串联纳米线探测器的双触发用于基于事件的光子数分配

中文摘要 AI 辅助

光子数分辨（PNR）探测器是光子量子技术的关键组成部分。然而，传统的单通道边沿触发读出难以实时分辨光子数 $n$，或表征定时抖动如何依赖于 $n$。在本工作中，我们在一个三像素串联的超导纳米线单光子探测器（SNSPD）上采用双触发方法，该探测器在探测脉冲的上升沿和下降沿均触发。通过这样做，我们保留了探测事件的精确到达时间，同时将光子数映射到上升沿和下降沿之间的时间间隔上，从而允许事件清晰分离。使用该技术，我们将每个探测事件分配到 $n = 1, 2$ 或 $3$ 个光子，所有三个类别的后验置信度为 $99\\%$。定时抖动随 $n$ 增加而减小，对于 $n \geq 2$ 达到低于 $41\\, \text{ps}$ 的值。将边沿触发与恒比鉴别（CFD）用于到达时间提取进行比较，我们发现CFD对单光子事件产生更低的抖动和几乎恒定的平均到达时间。总之，我们的结果确立了双触发作为PNR探测器的一种稳健、低延迟读出方案，同时揭示了定时抖动对光子数的依赖性，这与预示光子量子应用中可实现的定时精度相关。

英文摘要

Photon-number-resolving (PNR) detectors are essential components of photonic quantum technologies. However, conventional single-channel edge-triggered readout struggles to resolve the photon number $n$ in real time or to characterize how timing jitter depends on $n$. In this work, we use a dual-trigger method on a three-pixel series-connected superconducting nanowire single-photon detector (SNSPD) that triggers on both the rising and falling edges of the detection pulse. By doing so, we preserve the precise arrival time of the detection event while mapping the photon number onto the time interval between the rising and falling edges, allowing clear separation of the events. Using this technique, we assign each detection event to $n = 1, 2,$ or 3 photons with $99\,\%$ posterior confidence across all three classes. The timing jitter decreases as $n$ increases, reaching values below $41\, \text{ps}$ for $n \geq 2$. Comparing edge-triggering with constant-fraction discrimination (CFD) for arrival-time extraction, we find that CFD yields lower jitter for single-photon events and a nearly constant mean arrival time. Altogether, our results establish dual-triggering as a robust, low-latency readout scheme for PNR detectors, while revealing a photon-number dependence of the timing jitter relevant to timing precision achievable in heralded photonic quantum applications.

发表机构

• Walter Schottky Institut, Technische Universität München（瓦尔特·肖特基研究所，慕尼黑工业大学）
• TUM School of Natural Sciences, Technische Universität München（慕尼黑工业大学自然科学院）
• Munich Quantum Instruments GmbH（慕尼黑量子仪器有限公司）
• TUM School of Computation, Information and Technology, Technische Universität München（慕尼黑工业大学计算、信息与技术学院）
• PicoQuant GmbH（皮科量子有限公司）

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