Measuring the capabilities of quantum computers

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

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Quantum Computing in the NISQ era and beyond

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Quantum supremacy using a programmable superconducting processor

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Improved simulation of stabilizer circuits

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Quantum computing with realistically noisy devices

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Characterizing quantum supremacy in near-term devices

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Randomized benchmarking of quantum gates

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Quantum computational supremacy

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Quantum Theory of Electrical Transport Phenomena

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

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Scalable and Robust Randomized Benchmarking of Quantum Processes

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Validating quantum computers using randomized model circuits

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Exact and approximate unitary 2-designs and their application to fidelity estimation

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Efficient Z gates for quantum computing

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Noise tailoring for scalable quantum computation via randomized compiling

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Benchmarking an 11-qubit quantum computer

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Experimental comparison of two quantum computing architectures

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Scalable noise estimation with random unitary operators

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Characterizing quantum gates via randomized benchmarking

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A blueprint for demonstrating quantum supremacy with superconducting qubits

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Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography

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Evenly distributed unitaries: On the structure of unitary designs

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Characterization of Addressability by Simultaneous Randomized Benchmarking

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Symmetrized Characterization of Noisy Quantum Processes

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Characterizing large-scale quantum computers via cycle benchmarking

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Efficient learning of quantum noise

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Detecting crosstalk errors in quantum information processors

Sarovar, M., Proctor, T. J., Rudinger, K., Young, K., Nielsen, E., & Blume-Kohout, R. (2020) · Quantum · doi:10.22331/q-2020-09-11-321 · Cited by 249 · see citing works

Quantum chemistry as a benchmark for near-term quantum computers

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Ultrahigh Error Threshold for Surface Codes with Biased Noise

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Testing Statistical Hypotheses

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Quantum gate teleportation between separated qubits in a trapped-ion processor

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Three-Qubit Randomized Benchmarking

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Efficient Estimation of Pauli Channels

Flammia, S. T., & Wallman, J. J. (2020) · ACM Transactions on Quantum Computing · doi:10.1145/3408039 · Cited by 140 · see citing works

Full-stack, real-system quantum computer studies: architectural comparisons and design insights

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Comparing Experiments to the Fault-Tolerance Threshold

Kueng, R., Long, D. M., Doherty, A. C., & Flammia, S. T. (2016) · Physical Review Letters · doi:10.1103/physrevlett.117.170502 · Cited by 128 · see citing works

Quantum operation time reversal

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What Randomized Benchmarking Actually Measures

Proctor, T. J., Rudinger, K., Young, K. C., Sarovar, M., & Blume-Kohout, R. (2017) · Physical Review Letters · doi:10.1103/physrevlett.119.130502 · Cited by 124 · see citing works

Fault-Tolerant Thresholds for the Surface Code in Excess of 5% Under Biased Noise

Tuckett, D. K., Bartlett, S. D., Flammia, S. T., & Brown, B. J. (2020) · Physical Review Letters · doi:10.1103/physrevlett.124.130501 · Cited by 118 · see citing works

Direct Randomized Benchmarking for Multiqubit Devices

Proctor, T. J., Carignan-Dugas, A., Rudinger, K., Nielsen, E., Blume-Kohout, R., & Young, K. (2019) · Physical Review Letters · doi:10.1103/physrevlett.123.030503 · Cited by 118 · see citing works

Randomized benchmarking with gate-dependent noise

Wallman, J. J. (2018) · Quantum · doi:10.22331/q-2018-01-29-47 · Cited by 104 · see citing works

Detecting and tracking drift in quantum information processors

Proctor, T. J., Revelle, M., Nielsen, E., Rudinger, K., Lobser, D., Maunz, P., Blume-Kohout, R., & Young, K. C. (2020) · Nature Communications · doi:10.1038/s41467-020-19074-4 · Cited by 100 · see citing works

A volumetric framework for quantum computer benchmarks

Blume-Kohout, R., & Young, K. C. (2020) · Quantum · doi:10.22331/q-2020-11-15-362 · Cited by 98 · see citing works

Benchmarking gate-based quantum computers

Michielsen, K., Nocon, M., Willsch, D., Jin, F., Lippert, T., & De Raedt, H. (2017) · Computer Physics Communications · doi:10.1016/j.cpc.2017.06.011 · Cited by 82 · see citing works

