Title: Dynamic Dimensionality Reduction via Quantum Tunneling (DQR)

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Dynamic Dimensionality Reduction via Quantum Tunneling (DQR) presents a novel approach to data reduction leveraging quantum tunneling principles. This research investigates the potential of utilizing quantum tunneling to dynamically reduce the dimensionality of data, achieving enhanced representation capabilities for complex datasets. The core mechanism focuses on creating a reduced representation through quantum tunneling, optimized for improved analysis speed and capacity. This work explores the theoretical underpinnings of quantum tunneling and its practical application within the context of data dimensionality reduction. A comprehensive analysis of the algorithm's performance and potential advantages is presented, demonstrating the feasibility of this method.

DOI: 10.5281/zenodo.22331028

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