Nanoscale magnonic networks

Qi Wang (Korresp. Autor*in), Gyorgy Csaba, Roman Verba, Andrii V. Chumak, Philipp Pirro

Veröffentlichungen: Beitrag in FachzeitschriftArtikelPeer Reviewed

Abstract

With the rapid development of artificial intelligence in recent years, mankind is facing an unprecedented demand for data processing. Today, almost all data processing is performed using electrons in conventional CMOS circuits. Over the past few decades, scientists have been searching for faster and more efficient ways to process data. Now, magnons, the quanta of spin waves, show the potential for higher efficiency and lower energy consumption in solving some specific problems. While magnonics remains predominantly in the realm of academia, significant efforts are being made to explore the scientific and technological challenges of the field. Numerous proof-of-concept prototypes have already been successfully developed and tested in laboratories. In this Perspective, we review the developed magnonic devices and discuss the current challenges in realizing magnonic circuits based on these building blocks. We look at the application of spin waves in neuromorphic networks, stochastic, reservoir, and quantum computing and discuss the advantages over conventional electronics in these areas. We then discuss a powerful tool, inverse design magnonics, which has the potential to revolutionize the field by enabling the precise design and optimization of magnonic devices in a short time. Finally, we provide a theoretical prediction of energy consumption and propose benchmarks for universal magnonic circuits.
OriginalspracheEnglisch
Aufsatznummer040503
FachzeitschriftPhysical Review Applied
Jahrgang21
Ausgabenummer4
DOIs
PublikationsstatusVeröffentlicht - Apr. 2024

ÖFOS 2012

  • 103015 Kondensierte Materie
  • 103019 Mathematische Physik
  • 103017 Magnetismus

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