Atomic switch networks as complex adaptive systems
Atomic switch networks as complex adaptive systems
复制标题
作为复杂自适应系统的原子交换网络
DOI：
10.7567/jjap.57.03ed02
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发表时间：
2018
影响因子：
1.5
通讯作者：
J. Gimzewski
中科院分区：
文献类型：
--
作者：
Kelsey S. Scharnhorst;J. P. Carbajal;Renato Aguilera;Eric J. Sandouk;M. Aono;A. Stieg;J. Gimzewski
复杂性是社会、环境和生物现象中越来越重要的一个方面。使用合成突触的密集无组织网络，可以在专门为复杂问题构建的微芯片上物理创建复杂的适应系统。这些受神经启发的原子开关网络（ASN）是一个动态系统，具有固有的分布式记忆，循环路径和多达十亿个相互作用的元素。我们展示了描述自组织行为的关键参数，如非线性，幂律动力学和多态切换制度。然后使用反馈回路研究器件动态，该反馈回路提供对电流和电压幂律行为的控制。广泛的应用前景包括理解和最终预测未来的事件，显示复杂的紧急行为的关键制度。
Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.