In an era where digital technology is increasingly permeating every aspect of life, energy-efficient computing is not only desirable, but also essential. Researchers at University College London (UCL) and Imperial College London have taken a breakthrough step in this direction, unveiling a new approach to computing that could redefine the way we process large amounts of data. Their research, recently published in Nature Materials, explores the untapped potential of chiral magnets in neuromorphic computing (neuromorphic computing), a field inspired by the mechanisms of the human brain.

Core of Innovation: Physical Reservoir Computing

At the heart of this innovation is a concept known as Physical Reservoir Computing (physical reservoir computing PRC). Traditional computing systems, like busy post offices, constantly pass data between separate processing units and memory units, resulting in a lot of wasted energy-a problem known as the von Neumann bottleneck. Drawing inspiration from the interconnected, fluid nature of the human brain, PRC seeks to combine these separate processing units and storage units to produce more energy-efficient and faster computational processes.

Chiral Magnet: Game changer

The technical highlight of the study is how to manipulate these magnetic phases. By applying an external magnetic field and adjusting the temperature, the team can make the chiral magnet switch between different magnetic phases-each with a different computational advantage. For example, the skyrmion phase has a strong memory capacity that makes it suitable for prediction tasks, while the nonlinearity of the conical phase is well suited for tasks involving transformations and classification.

Task Adaptive Computing: A Critical Milestone