From 3D to 2D and back again
Author:
Affiliation:
1. Optics Laboratory , École polytechnique fédérale de Lausanne , Lausanne , Switzerland
2. Laboratory of Applied Photonics Devices , École polytechnique fédérale de Lausanne , Lausanne , Switzerland
Abstract
Funder
Swiss National Science Foundation
Publisher
Walter de Gruyter GmbH
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials,Biotechnology
Link
https://www.degruyter.com/document/doi/10.1515/nanoph-2022-0512/pdf
Reference101 articles.
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2. W. Bogaerts, D. Pérez, J. Capmany, et al.., “Programmable photonic circuits,” Nature, vol. 586, no. 7828, pp. 207–216, 2020. https://doi.org/10.1038/s41586-020-2764-0.
3. Y. Shen, N. C. Harris, S. Skirlo, et al.., “Deep learning with coherent nanophotonic circuits,” Nat. Photonics, vol. 11, no. 7, pp. 441–446, 2017. https://doi.org/10.1038/nphoton.2017.93.
4. J. Feldmann, N. Youngblood, M. Karpov, et al.., “Parallel convolutional processing using an integrated photonic tensor core,” Nature, vol. 589, no. 7840, pp. 52–58, 2021. https://doi.org/10.1038/s41586-020-03070-1.
5. X. Xu, G. Ren, T. Feleppa, et al.., “Self-calibrating programmable photonic integrated circuits,” Nat. Photonics, vol. 16, no. 8, pp. 595–602, 2022. https://doi.org/10.1038/s41566-022-01020-z.
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