THALVION: A Quantum-Inspired, Topology-Driven Framework for AGI (preprint, Oct.2025)

THALVION: A Quantum-Inspired, Topology-Driven Framework for Artificial General Intelligence presents a conceptual research framework that integrates combinatorial creativity, quantum-inspired optimization, and topological coherence to explore pathways toward self-evolving AI systems.

The paper introduces the Adaptive Collapse Oracle (ACO) as a probabilistic selection mechanism inspired by quantum measurement principles, coupled with persistent homology, sheaf theory, and manifold regularization to ensure structural and cross-domain consistency.

Preliminary simulations demonstrate improved few-shot generalization and robustness under noise using topology-inspired and entropy-biased learning processes. Ethical and governance protocols are included to ensure safe scaling and transparent experimentation.

This preprint is intended as a foundation for reproducible AGI research, emphasizing open scientific development, reproducibility, and theoretical rigor within the domains of artificial intelligence, quantum-inspired computation, and topological machine learning.