A physics-based transfer learning scheme improves a neural-network surrogate for quantum cascade laser design, enabling genetic-algorithm optimization about 80,000 times faster than numerical simulation.
Evaluation of some scattering times for electrons in unbiased and biased single- and multiple-quantum-well structures,
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Efficient nanophotonic devices optimization using deep neural network trained with physics-based transfer learning (PBTL) methodology
A physics-based transfer learning scheme improves a neural-network surrogate for quantum cascade laser design, enabling genetic-algorithm optimization about 80,000 times faster than numerical simulation.