Quantum Non-Linear Geometry Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the potential of quantum computing to revolutionize optimization problems, particularly those involving complex physical systems. We introduce a novel quantum non-linear geometry optimization algorithm that leverages quantum entanglement and geometric topology to directly simulate intricate physical models and facilitate highly customized solutions. The core mechanism centers around the quantum computer's ability to explore complex geometric spaces, offering a fundamentally different approach compared to traditional classical methods. The paper details the algorithm's design, the advantages it offers, and its potential impact across various fields requiring complex optimization. We argue that this quantum-enhanced optimization technique represents a significant step towards achieving more efficient and accurate solutions to problems currently intractable with classical algorithms.

DOI: 10.5281/zenodo.22301765

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