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Neuromorphic computing aims to revolutionize large-scale data processing by developing efficient methods and devices inspired by neural networks. Among these, the control of magnetism through ion migration has emerged as a promising…

Biologically-inspired computing models have made significant progress in recent years, but the conventional von Neumann architecture is inefficient for the large-scale matrix operations and massive parallelism required by these models. This…

Hardware Architecture · Computer Science 2025-09-23 Siqing Fu , Lizhou Wu , Tiejun Li , Chunyuan Zhang , Jianmin Zhang , Sheng Ma

Magnetic skyrmions are topologically protected spin swirling vertices, which are promising in device applications due to their particle-like nature and excellent controlability. Magnetic skyrmions have been extensively studied in a variety…

Materials Science · Physics 2025-09-10 Fawei Zheng

A magnetic skyrmion induced on a ferromagnetic topological insulator (TI) is a real-space manifestation of the chiral spin texture in the momentum space, and can be a carrier for information processing by manipulating it in tailored…

Magnetic skyrmions are topologically nontrivial particles with a potential application as information elements in future spintronic device architectures. While they are commonly portrayed as two dimensional objects, in reality magnetic…

Magnetic skyrmions, vortex-like swirling spin structures with quantized topological number, observed in chiral magnets, are appealing for potential applications in spintronics because it is possible to control their motion with ultralow…

Mesoscale and Nanoscale Physics · Physics 2013-10-08 Junichi Iwasaki , Masahito Mochizuki , Naoto Nagaosa

Inertial mass of a skyrmion arising from spin-phonon interaction is computed exactly within a toy model of the magnetoelastic coupling in a ferromagnetic film. The mass scales as the square of the strength of the magnetoelastic coupling, as…

Mesoscale and Nanoscale Physics · Physics 2020-08-19 D. Capic , E. M. Chudnovsky , D. A. Garanin

Skyrmions are emerging topological spin structures that are potentially revolutionary for future data storage and spintronics applications. The existence and stability of skyrmions in magnetic materials is usually associated to the presence…

Mesoscale and Nanoscale Physics · Physics 2018-03-14 R. L. Novak , F. Garcia , E. R. P. Novais , J. P. Sinnecker , A. P. Guimarães

Magnetic skyrmions are nanoscale windings of the spin configuration that hold great promise for technology due to their topology-related properties and extremely reduced sizes. After the recent observation at room temperature of sub-100 nm…

Magnetic skyrmions are textures behaving as quasiparticles which are topologically different from other states. Their discovery in systems with broken inversion symmetry sparked the search for materials containing such magnetic phase at…

Spiking neural networks (SNNs) promise energy-efficient computation by mimicking biological neural dynamics, yet existing plasticity rules focus on isolated spike pairs and fail to leverage the synchronous activity patterns that drive…

Neural and Evolutionary Computing · Computer Science 2025-08-26 Yuchen Tian , Assel Kembay , Samuel Tensingh , Nhan Duy Truong , Jason K. Eshraghian , Omid Kavehei

Magnetic skyrmions and multiferroics are the most interesting objects in nanostructure science that have great potential in future spin-electronic technology. The study of the multiferroic skyrmions has attracted much interest in recent…

Mesoscale and Nanoscale Physics · Physics 2016-08-03 Zidong Wang , Malcolm J. Grimson

Magnetic skyrmions are promising candidates as information carriers in a new generation of memories. How to generate and stabilize skyrmions is essential for their successful application to technology. Here we theoretically demonstrate that…

Materials Science · Physics 2015-10-28 Nuria Del-Valle , Sebastia Agramunt-Puig , Carles Navau , Alvaro Sanchez

Magnetic skyrmion, vortex-like swirling topologically stable spin configurations, is appealing as information carrier for future nanoelectronics, owing to the stability, small size and extremely low driving current density. One of the most…

Mesoscale and Nanoscale Physics · Physics 2017-02-21 Wang Kang , Yangqi Huang , Chentian Zheng , Weifeng Lv , Na Lei , Youguang Zhang , Xichao Zhang , Yan Zhou , Weisheng Zhao

Several analog and digital brain-inspired electronic systems have been recently proposed as dedicated solutions for fast simulations of spiking neural networks. While these architectures are useful for exploring the computational properties…

Emerging Technologies · Computer Science 2017-11-08 Elisabetta Chicca , Fabio Stefanini , Chiara Bartolozzi , Giacomo Indiveri

Thermodynamic-driven filament formation in redox-based resistive memory and the impact of thermal fluctuations on switching probability of emerging magnetic switches are probabilistic phenomena in nature, and thus, processes of binary…

Other Condensed Matter · Physics 2013-10-21 Omid Kavehei , Efstratios Skafidas

The increasing need for efficient thermal management in nanoelectronics requires innovative thermal sensing solutions, as conventional sensors often exhibit nonlinear responses, low sensitivity, and complex calibration. We predict a…

Magnetic skyrmions are chiral spin textures with a nontrivial topology that offer a potential for future magnetic memory and storage devices. The controlled formation and adjustment of size and density of magnetic skyrmions in Ta/CoFeB/MgO…

Magnetic skyrmions are stable topological solitons with complex non-coplanar spin structures. Their nanoscopic size and the low electric currents required to initiate and control their motion has opened a new field of research, skyrmionics,…

Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially…

Other Condensed Matter · Physics 2013-07-04 Siddharth Gaba , Patrick Sheridan , Jiantao Zhou , Shinhyun Choi , Wei Lu