Energy-efficient computing with tiny magnetic

magnetic vortex

image: A magnetic vortex, called a skymine (gray dot), being displaced into the corners of a triangular field by electric currents, where it bounces off the sides. The potentials shown in red are sufficient to perform Boolean logic operations.
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Credit: ill./©: Klaus Raab, JGU

A large percentage of the energy used today is consumed in the form of electrical power to process and store data and to run the relevant equipment and terminal devices. According to predictions, the level of energy used for these purposes will increase again in the future. Innovative concepts, such as neuromorphic computing, use an energy-saving approach to solve this problem. In a joint project by experimental and theoretical physicists at the Johannes Gutenberg University Mainz (JGU) with ERC Synergy Grant funding such an approach, known as Brownian reservoir computing, has now been realized. The results were also recently featured as Editors’ Highlights in the Devices scientific journal article Nature Communication.

Brownian computation uses ambient thermal energy

Brownian reservoir computing is a combination of two unconventional computing methods. Brownian computing takes advantage of the fact that computing processes usually run at room temperature so that there is the option of using the surrounding thermal energy and thus cutting down on electricity consumption. The thermal energy used in the computer system is essentially the random movement of particles, known as Brownian motion; which explains the name of this computing method.

Reservoir computing lends itself to highly efficient data processing

Reservoir computing exploits the complex response of the physical system to external stimuli, resulting in an extremely resource-efficient way to process data. Most of the calculation is done by the system itself, which does not require additional energy. In addition, this type of reservoir computer can be easily customized to perform different tasks because the solid-state system does not need to be adjusted to meet specific needs.

A team led by Professor Mathias Kläui from the Institute of Physics at the University of Mainz, with the support of Professor Johan Mentink from Radboud University Nijmegen in the Netherlands, succeeded in developing a prototype that combines these two computing methods. This prototype is capable of performing Boolean logic operations, which can be used as standard tests to validate reservoir computing.

The solid state system chosen in this case consists of thin metallic films that exhibit magnetic resonances. These magnetic vortices behave like particles and can be driven by electric currents. The behavior of the skylights is not only influenced by the applied current but also by their own Brownian motion. This Brownian motion of skyrmions can lead to a significant increase in energy savings as the system is automatically reset after each operation and prepared for the next calculation.

The first prototype was developed in Mainz

Although there have been many theoretical concepts for skyrmion-based reservoir computing in recent years, the researchers in Mainz succeeded in developing the first functional prototype only when they combined these concepts with the principle of Brownian computing. “The prototype is easy to produce from a lithography point of view and can theoretically be reduced to a size of just a nanometer,” said experimental physicist Klaus Raab. “We owe our success to the excellent collaboration between the experimental and theoretical physicists here at the University of Mainz,” emphasized theoretical physicist Maarten Brems. The project coordinator, Professor Mathias Kläui, said: “I am delighted that the funding made available through a Synergy Grant from the European Research Council has enabled us to collaborate with excellent colleagues in the Department of Theoretical Physics in Nijmegen, and the this collaboration that arose from that collaboration. I see great potential in non-conventional computing, a field that is also extensively supported here at Mainz through funding from the Carl Zeiss Foundation for the Emergency Center for Algorithmic Intelligence.”

Related links:
https://www.klaeui-lab.physik.uni-mainz.de – Kläui Lab at the Institute of Physics JGU ;
https://www.komet1.physik.uni-mainz.de – Group of Statistical Physics and Theory of Soft Matter at the Institute of Physics JGU ;
https://topdyn.uni-mainz.de/ – Advanced Research Area “TopDyn – Dynamics and Topology” at JGU ;
https://3d-magic-project.eu/ – ERC Synergy Grant 3D MAGiC ;
https://emergent-ai.uni-mainz.de/ – Emergent Center for Algorithm Intelligence at JGU

Read more:
https://www.uni-mainz.de/presse/aktuell/15662_ENG_HTML.php – press release “Obstacle course for microscopic vortices” (4 July 2022);
https://www.uni-mainz.de/presse/aktuell/14647_ENG_HTML.php – press release “Efficient readout in antiferromagnetic spintronics” (25 November 2021);
https://www.uni-mainz.de/presse/aktuell/13181_ENG_HTML.php – press release “Magnetic whirls in confined spaces” (4 March 2021);
https://www.uni-mainz.de/presse/aktuell/12071_ENG_HTML.php – press release “Magnetic vortices crystallize in two dimensions” (9 September 2020)


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