发表机构
North Carolina State University（北卡罗来纳州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究将量子信号处理映射到可编程光子集成电路，通过相位控制合成非线性函数，实验验证了深度达L=11的QSP序列，实现算法到硬件的非线性函数生成。
AI 中文摘要
可编程光子集成电路正逐渐成为在室温下运行、规模日益增大且功能多样的干涉处理器。然而，其原生操作是线性的，而许多计算任务需要非线性输入-输出变换，这些变换通常依赖于非线性光学材料或谐振器件。在此，我们建立了量子信号处理（QSP）与可编程干涉光子集成电路原生双模操作之间的直接映射，表明QSP所需的$SU(2)$结构可通过可编程相位控制和模式混合来实现。我们利用24模式可编程光子集成电路上的双轨单光子编码，实验验证了这种对应关系，实现了深度达$L=11$的QSP序列，并通过可编程相位控制合成了STEP、ReLU和SELU函数。光学变换保持线性，而输入变量的重复编码和相干干涉使得输出概率对编码变量产生非线性依赖。在所有可访问的电路深度下，测量响应均遵循编程的QSP变换，硬件引起的均方误差在$10^{-3}$到$10^{-2}$之间，均低于固有的有限深度近似误差。这些结果确立了QSP在可编程光子处理器上的算法到硬件的映射，也展示了在线性光子硬件上实现编码变量可编程非线性函数的算法路径。
英文摘要
Programmable photonic integrated circuits are emerging as increasingly large and versatile interferometric processors operating at room temperature. However, their native operations are linear, while many computational tasks require nonlinear input-output transformations that typically rely on nonlinear optical materials or resonant devices. Here, we establish a direct mapping between quantum signal processing (QSP) and the native two-mode operations of programmable interferometric photonic integrated circuits, showing that the $SU(2)$ structure required by QSP can be realized through programmable phase control and mode mixing. We experimentally demonstrate this correspondence using dual-rail single-photon encoding on a 24-mode programmable photonic integrated circuit, realizing QSP sequences up to depth $L=11$ and synthesizing STEP, ReLU and SELU functions through programmable phase control. The optical transformation remains linear, while repeated encoding of the input variable and coherent interference produce a nonlinear dependence of the output probabilities on the encoded variable. Across all accessible circuit depths, the measured responses follow the programmed QSP transformations, with hardware-induced mean squared errors between $10^{-3}$ and $10^{-2}$, all remaining below the intrinsic finite-depth approximation error. These results establish an algorithm-to-hardware mapping of QSP on programmable photonic processors. They also demonstrate an algorithmic route to programmable nonlinear functions of encoded variables on linear photonic hardware.
CommentsEqual contribution: Elaheh Karooby and Masoud Hakimi Heris
