiple classification tasks with a single detector OAM-encoded D2NN. (c) Multiple classification tasks with a multidetector OAM-encoded D2NN. Adapted from Ref. 10.$

Fig. 1. OAM-based all-optical classification schemes with diffractive deep neural networks ( $D^{2} NNs$ ). (a) A single classification task with a single detector OAM-encoded $D^{2} NN$ . (b) Multiple classification tasks with a single detector OAM-encoded $D^{2} NN$ . (c) Multiple classification tasks with a multidetector OAM-encoded $D^{2} NN$ . Adapted from Ref. 10.

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Md Sadman Sakib Rahman, Aydogan Ozcan, "OAM-based diffractive all-optical classification," Adv. Photon. 6, 010501 (2024)

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Paper Information

Category: News and Commentaries

Received: --

Accepted: --

Published Online: Jan. 22, 2024

The Author Email: Ozcan Aydogan (ozcan@ucla.edu)

DOI:10.1117/1.AP.6.1.010501

CSTR:32187.14.1.AP.6.1.010501

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology