549 citations · 1.5k across the 9 of their papers we have counts for
9 papers
Large-scale global optimization of ultra-high dimensional non-convex landscapes based on generative neural networks
Jiaqi Jiang, Jonathan A. Fan
We present a non-convex optimization algorithm metaheuristic, based on the training of a deep generative network, which enables effective searching within continuous, ultra-high di…
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…
Global optimization of dielectric metasurfaces using a physics-driven neural network
Jiaqi Jiang, Jonathan A. Fan
We present a global optimizer, based on a conditional generative neural network, which can output ensembles of highly efficient topology-optimized metasurfaces operating across a r…
Freeform Diffractive Metagrating Design Based on Generative Adversarial Networks
Jiaqi Jiang, David Sell, Stephan Hoyer +3
A key challenge in metasurface design is the development of algorithms that can effectively and efficiently produce high performance devices. Design methods based on iterative opti…