Optical computing with supercontinuum generation in photonic crystal fibers

2024/03/12 by Azka Maula Iskandar Muda, Muda, Azka Maula Iskandar, Uğur Teğin +1 · 1 citation
Engineering · #Advanced Photonic Communication Systems #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Physical sciences #Optical Network Technologies #Optics (physics.optics) #Semiconductor Lasers and Optical Devices

paper · pdf · doi:10.48550/arxiv.2403.07667

openalex publication_date 2024/03/12 · openalex created_date 2024/03/14 · openalex updated_date 2026/07/28

Abstract

We introduce a novel photonic neural network using photonic crystal fibers, leveraging femtosecond pulse supercontinuum generation for optical computing. Investigating its efficacy across machine learning tasks, we uncover the crucial impact of nonlinear pulse propagation dynamics on network performance. Our findings show that octave-spanning supercontinuum generation results in loss of dataset variety due to many-to-one mapping, and optimal performance requires balancing optical nonlinearity. This study offers guidance for designing energy-efficient and high-performance photonic neural network architectures by explaining the interplay between nonlinear dynamics and optical computing.

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• Fiber-based diffractive deep neural network

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