Much current computer hardware, such as hard drives, use magnetic memory devices. These rely on magnetic states – the direction microscopic magnets are pointing – to encode and read information.
Exotic magnetic states – such as a point where three south poles meet – represent complex systems. These may act in a similar way to many complex systems found in nature, such as the way our brains process information.
Existing neural nets have an efficiency constraint in that they [as software] on conventional computer hardware. The researchers from Imperial College London have devised a method for writing magnetic information in any pattern desired, using a very small magnetic probe called a magnetic force microscope.
With this new writing method, arrays of magnetic nanowires may be able to function as hardware neural networks - potentially more powerful and efficient than software-based approaches.
The team, from the Departments of Physics and Materials at Imperial, demonstrated their system by writing patterns that have never been seen before, for example as shown in Figure 1, “i nterlocking hexagon patterns with complex magnetisation”. They published their results in the journal Nature Nanotechnology ; “ Realization of ground state in artificial kagome spin ice via topological defect-driven magnetic writing ”, by Jack C. Gartside, Daan M. Arroo, David M. Burn, Victoria L. Bemmer, Andy Moskalenko, Lesley F. Cohen and Will R. Branford.
Figure 1. 'Hexagonal artificial spin ice ground state' – a pattern never demonstrated before. Coloured arrows show north or south polarisation (credit; Imperial College, London)
Dr Jack Gartside, first author from the Department of Physics, said: “With this new writing method, we open up research into ‘training’ these magnetic nanowires to solve useful problems. If successful, this will bring hardware neural networks a step closer to reality.”
As well as applications in computing, the method could be used to study fundamental aspects of complex systems, by