Abstract
While quantum computing has shown great promise in the field of computer science, a lack of actual practical quantum hardware means that mainstream research must rely on simulations. As such, a wide number of quantum computing simulation libraries have been developed, each with their own strengths and weaknesses. A good simulator must not just be accurate, but fast as well. This is especially relevant for quantum systems since the problem size growth for quantum systems is super-exponential. For this paper, we introduce a quantum computing simulation system that takes advantage of multiple gpus to achieve up to 400 times faster simulation time. We discuss the implementation details and provide analysis of its performance. We also demonstrate how the real-world phenomenon of quantum gate incoherence can be accurately simulated by varying the floating point precision and demonstrate it by using a precision of 9 bits, which we evaluate using Randomized Benchmarking.
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Acknowledgments
This material is based in part upon work supported by the National Science Foundation under grant number IIA- 1301726. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Zawad, S., Yan, F., Wu, R., Barford, L., Harris, F.C. (2019). Randomized Benchmarking of Quantum Gates on a GPU. In: Latifi, S. (eds) 16th International Conference on Information Technology-New Generations (ITNG 2019). Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-030-14070-0_42
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DOI: https://doi.org/10.1007/978-3-030-14070-0_42
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