Design for Robust and Efficient Neuromorphic Photonic Accelerator

In this work, we propose a novel architecture for building a robust integrated photonic neuromorphic accelerator based on a crossbar array design. Our architecture is based on an asymmetric multimode Y-coupler. A Y-coupler has the inherent benefit of high fabrication tolerance and broad optical bandwidth. From simulations, we show that our proposed Y-coupler has high coupling efficiency. Using modal decomposition analysis of our coupler, we numerically estimate the energy efficiency performance of a large-scale photonic network and show a 10% improvement in energy efficiency for large-scale photonic networks with high fabrication tolerance and broadband application and a small footprint.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-23
DOI
https://doi.org/10.5281/zenodo.13984383
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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article

Design for Robust and Efficient Neuromorphic Photonic Accelerator

Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
article

Design for Robust and Efficient Neuromorphic Photonic Accelerator

article en

Abstract

In this work, we propose a novel architecture for building a robust integrated photonic neuromorphic accelerator based on a crossbar array design. Our architecture is based on an asymmetric multimode Y-coupler. A Y-coupler has the inherent benefit of high fabrication tolerance and broad optical bandwidth. From simulations, we show that our proposed Y-coupler has high coupling efficiency. Using modal decomposition analysis of our coupler, we numerically estimate the energy efficiency performance of a large-scale photonic network and show a 10% improvement in energy efficiency for large-scale photonic networks with high fabrication tolerance and broadband application and a small footprint.

Zenodo (CERN European Organization for Nuclear Research)
Affordable and clean energy
Openalex Percentile: Top 61%
Neural Networks and Reservoir Computing
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Design for Robust and Efficient Neuromorphic Photonic Accelerator · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS