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Full-stack, real-system quantum computer studies: architectural comparisons and design insights
Open accessAbstract
In recent years, Quantum Computing (QC) has progressed to the point where small working prototypes are available for use. Termed Noisy Intermediate-Scale Quantum (NISQ) computers, these prototypes are too small for large benchmarks or even for Quantum Error Correction (QEC), but they do have sufficient resources to run small benchmarks, particularly if compiled with optimizations to make use of scarce qubits and limited operation counts and coherence times. QC has not yet, however, settled on a particular preferred device implementation technology, and indeed different NISQ prototypes implement qubits with very different physical approaches and therefore widely-varying device and machine characteristics.
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“These multi-controlled operations are not natively supported by most available NISQ devices [201], limiting the practical applicability of approaches relying on this concept.”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [201]
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Cites
Quantum Computing in the NISQ era and beyond
Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830
A fast quantum mechanical algorithm for database search
Grover, L. K. (1996) · Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96 · doi:10.1145/237814.237866 · Cited by 8,830
Fault-tolerant quantum computation by anyons
Kitaev, A. Y. (2003) · Annals of Physics · doi:10.1016/s0003-4916(02)00018-0 · Cited by 7,238
Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., & Lloyd, S. (2017) · Nature · doi:10.1038/nature23474 · Cited by 4,779
A variational eigenvalue solver on a photonic quantum processor
Peruzzo, A., McClean, J., Shadbolt, P., Yung, M.-H., Zhou, X.-Q., Love, P. J., Aspuru-Guzik, A., & O’Brien, J. L. (2014) · Nature Communications · doi:10.1038/ncomms5213 · Cited by 4,552 · cited 1×
“Quantum computing (QC) is emerging as a promising paradigm for solving classically intractable computational problems in areas such as machine learning [4, 39], cryptography [60], chemistry [32, 50] and others.”
BackgroundPolynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer
Shor, P. W. (1999) · SIAM Review · doi:10.1137/s0036144598347011 · Cited by 3,904
Quantum Computations with Cold Trapped Ions
Cirac, J. I., & Zoller, P. (1995) · Physical Review Letters · doi:10.1103/physrevlett.74.4091 · Cited by 3,733
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Kandala, A., Mezzacapo, A., Temme, K., Takita, M., Brink, M., Chow, J. M., & Gambetta, J. M. (2017) · Nature · doi:10.1038/nature23879 · Cited by 2,982
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2011) · Cited by 2,724
Introduction to Algorithms, third edition
Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009) · Cited by 2,309
Flagged first, then by citations
Research works printed but not linked: 7
- 10.5555/1792734.1792766 · DOI
- IBM. 2018. IBM Announces Advances to IBM Quantum Systems and Ecosystem. https://www-03.ibm.com/press/us/en/pressrelease/53374.wss. Accessed: 2018-08-05.
- 10.5555/977395.977673 · DOI
- 10.5555/1296197 · DOI
- 10.5555/1972505 · DOI
- Robert S. Smith, Michael J. Curtis, and William J. Zeng. 2016. A Practical Quantum Instruction Set Architecture. arXiv:1608.03355 · arXiv
- 10.5555/94938.94976 · DOI
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Liu, W., Wang, F., Lin, H., & Shang, J. (2023) · Quantum Information Processing · doi:10.1007/s11128-023-04154-3 · Cited by 2
EQUAL: Improving the Fidelity of Quantum Annealers by Injecting Controlled PerturbationsPreprint
Ayanzadeh, R., Das, P., Tannu, S., & Qureshi, M. K. (2022) · Research Square · doi:10.21203/rs.3.rs-1343360/v1 · Cited by 5
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Jiang, H., Deng, Y., & Xu, M. Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.05214 · Cited by 6
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Basili, R., Qian, W., Sarker, S., Tang, S., Castellino, A., Eshaghian‐Wilner, M. M., Khokhar, A., Luecke, G. R., & Vary, J. P. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07819-1 · Cited by 1
Directions for enhancing quantum resilience of blockchain platforms and ecosystems
Petrenko, S., Petrenko, A., Kazak, A., Makoveichuk, K. A., & Oleinikov, N. (2026) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2026.100390 · Cited by 1
Mechanizing Quantum Error Correction Through Entangled Quantum Machine Learning Techniques
Melvin, T. (2023) · IntechOpen eBooks · doi:10.5772/intechopen.1002876 · Cited by 1
