2 research outputs found
Magnetic skyrmion artificial synapse for neuromorphic computing
Since the experimental discovery of magnetic skyrmions achieved one decade
ago, there have been significant efforts to bring the virtual particles into
all-electrical fully functional devices, inspired by their fascinating physical
and topological properties suitable for future low-power electronics. Here, we
experimentally demonstrate such a device: electrically-operating skyrmion-based
artificial synaptic device designed for neuromorphic computing. We present that
controlled current-induced creation, motion, detection and deletion of
skyrmions in ferrimagnetic multilayers can be harnessed in a single device at
room temperature to imitate the behaviors of biological synapses. Using
simulations, we demonstrate that such skyrmion-based synapses could be used to
perform neuromorphic pattern-recognition computing using handwritten
recognition data set, reaching to the accuracy of ~89 percents, comparable to
the software-based training accuracy of ~94 percents. Chip-level simulation
then highlights the potential of skyrmion synapse compared to existing
technologies. Our findings experimentally illustrate the basic concepts of
skyrmion-based fully functional electronic devices while providing a new
building block in the emerging field of spintronics-based bio-inspired
computing.Comment: 11 pages, 4 figure
Thermal Brownian Motion of Skyrmion for True Random Number Generation
The true random number generators (TRNGs) have received extensive attention
because of their wide applications in information transmission and encryption.
The true random numbers generated by TRNG are typically applied to the
encryption algorithm or security protocol of the information security core.
Recently, TRNGs have also been employed in emerging stochastic computing
paradigm for reducing power consumption. Roughly speaking, TRNG can be divided
into circuits-based, e.g., oscillator sampling or directly noise amplifying;
and quantum physics-based, e.g., photoelectric effect. The former generally
requires a large area and has a large power consumption, whereas the latter is
intrinsic random but is more difficult to implement and usually requires
additional post-processing circuitry. Very recently, magnetic skyrmion has
become a promising candidate for implementing TRNG because of their nanometer
size, high stability, and intrinsic thermal Brownian motion dynamics. In this
work, we propose a TRNG based on continuous skyrmion thermal Brownian motion in
a confined geometry at room temperature. True random bitstream can be easily
obtained by periodically detecting the relative position of the skyrmion
without the need for additional current pulses. More importantly, we implement
a probability-adjustable TRNG, in which a desired ratio of 0 and 1 can be
acquired by adding an anisotropy gradient through voltage-controlled magnetic
anisotropy (VCMA) effect. The behaviors of the skyrmion-based TRNG are verified
by using micromagnetic simulations. The National Institute of Standards and
Technology (NIST) test results demonstrate that our proposed random number
generator is TRNG with good randomness. Our research provides a new perspective
for efficient TRNG realization