发表机构
Ulm University; Center for Integrated Quantum Science and Technology (IQST)（乌尔姆大学; 集成量子科学与技术中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过海森堡绘景张量网络形式研究高斯玻色采样，揭示相位扩散逐步抑制多体干涉，建立了连接相位涨落与量子干涉丧失的透明框架。
AI 中文摘要
我们发展了无碰撞高斯玻色采样的海森堡绘景张量网络形式，提供了基于实验可测量的输出概率的直接福克空间表达式。该表示自然恢复了哈夫尼结构，同时揭示了GBS概率分解为与完美匹配对相关的无相位贡献和干涉扇区层级。作为应用，我们研究了相位扩散，展示了其如何逐步抑制多体干涉，使输出统计趋近于经典二聚体模型 regime。我们的结果建立了一个透明框架，用于连接实验表征的相位涨落与光子量子采样实验中量子干涉的丧失。
英文摘要
We develop a Heisenberg-picture tensor-network formulation of collision-free Gaussian Boson Sampling, providing a direct Fock-space expression for output probabilities in terms of experimentally accessible quantities. The resulting representation naturally recovers the Hafnian structure while revealing the decomposition of GBS probability into a phase-insensitive contribution and a hierarchy of interference sectors associated with pairs of perfect matchings. As an application, we investigate phase diffusion and show how it progressively suppresses many-body interference, driving the output statistics toward a classical dimer-model regime. Our results establish a transparent framework for connecting experimentally characterized phase fluctuations with the loss of quantum interference in photonic quantum sampling experiments.
Comments7 pages, 1 figure
