高斯资源在预告纠缠态生成中的损耗与可区分性效应
Loss and distinguishability effects in heralded entangled state generation with Gaussian resources
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中文总结 AI 辅助
研究光损耗和光子可区分性对高斯资源预告纠缠态生成的影响，建立数值框架优化目标态保真度等，结果表明双轨编码等策略可抑制真空噪声，引入非高斯操作能提升性能，为可扩展态工程提供设计指南。
中文摘要 AI 辅助
本文定量研究了光损耗和光子可区分性对基于高斯资源的预告纠缠态生成的影响。通过将相依赖损耗和部分可区分光子的统计特性纳入相空间表示，建立了一个有效的数值框架来优化目标态保真度和成功概率，特别关注光子加减等非高斯操作引发的增强。数值优化结果表明，双轨编码框架内的非真空后选择策略，结合压缩参数和干涉仪网络的同时调谐，有效抑制了真空噪声，能在实际实验约束下生成高保真的贝尔、GHZ和W态。结果表明，引入非高斯操作可在实际缺陷下成功提升态生成性能，实验缺陷主要降低成功概率而非根本损害态保真度，为集成光子平台上的可扩展态工程提供了实用设计指南。
英文摘要
The effects of optical loss and photon distinguishability on the heralded generation of entangled states based on Gaussian resources are quantitatively investigated. By incorporating mode-dependent loss and the statistical characteristics of partially distinguishable photons into a phase-space representation, an efficient numerical framework is established to optimize target-state fidelity and success probability, with a specific focus on the enhancement triggered by non-Gaussian operations such as photon addition and subtraction. The numerical optimization results indicate that a non-vacuum post-selection strategy within a dual-rail encoding framework, combined with the simultaneous tuning of squeezing parameters and the interferometer network, effectively suppresses vacuum noise, enabling the generation of high-fidelity Bell, GHZ, and W states under realistic experimental constraints. The results show that introducing non-Gaussian operations can successfully enhance the state generation performance under realistic imperfections analogous to the enhancements observed under ideal conditions. This study demonstrates that experimental imperfections primarily scale down the success probability rather than fundamentally compromising the state fidelity, providing practical design guidelines for scalable state engineering on integrated photonic platforms.
