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从 dressed atoms 的级联四波混频实现多模非线性参量放大。

Experimental realization of multimode nonlinear parametric amplification from cascading four-wave mixing of dressed atoms.

出版信息

Opt Express. 2023 Feb 13;31(4):6982-6995. doi: 10.1364/OE.483374.

DOI:10.1364/OE.483374
PMID:36823944
Abstract

The nonlinear parametric process is of great significance for achieving high-quality coherent optical signals and quantum correlated photons. With the development of classical and quantum information processing, the study of the properties of parametric processes is evolving in complex scenarios of multimode, which is limited in conventional nonlinear media due to strict phase matching, e.g. nonlinear crystals. Here we study the dressing-energy-level-cascaded four-wave mixing process to generate multimode optical parametric signals. Via cascading double-Λ type configuration of Rb D line, the non-degenerate energy-level-cascaded FWM is constructed to generate multimode self-parametric amplification. Moreover, with the dressing effects based on atomic coherence, the spatial and frequency multimode characteristics of energy-level-cascaded FWM parametric amplification, i.e., the modes number and pattern, are actively modulated by the pump fields detuning. Also, the spatial modes from the coupling of two coexisting spontaneous parametric FWMs can be controlled to reach tremendous scalability via the atomic coherence and Kerr non-linearity. The atomic coherence effects and unique phase-matching symmetry nature allow flexible modulation of the multimode property of the generated parametric signals within a nonlinear device, which paves a way for multimode classical and quantum information processing.

摘要

非线性参量过程对于实现高质量相干光学信号和量子关联光子具有重要意义。随着经典和量子信息处理的发展,参量过程特性的研究在多模复杂情况下不断发展,由于严格的相位匹配,例如非线性晶体,这在传统的非线性介质中受到限制。在这里,我们研究了调谐能级级联四波混频过程,以产生多模光参量信号。通过级联铷 D 线的双Λ型结构,构建非简并能级级联 FWM,以产生多模自参量放大。此外,基于原子相干的调谐效应,通过泵浦场失谐,主动调制能级级联 FWM 参量放大的空间和频率多模特性,即模式数量和模式图案。此外,通过原子相干和克尔非线性,两个共存的自发参量 FWM 的耦合产生的空间模式可以得到控制,从而达到巨大的可扩展性。原子相干效应和独特的相位匹配对称性允许在非线性器件内灵活地调制产生的参量信号的多模特性,为多模经典和量子信息处理铺平了道路。

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