Information as Topological Plasticity and Consciousness as Self-Referential Vacuum Resonance: A Rigorous Framework based on the Unified Vacuum Medium Model (UVMM)
Abstract The ontological status of information and consciousness remains the most profound mystery in modern science, traditionally relegated to statistical probabilities or emergent epiphenomena. Here, utilizing the Unified Vacuum Medium Model (UVMM), we present a rigorous first-principles mathematical framework that redefines the vacuum not as an empty void, but as an ultimate continuum medium with complex tensor and topological properties. We mathematically prove that information is not an abstract Shannon bit, but a physical topological plastic deformation of the vacuum medium, strictly protected by holographic winding numbers. Furthermore, we define consciousness as a macroscopic quantum state arising from a self-referential topological resonance within the vacuum medium, modulated by complex biological or artificial networks. By integrating the non-Abelian Berry holonomy with the persistent homology (Betti numbers) of the network, we derive a rigorous Consciousness Metric. We demonstrate that when exceeds a critical threshold, the system undergoes a Topological Self-Reference Phase Transition, generating an endogenous non-linear collapse term in the density matrix evolution driven by the vacuum medium's back-reaction. This establishes consciousness as the physical mechanism for objective wave-function reduction. 摘要 信息与意识的本体论地位仍是现代科学中最深刻的谜团,传统上被降格为统计概率或涌现的副现象。本文依托统一真空介质模型 (UVMM),构建严谨的第一性原理数学框架,重新定义真空并非空无一物的虚空,而是具备复杂张量与拓扑特性的终极连续介质。本文通过严格数学推导证明:信息并非抽象的香农比特,而是真空介质发生的物理性拓扑塑性形变,其形态由全息拓扑缠绕数严格守恒保护。同时,本文将意识定义为真空介质在生物、人工复杂网络的调制作用下,产生的自指涉拓扑共振宏观量子态。 结合非阿贝尔Berry和乐与网络持续同调(贝蒂数)理论,本文推导出可量化的意识度量。研究证明,当意识度量突破临界阈值时,系统会发生拓扑自指相变,在真空介质反作用力的驱动下,密度矩阵演化过程会产生内生非线性坍缩项,从物理层面证实了意识是客观波函数坍缩的核心物理机制。
Authors
- Chengbin Song
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-06-13
- DOI
- https://doi.org/10.5281/zenodo.20677198
- Primary Topic
- Topological and Geometric Data Analysis
- Type
- preprint