Quantum State's Adaptive Geometry Deformation

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum state modeling has long been a significant challenge in the field of quantum computation and information processing. Traditional approaches often rely on static state representations, limiting the ability to accurately predict system behavior and identify subtle geometric structures that influence performance. This paper introduces a novel method based on the adaptive geometry of quantum states, aiming to revolutionize this process through a more dynamic and insightful approach. We propose a framework that dynamically adjusts the quantum state's geometry during computation, enabling a more precise and comprehensive modeling of quantum systems. This method is designed to uncover hidden geometric relationships between the system's structure and its computational capabilities, ultimately leading to improved quantum algorithms and a deeper understanding of fundamental quantum mechanics. The core mechanism involves constructing a geometric transformation model, employing iterative calculations to identify the most critical geometric features driving the system's behavior. This results in a new way of analyzing quantum states that goes beyond static representations.

DOI: 10.5281/zenodo.22221110

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