Neural network analysis of the magnetization reversal in magnetic dot arrays

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We simulated the remagnetization dynamics of the ultra-dense and ultra-thin magnetic dot array system with dipole-dipole and exchange coupling interactions. Within the proposed 2D XY superlattice model, the square dots are modeled by the spatially modulated exchange-couplings. The dipole-dipole interactions were approximated by the hierarchical sums and dynamics was reduced to damping term of the Landau-Lifshitz-Gilbert equation. The simulation of 40 000 spin system leads to nonequilibrium nonuniform configurations with soliton-antisoliton pairs detected at intra-dot and inter-dot scales. The classification of intra-dot magnetic configurations was performed using the self-adaptive neural networks with varying number of neurons.
5 pages, 6 figures. Accepted for publication: "Acta Electrotechnica et Informatica" (http://www.aei.tuke.sk/)

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Disordered Systems and Neural Networks, Statistical Mechanics

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http://salesiana.dossiersoluciones.com/handle/123456789/19914

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cond-mat/0209186
 http://arxiv.org/abs/cond-mat/0209186

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arXiv