Photonic Convolution Processing with Large-Scale Spectral Shaper and Frequency Comb

We present a large-scale photonic convolution processor leveraging a frequency comb and integrated multilane spectral shaper supporting 3200 implementable parameters with 72.4 TOPS computation speed. Enhanced scalability by separable convolution approach was also experimentally demonstrated.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.1364/cleo_si.2025.ss164_2
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Photonic Convolution Processing with Large-Scale Spectral Shaper and Frequency Comb

M. Nakajima, Toshikazu Hashimoto, Kohei Ikeda
Neural Networks and Reservoir Computing
article

Photonic Convolution Processing with Large-Scale Spectral Shaper and Frequency Comb

M. Nakajima, Toshikazu Hashimoto, Kohei Ikeda
article en

Abstract

We present a large-scale photonic convolution processor leveraging a frequency comb and integrated multilane spectral shaper supporting 3200 implementable parameters with 72.4 TOPS computation speed. Enhanced scalability by separable convolution approach was also experimentally demonstrated.

NTT (Japan) (JP), NTT Basic Research Laboratories (JP)
Openalex Percentile: Top 86%
Neural Networks and Reservoir Computing
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Photonic Convolution Processing with Large-Scale Spectral Shaper and Frequency Comb — M. Nakajima, Toshikazu Hashimoto, et al. · (2025) | TGRS Research Map | TGRS