AI & Computingpreprint2026-09-05

Inversion Number

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Abstract

The Inversion Number framework presents a novel mathematical structure that distinguishes between numerical magnitude and spatial allocation. Unlike conventional reciprocal operations, inversion is formalized as a conditional transfer of quantity between two distinct spaces A and B, governed by content-dependent connections. The theory introduces partial inversion through a continuous parameter t ∈ [0,1], yielding characteristic algebraic properties including the identity α² = I for complete inversion and β² = β for half-inversion. By incorporating admissibility conditions, content transformations, and transfer histories, the framework extends beyond elementary algebra to create a conditional mathematical system where the existence and nature of operations depend on the structural properties of transferred content.

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View paper (DOI)Open access versionOpenAlexZenodo (CERN European Organization for Nuclear Research)Published 2026-09-05

Authors: Ren Matsuoka