Training Passive Photonic Reservoirs with Integrated Optical Readout

Simple item page
dc.contributor.authorFreiberger, Matthias
dc.contributor.authorKatumba, Andrew
dc.contributor.authorBienstman, Peter
dc.contributor.authorDambre, Joni
dc.date.accessioned2022-12-01T19:21:17Z
dc.date.available2022-12-01T19:21:17Z
dc.date.issued2018
dc.description.abstractAs Moore’s law comes to an end, neuromorphic approaches to computing are on the rise. One of these, passive photonic reservoir computing, is a strong candidate for computing at high bitrates (>10 Gbps) and with low energy consumption. Currently though, both benefits are limited by the necessity to perform training and readout operations in the electrical domain. Thus, efforts are currently underway in the photonic community to design an integrated optical readout, which allows to perform all operations in the optical domain. In addition to the technological challenge of designing such a readout, new algorithms have to be designed in order to train it. Foremost, suitable algorithms need to be able to deal with the fact that the actual on-chip reservoir states are not directly observable. In this work, we investigate several options for such a training algorithm and propose a solution in which the complex states of the reservoir can be observed by appropriately setting the readout weights, while iterating over a predefined input sequence. We perform numerical simulations in order to compare our method with an ideal baseline requiring full observability as well as with an established black-box optimization approach (CMA-ES).en_US
dc.identifier.citationFreiberger, M., Katumba, A., Bienstman, P., & Dambre, J. (2018). Training passive photonic reservoirs with integrated optical readout. IEEE transactions on neural networks and learning systems , 30 (7), 1943-1953.en_US
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/8517105/
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/5638
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectCognitive Computingen_US
dc.subjectReservoir Computingen_US
dc.subjectPhotonic Computingen_US
dc.subjectNeuromorphic Computingen_US
dc.subjectNonlinearity Inversionen_US
dc.subjectIntegrated Optical Readouten_US
dc.subjectLimited Observabilityen_US
dc.titleTraining Passive Photonic Reservoirs with Integrated Optical Readouten_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Training Passive Photonic Reservoirs with.pdf
Size:
1.07 MB
Format:
Adobe Portable Document Format
Description:
Article
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Engineering and Technology