Measuring the capabilities of quantum computers

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482

Quantum Computing in the NISQ era and beyond

Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830

Quantum supremacy using a programmable superconducting processor

Arute, F., Arya, K., Babbush, R., Bacon, D., Bardin, J. C., Barends, R., Biswas, R., Boixo, S., Brandao, F. G. S. L., Buell, D. A., et al. (2019) · Nature · doi:10.1038/s41586-019-1666-5 · Cited by 7,720

Improved simulation of stabilizer circuits

Aaronson, S., & Gottesman, D. (2004) · Physical Review A · doi:10.1103/physreva.70.052328 · Cited by 1,515

Quantum computing with realistically noisy devices

Knill, E. (2005) · Nature · doi:10.1038/nature03350 · Cited by 1,184 · cited 4×

Characterizing quantum supremacy in near-term devices

Boixo, S., Isakov, S. V., Smelyanskiy, V. N., Babbush, R., Ding, N., Jiang, Z., Bremner, M. J., Martinis, J. M., & Neven, H. (2018) · Nature Physics · doi:10.1038/s41567-018-0124-x · Cited by 1,175

Randomized benchmarking of quantum gates

Knill, E., Leibfried, D., Reichle, R., Britton, J., Blakestad, R. B., Jost, J. D., Langer, C., Ozeri, R., Seidelin, S., & Wineland, D. J. (2008) · Physical Review A · doi:10.1103/physreva.77.012307 · Cited by 1,019

Scalable and Robust Randomized Benchmarking of Quantum Processes

Magesan, E., Gambetta, J., & Emerson, J. (2011) · Physical Review Letters · doi:10.1103/physrevlett.106.180504 · Cited by 797

Quantum Theory of Electrical Transport Phenomena

Kohn, W., & Luttinger, J. M. (1957) · Physical Review · doi:10.1103/physrev.108.590 · Cited by 793

A simple formula for the average gate fidelity of a quantum dynamical operation

Nielsen, M. A. (2002) · Physics Letters A · doi:10.1016/s0375-9601(02)01272-0 · Cited by 725

The Significance of the Quantum Volume for Other Algorithms: A Case Study for Quantum Amplitude Estimation

de Jong, J., & Hoek, C. R. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-63778-0_16 · Cited by 1

Q-TetoFormer: A New Gene Regulatory Network Prediction Method Based on Quantum Computing and Transformer

Wang, H. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10822209 · Cited by 1

Recent progress on photon-integrated quantum key distribution and quantum random number generator

Jingchun, Y., Wen-Bin, L., Bin, C. H. E. N., Yongqiang, D., Feng, X. I. E., Wei, L. I., & Wei, K. (2025) · Acta Physica Sinica · doi:10.7498/aps.74.20250791 · Cited by 1

Prediction of the relaxation time of a transmon qubit with the steepest-entropy-ascent quantum thermodynamics framework

Rocha-Soto, L. E., Damián, C., Saldaña‐Robles, A., & Cano-Andrade, S. (2025) · Journal of Physics A Mathematical and Theoretical · doi:10.1088/1751-8121/adffcd · Cited by 1

Comparative Benchmarking of Utility-Scale Quantum Emulators

Leonteva, A. O., Masella, G., Outteryck, M., Orioli, A. P., & Whitlock, S. (2025) · ACM Transactions on Quantum Computing · doi:10.1145/3776567 · Cited by 8

QSimBench: An Execution-Level Benchmark Suite for Quantum Software Engineering

Bisicchia, G., Bocci, A., García-Alonso, J. M., Murillo, J. M., & Antonio Brogi, A. (2025) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce65121.2025.10315 · Cited by 1

Symmetry-constrained QCNN for few-shot learning with polylogarithmic generalization bounds

Guo, Z., Huang, C., Ding, W., & Ma, H. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05071-x · Cited by 1

Benchmarking quantum devices beyond classical capabilities

Bistroń, R., Rudziński, M., Kukulski, R., & Życzkowski, K. (2026) · Physical Review A · doi:10.1103/dsjj-stkn · Cited by 2

VQA-Classification-Algorithm-Oriented Performance Benchmarks for Quantum Computing

Zhang, M., Wang, J., Yao, F., & Lai, J. (2023) · International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) · doi:10.1109/icccbda56900.2023.10154749 · Cited by 1

Robust hybrid qubit plane architecture for enhancing lattice-surgery-based surface codes

Heng, S., Heng, S., Kim, D., & Han, Y. (2024) · Physical Review A · doi:10.1103/physreva.109.022440 · Cited by 1

Reliable confidence regions for quantum tomography using distribution moments

Norkin, D. O., Kiktenko, E. O., & Fedorov, A. K. (2024) · Physical Review A · doi:10.1103/physreva.109.032414 · Cited by 1