Performance of quantum error correction with coherent errors

Huang, E., Doherty, A. C., & Flammia, S. T. (2019) · Physical Review A · doi:10.1103/physreva.99.022313 · Cited by 76 · see citing works

Probing quantum processor performance with pyGSTi

Nielsen, E., Rudinger, K., Proctor, T. J., Russo, A., Young, K. C., & Blume-Kohout, R. (2020) · Quantum Science and Technology · doi:10.1088/2058-9565/ab8aa4 · Cited by 76 · see citing works

Probing Context-Dependent Errors in Quantum Processors

Rudinger, K., Proctor, T. J., Langharst, D., Sarovar, M., Young, K. C., & Blume-Kohout, R. (2019) · Physical Review X · doi:10.1103/physrevx.9.021045 · Cited by 69 · see citing works

Experimental quantum verification in the presence of temporally correlated noise

Mavadia, S., Edmunds, C., Hempel, C., Ball, H., Roy, F., Stace, T. M., & Biercuk, M. J. (2018) · npj Quantum Information · doi:10.1038/s41534-017-0052-0 · Cited by 57 · see citing works

Shorter gate sequences for quantum computing by mixing unitaries

Campbell, E. T. (2017) · Physical Review A · doi:10.1103/physreva.95.042306 · Cited by 53 · see citing works

Bounding the average gate fidelity of composite channels using the unitarity

Carignan-Dugas, A., Wallman, J. J., & Emerson, J. (2019) · New Journal of Physics · doi:10.1088/1367-2630/ab1800 · Cited by 44 · see citing works

Randomized Benchmarking as Convolution: Fourier Analysis of Gate Dependent Errors

Merkel, S., Pritchett, E., & Fong, B. H. (2021) · Quantum · doi:10.22331/q-2021-11-16-581 · Cited by 38 · see citing works

Accrediting outputs of noisy intermediate-scale quantum computing devices

Ferracin, S., Kapourniotis, T., & Datta, A. (2019) · New Journal of Physics · doi:10.1088/1367-2630/ab4fd6 · Cited by 37 · see citing works

Controlling error orientation to improve quantum algorithm success rates

Murphy, D. C., & Brown, K. R. (2019) · Physical Review A · doi:10.1103/physreva.99.032318 · Cited by 25 · see citing works

pyGSTi: Version 0.9.1

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Measuring the Capabilities of Quantum Computers

Proctor, T. J., Rudinger, K., Nielsen, E., Young, K. C., & Blume-Kohout, R. (2021) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · doi:10.5281/zenodo.5197499 · Cited by 12 · see citing works

Detecting, tracking, and eliminating drift in quantum information processorsPreprint

Proctor, T. J., Revelle, M., Nielsen, E., Rudinger, K., Lobser, D., Maunz, P., Blume-Kohout, R., & Young, K. C. (2019) · arXiv (Cornell University) · Cited by 8 · see citing works

A Race-Track Trapped-Ion Quantum Processor

Moses, S. A., Baldwin, C. H., Allman, M. S., Ancona, R., Ascarrunz, L., Barnes, C., Bartolotta, J., Bjork, B., Blanchard, P., Bohn, M., et al. (2023) · Physical Review X · doi:10.1103/physrevx.13.041052 · Cited by 391 · see citing works

Application-Oriented Performance Benchmarks for Quantum Computing

Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C. H., Mayer, K., & Proctor, T. J. (2023) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2023.3253761 · Cited by 184 · see citing works

Benchmarking a trapped-ion quantum computer with 30 qubits

Chen, J.-S., Nielsen, E., Ebert, M., Inlek, V., Wright, K., Chaplin, V., Maksymov, A., Páez, E., Poudel, A., Maunz, P., et al. (2024) · Quantum · doi:10.22331/q-2024-11-07-1516 · Cited by 103 · see citing works

Near-term quantum computing techniques: Variational quantum algorithms, error mitigation, circuit compilation, benchmarking and classical simulation

Huang, H.-L., Xu, X., Guo, C., Tian, G., Wei, S.-J., Sun, X., Bao, W., & Long, G. (2023) · Science China Physics Mechanics and Astronomy · doi:10.1007/s11433-022-2057-y · Cited by 101 · see citing works

Quantum Volume in Practice: What Users Can Expect From NISQ Devices

Pelofske, E., Bärtschi, A., & Eidenbenz, S. (2022) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2022.3184764 · Cited by 74 · see citing works

