Title: Quantum Entanglement for Data Compression & Analysis

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, offers a unique potential for data compression and analysis beyond classical methods. This paper explores the design of a quantum algorithm predicated on leveraging entangled particles to achieve exponential compression. We propose a novel quantum state transfer algorithm centered on identifying and exploiting correlations inherent within entangled states, aiming to significantly reduce computational burden compared to classical approaches. The core mechanism involves meticulously constructing and manipulating quantum states to maximize the fidelity of correlations, ultimately leading to improved data compression rates. The study will detail the algorithm's design, potential challenges, and preliminary results demonstrating enhanced compression capabilities.

DOI: 10.5281/zenodo.22246727

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