The ability to switch magnets between two stable states has become the fastest and most widely used means to store information on devices. For information processing however, the standard von Neumann architecture is rapidly becoming obsolete, driven by the modern demands of computational resources for ultrahigh-speed mobile networks, machine learning and artificial intelligence.
Recent years have witnessed a strong surge in research on symmetry-driven phenomena in magnetism, concentrated on the effects introduced by chirality. Chiral magnetic states, with their flexibility and topological protection, have great potential to become the building blocks for processing and storage of information. However, the area of chiral magnetism is still in its infancy, with many fundamental challenges to be solved.
Towards ultra-efficient information processing and storage
The CHIROMAG project focuses on the ultimate challenge in this field: to discover ultrafast and energy-efficient ways to control magnetic topological states. This will be achieved using an open and inclusive approach that will join the existing expertise and capabilities of scientific communities across Europe dealing with ultrafast magnetism, spintronics, magnonics, photonics and advanced spectroscopy, and by sharing the new knowledge arising from the exchange between them.
The project will result in disruptive achievements in the area of ultrafast chiral magnetism and in a new generation of scientists that will be trained at the interfaces of the involved disciplines, translating scientific breakthroughs into innovative technological solutions for fast and ultra-efficient information processing and storage.
Wide European consortium
CHIROMAG connects researchers in more than 20 countries: Albania, Austria, Belgium, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, the Netherlands, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, and the United Kingdom. The consortium is led by Andrei Kirilyuk (uu77).
