Fully non-linear neuromorphic computing with linear wave scattering
Wanjura CC, Marquardt F (2025)
Publication Type: Conference contribution
Publication year: 2025
Publisher: SPIE
Book Volume: 13375
Conference Proceedings Title: Proceedings of SPIE - The International Society for Optical Engineering
Event location: San Francisco, CA, USA
ISBN: 9781510684980
DOI: 10.1117/12.3041808
Abstract
The increasing size of neural networks for deep learning applications and their energy consumption create a need for alternative neuromorphic approaches, e.g., using optics. Current proposals and implementations rely on physical non-linearities or opto-electronic conversion to realise the required non-linear activation function. However, there are significant challenges with these approaches related to power levels, control, energy-efficiency, and delays. Here, we review our scheme [Nat. Phys. 20, 1434–1440 (2024)] for a neuromorphic system that relies on linear wave scattering and yet achieves non-linear processing with a high expressivity. The key idea is to encode the input in physical parameters that affect the scattering processes. Moreover, gradients needed for training can be directly measured in scattering experiments. We propose an integrated-photonics implementation based on racetrack resonators that achieves high connectivity with a minimal number of waveguide crossings. Our work opens the door to a new, easily implementable paradigm of neuromorphic computing that can be widely applied in existing state-of-the-art, scalable platforms, such as optics, microwave and electrical circuits.
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Germany (DE)How to cite
APA:
Wanjura, C.C., & Marquardt, F. (2025). Fully non-linear neuromorphic computing with linear wave scattering. In Masaya Notomi, Tingyi Zhou (Eds.), Proceedings of SPIE - The International Society for Optical Engineering. San Francisco, CA, USA: SPIE.
MLA:
Wanjura, Clara C., and Florian Marquardt. "Fully non-linear neuromorphic computing with linear wave scattering." Proceedings of the AI and Optical Data Sciences VI 2025, San Francisco, CA, USA Ed. Masaya Notomi, Tingyi Zhou, SPIE, 2025.
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