Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation

H. Zhang; H. Cai; D. Paesani; R. Santagati; A. Laing; L. C. Kwek; A. Q. Liu

doi:10.23919/CLEO.2019.8749941

Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation

H. Zhang, H. Cai, D. Paesani, R. Santagati, A. Laing, L. C. Kwek, A. Q. Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

Optimal method are applied in characterizing and reconstructing designed unitary matrices on linear optical circuit. The scheme is based on the measurement of single-photon and two-photon statistics using coherent beams.

Original language	English
Title of host publication	2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)	9781943580576
DOIs	https://doi.org/10.23919/CLEO.2019.8749941
Publication status	Published - 1 May 2019
Event	2019 Conference on Lasers and Electro-Optics, CLEO 2019 - San Jose, United States Duration: 5 May 2019 → 10 May 2019

Publication series

Name	2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings

Conference

Conference	2019 Conference on Lasers and Electro-Optics, CLEO 2019
Country/Territory	United States
City	San Jose
Period	5/05/19 → 10/05/19

Research Groups and Themes

Bristol Quantum Information Institute
QETLabs

Keywords

Optical design
Photonics
Genetic Algorithms
Structural beams
quantum computing
quantum gates

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10.23919/CLEO.2019.8749941

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Zhang, H., Cai, H., Paesani, D., Santagati, R., Laing, A., Kwek, L. C., & Liu, A. Q. (2019). Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation. In 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings Article 8749941 (2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.23919/CLEO.2019.8749941

@inproceedings{fc64f2f4c60b4cbc984dd295923ef87a,

title = "Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation",

abstract = "Optimal method are applied in characterizing and reconstructing designed unitary matrices on linear optical circuit. The scheme is based on the measurement of single-photon and two-photon statistics using coherent beams.",

keywords = "Optical design, Photonics, Genetic Algorithms, Structural beams, quantum computing, quantum gates",

author = "H. Zhang and H. Cai and D. Paesani and R. Santagati and A. Laing and Kwek, {L. C.} and Liu, {A. Q.}",

year = "2019",

month = may,

day = "1",

doi = "10.23919/CLEO.2019.8749941",

language = "English",

series = "2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

booktitle = "2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings",

address = "United States",

note = "2019 Conference on Lasers and Electro-Optics, CLEO 2019 ; Conference date: 05-05-2019 Through 10-05-2019",

}

Zhang, H, Cai, H, Paesani, D, Santagati, R, Laing, A, Kwek, LC & Liu, AQ 2019, Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation. in 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings., 8749941, 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2019 Conference on Lasers and Electro-Optics, CLEO 2019, San Jose, United States, 5/05/19. https://doi.org/10.23919/CLEO.2019.8749941

Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation. / Zhang, H.; Cai, H.; Paesani, D. et al.
2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE), 2019. 8749941 (2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation

AU - Zhang, H.

AU - Cai, H.

AU - Paesani, D.

AU - Santagati, R.

AU - Laing, A.

AU - Kwek, L. C.

AU - Liu, A. Q.

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Optimal method are applied in characterizing and reconstructing designed unitary matrices on linear optical circuit. The scheme is based on the measurement of single-photon and two-photon statistics using coherent beams.

AB - Optimal method are applied in characterizing and reconstructing designed unitary matrices on linear optical circuit. The scheme is based on the measurement of single-photon and two-photon statistics using coherent beams.

KW - Optical design

KW - Photonics

KW - Genetic Algorithms

KW - Structural beams

KW - quantum computing

KW - quantum gates

UR - http://www.scopus.com/inward/record.url?scp=85069218058&partnerID=8YFLogxK

U2 - 10.23919/CLEO.2019.8749941

DO - 10.23919/CLEO.2019.8749941

M3 - Conference Contribution (Conference Proceeding)

AN - SCOPUS:85069218058

T3 - 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings

BT - 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2019 Conference on Lasers and Electro-Optics, CLEO 2019

Y2 - 5 May 2019 through 10 May 2019

ER -

Zhang H, Cai H, Paesani D, Santagati R, Laing A, Kwek LC et al. Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation. In 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE). 2019. 8749941. (2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings). doi: 10.23919/CLEO.2019.8749941

Machine Learning Applied in Reconstruction of Unitary Matrix for Quantum Computation

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