Benchmarking quantum computers

Proctor, T. J., Young, K. C., Baczewski, A., & Blume-Kohout, R. (2025) · Nature Reviews Physics · doi:10.1038/s42254-024-00796-z · Cited by 78 · see citing works

Scalable Randomized Benchmarking of Quantum Computers Using Mirror Circuits

Proctor, T., Seritan, S., Rudinger, K., Nielsen, E., Blume-Kohout, R., & Young, K. (2022) · Physical Review Letters · doi:10.1103/physrevlett.129.150502 · Cited by 68 · see citing works

Density-Matrix Renormalization Group Algorithm for Simulating Quantum Circuits with a Finite Fidelity

Ayral, T., Louvet, T., Zhou, Y., Lambert, C., Stoudenmire, E. M., & Waintal, X. (2023) · PRX Quantum · doi:10.1103/prxquantum.4.020304 · Cited by 66 · see citing works

Benchmarking Quantum Coprocessors in an Application-Centric, Hardware-Agnostic, and Scalable Way

Martiel, S., Ayral, T., & Allouche, C. (2021) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2021.3090207 · Cited by 60 · see citing works

Benchmarking highly entangled states on a 60-atom analogue quantum simulator

Shaw, A. L., Chen, Z., Choi, J., Mark, D. K., Scholl, P., Finkelstein, R., Elben, A., Choi, S., & Endres, M. (2024) · Nature · doi:10.1038/s41586-024-07173-x · Cited by 64 · see citing works

Suppressing Quantum Circuit Errors Due to System Variability

Nation, P. D., & Treinish, M. (2023) · PRX Quantum · doi:10.1103/prxquantum.4.010327 · Cited by 56 · see citing works

Quantum‐Classical Hybrid Genetic Evolutionary Algorithm for Topology Optimization of Continuum Structures

Wang, Z., & Wang, X. (2025) · International Journal for Numerical Methods in Engineering · doi:10.1002/nme.70073 · Cited by 56 · see citing works

Re-examining the quantum volume test: Ideal distributions, compiler optimizations, confidence intervals, and scalable resource estimations

Baldwin, C. H., Mayer, K., Brown, N. C., Ryan-Anderson, C., & Hayes, D. (2022) · Quantum · doi:10.22331/q-2022-05-09-707 · Cited by 54 · see citing works

Verifiable Blind Quantum Computing with Trapped Ions and Single Photons

Drmota, P., Nadlinger, D. P., Main, D., Nichol, B. C., Ainley, E. M., Leichtle, D., Mantri, A., Kashefi, E., Srinivas, R., Araneda, G., et al. (2024) · Physical Review Letters · doi:10.1103/physrevlett.132.150604 · Cited by 51 · see citing works

Error-Robust Quantum Logic Optimization Using a Cloud Quantum Computer Interface

Carvalho, A. R. R., Ball, H., Biercuk, M. J., Hush, M., & Thomsen, F. (2021) · Physical Review Applied · doi:10.1103/physrevapplied.15.064054 · Cited by 51 · see citing works

Quantum Fourier Transform Using Dynamic Circuits

Bäumer, E., Tripathi, V., Seif, A., Lidar, D. A., & Wang, D. S. (2024) · Physical Review Letters · doi:10.1103/physrevlett.133.150602 · Cited by 49 · see citing works

A Taxonomy of Small Markovian Errors

Blume-Kohout, R., Silva, M. P. D., Nielsen, E., Proctor, T. J., Rudinger, K., Sarovar, M., & Young, K. (2022) · PRX Quantum · doi:10.1103/prxquantum.3.020335 · Cited by 46 · see citing works

Computational Power of Random Quantum Circuits in Arbitrary Geometries

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Experimental Benchmarking of an Automated Deterministic Error-Suppression Workflow for Quantum Algorithms

Mundada, P., Barbosa, A., Maity, S., Wang, Y., Merkh, T., Stace, T. M., Nielson, F. F., Carvalho, A. R. R., Hush, M., Biercuk, M. J., et al. (2023) · Physical Review Applied · doi:10.1103/physrevapplied.20.024034 · Cited by 41 · see citing works

Urban quantum leap: A comprehensive review and analysis of quantum technologies for smart cities

Bonab, A. B., Fedele, M., Formisano, V., & Rudko, I. (2023) · Cities · doi:10.1016/j.cities.2023.104459 · Cited by 47 · see citing works

