Engineered systems typically separate mechanical function from information processing, whereas biological systems can exploit physical structure as a medium for information processing and computation. Motivated by this contrast, recent work in mechanics has explored embedding information-processing capabilities directly into mechanical structures. However, quantitative frameworks for evaluating such capabilities remain limited. Here we address a foundational question: how does information propagate through a solid body? Using elastic bodies as a model system, we apply information-theoretic tools to treat an elastic domain as an information encoder and quantify how information transmits from applied loads to discrete sensor locations. We further connect these measures to familiar mechanical phenomena, including Saint-Venant's effect and principal stress lines. Moving toward design, we show how geometry and architected materials can tune transmission, enabling elastic domains to either transmit or block information. Overall, this work advances quantifiable metrics and benchmark tasks for mechanical intelligence, supporting comparable designs of mechanically embodied information processing.

翻译：工程系统通常将机械功能与信息处理分离，而生物系统能够利用物理结构作为信息处理和计算的媒介。受此对比启发，力学领域近期研究探索了将信息处理能力直接嵌入机械结构的方法。然而，评估此类能力的量化框架仍然有限。本文致力于解决一个基础性问题：信息如何在固体中传播？以弹性体作为模型系统，我们应用信息论工具将弹性域视为信息编码器，并量化信息如何从施加的载荷传递到离散的传感器位置。我们进一步将这些度量与常见的力学现象联系起来，包括圣维南效应和主应力线。面向设计应用，我们展示了几何结构与构型材料如何调控信息传递，使弹性域能够传输或阻断信息。总体而言，本研究提出了机械智能的量化指标与基准任务，为机械实体信息处理的可比性设计提供了支撑。