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    Quantum computing (QC) is rapidly advancing with new tools and platforms. This article explores visualization challenges and opportunities for practical QC applications.

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    Area of Science:

    • Computer Science
    • Information Visualization
    • Quantum Information Science

    Background:

    • Quantum computing (QC) is experiencing significant growth.
    • Advancements include programming environments, simulators, and cloud-based hardware.
    • There is increasing interest in developing practical QC applications.

    Purpose of the Study:

    • Examine research challenges and opportunities in QC visualization.
    • Bridge the gap between QC feasibility and practical problem-solving.
    • Provide a visualization perspective on the QC development path.

    Main Methods:

    • Literature review of QC and visualization research.
    • Analysis of current QC platforms and their visualization needs.
    • Identification of key visualization challenges and potential solutions.

    Main Results:

    • Current visualization tools are often inadequate for complex QC data.
    • Opportunities exist in developing interactive and scalable visualization techniques.
    • Effective visualization is crucial for understanding QC algorithms and results.

    Conclusions:

    • Addressing visualization challenges is key to unlocking QC's practical potential.
    • Further research is needed in areas like quantum data representation and interaction.
    • Collaboration between QC and visualization experts is essential for progress.