Adaptive Quantum Field Mapping for Data Compression

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper investigates the potential of Adaptive Quantum Field Mapping (AQFM) as a novel approach to data compression, leveraging quantum entanglement to create a dynamic and adaptable representation of data. Traditional compression methods often struggle with data redundancy, leading to irreversible loss of information. AQFM proposes a system that utilizes quantum entanglement to generate a 'fuzzy' data representation, enabling the detection of subtle redundancies and facilitating lossless compression. This research explores the theoretical underpinnings of the system, discusses potential challenges and optimizations, and outlines a preliminary design for implementation. The core claim posits that AQFM represents a significant advancement in data compression, offering the prospect of lossless data storage and transmission.

DOI: 10.5281/zenodo.22635375

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