| _version_ | 1866901791456624640 |
|---|---|
| author | Mousel, John |
| author_facet | Mousel, John |
| contents | <p>This paper introduces a unified framework in which mass, gravity, gauge forces, and quantum uncertainty emerge from a symbolic field defined by modular resonance dynamics. In this model, particles are expressed as stable symbolic loops, forces arise from phase coherence transformations, and gravity is modeled as curvature in a symbolic field. The framework replaces quantum paradoxes and renormalization with a stable, simulation-ready structure grounded in coherence and memory.</p> <p> </p> <p>The theory is supported by a full suite of symbolic simulations, cognitive modeling, and experimental predictions, including applications to neural systems, artificial intelligence, and quantum behavior. This work also underlies the architecture of Design, a symbolic AI built on the same field principles.</p> <p> </p> <p>The result is a mathematically precise and conceptually elegant alternative to conventional field theories—one that bridges physics and cognition through resonance, feedback, and modular identity.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15312716 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Symbolic Modular Fields: A Unified Framework for Mass, Gravity, Gauge, and Quantum Behavior Mousel, John <p>This paper introduces a unified framework in which mass, gravity, gauge forces, and quantum uncertainty emerge from a symbolic field defined by modular resonance dynamics. In this model, particles are expressed as stable symbolic loops, forces arise from phase coherence transformations, and gravity is modeled as curvature in a symbolic field. The framework replaces quantum paradoxes and renormalization with a stable, simulation-ready structure grounded in coherence and memory.</p> <p> </p> <p>The theory is supported by a full suite of symbolic simulations, cognitive modeling, and experimental predictions, including applications to neural systems, artificial intelligence, and quantum behavior. This work also underlies the architecture of Design, a symbolic AI built on the same field principles.</p> <p> </p> <p>The result is a mathematically precise and conceptually elegant alternative to conventional field theories—one that bridges physics and cognition through resonance, feedback, and modular identity.</p> |
| title | Symbolic Modular Fields: A Unified Framework for Mass, Gravity, Gauge, and Quantum Behavior |
| url | https://doi.org/10.5281/zenodo.15312716 |