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Self-organization and Emergence of Dynamical Structures in Neuromorphic Atomic Switch Networks

Abstract

The self-organization of dynamical structures in complex natural systems is associated with an intrinsic capacity for computation. Beginning from the context of modern trends in neuromorphic engineering, this work introduces an effort toward the construction of purpose-built dynamical systems. Known as atomic switch networks (ASN), these systems consist of highly interconnected, physically recurrent networks of inorganic synapses (atomic switches). By combining the advantages of controlled design with those of self-organization, the functional topology of ASNs has been shown to produce emergent system-wide dynamics and a diverse set of complex behaviors with striking similarity to those observed in many natural systems including biological neural networks and assemblies. Numerical modeling and experimental investigations of their operational characteristics and intrinsic dynamical properties have facilitated progress toward toward implementation in neuromorphic reservoir computing. These achievements demonstrate the utility of ASNs as a uniquely scalable physical platform capable of exploring the dynamical interface of complexity, neuroscience, and engineering.

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Acknowledgements

This work was partially supported by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) World Premier International (WPI) Research Center for Materials Nanoarchitectonics (MANA), HRL Laboratories, and the Defense Advanced Research Projects Agency (DARPA) - Physical Intelligence Program (BAA-09-63), US Department of Defense. The authors acknowledge use of the Nanoelectronics Research Facility (NRF) and Nano and Pico Characterization Laboratory (NPC) at the University of California, Los Angeles.

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Stieg, A.Z. et al. (2019). Self-organization and Emergence of Dynamical Structures in Neuromorphic Atomic Switch Networks. In: Chua, L., Sirakoulis, G., Adamatzky, A. (eds) Handbook of Memristor Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-76375-0_14

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