J. Gartside, K. Stenning, A. Vanstone, T. Dion, Holly H. Holder, D. Arroo, H. Kurebayashi, W. Branford
{"title":"人工自旋冰的可重构训练、涡旋书写和自旋波指纹识别","authors":"J. Gartside, K. Stenning, A. Vanstone, T. Dion, Holly H. Holder, D. Arroo, H. Kurebayashi, W. Branford","doi":"10.21203/RS.3.RS-736619/V1","DOIUrl":null,"url":null,"abstract":"\n Strongly-interacting artificial spin systems are moving beyond mimicking naturally-occurring materials to find roles as versatile functional platforms, from reconfigurable magnonics to designer magnetic metamaterials. Typically artificial spin systems comprise nanomagnets with a single magnetisation texture: collinear macrospins or chiral vortices. By tuning nanoarray dimensions we achieve macrospin/vortex bistability and demonstrate a four-state metamaterial spin-system ‘Artificial Spin-Vortex Ice’ (ASVI). ASVI is capable of adopting Ising-like macrospins with strong ice-like vertex interactions, in addition to weakly-coupled vortices with low stray dipolar-field. The enhanced bi-texture microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex training and history-dependent nonlinear training dynamics. We observe vortex-domain formation alongside MFM tip vortex-writing. Tip-written vortices dramatically alter local reversal and memory dynamics. Vortices and macrospins exhibit starkly-differing spin-wave spectra with analogue-style mode-amplitude control via vortex training and mode-frequency shifts of ∆f = 3.8 GHz. We leverage spin-wave ‘spectral fingerprinting’ for rapid, scaleable readout of vortex and macrospin populations over complex training-protocols with applicability for functional magnonics and physical memory.","PeriodicalId":8465,"journal":{"name":"arXiv: Mesoscale and Nanoscale Physics","volume":"35 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconfigurable Training, Vortex Writing and Spin-Wave Fingerprinting in an Artificial Spin-Vortex Ice\",\"authors\":\"J. Gartside, K. Stenning, A. Vanstone, T. Dion, Holly H. Holder, D. Arroo, H. Kurebayashi, W. Branford\",\"doi\":\"10.21203/RS.3.RS-736619/V1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Strongly-interacting artificial spin systems are moving beyond mimicking naturally-occurring materials to find roles as versatile functional platforms, from reconfigurable magnonics to designer magnetic metamaterials. Typically artificial spin systems comprise nanomagnets with a single magnetisation texture: collinear macrospins or chiral vortices. By tuning nanoarray dimensions we achieve macrospin/vortex bistability and demonstrate a four-state metamaterial spin-system ‘Artificial Spin-Vortex Ice’ (ASVI). ASVI is capable of adopting Ising-like macrospins with strong ice-like vertex interactions, in addition to weakly-coupled vortices with low stray dipolar-field. The enhanced bi-texture microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex training and history-dependent nonlinear training dynamics. We observe vortex-domain formation alongside MFM tip vortex-writing. Tip-written vortices dramatically alter local reversal and memory dynamics. Vortices and macrospins exhibit starkly-differing spin-wave spectra with analogue-style mode-amplitude control via vortex training and mode-frequency shifts of ∆f = 3.8 GHz. We leverage spin-wave ‘spectral fingerprinting’ for rapid, scaleable readout of vortex and macrospin populations over complex training-protocols with applicability for functional magnonics and physical memory.\",\"PeriodicalId\":8465,\"journal\":{\"name\":\"arXiv: Mesoscale and Nanoscale Physics\",\"volume\":\"35 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv: Mesoscale and Nanoscale Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21203/RS.3.RS-736619/V1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv: Mesoscale and Nanoscale Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21203/RS.3.RS-736619/V1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconfigurable Training, Vortex Writing and Spin-Wave Fingerprinting in an Artificial Spin-Vortex Ice
Strongly-interacting artificial spin systems are moving beyond mimicking naturally-occurring materials to find roles as versatile functional platforms, from reconfigurable magnonics to designer magnetic metamaterials. Typically artificial spin systems comprise nanomagnets with a single magnetisation texture: collinear macrospins or chiral vortices. By tuning nanoarray dimensions we achieve macrospin/vortex bistability and demonstrate a four-state metamaterial spin-system ‘Artificial Spin-Vortex Ice’ (ASVI). ASVI is capable of adopting Ising-like macrospins with strong ice-like vertex interactions, in addition to weakly-coupled vortices with low stray dipolar-field. The enhanced bi-texture microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex training and history-dependent nonlinear training dynamics. We observe vortex-domain formation alongside MFM tip vortex-writing. Tip-written vortices dramatically alter local reversal and memory dynamics. Vortices and macrospins exhibit starkly-differing spin-wave spectra with analogue-style mode-amplitude control via vortex training and mode-frequency shifts of ∆f = 3.8 GHz. We leverage spin-wave ‘spectral fingerprinting’ for rapid, scaleable readout of vortex and macrospin populations over complex training-protocols with applicability for functional magnonics and physical memory.