21 citations · 26 across the 2 of their papers we have counts for
10 papers
Inverse design of photonic crystals through automatic differentiation
Momchil Minkov, Ian A. D. Williamson, Lucio C. Andreani +5
Gradient-based inverse design in photonics has already achieved remarkable results in designing small-footprint, high-performance optical devices. The adjoint variable method, whic…
Design of a multi-channel photonic crystal dielectric laser accelerator
Zhexin Zhao, Dylan S. Black, R. Joel England +5
To be useful for most scientific and medical applications, compact particle accelerators will require much higher average current than enabled by current architectures. For this pu…
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…
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…
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…
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…