Fig. 1 | Scientific Reports

Fig. 1

From: Efficient nanophotonic devices optimization using deep neural network trained with physics-based transfer learning methodology

Fig. 1

(a)Overall procedure of methodology, categorized to training dataset generation process (green), training of the DNN surrogate models (blue), optimization process of the QCLs (gray), and optimization result (red). (b) The wave functions, energy levels and (c) modal gain spectrum of a QCL superlattice structure, where 43/18/9/55/11/53/12/47/22/43/15/38/16 /34/18/30/21/28/25/27/32/27/36/25 with thicknesses are in angstroms. The InAlAs barriers’ thicknesses are bold, while the InGaAs wells are in normal face.

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