Engineering structured magnetic bits for magnonic holographic memory
Source abstract
Abstract
Magnonic holographic memory is a type of memory that uses spin waves for magnetic bit read-in and read-out. Its operation is based on the interaction between magnets and propagating spin waves where the phase and the amplitude of the spin wave are sensitive to the magnetic field produced by the magnet. Memory states 0 and 1 are associated with the presence/absence of the magnet in a specific location. In this work, we present experimental data showing the feasibility of magnetic bit location using spin waves. The testbed consists of four micro-antennas covered by Y3Fe2(FeO4)3 yttrium iron garnet (YIG) film. A constant in-plane bias magnetic field is provided by NdFeB permanent magnet. The magnetic bit is made of strips of magnetic steel to maximize interaction with propagating spin waves. In the first set of experiments, the position of the bit was concluded by the change produced in the transmittance between two antennas. The minima appear at different frequencies and show different depths for different positions of the bit. In the second set of experiments, two input spin waves were generated, where the phase difference between the waves is controlled by the phase shifter. The minima in the transmitted spectra appear at different phases for different positions of magnetic bit. The utilization of the structured bit enhances its interaction with propagating spin waves and improves recognition fidelity compared to a regular-shaped bit. The recognition accuracy is further improved by exploiting spin wave interference. The depth of the transmission minima corresponding to different magnet positions may exceed 30 dB. All experiments are accomplished at room temperature. Overall, the presented data demonstrate the practical feasibility of using spin waves for magnetic bit red-out. The practical challenges are also discussed.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Magneto-Optical Properties and Applications · Magnetic properties of thin films · Neural Networks and Reservoir Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Electrical Engineering Department, University of California—Riverside , Riverside, California 92521, USA
Funding
Division of Computing and Communication Foundations
References (19)
Show source-provided references
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