Title: Topological Quantum Computing Self-Adaptation

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

The development of robust and efficient quantum computing is paramount for realizing transformative technologies. Traditional quantum algorithms often rely on pre-defined parameters, limiting their adaptability and hindering performance in complex scenarios. This paper explores the potential of topological quantum computing and self-adaptive algorithms to overcome these limitations. We investigate a novel approach utilizing dynamically adjusted topological structures to optimize quantum computations, addressing the core claim that research is underway to design self-adaptive quantum computing systems capable of adjusting their topology in response to input data, thereby enhancing both efficiency and stability. This approach leverages adaptive algorithms to dynamically reshape the quantum system's topology, offering a pathway towards more versatile and reliable quantum computation. The research demonstrates the potential for significant advancements in quantum algorithms and system design through this self-adaptive methodology.

DOI: 10.5281/zenodo.22155571

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