Most of the energy used today is consumed in the form of electrical energy for processing and storing data and for operating equipment and peripheral devices. According to predictions, the level of energy used for these things will increase in the future. New concepts, such as neuromorphic computing, use energy conservation methods to solve this problem. In a joint project of research and engineering experts at the Johannes Gutenberg University Mainz (JGU) with funding from the ERC Synergy Grant, such a method, known as Brownian fluid calculations, (A computer that works hard has a small magnetic swirl), has now been implemented. The findings were recently presented as an editorial in the Tools section of the scientific journal Nature Communications.
Brownian computers use ambient light energy
The Brownian fluid equation is a combination of two nonlinear equations. Brownian computers take advantage of the fact that mathematical processes usually work at room temperature, so that it is possible to use the surrounding energy and thus reduce electricity consumption. The thermal energy used in computer systems is actually random movement of particles, known as Brownian motion; which defines the name of this calculation method.
Safe storage is ideal for efficient data processing
Security computing utilizes the complex responses of physical systems to external stimuli, leading to highly efficient methods of data processing. Most of the calculations are done by the system itself, which does not require additional power. Also, this type of tank computer can be easily configured to perform different tasks because there is no need to change the solid state system to meet the requirements.
Professor Mathias Kläui’s team from the Institute of Physics at the University of Mainz, supported by Professor Johan Mentink from Radboud University Nijmegen in the Netherlands, has now succeeded in creating an example to combine these two methods. This model can perform Boolean logic functions, which can be used as a standard test for hydrologic support.
The selected solid-state system in this case has a narrow band that falls in the magnetic field. These magnets behave like particles and can be moved by an electric current. The behavior of skyrmions is affected not only by the current input but also by their own Brownian motion. The Brownian transformation of skyrmions can result in significant energy savings because the system is automatically reset after each operation and prepared for the next assembly.
The first model developed in Mainz
Although there have been many theoretical ideas for liquid computing based on skyrmions in recent years, the Mainz researchers have managed to create the first kind of work by combining these ideas with the principles of Brownian computation.
“The prototype is easy to produce from a lithographic point of view and can be reduced to a size of a few nanometers,” said research scientist Klaus Raab. “We owe our success to the good cooperation between the physicists conducting the experiment in this case at the University of Mainz,” physicist Maarten Brems emphasized.
Project coordinator Professor Mathias Kläui added: “I am delighted that funding from the Synergy Grant from the European Research Council has enabled us to work with our outstanding colleagues from the Department of Theoretical Physics from Nijmegen collaboration, and that’s what worked out for us.
I see a lot of potential in random computing, and the area is receiving a lot of support here in Mainz with funding from the Carl Zeiss Foundation for Emerging Algorithmic Intelligence Center.”
