Magnetic Skyrmion as a Nonlinear Resistive Element: A Potential Building Block for Reservoir Computing

By Diana Prychynenko, Matthias Sitte, K. Litzius, Benjamin Krueger, George Bourianoff, M. Klaui, J. Sinova, Karin Everschor-Sitte. 2017

231 citations recorded by the source corpus.

The topologically protected magnetic textures called skyrmions may provide a suitable basis for $r\phantom{\rule{0}{0ex}}e\phantom{\rule{0}{0ex}}s\phantom{\rule{0}{0ex}}e\phantom{\rule{0}{0ex}}r\phantom{\rule{0}{0ex}}v\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}r$ $c\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}m\phantom{\rule{0}{0ex}}p\phantom{\rule{0}{0ex}}u\phantom{\rule{0}{0ex}}t\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}g$, one approach to brain-inspired cognitive computing. Reservoirs of self-organized skyrmions offer potential advantages in size, efficiency, and complexity, compared to systems of memristive devices, quantum-dot lasers, and atomic switches. The basic element here is an isolated skyrmion in a ferromagnetic ribbon; thus the authors examine current flow through magnetic skyrmions based on anisotropic magnetoresistance, analyzing the nonlinear current-voltage characteristics. The scheme they provide offers a path to spintronic neuromorphic computing.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/3a592c9cabac56f87e48956a8694dc419abc64a3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Seiji Takeda
2. Damien Querlioz
3. Gouhei Tanaka
4. Naoki Kanazawa
5. Daiju Nakano
6. Toshiyuki Yamane
7. Akira Hirose
8. Ryosho Nakane

In Atomic and Molecular Physics, and Optics

1. Julie Grollier
2. Karin Everschor-Sitte
3. Shunsuke Fukami
4. Mark D. Stiles
5. A. Slavin
6. V. Tiberkevich

In Electrical and Electronic Engineering

1. Julie Grollier
2. Seiji Takeda
3. Damien Querlioz
4. Gouhei Tanaka
5. Naoki Kanazawa
6. Daiju Nakano
7. Toshiyuki Yamane
8. Akira Hirose

Citations in the corpus

• Neuromorphic Spintronics (2020, background): “Computing with skyrmions Towards even deeper miniaturization, Prychynenko et al.(82) proposed to use skyrmion assemblies (see Fig.”
• Recent Advances in Physical Reservoir Computing: A Review (2018, background): “The possibility of using chaotic dynamics in an STO with time-delayed feedback for RC has been explored in Williame, (Prychynenko et al., 2018).”