神经形态工程学
计算机科学
氧化物
材料科学
人工智能
人工神经网络
冶金
作者
Uday S. Goteti,Ivan A. Zaluzhnyy,Shriram Ramanathan,R. C. Dynes,Alex Frañó
标识
DOI:10.1073/pnas.2103934118
摘要
Neuromorphic computing which aims to mimic the collective and emergent behavior of the brain's neurons, synapses, axons, dendrites offers an intriguing, potentially disruptive solution to society's ever-growing computational needs. Although much progress has been made in designing circuit elements that mimic the behavior of neurons and synapses, challenges remain in designing networks of elements that feature a collective response behavior. We present simulations of networks of circuits and devices based on superconducting and Mott-insulating oxides that display a multiplicity of emergent states that depend on the spatial configuration of the network. Our proposed network designs are based on experimentally known ways of tuning the properties of these oxides using light ions. We show how neuronal and synaptic behavior can be achieved with arrays of superconducting Josephson junction loops, all within the same device. We also show how a multiplicity of synaptic states could be achieved by designing arrays of devices based on hydrogenated rare-earth nickelates. Together, our results demonstrate a new research platform that utilizes the collective macroscopic properties of quantum materials to mimic the emergent behavior found in biological systems.
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