Quantum Adaptive Topology Optimization (QATO)

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum Adaptive Topology Optimization (QATO) is a novel optimization algorithm designed to leverage quantum self-adaptation principles to enhance the performance of quantum systems. This paper introduces a QATO algorithm that dynamically adjusts parameters within a quantum system to achieve optimal results, offering a significant departure from traditional optimization techniques. We detail the core mechanism, exploring how the quantum self-adaptation allows for the exploration of complex, multi-scale optimization landscapes, ultimately leading to improved system performance. The paper presents a comprehensive analysis of the algorithm's design, demonstrating its effectiveness through theoretical analysis and experimental validation. The primary goal is to provide a robust and efficient method for optimizing quantum systems, potentially unlocking new capabilities and applications.

DOI: 10.5281/zenodo.22601082

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