Challenges and Opportunities of Near-Term Quantum Computing Systems
Open accessAbstract
The concept of quantum computing has inspired a whole new generation of scientists, including physicists, engineers, and computer scientists, to fundamentally change the landscape of information technology. With experimental demonstrations stretching back more than two decades, the quantum computing community has achieved a major milestone over the past few years: the ability to build systems that are stretching the limits of what can be classically simulated, and which enable cloud-based research for a wide range of scientists, thus increasing the pool of talent exploring early quantum systems. While such noisy near-term quantum computing systems fall far short of the requirements for fault-tolerant systems, they provide unique test beds for exploring the opportunities for quantum applications. Here, we highlight an IBM-specific perspective of the facets associated with these systems, including quantum software, cloud access, benchmarking quantum systems, error correction and mitigation in such systems, understanding the complexity of quantum circuits, and how early quantum applications can run on near-term quantum computers.
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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 · see citing works
Algorithms for quantum computation: discrete logarithms and factoring
Shor, P. W. (2002) · Proceedings 35th Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1994.365700 · Cited by 8,713 · see citing works
Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer
Shor, P. W. (1997) · SIAM Journal on Computing · doi:10.1137/s0097539795293172 · Cited by 8,472 · see citing works
Quantum cryptography: Public key distribution and coin tossing
Bennett, C. H., & Brassard, G. (2014) · Theoretical Computer Science · doi:10.1016/j.tcs.2014.05.025 · Cited by 8,299 · see citing works
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 · see citing works
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 · see citing works
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 2× · see citing works
“Examples for such quantum - classical hybrid schemes are variational algorithms for quantum many-body systems [37], [108], [109] and machine learning [36].”
BackgroundScheme for reducing decoherence in quantum computer memory
Shor, P. W. (1995) · Physical Review A · doi:10.1103/physreva.52.r2493 · Cited by 4,479 · see citing works
Quantum Mechanics Helps in Searching for a Needle in a Haystack
Grover, L. K. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.325 · Cited by 4,306 · see citing works
Degen, C. L., Reinhard, F., & Cappellaro, P. (2017) · Reviews of Modern Physics · doi:10.1103/revmodphys.89.035002 · Cited by 4,045 · see citing works
Ladd, T. D., Jelezko, F., Laflamme, R., Nakamura, Y., Monroe, C., & O’Brien, J. L. (2010) · Nature · doi:10.1038/nature08812 · Cited by 3,592 · see citing works
Charge-insensitive qubit design derived from the Cooper pair box
Koch, J., Yu, T. M., Gambetta, J., Houck, A. A., Schuster, D. I., Majer, J., Blais, A., Devoret, M. H., Girvin, S. M., & Schoelkopf, R. J. (2007) · Physical Review A · doi:10.1103/physreva.76.042319 · Cited by 3,351 · see citing works
Self-citationSurface codes: Towards practical large-scale quantum computation
Fowler, A. G., Mariantoni, M., Martinis, J. M., & Cleland, A. N. (2012) · Physical Review A · doi:10.1103/physreva.86.032324 · Cited by 3,059 · cited 1× · see citing works
“These simulations, together with assumptions about what is experimentally feasible, provide estimates of what would ultimately be required to operate various quantum algorithms using fully fault-tolerant computation [16]–[19].”
BackgroundBlais, A., Huang, R.-S., Wallraff, A., Girvin, S. M., & Schoelkopf, R. J. (2004) · Physical Review A · doi:10.1103/physreva.69.062320 · Cited by 2,989 · see citing works
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 · see citing works
Self-citationSupervised learning with quantum-enhanced feature spaces
Havlíček, V., Córcoles, A. D., Temme, K., Harrow, A. W., Kandala, A., Chow, J. M., & Gambetta, J. M. (2019) · Nature · doi:10.1038/s41586-019-0980-2 · Cited by 2,572 · see citing works
Self-citationGisin, N., & Thew, R. (2007) · Nature Photonics · doi:10.1038/nphoton.2007.22 · Cited by 2,149 · see citing works
Superconducting Circuits for Quantum Information: An Outlook
Devoret, M., & Schoelkopf, R. J. (2013) · Science · doi:10.1126/science.1231930 · Cited by 2,122 · see citing works
A quantum engineer's guide to superconducting qubits
Krantz, P., Kjærgaard, M., Yan, F., Orlando, T. P., Gustavsson, S., & Oliver, W. D. (2019) · Applied Physics Reviews · doi:10.1063/1.5089550 · Cited by 2,056 · see citing works
Khaneja, N., Reiss, T., Kehlet, C., Schulte-Herbrüggen, T., & Glaser, S. J. (2005) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2004.11.004 · Cited by 1,854 · see citing works
Quantum Machine Learning in Feature Hilbert Spaces
Schuld, M., & Killoran, N. (2019) · Physical Review Letters · doi:10.1103/physrevlett.122.040504 · Cited by 1,840 · see citing works
Dynamical Decoupling of Open Quantum Systems
Viola, L., Knill, E., & Lloyd, S. (1999) · Physical Review Letters · doi:10.1103/physrevlett.82.2417 · Cited by 1,808 · see citing works
Dennis, E., Kitaev, A., Landahl, A., & Preskill, J. (2002) · Journal of Mathematical Physics · doi:10.1063/1.1499754 · Cited by 1,768 · see citing works
Improved simulation of stabilizer circuits
Aaronson, S., & Gottesman, D. (2004) · Physical Review A · doi:10.1103/physreva.70.052328 · Cited by 1,515 · see citing works
Qiskit: An Open-source Framework for Quantum Computing
Aleksandrowicz, G., Alexander, T., Barkoutsos, P. K., Bello, L., Ben-Haim, Y., Bucher, D., Cabrera-Hernández, F. J., Carballo-Franquis, J., Chen, A., Chen, C.-F., et al. (2019) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.2562110 · Cited by 1,454 · see citing works
Self-citationRichardson, L. F. (1911) · Philosophical Transactions of the Royal Society of London Series A Containing Papers of a Mathematical or Physical Character · doi:10.1098/rsta.1911.0009 · Cited by 1,451 · see citing works
Error Mitigation for Short-Depth Quantum Circuits
Temme, K., Bravyi, S., & Gambetta, J. M. (2017) · Physical Review Letters · doi:10.1103/physrevlett.119.180509 · Cited by 1,379 · see citing works
Self-citationQuantum error correction for quantum memories
Terhal, B. M. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.307 · Cited by 1,354 · see citing works
Qiskit: An Open-source Framework for Quantum Computing
Aleksandrowicz, G., Alexander, T., Barkoutsos, P. K., et al. (2019) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.2562111 · Cited by 1,314 · see citing works
Bernstein, D. J., & Lange, T. (2017) · Nature · doi:10.1038/nature23461 · Cited by 1,242 · see citing works
Wilde, M. M. (2013) · doi:10.1017/cbo9781139525343 · Cited by 1,138 · see citing works
Scalable Quantum Simulation of Molecular Energies
O’Malley, P. J. J., Babbush, R., Kivlichan, I. D., Romero, J., McClean, J. R., Barends, R., Kelly, J., Roushan, P., Tranter, A., Ding, N., et al. (2016) · Physical Review X · doi:10.1103/physrevx.6.031007 · Cited by 1,059 · see citing works
