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The recent demonstration of current-driven magnetic domain wall logic [Z. Luo et al., Nature 579:214] was based on a three-input logic gate that was identified as a reconfigurable NAND/NOR function. We reinterpret this logic gate as a minority gate within the context of threshold logic, enabling a domain wall threshold logic paradigm in which the device count can be reduced by 80%. Furthermore, by extending the logic gate to more than three inputs of non-equal weight, an 87% reduction in device count can be achieved.
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We investigated the aspect ratio (thickness/width) dependence of the threshold current density required for the current-driven domain wall (DW) motion for the Ni81Fe19 nanowires. It has been shown theoretically that the threshold current density is proportional to the product of the hard-axis magnetic anisotropy Kperp and the DW width lamda. (Phys. Rev. Lett. 92, 086601 (2004).) We show experimentally that Kperp can be controlled by the magnetic shape anisotropy in the case of the Ni81Fe19 nanowires, and that the threshold current density increases with an increase of Kperp*l. We succeeded to reduce the threshold current density by half by the shape control.
The motion of magnetic domain walls in ultrathin magnetic heterostructures driven by current via the spin Hall torque is described. We show results from perpendicularly magnetized CoFeB|MgO heterostructures with various heavy metal underlayers. The domain wall moves along or against the current flow depending on the underlayer material. The direction to which the domain wall moves is associated with the chirality of the domain wall spiral formed in these heterostructures. The one-dimensional model is used to describe the experimental results and extract parameters such as the Dzyaloshinskii-Moriya exchange constant which is responsible for the formation of the domain wall spiral. Fascinating effects arising from the control of interfaces in magnetic heterostructures are described.
Spin wave, the collective excitation of magnetic order, is one of the fundamental angular momentum carriers in magnetic systems. Understanding the spin wave propagation in magnetic textures lies in the heart of developing pure magnetic information processing schemes. Here we show that the spin wave propagation across a chiral domain wall follows simple geometric trajectories, similar to the geometric optics. And the geometric behaviors are qualitatively different in normally magnetized film and tangentially magnetized film. We identify the lateral shift, refraction, and total reflection of spin wave across a ferromagnetic domain wall. Moreover, these geometric scattering phenomena become polarization-dependent in antiferromagnets, indicating the emergence of spin wave birefringence inside antiferromagnetic domain wall.
Probabilistic Neural Network (PNN) is a feed-forward artificial neural network developed for solving classification problems. This paper proposes a hardware implementation of an approximated PNN (APNN) algorithm in which the conventional exponential function of the PNN is replaced with gated threshold logic. The weights of the PNN are approximated using a memristive crossbar architecture. In particular, the proposed algorithm performs normalization of the training weights, and quantization into 16 levels which significantly reduces the complexity of the circuit.
The recently proposed probabilistic spin logic presents promising solutions to novel computing applications. Multiple cases of implementations, including invertible logic gate, have been studied numerically by simulations. Here we report an experimental demonstration of a magnetic tunnel junction-based hardware implementation of probabilistic spin logic.
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