Cosmo-Predictive Analog Computing: A Unified Framework for Post-Quantum Computation via Spacetime Thermodynamics, Noncommutative Geometry, and Self-Predictive Intelligence

Cosmo-Predictive Analog Computing (CPAC) introduces a novel computational paradigm that transcends classical and quantum models by equating computation with the universe’s self-prediction mechanism. Information is encoded in Cosmic Predictive Patterns (CPPs), stable non-equilibrium attractors in the phase space of quantum spacetime geometry and a generative AI field. Grounded in noncommutative geometry, stochastic thermodynamics, and algorithmic information theory, CPAC defines a new complexity class CP, strictly containing BQP, and resolves undecidable problems via geometric regularization. The core dynamics, Reciprocal Self-Prediction (RSP), is a nonlinear, non-Markovian evolution on a spectral triple, yielding exponential computational speedups with intrinsic fault tolerance. An experimental pathway using braided photonic circuits as a physical analog enables near-term validation.