Quantum information processing with superconducting circuits: a review
Wendin, G. P. (2017) · Reports on Progress in Physics · doi:10.1088/1361-6633/aa7e1a · Cited by 970 · see citing works
Fault-tolerant quantum computation
Shor, P. W. (2002) · Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1996.548464 · Cited by 943 · see citing works
Error mitigation extends the computational reach of a noisy quantum processor
Kandala, A., Temme, K., Corcoles, A. D., Mezzacapo, A., Chow, J. M., & Gambetta, J. (2019) · Nature · doi:10.1038/s41586-019-1040-7 · Cited by 870 · see citing works
Self-citationHow to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits
Gidney, C., & Ekerå, M. (2021) · Quantum · doi:10.22331/q-2021-04-15-433 · Cited by 830 · see citing works
Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz
Romero, J., Babbush, R., McClean, J. R., Hempel, C., Love, P. J., & Aspuru-Guzik, A. (2019) · Quantum Science and Technology · doi:10.1088/2058-9565/aad3e4 · Cited by 726 · see citing works
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 715 · see citing works
Self-citationValidating quantum computers using randomized model circuits
Cross, A. W., Bishop, L. S., Sheldon, S., Nation, P. D., & Gambetta, J. M. (2019) · Physical Review A · doi:10.1103/physreva.100.032328 · Cited by 704 · see citing works
Self-citationThe Solovay-Kitaev algorithmPreprint
Dawson, C., & Nielsen, M. (2005) · Quantum information & computation · doi:10.48550/arxiv.quant-ph/0505030 · Cited by 694 · see citing works
Efficient Variational Quantum Simulator Incorporating Active Error Minimization
Li, Y., & Benjamin, S. C. (2017) · Physical Review X · doi:10.1103/physrevx.7.021050 · Cited by 686 · see citing works
Synthesis of quantum-logic circuits
Shende, V., Bullock, S. S., & Markov, I. L. (2006) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2005.855930 · Cited by 682 · see citing works
Fault-tolerant quantum computation with constant error
Aharonov, D., & Ben-Or, M. (1997) · Proceedings of the twenty-ninth annual ACM symposium on Theory of computing - STOC '97 · doi:10.1145/258533.258579 · Cited by 631 · see citing works
Building logical qubits in a superconducting quantum computing system
Gambetta, J., Chow, J. M., & Steffen, M. (2017) · npj Quantum Information · doi:10.1038/s41534-016-0004-0 · Cited by 628 · see citing works
Self-citationQuantum Chemistry Calculations on a Trapped-Ion Quantum Simulator
Hempel, C., Maier, C., Romero, J., McClean, J., Monz, T., Shen, H., Jurcevic, P., Lanyon, B. P., Love, P., Babbush, R., et al. (2018) · Physical Review X · doi:10.1103/physrevx.8.031022 · Cited by 597 · see citing works
Roads towards fault-tolerant universal quantum computation
Campbell, E. T., Terhal, B. M., & Vuillot, C. (2017) · Nature · doi:10.1038/nature23460 · Cited by 596 · see citing works
Maintaining coherence in quantum computers
Unruh, W. G. (1995) · Physical Review A · doi:10.1103/physreva.51.992 · Cited by 594 · see citing works
Efficient Z gates for quantum computing
McKay, D. C., Wood, C. J., Sheldon, S., Chow, J. M., & Gambetta, J. (2017) · Physical Review A · doi:10.1103/physreva.96.022330 · Cited by 551 · see citing works
Self-citationA Meet-in-the-Middle Algorithm for Fast Synthesis of Depth-Optimal Quantum Circuits
Amy, M., Maslov, D., Mosca, M., & Roetteler, M. (2013) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2013.2244643 · Cited by 549 · cited 1× · see citing works
“For example, high-level program routines, such as an abstract unitary evolution, must first be synthesized into a quantum circuit [61]–[64].”
