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利用激光对非线性光子电路的波函数进行直接表征。

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

作者信息

Lenzini Francesco, Poddubny Alexander N, Titchener James, Fisher Paul, Boes Andreas, Kasture Sachin, Haylock Ben, Villa Matteo, Mitchell Arnan, Solntsev Alexander S, Sukhorukov Andrey A, Lobino Mirko

机构信息

Centre for Quantum Dynamics, Griffith University, Brisbane, QLD 4111, Australia.

Nonlinear Physics Centre, Research School of Physics and Engineering, Australian National University, Canberra, ACT 2601, Australia.

出版信息

Light Sci Appl. 2018 Jan 12;7:17143. doi: 10.1038/lsa.2017.143. eCollection 2018.

Abstract

Integrated photonics is a leading platform for quantum technologies including nonclassical state generation, demonstration of quantum computational complexity and secure quantum communications. As photonic circuits grow in complexity, full quantum tomography becomes impractical, and therefore an efficient method for their characterization 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. 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.

摘要

集成光子学是量子技术的领先平台,包括非经典态生成、量子计算复杂性演示和安全量子通信。随着光子电路复杂性的增加,完全量子层析成像变得不切实际,因此一种有效的表征方法至关重要。在此,我们提出并演示了一种快速、可靠的方法,用于重建由任意二次非线性光学电路产生的双光子态。通过在生成的量子态与来自激光的经典和频产生测量之间建立严格对应关系,我们克服了先前有损多模器件方法的局限性。我们将此协议应用于多通道非线性波导网络,并测量了经典和量子表征之间99.28±0.31%的保真度。该技术能够快速、精确地评估非线性量子光子网络,这是迈向复杂、大规模器件生产的关键一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e0c/6107051/3b550695afdd/lsa2017143f1.jpg

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