Journal
NATURE COMMUNICATIONS
Volume 11, Issue 1, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41467-020-16105-y
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Funding
- College of Engineering at Purdue University
- AFOSR [FA9550-19-10351]
- ARO [W911NF1920237]
- Center for Brain Inspired Computing (C-BRIC)
- DARPA
- SRC
- Vannevar Bush Fellowship
- Quantum Materials for Energy Efficient Neuromorphic Computing, an Energy Frontier Research Center - U.S. Department of Energy (DOE), Offce of Science, Basic Energy Sciences [DE-SC0019273]
- U.S. DOE of Science [DE-SC0012704]
- DOE Office of Science
- U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences [DE-AC02-06CH11357]
- U.S. Department of Energy Office of Science User Facility [DE-AC02-05CH11231]
- [DE-SC0001805]
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Trees are used by animals, humans and machines to classify information and make decisions. Natural tree structures displayed by synapses of the brain involves potentiation and depression capable of branching and is essential for survival and learning. Demonstration of such features in synthetic matter is challenging due to the need to host a complex energy landscape capable of learning, memory and electrical interrogation. We report experimental realization of tree-like conductance states at room temperature in strongly correlated perovskite nickelates by modulating proton distribution under high speed electric pulses. This demonstration represents physical realization of ultrametric trees, a concept from number theory applied to the study of spin glasses in physics that inspired early neural network theory dating almost forty years ago. We apply the tree-like memory features in spiking neural networks to demonstrate high fidelity object recognition, and in future can open new directions for neuromorphic computing and artificial intelligence. Designing energy efficient and scalable artificial networks for neuromorphic computing remains a challenge. Here, the authors demonstrate tree-like conductance states at room temperature in strongly correlated perovskite nickelates by modulating proton distribution under high speed electric pulses.
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