activity
20142025
most citedAll-optical signal processing platforms for CMOS compatible integrated nonlinear optics

1.8k citations · 6.5k across the 30 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

physics.optics202176 cited

Enhancing the third-order optical nonlinear performance in CMOS devices with integrated 2D graphene oxide films

David Moss

We report enhanced nonlinear optics in complementary metal oxide semiconductor compatible photonic platforms through the use of layered two dimensional (2D) graphene oxide (GO) fil…

physics.optics202195 cited

Spectral Shaping with Integrated Self-Coupled Sagnac Loop Reflectors

David J. Moss

We propose and theoretically investigate integrated photonic filters based on coupled Sagnac loop reflectors (SLRs) formed by a self-coupled wire waveguide. By tailoring coherent m…

physics.app-ph202164 cited

Ultra-high bandwidth fiber-optic data transmission with a single chip source

David J. Moss

We report world record high data transmission over standard optical fiber from a single optical source. We achieve a line rate of 44.2 Terabits per second (Tb/s) employing only the…

physics.app-ph2021337 cited

High bandwidth temporal RF photonic signal processing with Kerr micro-combs: integration, fractional differentiation and Hilbert transforms

Mengxi Tan, Xingyuan Xu, Jiayang Wu +1

Integrated Kerr micro-combs, a powerful source of many wavelengths for photonic RF and microwave signal processing, are particularly useful for transversal filter systems. They hav…

physics.app-ph202164 cited

Optical data transmission field trial @ 44Tb/s with a 49GHz Kerr soliton crystal microcomb

Mengxi Tan, Xingyuan Xu, David J. Moss

We report world record high data transmission over standard optical fiber from a single optical source. We achieve a line rate of 44.2 Terabits per second (Tb/s) employing only the…

physics.app-ph202166 cited

Soliton crystal Kerr microcombs for high-speed, scalable optical neural networks at 10 GigaOPs/s

Xingyuan Xu, Mengxi Tan, David J. Moss

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a new approach to ONNs based on integrated Kerr…