Dr SENDY PHANG SENDY.PHANG@NOTTINGHAM.AC.UK
ASSISTANT PROFESSOR
Artificial intelligence (AI) drives the creation of future technologies that disrupt the way humans live and work, creating new solutions that change the way we approach tasks and activities, but it requires a lot of data processing, large amounts of data transfer, and computing speed. It has led to a growing interest of research in developing a new type of computing platform which is inspired by the architecture of the brain specifically those that exploit the benefits offered by photonic technologies, fast, low-power, and larger bandwidth. Here, a new computing platform based on the photonic reservoir computing architecture exploiting the non-linear wave-optical dynamics of the stimulated Brillouin scattering is reported. The kernel of the new photonic reservoir computing system is constructed of an entirely passive optical system. Moreover, it is readily suited for use in conjunction with high performance optical multiplexing techniques to enable real-time artificial intelligence. Here, a methodology to optimise the operational condition of the new photonic reservoir computing is described which is found to be strongly dependent on the dynamics of the stimulated Brillouin scattering system. The new architecture described here offers a new way of realising AI-hardware which highlight the application of photonics for AI.
Phang, S. (2023). Photonic reservoir computing enabled by stimulated Brillouin scattering. Optics Express, 31(13), 22061-22074. https://doi.org/10.1364/oe.489057
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 8, 2023 |
Online Publication Date | Jun 15, 2023 |
Publication Date | Jun 19, 2023 |
Deposit Date | Jun 14, 2023 |
Publicly Available Date | Jun 27, 2023 |
Journal | Optics Express |
Electronic ISSN | 1094-4087 |
Publisher | Optical Society of America |
Peer Reviewed | Peer Reviewed |
Volume | 31 |
Issue | 13 |
Pages | 22061-22074 |
DOI | https://doi.org/10.1364/oe.489057 |
Keywords | Atomic and Molecular Physics, and Optics |
Public URL | https://nottingham-repository.worktribe.com/output/21910366 |
Publisher URL | https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-13-22061&id=531780 |
Photonic reservoir computing
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