14 research outputs found
Bias-free spin-wave phase shifter for magnonic logic
A design of a magnonic phase shifter operating without an external bias
magnetic field is proposed. The phase shifter uses a localized collective spin
wave mode propagating along a domain wall "waveguide" in a dipolarly-coupled
magnetic dot array existing in a chessboard antiferromagnetic (CAFM) ground
state. It is demonstrated numerically that remagnetization of a single magnetic
dot adjacent to the domain wall waveguide introduces a controllable phase shift
in the propagating spin wave mode without significant change of the mode
amplitude. It is also demonstrated that a logic XOR gate can be realized in the
same system.Comment: 6 pages, 4 figure
Pattern recognition using spiking antiferromagnetic neurons
Spintronic devices offer a promising avenue for the development of nanoscale,
energy-efficient artificial neurons for neuromorphic computing. It has
previously been shown that with antiferromagnetic (AFM) oscillators, ultra-fast
spiking artificial neurons can be made that mimic many unique features of
biological neurons. In this work, we train an artificial neural network of AFM
neurons to perform pattern recognition. A simple machine learning algorithm
called spike pattern association neuron (SPAN), which relies on the temporal
position of neuron spikes, is used during training. In under a microsecond of
physical time, the AFM neural network is trained to recognize symbols composed
from a grid by producing a spike within a specified time window. We further
achieve multi-symbol recognition with the addition of an output layer to
suppress undesirable spikes. Through the utilization of AFM neurons and the
SPAN algorithm, we create a neural network capable of high-accuracy recognition
with overall power consumption on the order of picojoules
Low Power Microwave Signal Detection With a Spin-Torque Nano-Oscillator in the Active Self-Oscillating Regime
A spin-torque nano-oscillator (STNO) driven by a ramped bias current can
perform spectrum analysis quickly over a wide frequency bandwidth. The STNO
spectrum analyzer operates by injection locking to external microwave signals
and produces an output DC voltage that temporally encodes the
input spectrum. We found, via numerical analysis with a macrospin
approximation, that an STNO is able to scan a bandwidth in less
than (scanning rate exceeds ). In contrast to
conventional quadratic microwave detectors, the output voltage of the STNO
analyzer is proportional to the amplitude of the input microwave signal with sensitivity . The
minimum detectable signal of the analyzer depends on the scanning rate and,
at low , is about .Comment: 5 pages, 5 figure
Lumped circuit model for inductive antenna spin-wave transducers
We derive a lumped circuit model for inductive antenna spin-wave transducers
in the vicinity of a ferromagnetic medium. The model considers the antenna's
Ohmic resistance, its inductance, as well as the additional inductance due to
the excitation of ferromagnetic resonance or spin waves in the ferromagnetic
medium. As an example, the additional inductance is discussed for a wire
antenna on top of a ferromagnetic waveguide, a structure that is characteristic
for many magnonic devices and experiments. The model is used to assess the
scaling properties and the energy efficiency of inductive antennas. Issues
related to scaling antenna transducers to the nanoscale and possible solutions
are also addressed.Comment: This project has received funding from the European Union's Horizon
2020 research and innovation program under grant agreement No. 801055 "Spin
Wave Computing for Ultimately-Scaled Hybrid Low-Power Electronics" CHIRO
A spinwave Ising machine
Abstract Time-multiplexed Coherent Ising Machines (CIMs) have demonstrated promising results in rapidly solving large-scale combinatorial problems. However, CIMs remain relatively large and power-demanding. Here, we demonstrate a spinwave-based Ising machine (SWIM) that due to the low spinwave group velocity allows for sufficient miniaturization and reduced power consumption. The SWIM is implemented using a 10-mm-long 5-μm-thick Yttrium Iron Garnet film with off-the-shelf microwave components and can support an 8-spin MAX-CUT problem and solve it in less than 4 μs consuming only 7 μJ. As the SWIM minimizes its energy, we observe that the spin states can demonstrate both uniform and domain-propagation-like switching. The developed SWIM has the potential for substantial further miniaturization with reduction of power consumption, scalability in the number of supported spins, increase of operational speed, and may become a versatile platform for commercially feasible high-performance solvers of combinatorial optimization problems