activity
20172022
most citedExperimentally realized in situ backpropagation for deep learning in nanophotonic neural networks

330 citations · 422 across the 4 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.ET2019

Parallel fault-tolerant programming of an arbitrary feedforward photonic network

Sunil Pai, Ian A. D. Williamson, Tyler W. Hughes +4

Reconfigurable photonic mesh networks of tunable beamsplitter nodes can linearly transform -dimensional vectors representing input modal amplitudes of light for applications suc…

physics.optics2019

Forward-Mode Differentiation of Maxwell's Equations

Tyler W Hughes, Ian A D Williamson, Momchil Minkov +1

We present a previously unexplored forward-mode differentiation method for Maxwell's equations, with applications in the field of sensitivity analysis. This approach yields exact g…

physics.comp-ph2019

Wave Physics as an Analog Recurrent Neural Network

Tyler W. Hughes, Ian A. D. Williamson, Momchil Minkov +1

Analog machine learning hardware platforms promise to be faster and more energy-efficient than their digital counterparts. Wave physics, as found in acoustics and optics, is a natu…

eess.SP2019

Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks

Ian A. D. Williamson, Tyler W. Hughes, Momchil Minkov +3

We introduce an electro-optic hardware platform for nonlinear activation functions in optical neural networks. The optical-to-optical nonlinearity operates by converting a small po…

physics.optics2019★ 21 cited

Reconfigurable Photonic Circuit for Controlled Power Delivery to Laser-Driven Accelerators on a Chip

Tyler W. Hughes, R. Joel England, Shanhui Fan

Dielectric laser acceleration (DLA) represents a promising approach to building miniature particle accelerators on a chip. However, similar to conventional RF accelerators, an auto…