Chumak, A. V. ; Kabos, P. ; Wu, M. ; Abert, C. ; Adelmann, C. ; Adeyeye, A. O. ; 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. ; Kusminskiy, S. Viola ; 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, 58 (6). pp. 1-72. ISSN 0018-9464
Full text not available from this repository.
Official URL: http://doi.org/10.1109/TMAG.2022.3149664
Related URL: http://dx.doi.org/10.1109/TMAG.2022.3149664
Abstract
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.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Institute of Electrical and Electronic Engineers. |
| ID Code: | 129822 |
| Deposited On: | 02 Dec 2022 06:07 |
| Last Modified: | 05 Dec 2022 05:16 |
Repository Staff Only: item control page
