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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.
Superparamagnetic tunnel junctions (SMTJs) have emerged as a competitive, realistic nanotechnology to support novel forms of stochastic computation in CMOS-compatible platforms. One of their applications is to generate random bitstreams suitable for
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 w
Magnetic tunnel junctions operating in the superparamagnetic regime are promising devices in the field of probabilistic computing, which is suitable for applications like high-dimensional optimization or sampling problems. Further, random number gene
Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving brainlike compact and energy-effcient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity
Featuring low heat dissipation, devices based on spin-wave logic gates promise to comply with increasing future requirements in information processing. In this work, we present the experimental realization of a majority gate based on the interference