Self-Adaptive Geometric Topology Models for Quantum Simulation

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel quantum simulation framework, termed "Self-Adaptive Geometric Topology Models," designed to address the limitations of traditional numerical simulation techniques. The framework leverages quantum simulation to dynamically adjust geometric models based on input topological structures, enabling high-precision geometric modeling and optimization. We detail the core mechanism of this approach, emphasizing the use of quantum algorithms to iteratively refine geometric representations, ultimately leading to improved simulation accuracy and the ability to handle complex topological structures. The paper presents a preliminary investigation demonstrating the framework's potential for achieving significant gains in geometric modeling and optimization compared to existing methods.

DOI: 10.5281/zenodo.22266333

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