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Authors: F. Laporte, J. Dambre, P. Bienstman
Title: Highly parallel simulation and optimization of photonic circuits in time and frequency domain based on the deep-learning framework PyTorch
Format: International Journal
Publication date: 4/2019
Journal/Conference/Book: Scientific Reports
Volume(Issue): 9(1) p.5918
DOI: 10.1038/s41598-019-42408-2
Citations: 4 (Dimensions.ai - last update: 26/10/2020)
2 (OpenCitations - last update: 19/10/2020)
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Abstract

We propose a new method for performing photonic circuit simulations based on the scatter matrix formalism. We leverage the popular deep-learning framework PyTorch to reimagine photonic circuits as sparsely connected complex-valued neural networks. This allows for highly parallel simulation of large photonic circuits on graphical processing units in time and frequency domain while all parameters of each individual component can easily be optimized with well-established machine learning algorithms such as backpropagation.

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