Reducing Computation Complexity in Optimization of Nanophotonic Structures Using Pruning

Inverse design of complex nanophotonic devices is a very computation-consuming task. Deep-learning-based approaches can facilitate this process. However, due to the lack of solid knowledge about the underlying complexity of the input-output relation for a selected class of nanostructures, it is comm...

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Bibliographic Details
Published in:	IEEE photonics technology letters Vol. 36; no. 4; pp. 215 - 218
Main Authors:	Hadigheh Javani, Mohammad, Zandehshahvar, Mohammadreza, Adibi, Ali
Format:	Journal Article
Language:	English
Published:	New York IEEE 15.02.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Complexity Computation computation complexity Computational complexity Deep learning Inverse design Machine learning Metasurfaces Modelling Nanophotonics Nanostructure Nanostructures Neural networks Pruning Weak nodes
ISSN:	1041-1135, 1941-0174
Online Access:	Get full text
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