Quantum State Nonlinear Geometry Optimization

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm based on quantum state nonlinear geometry optimization, leveraging the unique properties of quantum states, particularly quantum entanglement. The core mechanism involves manipulating quantum states to generate complex geometric structures, enhancing algorithm efficiency. The algorithm's potential lies in its ability to surpass traditional optimization techniques by providing access to a broader range of solution spaces and facilitating the discovery of global optima. This work addresses the limitations of conventional optimization methods by introducing a fundamentally different approach that harnesses quantum phenomena for enhanced performance. We present a preliminary analysis demonstrating the potential of this approach across diverse geometrical datasets.

DOI: 10.5281/zenodo.22321824

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