Quantum Field Geometry Optimization Algorithm

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper presents a novel geometric optimization algorithm based on quantum fields, designed to address challenges in optimizing complex geometric models, particularly molecular structures and optical materials. The algorithm leverages quantum field theory to represent the geometry of the model and employs quantum computation to iteratively refine the shape, thereby enhancing computational efficiency. We explore the potential of this approach to significantly improve the performance of geometric modeling tasks. The core mechanism hinges on representing the geometry as a quantum field, allowing for a fundamentally different approach to optimization than traditional methods. This work introduces a new framework for geometric optimization, offering improved scalability and the potential for novel solutions in complex geometric problems. This research emphasizes the advantages of utilizing quantum fields for geometric modeling, addressing previously intractable challenges.

DOI: 10.5281/zenodo.22444251

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