QuantoTrace: quantum error correction as a service for robust quantum computing

Hasan, MM, Rahman, MM, Ali, MM and Machado, P ORCID: https://orcid.org/0000-0003-1760-3871, 2024. QuantoTrace: quantum error correction as a service for robust quantum computing. In: Proceedings: 6th International Conference on Electrical Engineering and Information and Communication Technology (ICEEICT). IEEE, pp. 616-621. ISBN 9798350385779

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Abstract

Quantum computing, despite its vast potential, is impeded by challenges like decoding and system noise, necessitating effective quantum error correction techniques. Our study investigates these techniques, focusing on their practical application. We introduce QuantoTrace, a cloud-based platform offering Error Correction as a Service (ECaaS). It enhances quantum system reliability by detecting, analysing, and rectifying errors, and implements bit-flip error correction compatible with various quantum technologies. Using 3-qubit and 5-qubit models, we demonstrated its efficacy on quantum simulators and IBM quantum hardware. Remarkably, we achieved 100% error correction accuracy on simulators and significant success rates on IBM hardware: 68.95% for error correction and 86.04% for error detection in 5-qubit systems. However, the Quantum Repetition Code (QRC) showed limitations in handling multiple-qubit errors in 5-qubit systems. These findings highlight the potential of QuantoTrace which is based on Software as a Service principles in enhancing quantum computing reliability towards further research needs in quantum error correction, especially for noisy intermediate-scale quantum (NISQ) devices. QuantoTrace aims to simplify quantum error management, making it accessible to a broad user base and facilitating optimized quantum computing strategies.

Item Type:	Chapter in book
Description:	Paper presented at 6th International Conference on Electrical Engineering and Information and Communication Technology (ICEEICT), Dhaka, Bangladesh, 2-4 May 2024
Creators:	Hasan, M.M., Rahman, M.M., Ali, M.M. and Machado, P.
Publisher:	IEEE
Date:	23 May 2024
ISBN:	9798350385779
Identifiers:	Number Type 10.1109/iceeict62016.2024.10534391 DOI 1898075 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Jeremy Silvester
Date Added:	31 May 2024 15:25
Last Modified:	31 May 2024 15:25
URI:	https://irep.ntu.ac.uk/id/eprint/51505

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