All-magnonic repeater based on bistability

Qi Wang (), Roman Verba, Kristýna Davídková, Björn Heinz, Shixian Tian, Yiheng Rao, Mengying Guo, Xueyu Guo, Carsten Dubs, Philipp Pirro and Andrii V. Chumak ()
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Qi Wang: Huazhong University of Science and Technology
Roman Verba: Institute of Magnetism
Kristýna Davídková: University of Vienna
Björn Heinz: Rheinland-Pfälzische Technische Universität Kaiserlautern-Landau
Shixian Tian: Hubei University
Yiheng Rao: Hubei University
Mengying Guo: Huazhong University of Science and Technology
Xueyu Guo: Huazhong University of Science and Technology
Carsten Dubs: INNOVENT e.V., Technologieentwicklung
Philipp Pirro: Rheinland-Pfälzische Technische Universität Kaiserlautern-Landau
Andrii V. Chumak: University of Vienna

Nature Communications, 2024, vol. 15, issue 1, 1-7

Abstract: Abstract Bistability, a universal phenomenon found in diverse fields such as biology, chemistry, and physics, describes a scenario in which a system has two stable equilibrium states and resets to one of the two states. The ability to switch between these two states is the basis for a wide range of applications, particularly in memory and logic operations. Here, we present a universal approach to achieve bistable switching in magnonics, the field processing data using spin waves. A pronounced bistable window is observed in a 1 μm wide magnonic conduit under an external rf drive. The system is characterized by two magnonic stable states defined as low and high spin-wave amplitude states. The switching between these two states is realized by another propagating spin wave sent into the rf driven region. This magnonic bistable switching is used to design a magnonic repeater, which receives the original decayed and distorted spin wave and regenerates a new spin wave with amplified amplitude and normalized phase. Our magnonic repeater can be installed at the inputs of each magnonic logic gate to overcome the spin-wave amplitude degradation and phase distortion during previous propagation and achieve integrated magnonic circuits or magnonic neuromorphic networks.

Date: 2024
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DOI: 10.1038/s41467-024-52084-0

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