Non-Linear Geometric Topology and Quantum Computing Synergistic Modeling

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the synergistic potential of non-linear geometric topology and quantum computing for complex geometric system modeling. We propose a novel model leveraging quantum computation to accelerate computationally intensive geometric topology tasks, while integrating quantum machine learning techniques to enhance the model's predictive power and efficiency. The core mechanism focuses on utilizing quantum acceleration to refine geometric structure analysis, thereby fostering improved accuracy and computational efficiency. This approach offers a paradigm shift in tackling intricate geometric systems, offering a pathway toward significant advancements in modeling, simulation, and analysis across diverse fields.

DOI: 10.5281/zenodo.22189481

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