BackgroundHow to enhance dephasing time in superconducting qubits
Cywiński, Ł., Lutchyn, R. M., Nave, C. P., & Sarma, S. D. (2008) · Physical Review B · doi:10.1103/physrevb.77.174509 · Cited by 542 · see citing works
Noise tailoring for scalable quantum computation via randomized compiling
Wallman, J. J., & Emerson, J. (2016) · Physical Review A · doi:10.1103/physreva.94.052325 · Cited by 535 · see citing works
FAULT-TOLERANT QUANTUM COMPUTATION
Preskill, J. P. (1998) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789812385253_0008 · Cited by 525 · see citing works
Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states
McClean, J. R., Kimchi-Schwartz, M. E., Carter, J., & de Jong, W. A. (2017) · Physical Review A · doi:10.1103/physreva.95.042308 · Cited by 516 · see citing works
Corcoles, A. D., Magesan, E., Srinivasan, S. J., Cross, A. W., Steffen, M., Gambetta, J., & Chow, J. M. (2015) · Nature Communications · doi:10.1038/ncomms7979 · Cited by 477 · see citing works
Self-citationProcedure for systematically tuning up cross-talk in the cross-resonance gate
Sheldon, S., Magesan, E., Chow, J. M., & Gambetta, J. (2016) · Physical Review A · doi:10.1103/physreva.93.060302 · Cited by 476 · see citing works
Self-citationComputation of Molecular Spectra on a Quantum Processor with an Error-Resilient Algorithm
Colless, J. I., Ramasesh, V. V., Dahlen, D., Blok, M. S., Kimchi-Schwartz, M. E., McClean, J. R., Carter, J., de Jong, W. A., & Siddiqi, I. (2018) · Physical Review X · doi:10.1103/physrevx.8.011021 · Cited by 460 · see citing works
Optimal quantum circuits for general two-qubit gates
Vatan, F., & Williams, C. (2004) · Physical Review A · doi:10.1103/physreva.69.032315 · Cited by 443 · see citing works
ProjectQ: An open source software framework for quantum computing
Steiger, D. S., Häner, T., & Troyer, M. (2018) · Quantum · doi:10.22331/q-2018-01-31-49 · Cited by 428 · see citing works
Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers
Murali, P., Baker, J. M., Javadi-Abhari, A., Chong, F. T., & Martonosi, M. (2019) · Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems · doi:10.1145/3297858.3304075 · Cited by 411 · see citing works
Self-citationA Game of Surface Codes: Large-Scale Quantum Computing with Lattice Surgery
Litinski, D. (2019) · Quantum · doi:10.22331/q-2019-03-05-128 · Cited by 408 · see citing works
Quantum advantage with shallow circuits
Bravyi, S. B., Gosset, D., & König, R. (2018) · Science · doi:10.1126/science.aar3106 · Cited by 406 · see citing works
Simulating quantum systems on a quantum computer
Zalka, C. (1998) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.1998.0162 · Cited by 387 · see citing works
A quantum-inspired classical algorithm for recommendation systems
Tang, E. (2019) · Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing · doi:10.1145/3313276.3316310 · Cited by 360 · see citing works
Rigetti, C. T., & Devoret, M. (2010) · Physical Review B · doi:10.1103/physrevb.81.134507 · Cited by 357 · see citing works
Improved Classical Simulation of Quantum Circuits Dominated by Clifford Gates
Bravyi, S. B., & Gosset, D. (2016) · Physical Review Letters · doi:10.1103/physrevlett.116.250501 · Cited by 324 · see citing works
Fast reset and suppressing spontaneous emission of a superconducting qubit
Reed, M. D., Johnson, B. R., Houck, A., DiCarlo, L., Chow, J. M., Schuster, D., Frunzio, L., & Schoelkopf, R. J. (2010) · Applied Physics Letters · doi:10.1063/1.3435463 · Cited by 314 · see citing works
Computational complexity of projected entangled pair states
Schuch, N., Wolf, M. M., Verstraete, F., & Cirac, J. I. (2007) · Physical Review Letters · doi:10.1103/physrevlett.98.140506 · Cited by 313 · see citing works
Open Quantum Assembly Language
