超選擇規則在量子人工智慧中的應用
IHSIEN CHOU
Abstract
Superselection Rules (SSR) are structural principles in quantum mechanics and quantum field theory that restrict coherent superposition between different eigensectors of conserved quantities. In recent years, with the rapid development of bosonic quantum computing, continuous-variable quantum information, and Quantum AI, SSR is no longer merely a "constraint condition" but is increasingly understood as a resource filter and structural design principle. This paper systematically organizes the theoretical foundations of SSR, its mathematical formalization, and its deep relationship with quantum entanglement resources. We introduce "Socratic Self-Refinement" as a conceptual methodology in Quantum AI architecture. The core thesis is: Truly useful entanglement for quantum computing and Quantum AI must exist within the same superselection sector.