AI Visibility Aggregation and Signal Formation Theorem

This document formalizes how information becomes a learnable signal in large language models through aggregation and repetition across time and surfaces. It operates as a supporting theorem to the AI Visibility Canonical Definition and explains why durable learning depends on semantic and structural consistency rather than isolated documents or volume alone, independent of downstream interaction or optimization mechanisms.