A recent article from ScienceDaily reports on a breakthrough in quantum materials research that could lead to more energy-efficient computing.
The article is titled “Quantum material exhibits ‘non-local’ behavior that mimics brain function: New research shows a possible way to improve energy-efficient computing” and was published on August 8, 2023.
The article describes the work of a consortium called Q-MEEN-C, led by the University of California San Diego, that aims to create brain-like computers using quantum materials. Quantum materials are substances that exhibit unusual properties at the atomic scale, such as superconductivity, magnetism, and topological phases.
One of the challenges of creating brain-like computers is to replicate the non-local interactions that occur in the brain. Non-locality means that stimuli applied to one part of a system can affect another part that is not directly connected. For example, in the brain, electrical signals can travel between distant neurons and synapses, enabling complex information processing.
The researchers from Q-MEEN-C discovered that a quantum material called samarium hexaboride (SmB6) can exhibit non-locality when stimulated by electrical pulses. They created an array of electrodes on top of a thin film of SmB6 and measured the resistance changes between them. They found that stimulating one pair of electrodes could also affect the resistance of another pair that was not adjacent.
This non-local behavior mimics the brain function and could enable new types of devices that perform neuromorphic computing. Neuromorphic computing is a paradigm that uses analog circuits and architectures inspired by the brain to perform tasks such as pattern recognition, learning, and memory.
The researchers believe that SmB6 is not the only quantum material that can exhibit non-locality and plan to explore other candidates in the future. They also hope to scale up their experiments to create larger arrays of electrodes and devices that can perform more complex functions.
The article concludes by highlighting the potential applications and benefits of neuromorphic computing using quantum materials. These include faster, more accurate, and more energy-efficient data processing, as well as new insights into the physics of quantum materials and the biology of the brain.
