Tension Propagation

Tension Propagation is the diffusion of accumulated computational stress through the dimensional hierarchy, so that a local perturbation produces a coherent response in every layer of the architecture. The book lists it with Dimensional Memory and Causal Nesting as the three features of the hierarchical dimensional architecture: each new axis joins a network that remembers, spreads tension and nests causes across scales. Tension that builds in one place does not stay there; it spreads, is fed by sources and is absorbed, and the whole stack responds together. In the chapter on null wells, the same process appears as the diffusion term of the collapse equation, where a diffusion coefficient σ [𝕃²·𝕋⁻¹] for recursive tension propagation balances nonlinear collapse of recursive density. The current lexicon statement gives the unified tension evolution as ∂T/∂t = D⊹ × ∇²T + S⟹ − A⟸ × T, where T is the accumulated tension, D⊹ the effective diffusion coefficient, ∇²T its spatial Laplacian, S⟹ the source of new tension and A⟸ the rate at which tension is absorbed. Tension Propagation connects to Accumulated Tension, Dimensional Memory, Causal Nesting, Recursive Tension Dynamics and Null Well Collapse Evolution.