Quantum utility – definition and assessment of a practical quantum advantage

Herrmann, N., Arya, D., Doherty, M. W., Mingare, A., Pillay, J. C., Preis, F., & Prestel, S. (2023) · IEEE International Conference on Quantum Software (QSW) · doi:10.1109/qsw59989.2023.00028 · Cited by 42 · see citing works

Optimized SWAP networks with equivalent circuit averaging for QAOA

Hashim, A., Rines, R., Omole, V., Naik, R., Kreikebaum, J. M., Santiago, D., Chong, F. T., Siddiqi, I. A., & Gokhale, P. (2022) · Physical Review Research · doi:10.1103/physrevresearch.4.033028 · Cited by 38 · see citing works

Variational Quantum Pulse Learning

Liang, Z., Wang, H., Cheng, J., Ding, Y., Ren, H., Gao, Z., Hu, Z., Boning, D. S., Qian, X., Han, S., et al. (2022) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce53715.2022.00078 · Cited by 36 · see citing works

Protecting expressive circuits with a quantum error detection code

Self, C. N., Benedetti, M., & Amaro, D. (2024) · Nature Physics · doi:10.1038/s41567-023-02282-2 · Cited by 31 · see citing works

Learning Correlated Noise in a 39-Qubit Quantum Processor

Harper, R., & Flammia, S. T. (2023) · PRX Quantum · doi:10.1103/prxquantum.4.040311 · Cited by 27 · see citing works

Practical Introduction to Benchmarking and Characterization of Quantum Computers

Hashim, A., Nguyen, L. B., Goss, N., Marinelli, B., Naik, R., Chistolini, T., Hines, J., Marceaux, J. P., Kim, Y., Gokhale, P., et al. (2025) · PRX Quantum · doi:10.1103/prxquantum.6.030202 · Cited by 34 · see citing works

Accelerating quantum computer developments

Alberts, G., Rol, M. A., Last, T., Broer, B. W., Bultink, C. C., Rijlaarsdam, M. S. C., & Hauwermeiren, A. E. V. (2021) · EPJ Quantum Technology · doi:10.1140/epjqt/s40507-021-00107-w · Cited by 28 · see citing works

HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware

Sawaya, N. P. D., Marti-Dafcik, D., Ho, Y., Tabor, D. P., Bernal, D. E., Magann, A. B., Premaratne, S., Dubey, P. K., Matsuura, A. Y., Bishop, N. C., et al. (2024) · Quantum · doi:10.22331/q-2024-12-11-1559 · Cited by 26 · see citing works

SoK: Benchmarking the Performance of a Quantum Computer

Wang, J., Guo, G., & Shan, Z. (2022) · Entropy · doi:10.3390/e24101467 · Cited by 25 · see citing works

Impact of time-correlated noise on zero-noise extrapolation

Schultz, K., LaRose, R., Mari, A., Quiroz, G., Shammah, N., Clader, B. D., & Zeng, W. J. (2022) · Physical Review A · doi:10.1103/physreva.106.052406 · Cited by 25 · see citing works

Rapid solution of logical equivalence problems by quantum computation algorithm

Zidan, M., Hegazy, S. F., Abdel‐Aty, M., & Obayya, S. S. A. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.109844 · Cited by 25 · see citing works

A quantum hamiltonian simulation benchmark

Dong, Y., Whaley, K. B., & Lin, L. (2022) · npj Quantum Information · doi:10.1038/s41534-022-00636-x · Cited by 26 · see citing works

Quantum circuit fidelity estimation using machine learning

Vadali, A., Kshirsagar, R., Shyamsundar, P., & Perdue, G. (2023) · Quantum Machine Intelligence · doi:10.1007/s42484-023-00121-4 · Cited by 24 · see citing works

Demonstrating Scalable Randomized Benchmarking of Universal Gate Sets

Hines, J., Lu, M., Naik, R., Hashim, A., Ville, J.-L., Mitchell, B., Kreikebaum, J. M., Santiago, D., Seritan, S., Nielsen, E., et al. (2023) · Physical Review X · doi:10.1103/physrevx.13.041030 · Cited by 25 · see citing works

Scaling of energy and power in a large quantum battery-charger model

Gao, L., Cheng, C., He, W., Mondaini, R., Guan, X.-W., & Lin, H. (2022) · Physical Review Research · doi:10.1103/physrevresearch.4.043150 · Cited by 22 · see citing works

