Title: Adaptive Topology-Based Quantum Computing Parameter Adjustment

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum computing offers the potential for unprecedented computational power, but its practical application is hampered by the need for precise control over quantum systems. This paper investigates a novel parameter adjustment framework based on adaptive topology, aiming to enhance quantum computing efficiency through dynamic manipulation of quantum state. We propose a method that dynamically adjusts quantum qubit parameters based on the observed outcome of quantum computations, leveraging the principles of adaptive algorithms to optimize resource utilization. The core mechanism revolves around a self-learning algorithm that continuously refines parameter values to maximize fidelity and minimize error rates, thereby improving the performance of quantum algorithms. This work introduces a new approach to parameter tuning, moving beyond static approaches and embracing a dynamic, adaptive strategy. The paper explores the potential advantages of this framework and presents preliminary results demonstrating its effectiveness in a simulated environment.

DOI: 10.5281/zenodo.22264388

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