All-Optical Nonlinear Activations Using Saturable Absorbers on a Generic InP Platform for Photonic Neural Networks
We experimentally demonstrate all-optical nonlinear activation functions using standalone saturable absorbers, as well as saturable absorbers integrated into microring resonators and Mach-Zehnder interferometer structures on a monolithic InP platform. These configurations enable programmable nonlinear responses and support both passive and active operation modes. The measured activation characteristics exhibit softplus- and ReLU-like behaviors, suitable for neuromorphic computing. When incorporated into a convolutional neural network for MNIST digit classification, the system achieves over 97% accuracy, highlighting the potential of SA-based photonic components for compact, low-power, and scalable optical neural networks.
Authors
- Rajib Ghosh (ORCID: https://orcid.org/0000-0001-6903-0169)
- Lukas Puts (ORCID: https://orcid.org/0000-0001-5416-3006)
- Julian König (ORCID: https://orcid.org/0000-0002-9398-5421)
- Weiming Yao (ORCID: https://orcid.org/0000-0002-4558-317X)
Institutions
- Eindhoven University of Technology (NL)
Publication Details
- Published
- 2025-11-04
- DOI
- https://doi.org/10.23919/piers-fall62445.2025.11394274
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00