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).
HermanDGooginCLiuX, et al. Quantum computing for finance. Nature Rev Phys2023; 5: 450–465.
7.
Ur RasoolRAhmadHFRafiqueW, et al. Quantum computing for healthcare: a review. Future Intern2023; 15: 94.
8.
TennieFPalmerTN. Quantum computers for weather and climate prediction: the good, the bad, and the noisy. Bullet Am Meteorol Soc2023; 104: E488–E500.
9.
AkhaiSKumarV. Quantum resilience and distributed trust: the promise of blockchain and quantum computing in defense. In: KumarAAhujaNJKaushikK, et al. (eds) Sustainable security practices using blockchain, quantum and post-quantum technologies for real time applications. New York: Springer, pp. 125–153.
10.
WaringJBPereCLe BeuxS. Noise aware utility optimization of NISQ devices. In: 2024 22nd IEEE Interregional NEWCAS Conference (NEWCAS), Sherbrooke, QC, 16–19 June 2024, pp. 168–172. New York: IEEE.
11.
YaminiBNithyanandhanRSudhaK, et al. Maximizing the revolutionary potential of quantum computing: challenges, opportunities, and future directions. In: 2024 10th international conference on communication and signal processing (ICCSP), Melmaruvathur, India, 12–14 April 2024, pp. 756–761. New York: IEEE.
Sanchez-RamirezSConejeroJLordanF, et al. RosneT: a block tensor algebra library for out-of-core quantum computing simulation. In: 2021 IEEE/ACM Second international workshop on quantum computing software (QCS), St. Louis, MO, 15 November 2021. New York: IEEE.
Huawei HiQ team. Huawei HiQ: a high-performance quantum computing simulator and programming framework, 2019, https://hiq.huaweicloud.com (accessed 10 July 2025).
30.
NguyenDMikushinDMan-HongY. HiQ-ProjectQ: towards user-friendly and high-performance quantum computing on GPUs. In: 2021 design, automation & test in Europe conference & exhibition (DATE), Grenoble, 1–5 February 2021, pp. 1056–1061.
31.
SteigerDSHänerTTroyerM. ProjectQ: an open source software framework for quantum computing. Quantum2018; 2: 49.
32.
DoiJHoriiH. Cache blocking technique to large scale quantum computing simulation on supercomputers. In: 2020 IEEE international conference on quantum computing and engineering (QCE), Denver, CO, 12–16 October 2020, pp. 212–222. New York: IEEE.
FiQCI. Breaking new ground: simulating quantum algorithms up to 44 Qubits on LUMI—FiQCI, 2025, https://fiqci.fi/publications/ 2025-04-01-LUMI-quantum-simulations-qiskit-aer (accessed 22 July 2025).
GuerreschiGGHogaboamJBaruffaF, et al. Intel quantum simulator: a cloud-ready high-performance simulator of quantum circuits. Quantum Sci Tech2020; 5: 034007.
37.
BayraktarHChararaAClarkD, et al. cuQuantum SDK: a high-performance library for accelerating quantum science. arXiv preprint, arxiv:2308.01999, 2023.
38.
LiAKrishnamoorthyS. SV-Sim: scalable PGAS-based state vector simulation of quantum circuits. In: Proceedings of the international conference for high performance computing, networking, storage and analysis, St. Louis, MO, 14–19 November 2021.
39.
SuhISLiA. Simulating quantum systems with NWQ-Sim on HPC. arXiv preprint, arxiv:2401.06861, 2024.
Bravo-MontesJBastanteMBotellaG, et al. A methodology to select and adjust quantum noise models through emulators: benchmarking against real backends. EPJ Quantum Technol2024; 11: 71.
FarhiEGoldstoneJGutmannS. A quantum approximate optimization algorithm. arXiv preprint, arxiv:1411.4028, 2014.
78.
WilleRBerentLForsterT, et al. The MQT handbook: a summary of design automation tools and software for quantum computing. In: IEEE International Conference on Quantum Software (QSW), Shenzhen, China, 7–13 July.