Testing Platform-Independent Quantum Error Mitigation on Noisy Quantum Computers

Russo, V., Mari, A., Shammah, N., LaRose, R., & Zeng, W. J. (2023) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2023.3305232 · Cited by 24 · see citing works

Quantum algorithms for scientific computing

Au-Yeung, R., Camino, B., Rathore, O., & Kendon, V. M. (2024) · Reports on Progress in Physics · doi:10.1088/1361-6633/ad85f0 · Cited by 25 · see citing works

Algorithmic QUBO formulations for k -SAT and hamiltonian cycles

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Realizing symmetry-protected topological phases in a spin-1/2 chain with next-nearest-neighbor hopping on superconducting qubits

Tan, A. T. K., Sun, S.-N., Tazhigulov, R. N., Chan, G. K., & Minnich, A. J. (2023) · Physical Review A · doi:10.1103/physreva.107.032614 · Cited by 21 · see citing works

Learning how to dynamically decouple by optimizing rotational gates

Rahman, A., Egger, D. J., & Arenz, C. (2024) · Physical Review Applied · doi:10.1103/physrevapplied.22.054074 · Cited by 18 · see citing works

In complexity we trust: A systematic literature review of urban quantum technologies

Bonab, A. B., Fedele, M., Formisano, V., & Rudko, I. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122642 · Cited by 17 · see citing works

Fair Sampling Error Analysis on NISQ Devices

Golden, J. K., Bärtschi, A., O’Malley, D., & Eidenbenz, S. (2022) · ACM Transactions on Quantum Computing · doi:10.1145/3510857 · Cited by 17 · see citing works

Volumetric Benchmarking of Error Mitigation with Qermit

Cîrstoiu, C., Dilkes, S., Mills, D., Sivarajah, S., & Duncan, R. (2023) · Quantum · doi:10.22331/q-2023-07-13-1059 · Cited by 16 · see citing works

Benchmarking Quantum Gates and Circuits

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Benchmarking quantum logic operations relative to thresholds for fault tolerance

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Using Shor’s algorithm on near term Quantum computers: a reduced version

Rossi, M. S., Asproni, L., Caputo, D., Rossi, S., Cusinato, A., Marini, R., Agosti, A., & Magagnini, M. (2022) · Quantum Machine Intelligence · doi:10.1007/s42484-022-00072-2 · Cited by 15 · see citing works

Highly optimized quantum circuits synthesized via data-flow engines

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Error estimation in current noisy quantum computers

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Defining Best Practices for Quantum Benchmarks

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Fully Scalable Randomized Benchmarking Without Motion Reversal

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Leveraging randomized compiling for the quantum imaginary-time-evolution algorithm

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Efficient Characterization of Qudit Logical Gates with Gate Set Tomography Using an Error-Free Virtual Z Gate Model

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Quantum error reduction with deep neural network applied at the post-processing stage

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Empirical Learning of Dynamical Decoupling on Quantum Processors

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Nanoionics enabled atomic point contact construction and quantum conductance effects

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An accurate and efficient analytic model of fidelity under depolarizing noise oriented to large scale quantum system design

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A 98-qubit trapped-ion quantum computer with all-to-all connectivity

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Benchmarking Quantum Generative Learning: A Study on Scalability and Noise Resilience using QUARK

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Benchmarking quantum computers: towards a standard performance evaluation approach

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Current Trends and Advances in Quantum Navigation for Maritime Applications: A Comprehensive Review

Sambataro, O., Costanzi, R., Alves, J., Caiti, A., Paglierani, P., Petroccia, R., & Munafò, A. (2025) · IEEE Journal of Oceanic Engineering · doi:10.1109/joe.2025.3538941 · Cited by 16 · see citing works

A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations

Chatterjee, A., Rappaport, S., Giri, A., Johri, S., Proctor, T. J., Neira, D. E. B., Sathe, P., & Lubinski, T. (2025) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2025.3558090 · Cited by 7 · see citing works

Dynamic Tariff Adjustment for Electric Vehicle Charging in Renewable-Rich Smart Grids: A Multi-Factor Optimization Approach to Load Balancing and Cost Efficiency

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Predictive Models from Quantum Computer Benchmarks

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Learning to rank quantum circuits for hardware-optimized performance enhancement

