Quantum Topology-Adaptive Geometric Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum Topology-Adaptive Geometric Algorithm explores the potential of leveraging quantum phenomena to enhance understanding and prediction of topological structures. This research proposes a novel algorithm that utilizes quantum learning to establish a foundational understanding of these structures and then employs adaptive geometric optimization to refine the algorithm's capabilities. The core mechanism involves creating a quantum state representation of a topological system, allowing for a more nuanced and efficient exploration of the system's properties. This approach seeks to move beyond traditional algorithmic approaches by directly incorporating quantum mechanics into the core of the optimization process. The development of this algorithm represents a significant step toward a deeper comprehension of topological systems and opens new avenues for advanced computational modeling.

DOI: 10.5281/zenodo.22279914

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