Quantum Topology-Driven Adaptive Geometry Transformation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Topology-Driven Adaptive Geometry Transformation presents a novel algorithmic framework for manipulating quantum topological structures through dynamic geometry transformations. This approach leverages the principles of quantum topology – a theoretical framework suggesting that space possesses inherent, discrete topology – to enable the algorithm to adapt its geometric operations based on input data. The core mechanism involves an iterative process of quantum state manipulation and geometric reconstruction, resulting in complex transformations with potentially significant implications for data analysis and representation. This work explores the fundamental concepts and potential applications of this technique, highlighting the advantages of automated and adaptive geometry transformations.

DOI: 10.5281/zenodo.22194366

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