Atomic switch networks-nanoarchitectonic design of a complex system for natural computing

被引:68
作者
Demis, E. C. [1 ]
Aguilera, R. [1 ]
Sillin, H. O. [1 ]
Scharnhorst, K. [1 ]
Sandouk, E. J. [1 ,2 ]
Aono, M. [3 ]
Stieg, A. Z. [3 ,4 ]
Gimzewski, J. K. [1 ,3 ,4 ,5 ]
机构
[1] Univ Calif Los Angeles, Dept Chem & Biochem, Los Angeles, CA 90024 USA
[2] Univ Calif Los Angeles, Dept Phys & Astron, Los Angeles, CA 90024 USA
[3] Natl Inst Mat Sci, WPI Ctr Mat Nanoarchitecton MANA, Tsukuba, Ibaraki 3050047, Japan
[4] Univ Calif Los Angeles, Calif NanoSyst Inst CNSI, Los Angeles, CA 90024 USA
[5] Univ Bristol, Ctr Nanosci & Quantum Informat, Sch Phys, Bristol BS8 1TH, Avon, England
关键词
nanoarchitechtonics; complex systems; memristor; atomic switch networks; natural computing; cognitive computing; reservoir computing; NEURAL-NETWORKS; CRITICALITY;
D O I
10.1088/0957-4484/26/20/204003
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.
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页数:11
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