连续驱动双能级系统中光子模式的纠缠

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Jiaying Yang, Ingrid Strandberg, Alejandro Vivas-Viaña, Akshay Gaikwad, Claudia Castillo-Moreno, Anton Frisk Kockum, Muhammad Asad Ullah, Carlos Sánchez Muñoz, Axel Martin Eriksson, Simone Gasparinetti
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引用次数: 0

摘要

产生光的纠缠态的能力是量子通信和分布式量子计算的关键基本要素。连续驱动源,包括那些基于自发参数下转换的源,通常是概率的,而确定性源需要控制场的精确定时。本文利用时域和频域模式匹配的优势,利用相干驱动器连续激发量子发射器(超导量子比特)产生纠缠光子模式。利用联合量子态层析成像和对数负性,我们证明了从共振荧光光谱的两个边带提取的模式之间产生纠缠。由于纠缠的光子模式是完全正交的,它们可以被转移到不同的量子存储器中。我们的方法可用于在各种物理平台上以高速率分布纠缠,并应用于波导量子电动力学,分布式量子计算和量子网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Entanglement of photonic modes from a continuously driven two-level system

Entanglement of photonic modes from a continuously driven two-level system

The ability to generate entangled states of light is a key primitive for quantum communication and distributed quantum computation. Continuously driven sources, including those based on spontaneous parametric downconversion, are usually probabilistic, whereas deterministic sources require accurate timing of the control fields. Here, we experimentally generate entangled photonic modes by continuously exciting a quantum emitter - a superconducting qubit - with a coherent drive, taking advantage of mode matching in the time and frequency domain. Using joint quantum state tomography and logarithmic negativity, we show that entanglement is generated between modes extracted from the two sidebands of the resonance fluorescence spectrum. Because the entangled photonic modes are perfectly orthogonal, they can be transferred into distinct quantum memories. Our approach can be utilized to distribute entanglement at a high rate in various physical platforms, with applications in waveguide quantum electrodynamics, distributed quantum computing, and quantum networks.

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来源期刊
npj Quantum Information
npj Quantum Information Computer Science-Computer Science (miscellaneous)
CiteScore
13.70
自引率
3.90%
发文量
130
审稿时长
29 weeks
期刊介绍: The scope of npj Quantum Information spans across all relevant disciplines, fields, approaches and levels and so considers outstanding work ranging from fundamental research to applications and technologies.
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