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Efficient flexible characterization of quantum processors with nested error models

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Towards a Quantum Benchmark Suite with Standardized KPIs

Becker, C. K., Tcholtchev, N., Gheorghe-Pop, I.-D., Bock, S., Seidel, R., & Hauswirth, M. (2022) · IEEE International Conference on Software Architecture Companion (ICSA-C) · doi:10.1109/icsa-c54293.2022.00038 · Cited by 7 · see citing works

Quantum circuit debugging and sensitivity analysis via local inversions

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Impact of Unreliable Devices on Stability of Quantum Computations

Dasgupta, S., & Humble, T. S. (2024) · ACM Transactions on Quantum Computing · doi:10.1145/3682071 · Cited by 26 · see citing works

Non-Markovian quantum gate set tomography

Li, Z., Zheng, C., Meng, F., Zeng, H., Luan, T., Zhang, Z., & Yu, X. (2024) · Quantum Science and Technology · doi:10.1088/2058-9565/ad3d80 · Cited by 6 · see citing works

Calibration and Performance Evaluation of a Superconducting Quantum Processor in an HPC Center

Deng, X., Pogorzalek, S., Vigneau, F., Yang, P., Schulz, M., & Schulz, L. B. (2024) · ISC High Performance (ISC) · doi:10.23919/isc.2024.10528924 · Cited by 6 · see citing works

Field-based formalism for calculating multiqubit exchange-coupling rates for transmon qubits

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Simulating Floquet scrambling circuits on trapped-ion quantum computers

Seki, K., Kikuchi, Y., Hayata, T., & Yunoki, S. (2025) · Physical Review Research · doi:10.1103/physrevresearch.7.023032 · Cited by 6 · see citing works

Unifying Non-Markovian Characterization with an Efficient and Self-Consistent Framework

White, G. A. L., Jurcevic, P., Hill, C. D., & Modi, K. K. (2025) · Physical Review X · doi:10.1103/physrevx.15.021047 · Cited by 6 · see citing works

Qubit Assignment Using Time Reversal

Peters, E., Shyamsundar, P., Li, A. C. Y., & Perdue, G. (2022) · PRX Quantum · doi:10.1103/prxquantum.3.040333 · Cited by 6 · see citing works

Robustness of chaotic behavior in iterated quantum protocols

Portik, A., Kálmán, O., Jex, I., & Kiss, T. (2024) · Physical Review A · doi:10.1103/physreva.109.042410 · Cited by 5 · see citing works

Measuring error rates of mid-circuit measurements

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QuAS: Quantum Application Score for Benchmarking the Utility of Quantum Computers

Mesman, K. J., van der Schoot, W., Möller, M., & Neumann, N. M. P. (2024) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce60285.2024.00111 · Cited by 5 · see citing works

Antenna Array Analysis Through Universal Quantum Computing Processors—A Study on Noise Modeling and Impact

Tosi, L., & Rocca, P. (2023) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2023.3344878 · Cited by 5 · see citing works

Construction and volumetric benchmarking of quantum computing noise models

Weber, T., Borras, K., Jansen, K., Krücker, D., & Riebisch, M. (2024) · Physica Scripta · doi:10.1088/1402-4896/ad406c · Cited by 5 · see citing works

A Theory of Direct Randomized Benchmarking

Polloreno, A., Carignan-Dugas, A., Hines, J., Blume-Kohout, R., Young, K. C., & Proctor, T. J. (2025) · Quantum · doi:10.22331/q-2025-09-05-1848 · Cited by 8 · see citing works

AppQSim: Application-oriented benchmarks for Hamiltonian simulation on a quantum computer

Granet, E., & Dreyer, H. (2025) · Physical Review Research · doi:10.1103/qt55-7d6r · Cited by 5 · see citing works

Cross-platform comparison of arbitrary quantum processes

Zheng, C., Yu, X., & Wang, K. (2024) · npj Quantum Information · doi:10.1038/s41534-023-00797-3 · Cited by 4 · see citing works

Characterizing non-Markovian and coherent errors in quantum simulation

Prakash, A., & Madhusudhana, B. H. (2024) · Physical Review Research · doi:10.1103/physrevresearch.6.043127 · Cited by 4 · see citing works

