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arXiv:2203.11332 · Physica Scripta

Information loss and run time from practical application of quantum data compression

Saahil Patel, Benjamin Collis, William Duong, Daniel Koch, Massimiliano Cutugno, Laura Wessing, Paul M. Alsing

Published Mar 15, 2023• 7 citations
arXivHTMLPDF

Abstract

Abstract We examine information loss, resource costs, and run time from practical application of quantum data compression. Compressing quantum data to fewer qubits enables efficient use of resources, as well as applications for quantum communication and denoising. In this context, we provide a description of the quantum and classical components of the hybrid quantum autoencoder algorithm, implemented using IBMs Qiskit language. Utilizing our own data sets, we encode bitmap images as quantum superposition states, which correspond to linearly independent vectors with density matrices of discrete values. We successfully compress this data with near-lossless compression using simulation, and then run our algorithm on an IBMQ quantum chip. We describe conditions and run times for training and compressing our data on quantum devices, and relate trainability to specific characteristics and performance metrics of our parametric quantum circuits.

DOI
10.1088/1402-4896/acc492

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Designing a quantum data compression circuit with reasonable error using autoencoders can be time-consuming. Previous studies have explored qubit compression using specially designed circuits or autoencoders, with some attempts to apply it to small 16-bit black-and-white images using four qubits. However, analysis regarding the errors using general data is not discussed enough. This paper proposes a practical technique to optimize quantum compression for general data comprising hundreds of thousands of classical data points. We introduce Quantum State Error to investigate the potential for improving accuracy through qubit selection using degree reduction in quantum compression. By doing so, imperfect quantum autoencoder circuits may exhibit enhanced performance, offering improved lossy compression capabilities. Our experiments show promising results, where certain kind of circuits responds well to degree reduction by a factor of 3/4, reducing the number of faulty qubits up to 11.44%.