Ascension: A Deterministic Software Evolution Engine for Cross-Primitive Capability Discovery

This paper presents Ascension, a deterministic software evolution engine that discovers emergent capabilities by colliding uploaded source code against a fixed 40-primitive cognitive substrate matrix. Unlike generative AI systems, Ascension preserves the developer’s original logic entirely and wraps it in a discovered cognitive overlay — producing portable, zero-dependency artifacts across 25 programming languages including 7 hardware description languages. The system operates without external AI API calls. All discovery, scoring, and export processes are purely algorithmic. This document is published as a prior art disclosure to establish the priority date of March 30, 2026 for all methods, concepts, and architectural patterns described herein.