Q-Embroidery: A Study on Weaving Quantum Error Correction into the Fabric of Quantum Classifiers
<|reference_start|>Q-Embroidery: A Study on Weaving Quantum Error Correction into the Fabric of Quantum Classifiers: Quantum computing holds transformative potential for various fields, yet its practical application is hindered by the susceptibility to errors. This study makes a pioneering contribution by applying quantum error correction codes (QECCs) for complex, multi-qubit classification tasks. We implement 1-qubit and 2-qubit quantum classifiers with QECCs, specifically the Steane code, and the distance 3 & 5 surface codes to analyze 2-dimensional and 4-dimensional datasets. This research uniquely evaluates the performance of these QECCs in enhancing the robustness and accuracy of quantum classifiers against various physical errors, including bit-flip, phase-flip, and depolarizing errors. The results emphasize that the effectiveness of a QECC in practical scenarios depends on various factors, including qubit availability, desired accuracy, and the specific types and levels of physical errors, rather than solely on theoretical superiority.<|reference_end|>
@article{chatterjee2024q-embroidery:,
    title={Q-Embroidery: A Study on Weaving Quantum Error Correction into the
  Fabric of Quantum Classifiers},
    author={Avimita Chatterjee, Debarshi Kundu and Swaroop Ghosh},
    journal={arXiv preprint arXiv:2402.11127},
    year={2024},
    doi={10.1145/3649476.3658750},
    archivePrefix={arXiv},
    eprint={2402.11127},
    primaryClass={quant-ph cs.ET}
}