Dynamic Adaptive Topology and Quantum Computing Integration: A Quantum Computing Optimization Strategy

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the synergistic integration of dynamic adaptive topology and quantum computing, aiming to enhance quantum computation through optimized parameter adjustments. Traditional quantum computing relies on static parameters, limiting computational potential. We propose a novel dynamic adaptive topology framework that dynamically adjusts quantum parameters based on the input data, ultimately optimizing quantum computation's performance. This integration offers a promising pathway towards more efficient and versatile quantum algorithms. The core of this work lies in the construction of a dynamic adaptive topology model, coupled with quantum computing, to leverage the inherent advantages of topology for enhanced optimization. The proposed methodology provides a fundamentally different approach to quantum algorithm design and parameter tuning, potentially unlocking significant performance improvements.

DOI: 10.5281/zenodo.22193468

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