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    Spin-orbit coupling induced fractionalized Skyrmion excitations in rotating and rapidly quenched spin-1 Bose-Einstein condensates

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    We investigate the fractionalized Skyrmion excitations induced by spin-orbit coupling in rotating and rapidly quenched spin-1 Bose-Einstein condensates. Our results show that the fractionalized Skyrmion excitation depends on the combination of spin-orbit coupling and rotation, and it originates from a dipole structure of spin which is always embedded in three vortices constructed by each condensate component respectively. When spin-orbit coupling is larger than a critical value, the fractionalized Skyrmions encircle the center with one or several circles to form a radial lattice, which occurs even in the strong ferromagnetic/antiferromagnetic condensates. We can use both the spin-orbit coupling and the rotation to adjust the radial lattice. The realization and the detection of the fractionalized Skyrmions are compatible with current experimental technology.Comment: 5 pages, 4 figure

    On Linearly Constrained Minimum Variance Beamforming

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    Beamforming is a widely used technique for source localization in signal processing and neuroimaging. A number of vector-beamformers have been introduced to localize neuronal activity by using magnetoencephalography (MEG) data in the literature. However, the existing theoretical analyses on these beamformers have been limited to simple cases, where no more than two sources are allowed in the associated model and the theoretical sensor covariance is also assumed known. The information about the effects of the MEG spatial and temporal dimensions on the consistency of vector-beamforming is incomplete. In the present study, we consider a class of vector-beamformers defined by thresholding the sensor covariance matrix, which include the standard vector-beamformer as a special case. A general asymptotic theory is developed for these vector-beamformers, which shows the extent of effects to which the MEG spatial and temporal dimensions on estimating the neuronal activity index. The performances of the proposed beamformers are assessed by simulation studies. Superior performances of the proposed beamformers are obtained when the signal-to-noise ratio is low. We apply the proposed procedure to real MEG datasets derived from five sessions of a human face-perception experiment, finding several highly active areas in the brain. A good agreement between these findings and the known neurophysiology of the MEG response to human face perception is shown
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