Resolution of Asymptotic Latent Drift via Non-Expansive NIR-Projection and Admissibility Gate Governance Solved

As computational systems transition from static heuristics to high-dimensional adaptive manifolds, the preservation of semantic integrity becomes a governance crisis. Traditional error-correction methods fail to address latent drift—the gradual accumulation of infinitesimal geometric offsets within the latent space that eventually manifest as catastrophic structural fabrication. This research posits that drift is not a stochastic error but a topological necessity in unconstrained systems. To resolve this, we propose the **Morrison Admissibility Gate (MAG)**, a deterministic filter that enforces boundary conditions at the point of state transition, ensuring all computational outputs remain within the admissible spectral centroid of the system. Latent drift in adaptive computational systems is commonly treated as a stochastic or data-dependent artifact. This work shows instead that drift is a deterministic consequence of expansive state evolution in unconstrained latent spaces. We introduce the Morrison Admissibility Gate (MAG), a runtime governance operator enforcing non-expansive, anchor-locked state transitions. Using Lyapunov analysis, we prove that governed evolution precludes asymptotic drift as a class of failure. Adversarial long-horizon benchmarks confirm contraction of latent drift to numerical zero and complete elimination of hallucination under conditions where conventional systems diverge. These results establish drift elimination as a governance-level invariant rather than a model- or data-dependent phenomenon.