Direct characterization of a nonlinear photonic circuit's wave function with laser light

Lenzini, F, Poddubny, A, Titchener, J, Fisher, P, Boes, A, Kasture, S, Haylock, B, Villa, M, Mitchell, A, Solntsev, A, Sukhorukov, A and Lobino, M 2018, 'Direct characterization of a nonlinear photonic circuit's wave function with laser light', Light: Science and Applications, vol. 7, no. 1, pp. 1-5.

Document type: Journal Article
Collection: Journal Articles

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Title Direct characterization of a nonlinear photonic circuit's wave function with laser light
Author(s) Lenzini, F
Poddubny, A
Titchener, J
Fisher, P
Boes, A
Kasture, S
Haylock, B
Villa, M
Mitchell, A
Solntsev, A
Sukhorukov, A
Lobino, M
Year 2018
Journal name Light: Science and Applications
Volume number 7
Issue number 1
Start page 1
End page 5
Total pages 5
Publisher Nature
Abstract Integrated photonics is a leading platform for quantum technologies including nonclassical state generation 1, 2, 3, 4, demonstration of quantum computational complexity 5 and secure quantum communications 6. As photonic circuits grow in complexity, full quantum tomography becomes impractical, and therefore an efficient method for their characterization 7, 8 is essential. Here we propose and demonstrate a fast, reliable method for reconstructing the two-photon state produced by an arbitrary quadratically nonlinear optical circuit. By establishing a rigorous correspondence between the generated quantum state and classical sum-frequency generation measurements from laser light, we overcome the limitations of previous approaches for lossy multi-mode devices 9, 10. We applied this protocol to a multi-channel nonlinear waveguide network and measured a 99.28±0.31% fidelity between classical and quantum characterization. This technique enables fast and precise evaluation of nonlinear quantum photonic networks, a crucial step towards complex, large-scale, device production.
Subject Quantum Optics
Nonlinear Optics and Spectroscopy
DOI - identifier 10.1038/lsa.2017.143
Copyright notice © The Author(s) 2018. This work is licensed under a Creative Commons Attribution 4.0
ISSN 2095-5545
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Citation counts: TR Web of Science Citation Count  Cited 11 times in Thomson Reuters Web of Science Article | Citations
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