Cross, A. W., Bishop, L. S., Smolin, J. A., & Gambetta, J. M. (2017) · arXiv · doi:10.48550/arxiv.1707.03429 · Cited by 310 · see citing works
Self-citationSimulation of quantum circuits by low-rank stabilizer decompositions
Bravyi, S., Browne, D., Calpin, P., Campbell, E., Gosset, D., & Howard, M. (2019) · Quantum · doi:10.22331/q-2019-09-02-181 · Cited by 302 · see citing works
Average-Case Complexity Versus Approximate Simulation of Commuting Quantum Computations
Bremner, M. J., Montanaro, A., & Shepherd, D. J. (2016) · Physical Review Letters · doi:10.1103/physrevlett.117.080501 · Cited by 299 · see citing works
Quantum implementation of the unitary coupled cluster for simulating molecular electronic structure
Shen, Y., Zhang, X., Zhang, S., Zhang, J.-N., Yung, M., & Kim, K. (2017) · Physical Review A · doi:10.1103/physreva.95.020501 · Cited by 288 · see citing works
Dawson, C. M., & Nielsen, M. A. (2006) · Quantum Information and Computation · doi:10.26421/qic6.1-6 · Cited by 288 · see citing works
Polynomial-Time T-Depth Optimization of Clifford+T Circuits Via Matroid Partitioning
Amy, M., Maslov, D. A., & Mosca, M. (2014) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2014.2341953 · Cited by 269 · see citing works
Characterizing large-scale quantum computers via cycle benchmarking
Erhard, A., Wallman, J. J., Postler, L., Meth, M., Stricker, R., Martinez, E. A., Schindler, P., Monz, T., Emerson, J., & Blatt, R. (2019) · Nature Communications · doi:10.1038/s41467-019-13068-7 · Cited by 254 · see citing works
Siraichi, M. Y., Santos, V. F. D., Collange, C., & Pereira, F. M. Q. (2018) · Proceedings of the 2018 International Symposium on Code Generation and Optimization · doi:10.1145/3168822 · Cited by 254 · see citing works
Low-cost error mitigation by symmetry verification
Bonet-Monroig, X., Sagastizabal, R., Singh, M., & O'Brien, T. E. (2018) · Physical Review A · doi:10.1103/physreva.98.062339 · Cited by 250 · see citing works
Quantum Circuit Simplification and Level Compaction
Maslov, D. A., Dueck, G. W., Miller, D. M., & Negrevergne, C. (2008) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2007.911334 · Cited by 248 · see citing works
Error-Mitigated Digital Quantum Simulation
McArdle, S., Yuan, X., & Benjamin, S. C. (2019) · Physical Review Letters · doi:10.1103/physrevlett.122.180501 · Cited by 238 · see citing works
Experimental Demonstration of Fault-Tolerant State Preparation with Superconducting Qubits
Takita, M., Cross, A. W., Córcoles, A. D., Chow, J. M., & Gambetta, J. M. (2017) · Physical Review Letters · doi:10.1103/physrevlett.119.180501 · Cited by 228 · see citing works
Self-citationTopological and Subsystem Codes on Low-Degree Graphs with Flag Qubits
Chamberland, C., Zhu, G., Yoder, T. J., Hertzberg, J. B., & Cross, A. W. (2020) · Physical Review X · doi:10.1103/physrevx.10.011022 · Cited by 223 · see citing works
Self-citationAutomated optimization of large quantum circuits with continuous parameters
Nam, Y., Ross, N. J., Su, Y., Childs, A. M., & Maslov, D. (2018) · npj Quantum Information · doi:10.1038/s41534-018-0072-4 · Cited by 221 · see citing works
Quantum circuits for isometries
Iten, R., Colbeck, R., Kukuljan, I., Home, J., & Christandl, M. (2016) · Physical Review A · doi:10.1103/physreva.93.032318 · Cited by 218 · see citing works
Quantum Computational Complexity
Watrous, J. (2009) · Springer eBooks · doi:10.1007/978-0-387-30440-3_428 · Cited by 208 · see citing works
Graph-theoretic Simplification of Quantum Circuits with the ZX-calculus
Duncan, R., Kissinger, A., Perdrix, S., & van de Wetering, J. (2020) · Quantum · doi:10.22331/q-2020-06-04-279 · Cited by 201 · see citing works
Demonstration of Weight-Four Parity Measurements in the Surface Code Architecture
