441 citations · 452 across the 4 of their papers we have counts for
8 papers
WaveY-Net: Physics-augmented deep learning for high-speed electromagnetic simulation and optimization
Mingkun Chen, Robert Lupoiu, Chenkai Mao +4
The calculation of electromagnetic field distributions within structured media is central to the optimization and validation of photonic devices. We introduce WaveY-Net, a hybrid d…
Design space reparameterization enforces hard geometric constraints in inverse-designed nanophotonic devices
Mingkun Chen, Jiaqi Jiang, Jonathan Fan
Inverse design algorithms are the basis for realizing high-performance, freeform nanophotonic devices. Current methods to enforce geometric constraints, such as practical fabricati…
Multi-objective and categorical global optimization of photonic structures based on ResNet generative neural networks
Jiaqi Jiang, Jonathan A. Fan
We show that deep generative neural networks, based on global topology optimization networks (GLOnets), can be configured to perform the multi-objective and categorical global opti…
Deep neural networks for the evaluation and design of photonic devices
Jiaqi Jiang, Mingkun Chen, Jonathan A. Fan
The data sciences revolution is poised to transform the way photonic systems are simulated and designed. Photonics are in many ways an ideal substrate for machine learning: the obj…
MetaNet: A new paradigm for data sharing in photonics research
Jiaqi Jiang, Robert Lupoiu, Evan W. Wang +4
Optimization methods are playing an increasingly important role in all facets of photonics engineering, from integrated photonics to free space diffractive optics. However, efforts…
Progressive-Growing of Generative Adversarial Networks for Metasurface Optimization
Fufang Wen, Jiaqi Jiang, Jonathan A. Fan
Generative adversarial networks, which can generate metasurfaces based on a training set of high performance device layouts, have the potential to significantly reduce the computat…