Optoacoustic Building Blocks for Photonic Neural Networks
Cabello JHM, Slinkov G, Saffer O, Braband N, Geilen A, Becker S, Stiller B (2025)
Publication Type: Conference contribution
Publication year: 2025
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: 2025 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2025
Event location: Munich, DEU
ISBN: 9798331512521
DOI: 10.1109/CLEO/EUROPE-EQEC65582.2025.11111266
Abstract
The realization of massive machine learning models has integrated artificial intelligence into our daily lives, yet, their training, maintenance, and scalability rely on power-hungry electronic processors [1]. Neuromorphic computing seeks to address these challenges by mimicking neural architechtures directly in physical systems. Photonics is a promising platform as it offers high bandwidth, rapid processing speeds, and low energy consumption [2, 3]. Examples showing the potential of photonics include reservoir computing and extreme learning machines using optical components [4], deep diffractive neural networks [5], and Mach-Zender interferometer meshes [6].
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Germany (DE)How to cite
APA:
Cabello, J.H.M., Slinkov, G., Saffer, O., Braband, N., Geilen, A., Becker, S., & Stiller, B. (2025). Optoacoustic Building Blocks for Photonic Neural Networks. In 2025 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2025. Munich, DEU: Institute of Electrical and Electronics Engineers Inc..
MLA:
Cabello, Jesús Humberto Marines, et al. "Optoacoustic Building Blocks for Photonic Neural Networks." Proceedings of the 2025 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2025, Munich, DEU Institute of Electrical and Electronics Engineers Inc., 2025.
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