Causal analysis and visualization of magnetization reversal using feature extended landau free energy.

The magnetization reversal in nanomagnets is causally analyzed using an extended Landau free-energy model. This model draws an energy landscape in the information space using physics-based features. Thus, the origin of the magnetic effect in macroscopic pinning phenomena can be identified. The microscopic magnetic domain beyond the hierarchy can be explained using energy gradient analysis and its decomposition. Structural features from the magnetic domains are extracted using persistent homology. Extended energy is visualized using ridge regression, principal component analysis, and Hadamard products. We found that the demagnetization energy concentration near a defect causes the demagnetization effect, which quantitatively dominates the pinning phenomenon. The exchange energy inhibits pinning, promotes saturation, and shows slight interactions with the defect. Furthermore, the energy distributions are visualized in real space. Left-position defects reduce the energy barrier and are useful for the topological inverse design of recording devices.

Accelerating small-angle scattering experiments on anisotropic samples using kernel density estimation.

We propose a method to accelerate small-angle scattering experiments by exploiting spatial correlation in two-dimensional data. We applied kernel density estimation to the average of a hundred short scans and evaluated noise reduction effects of kernel density estimation (smoothing). Although there is no advantage of using smoothing for isotropic data due to the powerful noise reduction effect of radial averaging, smoothing with a statistically and physically appropriate kernel can shorten measurement time by less than half to obtain sector averages with comparable statistical quality to that of sector averages without smoothing. This benefit will encourage researchers not to use full radial average on anisotropic data sacrificing anisotropy for statistical quality. We also confirmed that statistically reasonable estimation of measurement time is feasible on site by evaluating how intensity variances improve with accumulating counts. The noise reduction effect of smoothing will bring benefits to a wide range of applications from efficient use of beamtime at laboratories and large experimental facilities to stroboscopic measurements suffering low statistical quality.

Reconstruction of magnetic domain structure using the reverse Monte Carlo method with an extended Fourier image.

Visualization of the magnetic domain structure is indispensable to the investigation of magnetization processes and the coercivity mechanism. It is necessary to develop a reconstruction method from the reciprocal-space image to the real-space image. For this purpose, it is necessary to solve the problem of missing phase information in the reciprocal-space image. We propose the method of extend Fourier image with mean-value padding to compensate for the phase information. We visualized the magnetic domain structure using the Reverse Monte Carlo method with simulated annealing to accelerate the calculation. With this technique, we demonstrated the restoration of the magnetic domain structure, obtained magnetization and magnetic domain width, and reproduced the characteristic form that constitutes a magnetic domain.

Electron magnetic resonance in interacting ferromagnetic-metal nanoparticle systems: experiment and numerical simulation.

We have studied electron magnetic resonance (EMR) in ferromagnetic-metal nanoparticle systems which show promise as a component of left-handed metamaterials. Metallic Ni nanoparticles of about 8 nm in diameter are embedded in polymer films. When the average distance between the nanoparticles is decreased, we observed that the EMR signal shifts and broadens. Theoretical analyses based on micromagnetics simulation confirm that the shift of the signal is traced back to an increase in the magnetic dipole field in the nanoparticle systems due to the decrease in interparticle distance. Moreover, the simulation reveals that the perpendicular component of the dipolar field causes the broadening of the signal. The present study demonstrates that a dynamic analysis of the magnetization, with an explicit treatment of the magnetic dipole interactions, is necessary for a thorough understanding of the EMR and magnetic permeability of interacting nanoparticle systems.