The human brain is extremely complex: Information is transmitted between neurons via synapses. Researchers have taken the brain as a model to construct particularly effective computers, so-called neuromorphic computers. Here, too, artificial neurons are highly interconnected via artificial synapses. With the help of such computers, data processing should be significantly accelerated in the future, which is important, for example, for autonomous driving or the recognition of patterns in complex databases.
For this system to run smoothly, the technical design of the synaptic connections is crucial. "They are very complex, so it is difficult to realize them with conventional electronic circuits," says junior professor Dr. Philipp Pirro, who conducts research in the field of magnetism at TUK.
The team led by the physicist from Kaiserslautern is working to overcome this problem. To do so, they are relying on spin waves, the collective excitations of spins in a magnetic material. Spin is the intrinsic angular momentum of a quantum particle, such as an electron or proton. It thus lays the foundation for magnetic phenomena.
Spin waves are interesting for applications because their quantum particles, the magnons, can transport more information than electrons while consuming significantly less energy.
In the ERC-funded project "CoSpiN - Coherent Spintronic Networks for Neuromorphic Computing," spin waves will be used to enable linking and information transfer. "The principle is similar to broadband communication, where information is transported via light waves. We want to work with spin waves that can transport information at different frequencies," Pirro continued. "They act as synapses." Nano-oscillators will serve as artificial neurons. These are tiny oscillation generators that emit spin waves.
The goal is to develop physical building blocks for a novel spintronic network on the nanoscale. "In this way, we want to lay the foundation for an artificial brain that is as close as possible to the natural model," says the physicist from Kaiserslautern. In the future, such technology could be used to realize faster and more powerful computers, for example.
COMPAMED-tradefair.com; Source: Technische Universität Kaiserslautern