Design of modern photonic devices requires to handle a large number of parameters and figures of merit. By scaling down the complexity of the problem, machine learning dimensionality reduction enables the discovery of better performing devices, higher integration scale, and efficient evaluation of fabrication tolerances.
Dimensionality reduction for the on-chip integration of advanced photonic devices and functionalities / Melati, Daniele; Dezfouli, Mohsen Kamandar; Grinberg, Yuri; Al-Digeil, Muhammad; Xu, Dan-Xia; Schmid, Jens H.; Cheben, Pavel; Waqas, Abi; Manfredi, Paolo; Zhang, Jianhao; Vivien, Laurent; Alonso-Ramos, Carlos. - ELETTRONICO. - (2021), pp. 1-4. ((Intervento presentato al convegno 2021 European Conference on Optical Communication (ECOC 2021) tenutosi a Bordeaux, Francia nel 13-16 settembre 2021 [10.1109/ECOC52684.2021.9606084].
Titolo: | Dimensionality reduction for the on-chip integration of advanced photonic devices and functionalities | |
Autori: | ||
Data di pubblicazione: | 2021 | |
Abstract: | Design of modern photonic devices requires to handle a large number of parameters and figures of ...merit. By scaling down the complexity of the problem, machine learning dimensionality reduction enables the discovery of better performing devices, higher integration scale, and efficient evaluation of fabrication tolerances. | |
ISBN: | 978-1-6654-3868-1 | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2949643