Unidirectional information flow in a nanomagnetic metamaterial
2026-04-10 • Emerging Technologies
Emerging Technologies
AI summaryⓘ
The authors study artificial spin ice (ASI), which are tiny magnets arranged in special patterns. They develop a way to make the magnets influence each other in one direction only, causing magnetic areas to grow and shrink moving forward instead of back and forth. This directional behavior lets them move magnetic domains in a controlled way, and they show this can improve memory use in computing setups that mimic brain-like functions. Their work is the first to create ASI that naturally prefers one direction, combining storage and processing of information in one system.
Artificial Spin IceNanomagnetsNon-reciprocal TransportDomain GrowthExternal Magnetic FieldNeuromorphic ComputingReservoir ComputingMagnetic MemoryDirectional Metamaterials
Authors
Johannes H. Jensen, Ida Breivik, Arthur Penty, Anders Strømberg, Henrik Tidemann Kaarbø, Dheerendra S. Bhandari, Thea M. Dale, Michael Foerster, Miguel Angel Niño, Deepak Dagur, Magnus Själander, Gunnar Tufte, Erik Folven
Abstract
Artificial spin ice (ASI) are metamaterials composed of interacting nanomagnets. Although ASI hold promise for low-power computing, the ability to transmit information through these two-dimensional systems has been limited. Inspired by non-reciprocal transport in nature, we develop a framework for non-reciprocal influence between nanomagnets. Using the framework we discover a family of ASI geometries with inherent directionality. Directional ASI have the property that, when driven by an external field protocol, domains grow and reverse in the same direction, illustrating an emergent non-reciprocity of the system. Combining growth and reversal results in unidirectional domain movement through the metamaterial. We focus on one member of the directional ASI family, and demonstrate unidirectional domain growth experimentally. Furthermore, we show that the direction of growth is reconfigurable by tuning the external field strengths. Finally, we demonstrate how the directionality of the system significantly improves memory capabilities in a reservoir computing framework. Our work is the first demonstration of an ASI with inherent directionality, offering a magnetic computing platform that combines memory and computation within a single neuromorphic substrate.