Optical Echo State Network Reservoir Computing Article Swipe

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Ishwar S Kaushik , Peter J. Ehlers , Daniel Soh ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2504.08224

We propose an innovative design for an optical Echo State Network (ESN), an advanced type of reservoir computer known for its universal computational capabilities. Our design enables an optical implementation of arbitrary ESNs, featuring flexibility in optical matrix multiplication and nonlinear activation. Leveraging the nonlinear characteristics of stimulated Brillouin scattering (SBS), the architecture efficiently realizes measurement-free nonlinear activation. The approach significantly reduces computational overhead and energy consumption compared to traditional software-based methods. Comprehensive simulations validate the system's memory capacity, nonlinear processing strength, and polynomial algebra capabilities, showcasing performance comparable to software ESNs across key benchmark tasks. Our design establishes a feasible, scalable, and universally applicable framework for optical reservoir computing, suitable for diverse machine learning applications.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2504.08224
PDF: https://arxiv.org/pdf/2504.08224
OA Status: green
OpenAlex ID: https://openalex.org/W4414827774

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OpenAlex ID: https://openalex.org/W4414827774

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.48550/arxiv.2504.08224

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Title: Optical Echo State Network Reservoir Computing

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-04-11

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Authors: Ishwar S Kaushik, Peter J. Ehlers, Daniel Soh

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Landing page: https://arxiv.org/abs/2504.08224

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PDF URL: https://arxiv.org/pdf/2504.08224

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Open access: Yes

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OA status: green

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OA URL: https://arxiv.org/pdf/2504.08224

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Cited by: 0

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