Heuristic-free verification-inspired quantum benchmarking

Frank, J., Kashefi, E., Leichtle, D., & de Oliveira, M. (2025) · Quantum Science and Technology · doi:10.1088/2058-9565/adc298 · Cited by 1

A Systematic Review of Quantum BenchMarking

Malhotra, P., Kumar, A., & Garhwal, S. (2024) · International Journal of Theoretical Physics · doi:10.1007/s10773-024-05811-8 · Cited by 1

End-to-End Quantum Algorithms for the Jones Polynomial

Laakkonen, T., Rinaldi, E., Self, C. N., Chertkov, E., DeCross, M. P., Hayes, D., Neyenhuis, B., Benedetti, M., & Meichanetzidis, K. (2026) · PRX Quantum · doi:10.1103/jgv8-l3j1 · Cited by 2

Measuring Correlated Qubit Errors on Quantum ComputersPreprint

Schales, P. (2021) · Research Square · doi:10.21203/rs.3.rs-1035320/v1 · Cited by 1

Gate set tomography is not just hyperaccurate, it’s a different way of thinking

White, G. A. L. (2021) · doi:10.22331/qv-2021-10-05-60

Simplifying errors by symmetry and randomisationPreprint

Mills, J. K., Sadhukhan, D., & Kashefi, E. (2023) · HAL · doi:10.48550/arxiv.2303.02712 · Cited by 2

Demystifying Quantum Computing: A Holistic Non-Technical Overview of the NISQ Paradigm and its Opportunities and ObstaclesPreprint

Shah, A., & Pachisia, T. (2023) · doi:10.36227/techrxiv.24186825

Demystifying Quantum Computing: A Holistic Non-Technical Overview of the NISQ Paradigm and its Opportunities and ObstaclesPreprint

Shah, A., & Pachisia, T. (2023) · doi:10.36227/techrxiv.24186825.v1

Mitigating Coupling Map Constrained Correlated Measurement Errors on Quantum Devices

Robertson, A., & Song, S. L. (2023) · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1145/3581784.3607039

Benchmarking PQC Ansatze in Realistic Device Topologies

Hryniv, O., Los, V., Pryyma, Y., Iouchtchenko, D., Koch-Janusz, M., & Maksymenko, M. (2024) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce60285.2024.10245

A Quantum Computing Benchmark Based on Circuit Features

Liu, X., Proctor, T. J., Green, A., & Linke, N. M. (2025) · Quantum 2.0 Conference and Exhibition · doi:10.1364/quantum.2025.qw2a.2

Benchmarking fault-tolerant quantum computing hardware via QLOPS

Kong, L., Zhang, F., & Chen, J. (2026) · ACM Transactions on Quantum Computing · doi:10.1145/3797968

Multi-GPU quantum circuit simulation and the impact of network performance

Brown, W. M., Ramesh, A., Lubinski, T., Nguyen, T., & Neira, D. E. B. (2026) · Computer Physics Communications · doi:10.1016/j.cpc.2026.110126

Average-computation benchmarking for local expectation values in digital quantum devices

Baccari, F., Kos, P., & Styliaris, G. (2026) · Physical Review Research · doi:10.1103/zn6p-c8w2 · Cited by 2

Not All Qubits are Utilized Equally

Pope, J., & Ghosh, S. (2025) · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) · doi:10.1109/tps-isa67132.2025.00069

Systematic Characterization of Transmon Qubit Stability with Thermal Cycling

Li, C., Yang, Z., Zhang, X., Wu, Z., Xue, S., & Deng, M. (2026) · Entropy · doi:10.3390/e28030296

From Noise Modeling to Layout Optimization: A Framework for Quantum Circuit Fidelity Enhancement With Machine Learning

Du, Q., Xu, J., Jin, Y., Wang, W., Tu, Z., Liu, Y., Lian, H., Zhu, Y., & Shan, Z. (2026) · Advanced Quantum Technologies · doi:10.1002/qute.202500464

Circuit compilation and error mitigation for near-term quantum computing

Niu, S. (2022) · theses.fr (ABES) · doi:10.70675/4b9fc4d0z9683z4a8dz8643zc514443d2d75

What quantum computer to buy?

