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arXiv · 2203.13892

Accelerating Simulation of Quantum Circuits under Noise via Computational Reuse

Meng Wang·Swamit Tannu·Prashant J. Nair
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Abstract

To realize the full potential of quantum computers, we must mitigate qubit errors by developing noise-aware algorithms, compilers, and architectures. Thus, simulating quantum programs on high-performance computing (HPC) systems with different noise models is a de facto tool researchers use. Unfortunately, noisy simulators iteratively execute a similar circuit for thousands of trials, thereby incurring significant performance overheads. To address this, we propose a noisy simulation technique called Tree-Based Quantum Circuit Simulation (TQSim). TQSim exploits the reusability of intermediate results during the noisy simulation, reducing computation. TQSim dynamically partitions a circuit into several subcircuits. It then reuses the intermediate results from these subcircuits during computation. Compared to a noisy Qulacs-based baseline simulator, TQSim achieves a speedup of up to 3.89x for noisy simulations. TQSim is designed to be efficient with multi-node setups while also maintaining tight fidelity bounds.

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Meng Wang, Swamit Tannu, Prashant J. Nair. 2022-03-25. Accelerating Simulation of Quantum Circuits under Noise via Computational Reuse. https://doi.org/10.1145/3695053.3730992

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