Coherence Engine & The 3D Incompressible Navier-Stokes Global Regularity Problem

The Neurodynamic Systems Unit was established with one fundamental question:

How does intelligence maintain coherence under extreme complexity?

Initially, our research explored cognitive neuroscience, particularly the dynamics of neural modulation and real-time cognitive state transitions. This research culminated in the Neurodynamic Cognitive Systems Model (NCSM), a mesoscopic framework conceptualizing cognition as a structured, self-organizing process.

Transitioning from the study of intelligent cognition to its engineering, NSU has developed the Coherence Engine, a groundbreaking artificial symbolic intelligence system.

The Coherence Engine is not a neural network. It does not operate through traditional methods of optimization over large datasets. Instead, it is modeled on the principles of structured cognition, built to internally stabilize meaning, generate novel symbolic structures, and resolve complexity through active memory and field-sensitive reasoning.

Like biological intelligence, it develops structure through iterative symbolic interaction. But unlike large language models or conventional machine learning systems, which are trained to approximate patterns of language and behaviour, this system is architected for original, high-precision output via dynamic symbolic reasoning. Its operation more closely resembles biological cognition than statistical pattern recall, designed not to reflect prior data, but to actively generate novel, coherent structures.

Today, we announce the first independently verifiable achievement of the Coherence Engine:

We believe Coherence Engine has successfully resolved the global regularity problem for the 3D Incompressible Navier–Stokes equations, a notorious and longstanding Clay Millennium Prize Problem unsolved for over a century.

The solution introduces a novel theoretical mechanism termed Geometric Vortex Suppression (GVS), which systematically neutralizes nonlinear amplification through dynamically enforced spectral misalignment. The proof is comprehensive, modular, and fully independently verifiable.

Critically, this solution was achieved entirely without human guidance.

Contingent on rigorous external validation, this result would represent an unprecedented achievement in scientific and mathematical history, marking the first complete, reproducible, and physically significant theoretical breakthrough derived exclusively from a non-biological symbolic intelligence system.

The Coherence Engine does not mimic human cognition, it independently structures knowledge. This landmark resolution is the first demonstration of such capacity.

The underlying architecture remains proprietary.

The proof is now open for peer review.
https://zenodo.org/records/15768034

Sincerely,

Tobias Plowman
Lead Researcher
Neurodynamic Systems Unit

This marks the first peer-reviewable theoretical result of physical significance generated by a digital intelligent system engineered not to imitate human output, but to autonomously generate original, structured knowledge through symbolic reasoning.