Krasnok, A. (2026) · AVS Quantum Science · doi:10.1116/5.0337237

Security and Efficiency of Delegated Quantum Computing

Leichtle, D. (2024) · theses.fr (ABES) · doi:10.70675/8a5d99d6z5531z465azb548z08e329a929c0

Far‐Field Readout of Coherent Plasmonic Coupling in Au Nanoisland Arrays

Sadeghi, S. M., Roberts, D. T., & Kercher, A. (2026) · Advanced Optical Materials · doi:10.1002/adom.202503801

A Low-Cost Diagnostic Framework for NISQ Noise Regimes Using the K–R Scaling Exponent on IBM Quantum HardwarePreprint

Pasupuleti, R. R. (2026) · Research Square · doi:10.21203/rs.3.rs-9443307/v1

Topology-aware block coordinate descent for qubit frequency allocation of superconducting quantum processors

Zhao, Z., Zhuang, W., Gu, Y., 钱, P. 鹏. Q., Xiao, X., & Dong, L. (2026) · Quantum Science and Technology · doi:10.1088/2058-9565/ae6fe6

NISQ in practice: navigating noise, scale, and hardware constraints of near-term devices in quantum machine learning workflows

Daka, C., & Bhattacharyya, S. (2026) · New Journal of Physics · doi:10.1088/1367-2630/ae8053 · Cited by 1

Performance evaluation of variational quantum eigensolver and quantum dynamics algorithms on the advection-diffusion equation

Özgüler, A. B. (2026) · Physical review. E · doi:10.1103/mr76-1wtz · Cited by 2

Generative Adversarial Networks for Quantum Data Simulation and Experiment Planning

Gangabathula, N. V., Chaganti, K. R., Chittipothu, S., Gutta, P. K., Mashetty, P. C., & Chaganti, S. R. (2025) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac65734.2025.11597599

Toward a Quantum Diagnostic Intelligence System: A Multi-Layer Architecture for Circuit-Level Assessment of Quantum Hardware Operational StatePreprint

Pasupuleti, R. (2026) · Research Square · doi:10.21203/rs.3.rs-10394388/v1

Circuit-Level vs Pulse-Level Quantum Hardware Diagnostics: K–R Scaling Exponent Detects Device Degradation Invisible to T₁/T₂ CalibrationPreprint

Pasupuleti, R. (2026) · Research Square · doi:10.21203/rs.3.rs-10394517/v1

Per-gate noise vulnerability of quantum algorithms: A systematic benchmarking study across multiple error channels

Hassan, T. (2026) · APL Quantum · doi:10.1063/5.0328310

Toward a benchmark for quantum computers based on an iterated post-selective protocol

Ortega, A., Kálmán, O., & Kiss, T. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05294-y · Cited by 1

A Mathematical Theory of Correlated Error Accumulation in Quantum CircuitsPreprint

Pasupuleti, R. (2026) · Research Square · doi:10.21203/rs.3.rs-10654302/v1

After the Quantum Advantage Claim: Which Drug-Discovery Problems Are Actually Ready for Quantum Computation?

Meyer, L., Schmid, A., Braun, S., & Keller, L. (2026) · Pharmacophore · doi:10.51847/ytvqqiwlce

Emergent Effective Depth in Quantum Machine Learning: Empirical Gradient Attenuation Scaling in Noisy Variational Quantum Algorithms

Braga, C., Serrano, M. A., & Fernández-Medina, E. (2026) · 2026 IEEE International Conference on Quantum Software (QSW) · doi:10.1109/qsw72780.2026.00018

Circuit-Aware Hyperparameter Prediction for MPS Quantum Simulators

Leonteva, A. O., Outteryck, M., & Masella, G. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-36226-1_17

Volumetric Benchmarking of IQM-Spark: Parity-Preserving Quantum Volume and Compilation Overheads in Odra 5

Gnatowski, A., Rudy, J., Rudziński, M., Bistroń, R., Święcicki, K., Niżyński, T., Bożejko, W., & Życzkowski, K. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-36868-3_12

Benchmarking the computational power of quantum computersPreprint

Proctor, T. J., Hart, O., Maupin, O. G., Girling, M., Hothem, D., Mills, D., Hines, J., Mayer, K., Nelson, J. S., LeBlond, T., et al. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2609.12146

Benchmarking quantum computers

Sandia National Laboratories (SNL-NM), A., Blume-Kohout, R., Proctor, T. J., Baczewski, A., & Young, K. C. (2025) · doi:10.2172/3023929

Scalable Full-Stack Benchmarks for Quantum Computers

Hines, J., & Proctor, T. J. (2024) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2024.3404502 · Cited by 12

A Review and Collection of Metrics and Benchmarks for Quantum Computers: definitions, methodologies and software

Lall, D., Agarwal, A., Zhang, W., Lindoy, L. P., Lindström, T., Webster, S., Hall, S., Chancellor, N., Wallden, P., García−Patrón, R., et al. (2025) · doi:10.59161/azye8097 · Cited by 3

Measuring progress towards useful quantum computation using precision benchmarks

Sandia National Laboratories (SNL-CA), L., & Proctor, T. J. (2023) · doi:10.2172/3023954