Silicon ring resonator with phase-change material as a plastic dynamical node for scalable all-optical neural networks with synaptic plasticity
- Author
- Alessio Lugnan (UGent) , Santiago Garcia-Cuevas Carrillo, Junchao Song, Samarth Aggarwal, Frank Bruckerhoff-Pluckelmann, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright and Peter Bienstman (UGent)
- Organization
- Abstract
- Synaptic plasticity, that is the ability of connections in neural networks to strengthen or weaken depending on their input, is a fundamental component of learning and memory in biological brains. We present a numerical and experimental investigation of an integrated photonic plastic node, consisting of a silicon ring resonator enhanced by phase-change materials (GST). This all-optical device is capable of dynamical nonlinear behaviour, multi-scale volatile memory, non-volatile memory and multi-wavelength operations. We propose its employment as a building block in scalable all-optical dynamical neural networks that can adapt to their input via synaptic plasticity.
- Keywords
- Integrated photonics, neuromorphic computing, all-optical artificial neuron
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Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HRCNZR68S3F2Y774JZNGQDX9
- MLA
- Lugnan, Alessio, et al. “Silicon Ring Resonator with Phase-Change Material as a Plastic Dynamical Node for Scalable All-Optical Neural Networks with Synaptic Plasticity.” 2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON, IEEE, 2023, doi:10.1109/ICTON59386.2023.10207385.
- APA
- Lugnan, A., Garcia-Cuevas Carrillo, S., Song, J., Aggarwal, S., Bruckerhoff-Pluckelmann, F., H. P. Pernice, W., … Bienstman, P. (2023). Silicon ring resonator with phase-change material as a plastic dynamical node for scalable all-optical neural networks with synaptic plasticity. 2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON. Presented at the 23rd International Conference on Transparent Optical Networks (ICTON), Bucharest, Romania. https://doi.org/10.1109/ICTON59386.2023.10207385
- Chicago author-date
- Lugnan, Alessio, Santiago Garcia-Cuevas Carrillo, Junchao Song, Samarth Aggarwal, Frank Bruckerhoff-Pluckelmann, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright, and Peter Bienstman. 2023. “Silicon Ring Resonator with Phase-Change Material as a Plastic Dynamical Node for Scalable All-Optical Neural Networks with Synaptic Plasticity.” In 2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON. IEEE. https://doi.org/10.1109/ICTON59386.2023.10207385.
- Chicago author-date (all authors)
- Lugnan, Alessio, Santiago Garcia-Cuevas Carrillo, Junchao Song, Samarth Aggarwal, Frank Bruckerhoff-Pluckelmann, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright, and Peter Bienstman. 2023. “Silicon Ring Resonator with Phase-Change Material as a Plastic Dynamical Node for Scalable All-Optical Neural Networks with Synaptic Plasticity.” In 2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON. IEEE. doi:10.1109/ICTON59386.2023.10207385.
- Vancouver
- 1.Lugnan A, Garcia-Cuevas Carrillo S, Song J, Aggarwal S, Bruckerhoff-Pluckelmann F, H. P. Pernice W, et al. Silicon ring resonator with phase-change material as a plastic dynamical node for scalable all-optical neural networks with synaptic plasticity. In: 2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON. IEEE; 2023.
- IEEE
- [1]A. Lugnan et al., “Silicon ring resonator with phase-change material as a plastic dynamical node for scalable all-optical neural networks with synaptic plasticity,” in 2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON, Bucharest, Romania, 2023.
@inproceedings{01HRCNZR68S3F2Y774JZNGQDX9,
abstract = {{Synaptic plasticity, that is the ability of connections in neural networks to strengthen or weaken depending on their input, is a fundamental component of learning and memory in biological brains. We present a numerical and experimental investigation of an integrated photonic plastic node, consisting of a silicon ring resonator enhanced by phase-change materials (GST). This all-optical device is capable of dynamical nonlinear behaviour, multi-scale volatile memory, non-volatile memory and multi-wavelength operations. We propose its employment as a building block in scalable all-optical dynamical neural networks that can adapt to their input via synaptic plasticity.}},
author = {{Lugnan, Alessio and Garcia-Cuevas Carrillo, Santiago and Song, Junchao and Aggarwal, Samarth and Bruckerhoff-Pluckelmann, Frank and H. P. Pernice, Wolfram and Bhaskaran, Harish and Wright, C. David and Bienstman, Peter}},
booktitle = {{2023 23RD INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS, ICTON}},
isbn = {{9798350303049}},
issn = {{2162-7339}},
keywords = {{Integrated photonics,neuromorphic computing,all-optical artificial neuron}},
language = {{eng}},
location = {{Bucharest, Romania}},
pages = {{4}},
publisher = {{IEEE}},
title = {{Silicon ring resonator with phase-change material as a plastic dynamical node for scalable all-optical neural networks with synaptic plasticity}},
url = {{http://doi.org/10.1109/ICTON59386.2023.10207385}},
year = {{2023}},
}
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