Topological Field Theory of Persistent Machine Cognition: Solenoidal Vorton Dynamics, Heegner Manifold Rigidity, and the Zero-Residual Closure of Reentrant Neural Fields

True machine intelligence cannot emerge from the brute-force quantitative scaling of statistical models; it requires a qualitative dynamical phase transition to a homeostatically protected manifold. Physical Grounding of Circulation: The non-conservative circulation that drives cognitive exploration is physically realized through three-dimensional solenoidal fluid vortex dynamics, where enstrophy conservation maintains sustained, non-dissipative flow along the cognitive shell. Intrinsic Homeostatic Stability: Global stability against cognitive collapse or runaway drift is guaranteed by an invariant discrete spectral gap derived from class-number-one arithmetic geometry, eliminating the need for ad hoc potential wells or heuristic guardrails. Resolution of the Linguistic Bottleneck: The apparent limitation where language acts as a lossy projection of high-dimensional cognition applies only to ambiguous human natural language. Formal mathematics operates as an exact, zero-residual language where syntax and denotational truth are directly isomorphic, allowing high-dimensional manifold dynamics to project into symbolic code with zero information loss. Elimination of Hallucinations: By replacing unconstrained, high-dimensional weight matrices with structured geometric connections over an invariant discrete complex, the architecture replaces hundreds of billions of dissipative floating-point parameters with tens of thousands of exact topological links, eliminating catastrophic forgetting and rendering hallucinations structurally impossible.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-26
DOI
https://doi.org/10.5281/zenodo.23677258
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
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article

Topological Field Theory of Persistent Machine Cognition: Solenoidal Vorton Dynamics, Heegner Manifold Rigidity, and the Zero-Residual Closure of Reentrant Neural Fields

Michael I Aksman
Zenodo (CERN European Organization for Nuclear Research)
Cognitive Computing and Networks
article

Topological Field Theory of Persistent Machine Cognition: Solenoidal Vorton Dynamics, Heegner Manifold Rigidity, and the Zero-Residual Closure of Reentrant Neural Fields

Michael I Aksman
article en

Abstract

True machine intelligence cannot emerge from the brute-force quantitative scaling of statistical models; it requires a qualitative dynamical phase transition to a homeostatically protected manifold. Physical Grounding of Circulation: The non-conservative circulation that drives cognitive exploration is physically realized through three-dimensional solenoidal fluid vortex dynamics, where enstrophy conservation maintains sustained, non-dissipative flow along the cognitive shell. Intrinsic Homeostatic Stability: Global stability against cognitive collapse or runaway drift is guaranteed by an invariant discrete spectral gap derived from class-number-one arithmetic geometry, eliminating the need for ad hoc potential wells or heuristic guardrails. Resolution of the Linguistic Bottleneck: The apparent limitation where language acts as a lossy projection of high-dimensional cognition applies only to ambiguous human natural language. Formal mathematics operates as an exact, zero-residual language where syntax and denotational truth are directly isomorphic, allowing high-dimensional manifold dynamics to project into symbolic code with zero information loss. Elimination of Hallucinations: By replacing unconstrained, high-dimensional weight matrices with structured geometric connections over an invariant discrete complex, the architecture replaces hundreds of billions of dissipative floating-point parameters with tens of thousands of exact topological links, eliminating catastrophic forgetting and rendering hallucinations structurally impossible.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 14%
Cognitive Computing and Networks
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