Quantum Geometry Optimization: A Novel Approach to Complex System Optimization

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm based on quantum geometry, designed to address the challenges of optimizing complex systems such as machine learning models, neural network architecture design, and optimization problems. The core mechanism leverages quantum search principles, utilizing quantum states to iteratively explore the solution space and identify optimal configurations. This approach offers a fundamentally different approach to optimization, potentially leading to significant improvements in efficiency and effectiveness compared to traditional algorithms. The paper details the algorithm's design, its potential benefits, and preliminary results demonstrating its effectiveness in a specific case study.

DOI: 10.5281/zenodo.22520769

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