Artificial Spin Ice: A Tutorial on Design and Control of Geometry, Microstate, Magnon Dynamics & Neuromorphic Computing
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918135457644544 |
|---|---|
| author | Sultana, Rawnak Mondal, Amrit Kumar Bhat, Vinayak Shantaram Stenning, Kilian Li, Yue Arroo, Daan M. Vasdev, Aastha McCarter, Margaret R. De Long, Lance E. Hastings, J. Todd Gartside, Jack C. Jungfleisch, M. Benjamin |
| author_facet | Sultana, Rawnak Mondal, Amrit Kumar Bhat, Vinayak Shantaram Stenning, Kilian Li, Yue Arroo, Daan M. Vasdev, Aastha McCarter, Margaret R. De Long, Lance E. Hastings, J. Todd Gartside, Jack C. Jungfleisch, M. Benjamin |
| contents | Artificial spin ice, arrays of strongly interacting nanomagnets, are complex magnetic systems with many emergent properties, rich microstate spaces, intrinsic physical memory, high-frequency dynamics in the GHz range and compatibility with a broad range of measurement approaches. This tutorial article aims to provide the foundational knowledge needed to understand, design, develop, and improve the dynamic properties of artificial spin ice (ASI). Special emphasis is placed on introducing the theory of micromagnetics, which describes the complex dynamics within these systems, along with their design, fabrication methods, and standard measurement and control techniques. The article begins with a review of the historical background, introducing the underlying physical phenomena and interactions that govern artificial spin ice. We then explore standard experimental techniques used to prepare the microstate space of the nanomagnetic array and to characterize magnetization dynamics, both in artificial spin ice and more broadly in ferromagnetic materials. Finally, we introduce the basics of neuromorphic computing applied to the case of artificial spin ice systems with goal to help researchers new to the field grasp these exciting new developments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_06548 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Artificial Spin Ice: A Tutorial on Design and Control of Geometry, Microstate, Magnon Dynamics & Neuromorphic Computing Sultana, Rawnak Mondal, Amrit Kumar Bhat, Vinayak Shantaram Stenning, Kilian Li, Yue Arroo, Daan M. Vasdev, Aastha McCarter, Margaret R. De Long, Lance E. Hastings, J. Todd Gartside, Jack C. Jungfleisch, M. Benjamin Mesoscale and Nanoscale Physics Disordered Systems and Neural Networks Materials Science Artificial spin ice, arrays of strongly interacting nanomagnets, are complex magnetic systems with many emergent properties, rich microstate spaces, intrinsic physical memory, high-frequency dynamics in the GHz range and compatibility with a broad range of measurement approaches. This tutorial article aims to provide the foundational knowledge needed to understand, design, develop, and improve the dynamic properties of artificial spin ice (ASI). Special emphasis is placed on introducing the theory of micromagnetics, which describes the complex dynamics within these systems, along with their design, fabrication methods, and standard measurement and control techniques. The article begins with a review of the historical background, introducing the underlying physical phenomena and interactions that govern artificial spin ice. We then explore standard experimental techniques used to prepare the microstate space of the nanomagnetic array and to characterize magnetization dynamics, both in artificial spin ice and more broadly in ferromagnetic materials. Finally, we introduce the basics of neuromorphic computing applied to the case of artificial spin ice systems with goal to help researchers new to the field grasp these exciting new developments. |
| title | Artificial Spin Ice: A Tutorial on Design and Control of Geometry, Microstate, Magnon Dynamics & Neuromorphic Computing |
| topic | Mesoscale and Nanoscale Physics Disordered Systems and Neural Networks Materials Science |
| url | https://arxiv.org/abs/2504.06548 |