A Pattern Matching Based Framework for Quantum Circuit Rewriting
Jiang, H., Li, D.-K., Deng, Y., & Xu, M. Q. (2024) · Journal of Computer Science and Technology · doi:10.1007/s11390-024-2726-3 · Cited by 2
Coreset Clustering on Small Quantum Computers
Tomesh, T., Gokhale, P., Anschuetz, E. R., & Chong, F. T. (2021) · Electronics · doi:10.3390/electronics10141690 · Cited by 27
Muñoz‐Coreas, E. (2020) · UKnowledge (University of Kentucky) · doi:10.13023/etd.2020.365 · Cited by 1
Learning Based Hardware-Centric Quantum Circuit Generation
Schalkers, M. A., & Möller, M. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-06668-9_22 · Cited by 1
Graphical Calculi and their Conjecture SynthesisPreprint
Miller-Bakewell, H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.03914 · Cited by 1
Дорофєєва, Т. (2022) · Financial and credit activity problems of theory and practice · doi:10.18371/fcaptp.v6i41.251474
Layout Synthesis for Near-Term Quantum Computing: Gap Analysis and Optimal Solution
Tan, D. B., & Cong, J. (2022) · Springer eBooks · doi:10.1007/978-3-031-15699-1_2
QC-Stack: A Layered Reference Model for Quantum Computers
Bhatia, A., Bitragunta, S., & Tiwari, K. (2024) · International Conference on Communication Systems & Networks (COMSNETS) · doi:10.1109/comsnets59351.2024.10427378
Noise-Aware Compilation Techniques for Enhanced Fault-Tolerant Preparation of Polar Code States
Kurniawan, H., Savin, V., Almudéver, C. G., & García-Herrero, F. (2024) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce60285.2024.10325
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Zhao, Y., Chen, Y., Chang, K., Li, H., Li, B., Han, Y., & Wang, Y. (2026) · ACM Transactions on Architecture and Code Optimization · doi:10.1145/3845611 · Cited by 1
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Cho, J., Jeong, H., Kim, J., Choi, J., Hong, J., & Kim, J. (2026) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/3779212.3790122
Layer model for gate-based modular quantum computers
van den Brink, R. F. M., Boschero, J. C., & Amoretti, M. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05119-y
The resource cost of large scale quantum computing
Fellous-Asiani, M. (2021) · theses.fr (ABES) · doi:10.70675/d1a944bez79cez43e1zaefcz785bf1e97f74 · Cited by 9
Circuit compilation and error mitigation for near-term quantum computing
Niu, S. (2022) · theses.fr (ABES) · doi:10.70675/4b9fc4d0z9683z4a8dz8643zc514443d2d75
Crosstalk-robust dynamical decoupling for bipartite-topology quantum processors
Hickman, E., Wu, X., & Quiroz, G. (2026) · Physical Review Applied · doi:10.1103/r75m-b2d9 · Cited by 1
Q-ST: A Comprehensive Review of Quantum Software and Toolchains, Ecosystems, and Technologies
Hassan, S., & Giri, K. J. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10615-6
Wang, Q., Zhukas, L. A., Miao, Q., Dalvi, A. S., Love, P. J., Monroe, C., Chong, F. T., & Ravi, G. S. (2026) · npj Unconventional Computing · doi:10.1038/s44335-026-00073-5
QCLink: Offloading Hybrid Quantum-Classical Computation to SmartNICs via RDMA
Li, X., Lu, Y., Liu, Z., Yue, X.-F., Chen, J., Peng, Y., Li, T.-T., Li, Z.-X., Zhao, Z.-M., & Yin, J. (2026) · IEEE International Conference on Distributed Computing Systems · doi:10.1109/2575-8411.2026.00013
Joseph, A., & Delhibabu, R. (2026) · Frontiers in Computer Science · doi:10.3389/fcomp.2026.1879744
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Sun, M., Jia, F., Yang, Y., & Zhou, Y. (2026) · Proceedings of the ACM on Programming Languages · doi:10.1145/3839537
Agyemang, J. O., Kponyo, J. J., Amponsah, E., Boakye, G. M. A., Agyekum, K. A.-P., & Agyare, M. (2026) · Quantum Engineering · doi:10.1155/que2/3380225
Metadata
- Authors
- Murali, P., Linke, N. M., Martonosi, M., Abhari, A. J., Nguyen, N. H., & Alderete, C. H.
- Affiliations
- Princeton University (US)
- University of Maryland, College Park (US)
- IBM T. J. Watson Research Center
- ORCID
- Venue
- Proceedings of the 46th International Symposium on Computer Architecture
- Publisher
- ACM
- Published
- 2019-06-22
- Pages
- 527-540
- ISSN
- 1063-6897 (ISSN-L)
- OpenAlex
- W2950036696
- Cited by
- 128
- References
- 57
- Citations by year
- 2026: 11 · 2025: 5 · 2024: 11 · 2023: 16 · 2022: 29 · 2021: 25 · 2020: 27 · 2019: 4
- FWCI
- 8.13
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings - International Symposium on Computer Architecture/Proceedings (publishedVersion)
- Funders
- National Science Foundation (1730449)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Keywords
- quantum computing, NISQ devices, quantum error correction, quantum benchmarking, quantum circuit compilation, coherence time
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