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Silicon Photonic Modulator Neuron
Open accessAbstract
Neural networks based on optoelectronics could be more than a million times as fast as electronic implementations, opening uncharted regimes of information processing. Despite advances in laser-based neurons and programmable Si photonic interconnects, a photonic neuron compatible with a photonic network is missing. These challenges could be addressed by photonic-modulator-based neurons that were integrable on the same platform as Si interconnects. The authors fabricate a Si photonic-modulator neuron and observe all essential networking properties of fan-in, cascadability, and high-gain nonlinearity, plus programmable, multi-input, time-resolved, and self-feedback processing behaviors.
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Metadata
- Authors
- Tait, A. N., Ferreira de Lima, T., Nahmias, M. A., Miller, H. B., Peng, H.-T., Shastri, B. J., & Prucnal, P. R.
- Venue
- Physical Review Applied
- Publisher
- American Physical Society (APS)
- Published
- 2019-06-18
- Volume
- 11
- Issue
- 6
- ISSN
- 2331-7019 (ISSN-L)
- OpenAlex
- W2906829733
- Cited by
- 331
- References
- 95
- FWCI
- 17.73
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
