发表机构
Paderborn University; Czech Technical University in Prague（帕德博恩大学; 布拉格捷克技术大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究通过光子时间复用量子行走，在混合量子-经典追逐问题中，发现增加经典捕食者（狮子）的移动性可增强量子猎物（羊）的生存，展示了经典随机控制对量子特征的促进作用。
AI 中文摘要
测量和经典随机性通常会降低相干性；但控制子系统被监测的地点和时间，反而能使它们成为一种可调资源。我们引入了一种光子时间复用量子行走，其快速可重构性实现了精确的位置测量，使我们能够在混合量子-经典追逐问题中研究这种相互作用：一个量子行走者（羊）在一条线上演化，而一个经典追逐者（狮子）进行懒惰随机行走。每条狮子轨迹驱动羊的不同的相干、范数减少演化，通过狮子位置的测量实现捕获；对记录轨迹进行平均，则合成一个退相干过程。反直觉的是，增加狮子的移动性并不会单调地抑制生存：在广泛的跳跃概率范围内，羊的生存情况优于面对静止捕食者时。直接观察到这种局部增强，我们展示了一个明显的量子特征，它受到经典随机控制的帮助而非阻碍。
英文摘要
Measurement and classical randomness usually degrade coherence; controlling where and when a subsystem is monitored can instead make them a tunable resource. We introduce a photonic time-multiplexed quantum walk whose fast reconfigurability enables precise position measurements, allowing us to study this interplay in a hybrid quantum-classical pursuit problem: A quantum walker (lamb) evolves on a line while a classical pursuer (lion) performs a lazy random walk. Each lion trajectory drives a distinct coherent, norm-reducing evolution of the lamb, with capture implemented by measurements at the lion's positions; averaging over the recorded trajectories then synthesizes a decoherent process. Counterintuitively, increasing the lion's mobility does not monotonically suppress survival: over a broad range of hopping probabilities, the lamb survives better than against an immobile predator. Directly observing this local enhancement, we demonstrate a manifestly quantum feature aided rather than hindered by classical stochastic control.
