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20162026
most cited11 TeraFLOPs per second photonic convolutional accelerator for deep learning optical neural networks

1.5k citations · 4.2k across the 21 of their papers we have counts for

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physics.optics2026

Reconfigurable microwave photonic Fano filters based on optical Kerr microcombs

Qi Zou, Jiayang Wu, Yang Sun +9

Microwave photonic (MWP) Fano filters, featuring asymmetric filter shapes that enable steep spectral transitions, are attractive for high bandwidth microwave signal processing such…

physics.optics2024★ 1 cited

Ultra-wideband integrated microwave photonic multi-parameter measurement system on thin-film lithium niobate

Yong Zheng, Zhen Han, LiHeng Wang +13

Research on microwave signal measurement techniques is risen, driven by the expanding urgent demands of wireless communication, global positioning systems, remote sensing and 6G ne…

physics.optics2024★ 57 cited

Photonic real time video image signal processor at 17Tb/s based on a Kerr microcomb

Mengxi Tan, Xingyuan Xu, Andreas Boes +8

Signal processing has become central to many fields, from coherent optical telecommunications, where it is used to compensate signal impairments, to video image processing. Image p…

physics.optics2022★ 18 cited

Spatio-temporal isolator in lithium niobate on insulator

Haijin Huang, Armandas Balcytis, Aditya Dubey +5

In this contribution, we simulate, design, and experimentally demonstrate an integrated optical isolator based on spatiotemporal modulation in the thin-film lithium niobate on insu…

physics.optics2022★ 27 cited

Recirculating Light Phase Modulator

Haijin Huang, Xu Han, Armandas Balčytis +7

High efficiency and a compact footprint are desired properties for electro-optic modulators. In this paper, we propose, theoretically investigate and experimentally demonstrate a r…

physics.optics2020★ 1 cited

Single photonic perceptron based on a soliton crystal Kerr microcomb for high-speed, scalable, optical neural networks

Xingyuan Xu, Mengxi Tan, Bill Corcoran +9

Optical artificial neural networks (ONNs), analog computing hardware tailored for machine learning, have significant potential for ultra-high computing speed and energy efficiency.…