Title: Adaptive Geometric Transformation Modeling of Spin Properties

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper presents a novel framework for modeling spin properties through adaptive geometric transformation. The core concept revolves around utilizing the quantum nature of spin to dynamically adjust geometric transformation parameters, enabling highly accurate spin simulation and control. Existing methods often rely on static representations, limiting the model's flexibility. This work introduces a dynamic topology-based approach, providing a more comprehensive and robust framework for spin manipulation and control. The framework leverages the inherent properties of quantum spin to achieve unprecedented precision in simulating and controlling spin states. We demonstrate the framework's efficacy through rigorous simulations and analysis, highlighting its advantages over existing approaches.

DOI: 10.5281/zenodo.22635849

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