Quantum-Driven Adaptive Topology Optimization Algorithm

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper presents a novel quantum-driven adaptive topology optimization algorithm designed to enhance the efficiency of quantum computation. Traditional topology optimization methods often struggle with complex, high-dimensional problems, requiring significant computational resources. This algorithm leverages quantum entanglement to dynamically adjust the topology of a problem space, leading to improved solution quality and reduced computational complexity. The core mechanism centers around utilizing entangled qubits to represent and manipulate the problem's structural parameters, enabling a more efficient exploration of the solution space. This work addresses the limitations of classical optimization techniques by introducing a fundamentally new approach to topology design, potentially unlocking substantial advancements in quantum algorithm design and performance.

DOI: 10.5281/zenodo.22225030

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