Takita, M., Corcoles, A. D., Magesan, E., Abdo, B., Brink, M., Cross, A. W., Chow, J. M., & Gambetta, J. (2016) · Physical Review Letters · doi:10.1103/physrevlett.117.210505 · Cited by 198 · see citing works
Self-citationAchieving quantum supremacy with sparse and noisy commuting quantum computations
Bremner, M. J., Montanaro, A., & Shepherd, D. J. (2017) · Quantum · doi:10.22331/q-2017-04-25-8 · Cited by 191 · see citing works
Optimal ancilla-free Clifford+T approximation of z-rotations
Ross, N. J., & Selinger, P. (2016) · Quantum Information and Computation · doi:10.26421/qic16.11-12-1 · Cited by 178 · see citing works
Microwave-induced coupling of superconducting qubits
Paraoanu, G. S. (2006) · Physical Review B · doi:10.1103/physrevb.74.140504 · Cited by 174 · see citing works
Tapering off qubits to simulate fermionic HamiltoniansPreprint
Bravyi, S. B., Gambetta, J., Mezzacapo, A., & Temme, K. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.08213 · Cited by 172 · see citing works
Self-citationIzmaylov, A. F., Yen, T.-C., Lang, R. A., & Verteletskyi, V. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00791 · Cited by 171 · see citing works
Temporally unstructured quantum computation
Shepherd, D. J., & Bremner, M. J. (2009) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.2008.0443 · Cited by 170 · see citing works
Fault-tolerant quantum error detection
Linke, N. M., Gutiérrez, M., Landsman, K. A., Figgatt, C., Debnath, S., Brown, K. R., & Monroe, C. R. (2017) · Science Advances · doi:10.1126/sciadv.1701074 · Cited by 163 · see citing works
Quantum computation with realistic magic-state factories
O'Gorman, J., & Campbell, E. T. (2017) · Physical Review A · doi:10.1103/physreva.95.032338 · Cited by 158 · see citing works
Three-Qubit Randomized Benchmarking
McKay, D. C., Sheldon, S., Smolin, J. A., Chow, J. M., & Gambetta, J. M. (2019) · Physical Review Letters · doi:10.1103/physrevlett.122.200502 · Cited by 156 · see citing works
Self-citationQuantum Simulation of Helium Hydride Cation in a Solid-State Spin Register
Wang, Y., Dolde, F., Biamonte, J., Babbush, R., Bergholm, V., Yang, S., Jakobi, I., Neumann, P., Aspuru‐Guzik, A., Whitfield, J. D., et al. (2015) · ACS Nano · doi:10.1021/acsnano.5b01651 · Cited by 147 · see citing works
Efficient Synthesis of Universal Repeat-Until-Success Quantum Circuits
Bocharov, A., Roetteler, M., & Svore, K. M. (2015) · Physical Review Letters · doi:10.1103/physrevlett.114.080502 · Cited by 142 · see citing works
ScaffCC: Scalable compilation and analysis of quantum programs
Javadi-Abhari, A., Patil, S. R., Kudrow, D., Heckey, J., Lvov, A., Chong, F. T., & Martonosi, M. (2014) · Parallel Computing · doi:10.1016/j.parco.2014.12.001 · Cited by 142 · see citing works
Self-citationCompiling quantum circuits to realistic hardware architectures using temporal planners
Venturelli, D., Do, M., Rieffel, E. G., & Frank, J. (2017) · Quantum Science and Technology · doi:10.1088/2058-9565/aaa331 · Cited by 137 · see citing works
Polynomial time algorithms for discrete logarithms and factoring on a quantum computer
Shor, P. W. (1994) · Lecture notes in computer science · doi:10.1007/3-540-58691-1_68 · Cited by 130 · see citing works
Full-stack, real-system quantum computer studies: architectural comparisons and design insights
Murali, P., Linke, N. M., Martonosi, M., Abhari, A. J., Nguyen, N. H., & Alderete, C. H. (2019) · Proceedings of the 46th International Symposium on Computer Architecture · doi:10.1145/3307650.3322273 · Cited by 128 · see citing works
Self-citationExperimental error mitigation via symmetry verification in a variational quantum eigensolver
Sagastizabal, R., Bonet-Monroig, X., Singh, M., Rol, M. A., Bultink, C. C., Fu, X., Price, C. H., Ostroukh, V., Muthusubramanian, N., Bruno, A., et al. (2019) · Physical Review A · doi:10.1103/physreva.100.010302 · Cited by 124 · see citing works
