Nonlinear Quantum Graphs for Adaptive Modeling

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper introduces a novel adaptive modeling approach utilizing non-linear quantum graphs. Complex systems often require simplification, and traditional methods can be computationally demanding. This work proposes a method that leverages the inherent properties of non-linear quantum graphs to streamline the representation of intricate systems. The core mechanism involves dynamically adjusting model parameters based on the graph's topology, enabling a simplified representation without significant loss of accuracy. We demonstrate the effectiveness of this approach through a series of illustrative examples, showcasing its capability to effectively model various systems. The research aims to provide a more efficient and flexible method for simplifying complex systems through the application of quantum graph theory.

DOI: 10.5281/zenodo.22222550

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