Suppr超能文献

在超高频率分辨率下检测到的非线性磁子波导中的涌现相干模式。

Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution.

作者信息

An K, Xu M, Mucchietto A, Kim C, Moon K-W, Hwang C, Grundler D

机构信息

Laboratory of Nanoscale Magnetic Materials and Magnonics, Institute of Materials (IMX), School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, 1015, Switzerland.

Quantum Technology Institute, Korea Research Institute of Standards and Science, Daejeon, 34113, Republic of Korea.

出版信息

Nat Commun. 2024 Aug 24;15(1):7302. doi: 10.1038/s41467-024-51483-7.

Abstract

Nonlinearity of dynamic systems plays a key role in neuromorphic computing, which is expected to reduce the ever-increasing power consumption of machine learning and artificial intelligence applications. For spin waves (magnons), nonlinearity combined with phase coherence is the basis of phenomena like Bose-Einstein condensation, frequency combs, and pattern recognition in neuromorphic computing. Yet, the broadband electrical detection of these phenomena with high-frequency resolution remains a challenge. Here, we demonstrate the generation and detection of phase-coherent nonlinear magnons in an all-electrical GHz probe station based on coplanar waveguides connected to a vector network analyzer which we operate in a frequency-offset mode. Making use of an unprecedented frequency resolution, we resolve the nonlocal emergence of a fine structure of propagating nonlinear magnons, which sensitively depends on both power and a magnetic field. These magnons are shown to maintain coherency with the microwave source while propagating over macroscopic distances. We propose a multi-band four-magnon scattering scheme that is in agreement with the field-dependent characteristics of coherent nonlocal signals in the nonlinear excitation regime. Our findings are key to enable the seamless integration of nonlinear magnon processes into high-speed microwave electronics and to advance phase-encoded information processing in magnonic neuronal networks.

摘要

动态系统的非线性在神经形态计算中起着关键作用,神经形态计算有望降低机器学习和人工智能应用中不断增加的功耗。对于自旋波(磁振子)而言,非线性与相位相干相结合是玻色 - 爱因斯坦凝聚、频率梳以及神经形态计算中的模式识别等现象的基础。然而,以高频率分辨率对这些现象进行宽带电学检测仍然是一项挑战。在此,我们展示了在基于与矢量网络分析仪相连的共面波导的全电学GHz探针站中,相位相干非线性磁振子的产生与检测,我们在频率偏移模式下操作该矢量网络分析仪。利用前所未有的频率分辨率,我们解析了传播的非线性磁振子精细结构的非局域出现,其敏感地依赖于功率和磁场。这些磁振子在宏观距离上传播时被证明与微波源保持相干。我们提出了一种多波段四磁振子散射方案,该方案与非线性激发 regime 中相干非局域信号的场依赖特性一致。我们的发现对于使非线性磁振子过程无缝集成到高速微波电子学中以及推进磁振子神经网络中的相位编码信息处理至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b26/11344808/bbf9dbefa879/41467_2024_51483_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验