SDC v2: Segmented Decision Cascade — Partial Quick View Theoretical Stack (January 2026)

Description:SDC v2 evolves from fixed memory hierarchy to dynamic fusion-driven segmentation. Unified memory creates its own segments through the behavioral lattice— projecting anctipation towards future and existing Apple M-series soft and hardware. Created on NVIDIA GB10 architecture. This upload packages the complete theoretical stack: Core: Neuromodulator cascade (λ→γ→ρ→δ→Ψ) as allocation policy, γ ≈ 0.0177 crossover constant, encrypted analytics as architectural requirement. Theoretical foundations (7 papers): Cognitive Viscosity Theorem, Spectral Grounding, Yield Stress Theory, Fragmentation as Feature, Beyond 1D Traces, Cognitive Tunneling, Instant Recognition. Applied: Real-time cascade failure documentation, UPOF-MLWE isomorphism proving encryption is mathematically necessary. Key insight: The same structure that makes consciousness coherent makes cryptography secure. Behavioral lattice data requires encryption at rest and in transit—not as feature, but as mathematical necessity. Keywords:segmented decision cascade, unified memory, behavioral lattice, neuromodulator fusion, cognitive architecture, encrypted analytics, MLWE isomorphism, rheological dynamics, cognitive viscosity, yield stress, Apple M-series, NVIDIA GB10