arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2203.06368quant-phphysics.optics
收藏

集成电路中多光子分裂态的复杂结构与表征

Complex structure and characterization of multi-photon split states in integrated circuits

Jihua Zhang, Andrey A. Sukhorukov

AI总结:

本研究针对多光子分裂态高效表征难题,推导其约化密度矩阵结构与独立系数,提出通过静态集成光子电路干涉测量实现次二次规模表征的方法,并设计了鲁棒的线性光学神经网络优化电路。

摘要:

多光子分裂态(每个光子处于不同空间模式)是各类量子应用的核心资源,但其高效表征仍是一个待解决的问题。本文推导了其约化空间密度矩阵的通用结构,确定了实值与复值独立系数的数量,这些系数尤其能完全决定所有光子的可区分性。随后,我们证明通过测量静态集成电路中光子干涉后的相关性,可完全表征该密度矩阵,且所需输出数量随光子数呈次二次增长。我们提出了由分段耦合波导构成的优化电路设计,该设计属于线性光学神经网络,可最小化重构误差,并提升对制造偏差的鲁棒性。

英文摘要:

Multi-photon split states, where each photon is in a different spatial mode, represent an essential resource for various quantum applications, yet their efficient characterization remains an open problem. Here, we formulate the general structure of their reduced spatial density matrices and identify the number of real and complex-valued independent coefficients, which in particular completely determine the distinguishability of all photons. Then, we show that this density matrix can be fully characterized by measuring correlations after photon interference in a static integrated circuit, where the required outputs scale sub-quadratically versus the number of photons. We present optimized circuit designs composed of segmented coupled waveguides, representing a linear optical neural network, which minimize the reconstruction error and facilitate robustness to fabrication deviations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