双稳态元素网络中的几何控制和记忆

Dor Shohat, Martin van Hecke
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引用次数: 0

摘要

受驱动的受挫介质的顺序响应包含了记忆效应和隐藏的计算能力。虽然抽象的滞留子模型可以捕捉这些效应,但它们需要从现象学角度引入相互作用,这限制了它们的预测能力。在这里,我们引入了双稳态元件网络--物理滞留子--其相互作用由网络的几何形状控制。这些网络实现了一系列以前未曾观察到的奇异路径,包括那些超越当前滞留子模型的路径。我们的工作为建立先进的记忆微观模型以及合理设计具有目标途径和能力的(元)材料铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geometric control and memory in networks of bistable elements
The sequential response of driven frustrated media encodes memory effects and hidden computational capabilities. While abstract hysteron models can capture these effects, they require phenomenologically introduced interactions, limiting their predictive power. Here we introduce networks of bistable elements - physical hysterons - whose interactions are controlled by the networks' geometry. These networks realize a wide range of previously unobserved exotic pathways, including those that surpass current hysteron models. Our work paves the way for advanced microscopic models of memory and the rational design of (meta)materials with targeted pathways and capabilities.
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