Critical Flow Theory stress-tests OpenAI Navier–Stokes singularity

As frontier AI systems begin generating candidate proofs for longstanding mathematical conjectures, empirical verification tools must shift from passively visualizing collapse to actively attempting to falsify proposed singularity mechanisms. Visual indicators like vortex stretching and localized vorticity spikes can easily deceive naive metrics, making trajectory dynamics over time essential to ensure scaling invariants are genuinely earned rather than coincidentally matched. Incorporating designed negative control fields establishes necessary baseline hurdles to filter out non-singular flows that masquerade as critical phenomena, providing the rigorous computational interrogation needed before community consensus can form around complex AI-generated mathematical solutions.