Quantum-Based Geometric Simulation for High-Dimensional Data

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum-based geometric simulation offers a promising approach to handling high-dimensional data, leveraging the unique properties of quantum mechanics to represent and analyze complex patterns. This paper proposes a novel quantum algorithm for simulating high-dimensional data, centered around the concept of quantum superposition to explore the data's inherent structure, aiming to achieve a more accurate representation than traditional geometric methods. The core mechanism involves utilizing quantum superposition to identify and quantify relationships within the data, potentially uncovering hidden structures and trends that are difficult to discern with classical approaches. The paper details the algorithm's design, its theoretical underpinnings, and initial experimental validation, showcasing the potential for enhanced data analysis and representation.

DOI: 10.5281/zenodo.22277074

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