We present Genesis-D, a cognitive computing architecture grounded in Clifford algebra Cl (3, 0) operating on an 8-plane spinor field evolving via nonlinear partial differential equations. The system maintains persistent topological memory through solitonic structures classified by winding number Q, distinguishing transient scalar blobs (Q=0) from stable vortices (Q=±1). A hyperchaotic attractor governs cognitive diversity with Lyapunov spectrum λ₁=+0. 2635, λ₂=+0. 1583, λ₃=+0. 0161, yielding Kaplan-Yorke dimension DKY=5. 44. A Fourier Neural Operator provides learnable spectral adaptation per Clifford grade. We demonstrate a natural mapping of the Clifford Fourier Transform to wavelength-division multiplexed photonic hardware, thermodynamic stochastic processing units, and analog memristor crossbars, positioning Genesis-D as a candidate kernel architecture for next-generation non-von-Neumann thermodynamic processors.
Ruben Garcia Abad (Mon,) studied this question.
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