Title: Adaptive Quantum Computing Topology Transformation Algorithm

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

This paper presents an innovative algorithm for quantum computing topology transformation, leveraging dynamic adjustments to the system's topological structure to enhance both efficiency and precision. Traditional topological transformation methods are often static, limiting potential improvements. Our proposed algorithm employs an adaptive transformation strategy, dynamically modifying the quantum system's topology to optimize the resulting computational outcomes. The core mechanism centers around a self-learning approach to the quantum state, allowing the algorithm to continuously refine the topological landscape for improved performance. This approach addresses limitations of static transformations and offers a novel pathway towards more robust and accurate quantum computation. This work contributes to the field of quantum computing by presenting a practical and adaptable topology transformation technique.

DOI: 10.5281/zenodo.22157683

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