Nonlinear Adaptive Geometry Topology Algorithm for Optimization

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper investigates the application of a novel non-linear adaptive geometry topology algorithm to optimization problems. Traditional optimization techniques often rely on handcrafted optimization methods, while quantum optimization algorithms demonstrate the potential to learn complex topological structures. We propose a new algorithm that dynamically adjusts parameters to optimize the effectiveness of the algorithm itself, leading to improved efficiency and enhanced performance. The core mechanism involves calculating geometric topologies and employing them to guide the optimization process. This paper explores the potential of this approach to overcome limitations of existing optimization methods and provides a framework for utilizing topological principles in a computationally efficient manner.

DOI: 10.5281/zenodo.22516590

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