Non-Linear Geometry Structure Optimization Based Quantum Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper presents a novel approach to non-linear geometry structure optimization utilizing adaptive quantum algorithms. We propose a framework where quantum algorithms are employed to efficiently and effectively optimize complex geometric structures. The core mechanism revolves around leveraging quantum phenomena, specifically superposition and entanglement, to achieve enhanced optimization capabilities compared to traditional methods. This work addresses the limitations of existing algorithms by integrating quantum optimization techniques into a comprehensive optimization pipeline. The goal is to develop a robust and scalable method for modeling and optimizing intricate geometric configurations, ultimately aiming for improved performance in various geometric applications. This paper will detail the design of the algorithm, its theoretical underpinnings, and preliminary experimental results demonstrating its effectiveness.

DOI: 10.5281/zenodo.22183560

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