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We derive a BPS-like first order system of equations for a family of flat static domain walls (DWs) of dimensionally extended cubic Lovelock Gravity coupled to massive scalar self-interacting matter. The explicit construction of such DWs is…
Two-dimensional (2D) nanomaterials derived from non-van der Waals solids are promising due to their fantastic physical and chemical properties, but it remains challenging to obtain 2D atomic laminates with high stability owing to the strong…
We propose the use of periodic arrays of permanent magnetic films for producing magnetic lattices of microtraps for confining, manipulating and controlling small clouds of ultracold atoms and quantum degenerate gases. Using analytical…
We report on the design, fabrication and characterization of magnetic nanostructures to create a lattice of magnetic traps with sub--micron period for trapping ultracold atoms. These magnetic nanostructures were fabricated by patterning a…
Tunable magnetic interactions in high-mobility nonmagnetic semiconductor heterostructures are centrally important to spin-based quantum technologies. Conventionally, this requires incorporation of "magnetic impurities" within the…
A series of microstructures designed to pin domain-walls (DWs) in (Ga,Mn)As with perpendicular magnetic anisotropy has been employed to determine extrinsic and intrinsic contributions to DW resistance. The former is explained quantitatively…
Standard optical potentials use off-resonant laser standing wave induced AC-Stark shift. In a recent development [Phys. Rev. Lett. {\bf 117}, 233001 (2016)] a three-level scheme in $\Lambda$ configuration coupled coherently by resonant…
One well-known argument about one dimensional(1D) system is that 1D phase transition at finite temperature cannot exist, despite this concept depends on conditions such as range of interaction, external fields and periodicity. Therefore 1D…
Deep neural networks (DNNs) usually contain massive parameters, but there is redundancy such that it is guessed that the DNNs could be trained in low-dimensional subspaces. In this paper, we propose a Dynamic Linear Dimensionality Reduction…
Developmental plasticity plays a prominent role in shaping the brain's structure during ongoing learning in response to dynamically changing environments. However, the existing network compression methods for deep artificial neural networks…
We study null 1/4 BPS deformations of flat domain wall solutions (NDDW) in N=2, d=5 gauged supergravity with hypermultiplets and vector multiplets coupled. These are uncharged time-dependent configurations and contain as special case, 1/2…
A wedge-shaped structure made of split-ring resonators (SRR) and wires is numerically simulated to evaluate its refraction behavior. Four frequency bands, namely, the stop band, left-handed band, ultralow-index band, and positive-index…
Synthetic aperture radar (SAR) imagery exhibits intrinsic information sparsity due to its unique electromagnetic scattering mechanism. Despite the widespread adoption of deep neural network (DNN)-based SAR automatic target recognition…
In wave propagation problems, finite difference methods implemented on staggered grids are commonly used to avoid checkerboard patterns and to improve accuracy in the approximation of short-wavelength components of the solutions. In this…
In nearly free electron theory the imposition of a periodic electrostatic potential on free electrons creates the bandstructure of a material, determined by the crystal lattice spacing and geometry. Imposing an artificially designed…
There was shown that Fourier transform of the negative magnetoresistance (NMR) which is due to interference correction to the conductivity contains the information about the area distribution function of the closed paths and about area…
The structural and electronic properties of new structural cubic (GaN)$_1$/(ZnO)$_1$ superlattice have been investigated using two different theoretical techniques: the full potential-linearized augmented plane wave (FP-LAPW) method and the…
Dynamic substructuring (DS) methods encompass a range of techniques to decompose large structural systems into multiple coupled subsystems. This decomposition has the principle benefit of reducing computational time for dynamic simulation…
Sensing the direction of arrival and polarization of impinging signals is a key prerequisite for beamforming and interference mitigation in modern wireless communication systems. Dynamic metasurface antennas (DMAs) can multiplex direction-…
Neuromorphic computing (NC) is considered as a potential vehicle for implementing energy-efficient artificial intelligence (AI). To realize NC, several materials systems are being investigated. Among them, the spin-orbit torque (SOT)…