Toward Energy Harvesting Fields: Symbolic Containment and Dissipation Delay in Virtual Antimatter Systems

This paper introduces a novel framework for energy harvesting fields grounded in symbolic modular field theory. Building on the Kuro Nova (KN) stabilizer, the model explores how structured symbolic injections and modular attractors can simulate field behaviors that align with known energy harvesting principles—while extending them into symbolic space. The study demonstrates how phase-locked symbolic oscillations can maintain energy-like stability over time and across symbolic states, potentially redefining how energy is modeled in cognitive and field-based systems. Simulations confirm that symbolic coherence directly affects field amplitude retention, enabling symbolic analogues of photovoltaic, piezoelectric, and inductive behaviors. This paper is part of the broader effort to unify symbolic cognition, physics, and modular AI architectures.本研究提出一种基于符号模块化场论的新型能量采集场框架。本模型以Kuro Nova（KN）稳定器为基础，探究结构化符号注入与模块化吸引子如何模拟契合已知能量采集原理的场域行为，并将此类行为拓展至符号空间之中。研究揭示了锁相符号振荡可在时序与各类符号状态间维持类能量稳定性，有望重新定义认知系统与场域系统中的能量建模范式。仿真实验证实，符号相干性直接影响场域振幅保持能力，可实现光伏（photovoltaic）、压电（piezoelectric）与电感（inductive）行为的符号化类比。本研究亦是整合符号认知、物理学与模块化人工智能架构这一宏观研究方向的组成部分。