Large-scale nanophotonic phased array

By Jie Sun, Erman Timurdogan, A. Yaacobi, E. Hosseini, M. Watts. Nature, 2013

1,149 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2185c30eb4f1d7720b3a231b1d693e0029db08c5

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In Biomedical Engineering

In Electrical and Electronic Engineering

Citations in the corpus

MEMS Mirrors for LiDAR: A Review (2020, background): “Silicon photonic phased arrays have the benefits of large-scale arrays, CMOS process compatibility, high integration and low cost [19].”
Large-scale quantum photonic circuits in silicon (2016, methodology): “SOI nanophotonics platforms have been used to implement systems containing hundreds of optical components on a single chip [48, 57, 58].”
On-chip quantum interference between silicon photon-pair sources (2013, background): “The silicon-on-insulator photonics platform (SOI), recently developed for classical applications[10, 11], has several advantages over glass-based systems, including a high component density, a strong χ optical nonlinearity, mature fabrication techniques, fast optical modulators[12], and compatibilit”
Why I am optimistic about the silicon-photonic route to quantum computing (2016, background): “CMOS technology), so that while current classical PICs only contain several thousands of components (in a few hundred square microns) [3], it is reasonable to expect PICs containing many hundreds of thousands of components soon.”
Deep neural networks for the evaluation and design of photonic devices (2020, background): “to be (x;yˆ) and the outputs of the network, given network inputs of x from the training set, to be y. A common loss function for this problem is mean squared error: L(y;yˆ)= 1 N N å n=1 (y (n) yˆ )2 (1) N is the batch size. If N is equal to the training set size, the entire training set is used eac”
Lidar System Architectures and Circuits (2017, neutral): “[5] J.”