Computing with integrated photonic reservoirs
- Author
- Joni Dambre (UGent) , Andrew Katumba (UGent) , Chonghuai Ma, Stijn Sackesyn (UGent) , Floris Laporte, Matthias Freiberger (UGent) and Peter Bienstman (UGent)
- Organization
- Project
- Abstract
- The idea of using photonic systems as reservoirs to perform general-purpose computing was first introduced in 2008. Since then, a wide range of systems using either discrete or integrated optical components has been explored. In this chapter, we summarise a decade of research into integrated coherent photonic reservoirs. In these systems, information is carried by the intensity and the phase of light waves. Computations emerge from the way the light propagates inside the system, and the ways in which light that travels along different paths is mixed and transformed. We discuss the computational capabilities of these reservoirs and the trade-offs that can be made to optimise them. We also discuss the technological constraints that are encountered in building such systems and the ways these reflect on their design and training. Finally, we give an overview of recent approaches to combining multiple such reservoirs into larger and computationally more powerful systems.
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8738698
- MLA
- Dambre, Joni, et al. “Computing with Integrated Photonic Reservoirs.” Reservoir Computing : Theory, Physical Implementations, and Applications, edited by Kohei Nakajima and Ingo Fischer, Springer, 2021, pp. 397–419, doi:10.1007/978-981-13-1687-6_17.
- APA
- Dambre, J., Katumba, A., Ma, C., Sackesyn, S., Laporte, F., Freiberger, M., & Bienstman, P. (2021). Computing with integrated photonic reservoirs. In K. Nakajima & I. Fischer (Eds.), Reservoir computing : theory, physical implementations, and applications (pp. 397–419). https://doi.org/10.1007/978-981-13-1687-6_17
- Chicago author-date
- Dambre, Joni, Andrew Katumba, Chonghuai Ma, Stijn Sackesyn, Floris Laporte, Matthias Freiberger, and Peter Bienstman. 2021. “Computing with Integrated Photonic Reservoirs.” In Reservoir Computing : Theory, Physical Implementations, and Applications, edited by Kohei Nakajima and Ingo Fischer, 397–419. Springer. https://doi.org/10.1007/978-981-13-1687-6_17.
- Chicago author-date (all authors)
- Dambre, Joni, Andrew Katumba, Chonghuai Ma, Stijn Sackesyn, Floris Laporte, Matthias Freiberger, and Peter Bienstman. 2021. “Computing with Integrated Photonic Reservoirs.” In Reservoir Computing : Theory, Physical Implementations, and Applications, ed by. Kohei Nakajima and Ingo Fischer, 397–419. Springer. doi:10.1007/978-981-13-1687-6_17.
- Vancouver
- 1.Dambre J, Katumba A, Ma C, Sackesyn S, Laporte F, Freiberger M, et al. Computing with integrated photonic reservoirs. In: Nakajima K, Fischer I, editors. Reservoir computing : theory, physical implementations, and applications. Springer; 2021. p. 397–419.
- IEEE
- [1]J. Dambre et al., “Computing with integrated photonic reservoirs,” in Reservoir computing : theory, physical implementations, and applications, K. Nakajima and I. Fischer, Eds. Springer, 2021, pp. 397–419.
@incollection{8738698,
abstract = {{The idea of using photonic systems as reservoirs to perform general-purpose computing was first introduced in 2008. Since then, a wide range of systems using either discrete or integrated optical components has been explored. In this chapter, we summarise a decade of research into integrated coherent photonic reservoirs. In these systems, information is carried by the intensity and the phase of light waves. Computations emerge from the way the light propagates inside the system, and the ways in which light that travels along different paths is mixed and transformed. We discuss the computational capabilities of these reservoirs and the trade-offs that can be made to optimise them. We also discuss the technological constraints that are encountered in building such systems and the ways these reflect on their design and training. Finally, we give an overview of recent approaches to combining multiple such reservoirs into larger and computationally more powerful systems.}},
author = {{Dambre, Joni and Katumba, Andrew and Ma, Chonghuai and Sackesyn, Stijn and Laporte, Floris and Freiberger, Matthias and Bienstman, Peter}},
booktitle = {{Reservoir computing : theory, physical implementations, and applications}},
editor = {{Nakajima, Kohei and Fischer, Ingo}},
isbn = {{9789811316869}},
issn = {{1619-7127}},
language = {{eng}},
pages = {{397--419}},
publisher = {{Springer}},
series = {{Natural Computing Series}},
title = {{Computing with integrated photonic reservoirs}},
url = {{http://doi.org/10.1007/978-981-13-1687-6_17}},
year = {{2021}},
}
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