基于白盒多平面光转换的集成鲁棒通用线性光学

中文摘要 AI 辅助

通过多平面光转换（MPLC）实现的集成通用线性光学处理器具有低硬件复杂度和高制造鲁棒性的特点，适用于多种光子处理任务。然而，缺乏经过验证的校准协议限制了其通用性和潜力。在此，我们提出了一种基于机器学习的校准方法，并使用由交错多端口定向耦合器和移相器阵列组成的八模硅光子处理器进行了验证。我们表征了耦合器传递矩阵和各个移相器的电流-相位响应。为了验证鲁棒性，我们在1500、1550和1580 nm波长下以及部分移相器停用的情况下，使用Haar随机酉矩阵展示了其通用性。借助这一白盒设备，我们还展示了高维量子门和用于手写数字分类的量子储备计算。我们的工作推进了基于集成MPLC的通用线性光学，并为大规模、制造鲁棒、宽带的经典和量子光子信息处理硬件铺平了道路。

英文摘要

The integrated universal linear optical processor realized via multi-plane light conversion (MPLC) features low hardware complexity and high fabrication robustness, suitable for diverse photonic processing tasks. However, the lack of validated calibration protocols limits its universality and potential. Here, we propose a machine-learning-based calibration method and verify it using an eight-mode silicon photonic processor composed of interleaved multiport directional couplers and phase-shifter arrays. We characterize coupler transfer matrices and current-phase responses of individual phase shifters. To validate the robustness, we demonstrate its universality with Haar-random unitary matrices at wavelengths of 1500, 1550, and 1580 nm, and under partial phase-shifter deactivation. With this white-boxed device, we also demonstrate high-dimensional quantum gates and quantum reservoir computing for handwritten digit classification. Our work advances integrated MPLC-based universal linear optics and paves the way for large-scale, fabrication-robust, broadband hardware for classical and quantum photonic information processing.

发表机构

• University of Science and Technology of China（中国科学技术大学）
• Anhui Province Key Laboratory of Quantum Network（安徽省量子通信网络重点实验室）
• Hefei National Laboratory（合肥国家实验室）
• Hefei Guizhen Chip Technologies Co., Ltd.（合肥贵阵芯片技术有限公司）

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