Spectral gap for the three-dimensional damped cubic wave equation with degenerate noise

What the math gives to ML

The paper develops a non-parabolic mixing mechanism in which finite-rank noise becomes effective through nonlinear saturation: a finite-dimensional Cameron–Martin correction compensates a compact mismatch in a deliberately weaker topology, while dissipation controls large-energy states. The transferable asset is not the wave equation itself, but the separation of contraction into a weak-topology compact-defect step and a high-energy dissipative step. A practical experiment can test whether low-rank stochastic control directions become broadly effective after transport through network curvature, improving stability or escape from bad basins at fixed compute.