Title: Adaptive Information Bottleneck for Quantum Data Compression

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum data compression presents a significant challenge due to the inherent fragility of quantum states and the difficulty in representing them efficiently. Traditional methods often struggle with the exponential growth of state space, requiring substantial computational resources. This paper proposes an Adaptive Information Bottleneck (AIB) technique for quantum data compression, leveraging the information bottleneck principle to achieve efficient compression while safeguarding essential quantum information. The AIB framework dynamically adjusts the bottleneck size based on the state's characteristics, optimizing compression ratios and minimizing information loss. We present a novel implementation of the bottleneck-based compression algorithm, demonstrating its efficacy through simulations and initial experimental results on a small-scale quantum state. The paper explores the potential of AIB to address the limitations of existing quantum data compression methods and opens avenues for further research into quantum information processing.

DOI: 10.5281/zenodo.22472347

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