Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138875
Title: Determinating full parameters of U-matrix for reconfigurable Boson sampling circuits using machine learning
Authors: Wan, L. X.
Zhang, Haochi
Huang, Jian Guo
Zhang, Gong
Kwek, L. C.
Fitzsimons, J.
Chong, Yi Dong
Gong, J. B.
Szameit, A.
Zhou, X. Q.
Yung, M. H.
Jin, X. M.
Su, X. L.
Ser, Wee
Gao, W. B.
Liu, Ai Qun
Keywords: Engineering::Electrical and electronic engineering::Optics, optoelectronics, photonics
Issue Date: 2018
Source: Wan, L. X., Zhang, H., Huang, J. G., Zhang, G., Kwek, L. C., Fitzsimons, J., . . . Liu, A. Q. (2018). Determinating full parameters of U-matrix for reconfigurable Boson sampling circuits using machine learning. 2018 Conference on Lasers and Electro-Optics (CLEO): Applications and Technology, FM1G.2-. doi:10.1364/CLEO_AT.2018.JTh2A.18
Project: NRF-CRP13-2014-01
Conference: 2018 Conference on Lasers and Electro-Optics (CLEO): Applications and Technology
Abstract: A method of tuning a reconfigurable silicon photonic circuit into an arbitrary unitary operator with machine learning was proposed to bypass the traditional phase-voltage calibration process and make the prediction of applied heating voltage directly.
URI: https://hdl.handle.net/10356/138875
ISBN: 9781943580422
DOI: 10.1364/CLEO_AT.2018.JTh2A.18
Schools: School of Electrical and Electronic Engineering 
School of Physical and Mathematical Sciences 
Rights: © The Author(s). All rights reserved. This paper was published by Optical Society of America (OSA) in 2018 Conference on Lasers and Electro-Optics (CLEO): Applications and Technology and is made available with permission of the author(s).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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