The magnetic reversal in dot arrays recognized by the self-organized adaptive neural network

Martin Gmitra; Denis Horvath

doi:10.1016/s0304-8853(03)00226-9

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The magnetic reversal in dot arrays recognized by the self-organized adaptive neural network

Martin Gmitra·Denis Horvath

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Abstract

The remagnetization dynamics of monolayer dot array superlattice XY 2-D spin model with dipole-dipole interactions is simulated. Within the proposed model of array, the square dots are described by the spatially modulated exchange-couplings. The dipole-dipole interactions are approximated by the hierarchical sums and spin dynamics is considered in regime of the Landau-Lifshitz equation. The simulation of reversal for $40 000$ spins exhibits formation of nonuniform intra-dot configurations with nonlinear wave/anti-wave pairs developed at intra-dot and inter-dot scales. Several geometric and parametric dependences are calculated and compared with oversimplified four-spin model of reversal. The role of initial conditions and the occurrence of coherent rotation mode is also investigated. The emphasis is on the classification of intra-dot or inter-dot (interfacial) magnetic configurations done by adaptive neural network with varying number of neurons.

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Martin Gmitra, Denis Horvath. 2003-08-14. The magnetic reversal in dot arrays recognized by the self-organized adaptive neural network. https://doi.org/10.1016/s0304-8853(03)00226-9

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