Quantum Geometry Topology Adaptive Transformation

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum Geometry Topology Adaptive Transformation explores the potential of quantum geometry topology to drive automated and optimized geometric transformations. This research proposes a novel algorithm based on quantum entanglement and topology, aiming to overcome the limitations of traditional optimization techniques. The core mechanism centers around leveraging quantum entanglement to induce topological changes, which then guides the algorithm towards the desired transformation. The paper details the algorithm's design, the rationale behind its quantum-based approach, and preliminary results demonstrating improved efficiency and adaptability compared to existing methods. The focus is on automating and optimizing geometric transformations, highlighting the potential for novel quantum-enhanced computational paradigms.

DOI: 10.5281/zenodo.22267916

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