All-optical nonlinear activation function based on stimulated Brillouin scattering
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.
Details
- Organisationseinheit(en)
-
Institut für Photonik
- Externe Organisation(en)
-
Max-Planck-Institut für die Physik des Lichts
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU Erlangen-Nürnberg)
Massachusetts Institute of Technology (MIT)
- Typ
- Artikel
- Journal
- Nanophotonics
- Band
- 14
- Seiten
- 2711-2722
- Anzahl der Seiten
- 12
- ISSN
- 2192-8606
- Publikationsdatum
- 02.08.2025
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Biotechnologie, Elektronische, optische und magnetische Materialien, Atom- und Molekularphysik sowie Optik, Elektrotechnik und Elektronik
- Elektronische Version(en)
-
https://doi.org/10.1515/nanoph-2024-0513 (Zugang:
Offen
)
https://doi.org/10.48550/arXiv.2401.05135 (Zugang: Offen )