Q‐fid: Quantum Circuit Fidelity Improvement with LSTM Networks

Mao, Y., Shresthamali, S., & Kondo, M. (2025) · Advanced Quantum Technologies · doi:10.1002/qute.202500022 · Cited by 4 · see citing works

Testing quantum computers with the protocol of quantum state matching

Ortega, A., Kálmán, O., & Kiss, T. (2023) · Physica Scripta · doi:10.1088/1402-4896/acb2ff · Cited by 4 · see citing works

Perturbative analysis of quasiperiodic patterning of transmon quantum computers: Enhancement of many-body localization

Varvelis, E., & Divincenzo, D. P. (2024) · Physical review. B./Physical review. B · doi:10.1103/physrevb.109.144201 · Cited by 4 · see citing works

Simulating sparse SYK model with a randomized algorithm on a trapped-ion quantum computer

Granet, E., Kikuchi, Y., Dreyer, H., & Rinaldi, E. (2026) · npj Quantum Information · doi:10.1038/s41534-026-01206-1 · Cited by 3 · see citing works

Joint encryption and error correction for secure quantum communication

Jha, N., Parakh, A., & Subramaniam, M. (2024) · Scientific Reports · doi:10.1038/s41598-024-75212-8 · Cited by 3 · see citing works

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 3 · see citing works

Cyber Security in the Post Quantum Computer Era: Threats and Perspectives

Iqbal, M. S., Sajid, A., & Malik, R. (2025) · Information systems engineering and management · doi:10.1007/978-3-031-81481-5_2 · Cited by 3 · see citing works

Analysis on noise impact in algorithm-based quantum computing benchmark

Wang, J., Zhang, M., Lai, J., Zhao, W., & Zhang, H. (2022) · International Conference on Optical Communications and Networks (ICOCN) · doi:10.1109/icocn55511.2022.9901092 · Cited by 3 · see citing works

A Practical Framework for Assessing the Performance of Observable Estimation in Quantum Simulation

Niu, S., Kökcü, E., Johri, S., Ramesh, A., Chatterjee, A., Neira, D. E. B., Camps, D., & Lubinski, T. (2025) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce65121.2025.00050 · Cited by 2 · see citing works

Magic states in the asymmetric quantum Rabi model

Campos-Uscanga, A., Rodríguez, E. B., Martínez, E. P., & Bastarrachea-Magnani, M. A. (2025) · Physical Review A · doi:10.1103/qmw5-2wbf · Cited by 2 · see citing works

Distributing Quantum Computations, Shot-Wise

Bisicchia, G., Clemente, G., García-Alonso, J. M., Murillo, J. M., D’Elia, M., & Antonio Brogi, A. (2025) · Future Internet · doi:10.3390/fi17110507 · Cited by 2 · see citing works

Scalable Programming Workflows for Validation of Quantum Computers

Nguyen, T., Oftelie, L. B., Lyakh, D. I., Lotshaw, P. C., McCaskey, A., Bennink, R. S., Leyton‐Ortega, V., Pooser, R. C., Humble, T. S., & de Jong, W. A. (2021) · IEEE/ACM International Workshop on Quantum Computing Software (QCS) · doi:10.1109/qcs54837.2021.00013 · Cited by 2 · see citing works

Qubit Condensation for Assessing Efficacy of Molecular Simulation on Quantum Computers

Sager-Smith, L. M., Smart, S. E., & Mazziotti, D. A. (2023) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.3c02583 · Cited by 2 · see citing works

A Testing Pipeline for Quantum Computing Applications

Becker, C. K., Gheorghe-Pop, I.-D., & Tcholtchev, N. (2023) · IEEE International Conference on Quantum Software (QSW) · doi:10.1109/qsw59989.2023.00016 · Cited by 2 · see citing works

A user-centric quantum benchmarking test suite and evaluation framework

Liu, W., Wang, F., Lin, H., & Shang, J. (2023) · Quantum Information Processing · doi:10.1007/s11128-023-04154-3 · Cited by 2 · see citing works

Quantum Gates for Electronics Engineers

Borgarino, M., & Badiali, A. (2023) · Electronics · doi:10.3390/electronics12224664 · Cited by 2 · see citing works

Learning a Quantum Computer's Capability

Hothem, D., Young, K. C., Catanach, T., & Proctor, T. J. (2024) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2024.3430215 · Cited by 5 · see citing works

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 3 · see citing works

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 · see citing works

Measuring progress towards useful quantum computation using precision benchmarks

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