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Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing
Open accessAbstract
Many information processing challenges are difficult to solve with traditional Turing or von Neumann approaches. Implementing unconventional computational methods is therefore essential and optics provides promising opportunities. Here we experimentally demonstrate optical information processing using a nonlinear optoelectronic oscillator subject to delayed feedback. We implement a neuro-inspired concept, called Reservoir Computing, proven to possess universal computational capabilities. We particularly exploit the transient response of a complex dynamical system to an input data stream. We employ spoken digit recognition and time series prediction tasks as benchmarks, achieving competitive processing figures of merit.
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Citations
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Cited by
Deep learning with coherent nanophotonic circuits
Shen, Y., Harris, N. C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., Sun, X., Zhao, S., Larochelle, H., Englund, D., et al. (2017) · Nature Photonics · doi:10.1038/nphoton.2017.93 · Cited by 3,340
Recent advances in physical reservoir computing: A review
Tanaka, G., Yamane, T., Héroux, J. B., Nakane, R., Kanazawa, N., Takeda, S., Numata, H., Nakano, D., & Hirose, A. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.03.005 · Cited by 2,146
Photonics for artificial intelligence and neuromorphic computing
Shastri, B. J., Tait, A. N., Ferreira de Lima, T., Pernice, W. H. P., Bhaskaran, H., Wright, C. D., & Prucnal, P. R. (2021) · Nature Photonics · doi:10.1038/s41566-020-00754-y · Cited by 1,756
Parallel photonic information processing at gigabyte per second data rates using transient states
Brunner, D., Soriano, M. C., Mirasso, C. R., & Fischer, I. (2013) · Nature Communications · doi:10.1038/ncomms2368 · Cited by 938
Self-citationTemporal data classification and forecasting using a memristor-based reservoir computing system
Moon, J., Ma, W., Shin, J. H., Cai, F., Du, C., Lee, S. H., & Lu, W. D. (2019) · Nature Electronics · doi:10.1038/s41928-019-0313-3 · Cited by 645
Metadata
- Authors
- Larger, L., Soriano, M. C., Brunner, D., Appeltant, L., Gutierrez, J. M., Pesquera, L., Mirasso, C. R., & Fischer, I.
- Venue
- Optics Express
- Publisher
- Optica Publishing Group
- Published
- 2012-01-27
- Volume
- 20
- Issue
- 3
- Pages
- 3241
- ISSN
- 1094-4087 (ISSN-L)
- OpenAlex
- W2022248835
- Cited by
- 864
- References
- 2
- FWCI
- 30.40
- Type
- journal article
- Language
- en
- Open access
- gold
- Licence
- doi.org/10.1364/OA_License_v1#VOR-OA (vor)
- opg.optica.org/policies/opg-tdm-policy.json (tdm)
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- Larger, L., Soriano, M. C., Brunner, D., Appeltant, L., Gutierrez, J. M., Pesquera, L., Mirasso, C. R., & Fischer, I. (2012). Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing. Optics Express. https://doi.org/10.1364/oe.20.003241
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
