A physics-informed DIP method using a simple convolutional autoencoder reconstructs complex in-plane magnetization from NV magnetometry, with optimal mask orientation improving SNR by up to 3 dB.
Magnetic domain-wall logic
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Approximate analytical solutions for 1D topologically trivial magnetic solitons in nanowires are presented with numerical validation, nonlinear interface behavior, pulse-based generation, and application to controlled domain wall driving.
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Physics-Informed Deep Image Prior Reconstruction of In-Plane Magnetization from Scanning NV Magnetometry
A physics-informed DIP method using a simple convolutional autoencoder reconstructs complex in-plane magnetization from NV magnetometry, with optimal mask orientation improving SNR by up to 3 dB.
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Propagation, generation, and utilization of topologically trivial magnetic solitons in magnetic nanowires
Approximate analytical solutions for 1D topologically trivial magnetic solitons in nanowires are presented with numerical validation, nonlinear interface behavior, pulse-based generation, and application to controlled domain wall driving.