ArticleNanophotonics (Berlin, Germany)2025
All-optical nonlinear activation function based on stimulated Brillouin scattering.
Article in Nanophotonics (Berlin, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Emerging integrated photonic neural network technologies for artificial intelligence: from devices to systems.National science review · 2026Review
- Dual-Mode MOSCAP Silicon Microring Resonator for Energy-Efficient Analog Optical Computing.ACS photonics · 2026Article
- Femto-joule threshold reconfigurable all-optical nonlinear activators for picosecond pulsed optical neural networks.Light, science & applications · 2026Article
- Guided nonlinear optics for information processing.Nanophotonics (Berlin, Germany) · 2025Article
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4 authors.
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Abstract
Optical neural networks have demonstrated their potential to overcome the computational bottleneck of modern digital electronics. However, their development towards high-performing computing alternatives is hindered by one of the optical neural networks' key components: the activation function. Most of the reported activation functions rely on opto-electronic conversion, sacrificing the unique advantages of photonics, such as resource-efficient coherent and frequency-multiplexed information encoding. Here, we experimentally demonstrate a photonic nonlinear activation function based on stimulated Brillouin scattering. It is coherent and frequency selective and can be tuned all-optically to take LeakyReLU, Sigmoid, and Quadratic shape. Our design compensates for the insertion loss automatically by providing net gain as high as 20 dB, paving the way for deep optical neural networks.
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