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Comparative analysis of quantum emulation for high-performance computing centers

JA Bravo-Montes et al.

SIMULATION: Transactions of The Society for Modeling and Simulation International2026https://doi.org/10.1177/00375497261430860article
AJG 1
Weight
0.50

What the paper says

Quantum computing in the NISQ era requires advanced emulation tools to facilitate the development and validation of complex quantum algorithms, as current quantum devices remain too noisy and resource-limited. This work presents a comprehensive review of quantum emulation software available for HPC centers using various comparison metrics to evaluate parallelization, precision, acceleration via Graphics Processing Unit (GPU), emulation with noise, among others. The comparative analysis evaluates four quantum emulation frameworks (QuEST, Qaptiva HPC, CUDA-Q, and PennyLane) across three hardware platforms with distinct characteristics: two HPC clusters (Spartan-Eviden and Joliot-Curie TGCC) and one quantum emulation appliance (Eviden Qaptiva 804). The scope of this analysis is fundamentally tied to the state-vector emulation paradigm. The experimental results of our evaluation reveal that performance depends on classical hardware configuration and circuit characteristics, that is, CUDA-Q excels in single-GPU environments, while Qaptiva HPC shows advantages in distributed multi-node configurations (both CPU and GPU).

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https://doi.org/https://doi.org/10.1177/00375497261430860

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@article{ja2026,
  title        = {{Comparative analysis of quantum emulation for high-performance computing centers}},
  author       = {JA Bravo-Montes et al.},
  journal      = {SIMULATION: Transactions of The Society for Modeling and Simulation International},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00375497261430860},
}

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Comparative analysis of quantum emulation for high-performance computing centers

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.