Advances in Magnetics Roadmap on Spin-Wave Computing

Magnonics addresses the physical properties of spin waves and utilizes them for data processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency range, utilization of nonlinear and nonreciprocal phenomena, and compatibility with CMOS are just a few of many advantages offered by magnons. Although magnonics is still primarily positioned in the academic domain, the scientific and technological challenges of the field are being extensively investigated, and many proof-of-concept prototypes have already been realized in laboratories. This roadmap is a product of the collective work of many authors, which covers versatile spin-wave computing approaches, conceptual building blocks, and underlying physical phenomena. In particular, the roadmap discusses the computation operations with the Boolean digital data, unconventional approaches, such as neuromorphic computing, and the progress toward magnon-based quantum computing. This article is organized as a collection of sub-sections grouped into seven large thematic sections. Each sub-section is prepared by one or a group of authors and concludes with a brief description of current challenges and the outlook of further development for each research direction.

Description

| openaire: EC/H2020/801055/EU//CHIRON

Keywords

computing, data processing, Logic gates, Magnetic domains, magnon, magnonics, Magnonics, Nanoscale devices, Physics, Quantum computing, Spin wave, Three-dimensional displays

DOI

10.1109/TMAG.2022.3149664

Citation

Chumak , A V , Kabos , P , Wu , M , Abert , C , Adelmann , C , Adeyeye , A , Akerman , J , Aliev , F G , Anane , A , Awad , A , Back , C H , Barman , A , Bauer , G E W , Becherer , M , Beginin , E N , Bittencourt , V A S V , Blanter , Y M , Bortolotti , P , Boventer , I , Bozhko , D A , Bunyaev , S A , Carmiggelt , J J , Cheenikundil , R R , Ciubotaru , F , Cotofana , S , Csaba , G , Dobrovolskiy , O V , Dubs , C , Elyasi , M , Fripp , K G , Fulara , H , Golovchanskiy , I A , Gonzalez-Ballestero , C , Graczyk , P , Grundler , D , Gruszecki , P , Gubbiotti , G , Guslienko , K , Haldar , A , Hamdioui , S , Hertel , R , Hillebrands , B , Hioki , T , Houshang , A , Hu , C M , Huebl , H , Huth , M , Iacocca , E , Jungfleisch , M B , Kakazei , G N , Khitun , A , Khymyn , R , Kikkawa , T , Klaui , M , Klein , O , Klos , J W , Knauer , S , Koraltan , S , Kostylev , M , Krawczyk , M , Krivorotov , I N , Kruglyak , V V , Lachance-Quirion , D , Ladak , S , Lebrun , R , Li , Y , Lindner , M , Macedo , R , Mayr , S , Melkov , G A , Mieszczak , S , Nakamura , Y , Nembach , H T , Nikitin , A A , Nikitov , S A , Novosad , V , Otalora , J A , Otani , Y , Papp , A , Pigeau , B , Pirro , P , Porod , W , Porrati , F , Qin , H , Rana , B , Reimann , T , Riente , F , Romero-Isart , O , Ross , A , Sadovnikov , A V , Safin , A R , Saitoh , E , Schmidt , G , Schultheiss , H , Schultheiss , K , Serga , A A , Sharma , S , Shaw , J M , Suess , D , Surzhenko , O , Szulc , K , Taniguchi , T , Urbanek , M , Usami , K , Ustinov , A B , Van der Sar , T , Van Dijken , S , Vasyuchka , V I , Verba , R , Viola Kusminskiy , S , Wang , Q , Weides , M , Weiler , M , Wintz , S , Wolski , S P & Zhang , X 2022 , ' Advances in Magnetics Roadmap on Spin-Wave Computing ' , IEEE Transactions on Magnetics , vol. 58 , no. 6 , 0800172 . https://doi.org/10.1109/TMAG.2022.3149664

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202203032103

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[article-cris] Perustieteiden korkeakoulu / SCI

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