441 citations · 523 across the 6 of their papers we have counts for
6 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…
Automated Atomic Silicon Quantum Dot Circuit Design via Deep Reinforcement Learning
Robert Lupoiu, Samuel S. H. Ng, Jonathan A. Fan +1
Robust automated design tools are crucial for the proliferation of any computing technology. We introduce the first automated design tool for the silicon dangling bond quantum dot…
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…
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…
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…