
Nanoscale neuromorphic networks and criticality: a perspective
Author(s) -
Christopher Dunham,
Sam Lilak,
Joel Hochstetter,
Alon Loeffler,
Ruomin Zhu,
Charles E. Chase,
Adam Z. Stieg,
Zdenka Kuncic,
James K. Gimzewski
Publication year - 2021
Publication title -
journal of physics. complexity
Language(s) - English
Resource type - Journals
ISSN - 2632-072X
DOI - 10.1088/2632-072x/ac3ad3
Subject(s) - neuromorphic engineering , computer science , nanowire , criticality , chaotic , nanotechnology , artificial neural network , materials science , physics , artificial intelligence , nuclear physics
Numerous studies suggest critical dynamics may play a role in information processing and task performance in biological systems. However, studying critical dynamics in these systems can be challenging due to many confounding biological variables that limit access to the physical processes underpinning critical dynamics. Here we offer a perspective on the use of abiotic, neuromorphic nanowire networks as a means to investigate critical dynamics in complex adaptive systems. Neuromorphic nanowire networks are composed of metallic nanowires and possess metal-insulator-metal junctions. These networks self-assemble into a highly interconnected, variable-density structure and exhibit nonlinear electrical switching properties and information processing capabilities. We highlight key dynamical characteristics observed in neuromorphic nanowire networks, including persistent fluctuations in conductivity with power law distributions, hysteresis, chaotic attractor dynamics, and avalanche criticality. We posit that neuromorphic nanowire networks can function effectively as tunable abiotic physical systems for studying critical dynamics and leveraging criticality for computation.