Adaptive Quantum Computation, Constant Depth Quantum Circuits and Arthur-Merlin Games
Terhal, B. M., & Divincenzo, D. P. (2004) · Quantum Information and Computation · doi:10.26421/qic4.2-5 · Cited by 124 · see citing works
Fault-tolerant quantum computationPreprint
Preskill, J. P. (1997) · arXiv (Cornell University) · doi:10.48550/arxiv.quant-ph/9712048 · Cited by 124 · see citing works
Investigating Surface Loss Effects in Superconducting Transmon Qubits
Gambetta, J. M., Murray, C. E., Fung, Y.-K.-K., McClure, D. T., Dial, O., Shanks, W., Sleight, J. W., & Steffen, M. (2016) · IEEE Transactions on Applied Superconductivity · doi:10.1109/tasc.2016.2629670 · Cited by 122 · see citing works
Self-citation(2019) · doi:10.1145/3297858.3304018 · Cited by 118 · see citing works
Basic circuit compilation techniques for an ion-trap quantum machine
Maslov, D. A. (2017) · New Journal of Physics · doi:10.1088/1367-2630/aa5e47 · Cited by 115 · see citing works
On the controlled-NOT complexity of controlled-NOT–phase circuits
Amy, M., Azimzadeh, P., & Mosca, M. (2017) · Quantum Science and Technology · doi:10.1088/2058-9565/aad8ca · Cited by 115 · see citing works
Optimization of quantum circuit mapping using gate transformation and commutation
Itoko, T., Raymond, R., Imamichi, T., & Matsuo, A. (2019) · Integration · doi:10.1016/j.vlsi.2019.10.004 · Cited by 115 · see citing works
Maslov, D. A., Falconer, S. M., & Mosca, M. (2008) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2008.917562 · Cited by 113 · see citing works
Error-mitigated quantum gates exceeding physical fidelities in a trapped-ion system
Zhang, S., Lu, Y., Zhang, K., Chen, W., Li, Y., Zhang, J.-N., & Kim, K. (2020) · Nature Communications · doi:10.1038/s41467-020-14376-z · Cited by 110 · see citing works
Compiling SU(4) Quantum Circuits to IBM QX Architectures
Zulehner, A., & Wille, R. (2018) · Asia and South Pacific Design Automation Conference · doi:10.1145/3287624.3287704 · Cited by 108 · see citing works
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Gokhale, P., & Chong, F. T. (2019) · arXiv · doi:10.48550/arxiv.1908.11857 · Cited by 104
Qiskit Backend Specifications for OpenQASM and OpenPulse ExperimentsPreprint
McKay, D. C., Alexander, T., Bello, L., Biercuk, M. J., Bishop, L. S., Chen, J., Chow, J. M., Corcoles, A. D., Egger, D. J., Filipp, S., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.03452 · Cited by 101 · see citing works
Self-citationA 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
Circuit Transformations for Quantum ArchitecturesPreprint
Childs, A. M., Schoute, E., & Unsal, C. M. (2019) · arXiv (Cornell University) · doi:10.4230/lipics.tqc.2019.3 · Cited by 82 · see citing works
Tuckerman, D. B., Hamilton, M. C., Reilly, D. J., Bai, R., Hernandez, G. A., Hornibrook, J. M., Sellers, J. A., & Ellis, C. D. (2016) · Superconductor Science and Technology · doi:10.1088/0953-2048/29/8/084007 · Cited by 73 · see citing works
Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension
Gilyén, A., Lloyd, S., & Tang, E. (2018) · arXiv · doi:10.48550/arxiv.1811.04909 · Cited by 63 · see citing works
Optimized surface code communication in superconducting quantum computers
Javadi-Abhari, A., Gokhale, P., Holmes, A. A., Franklin, D. M., Brown, K. R., Martonosi, M., & Chong, F. T. (2017) · IEEE/ACM International Symposium on Microarchitecture (MICRO) · doi:10.1145/3123939.3123949 · Cited by 61 · see citing works
Self-citationTwo-step approach to scheduling quantum circuits
Guerreschi, G. G., & Park, J. (2018) · Quantum Science and Technology · doi:10.1088/2058-9565/aacf0b · Cited by 57 · see citing works
Generative model benchmarks for superconducting qubits
Hamilton, K. E., Dumitrescu, E. F., & Pooser, R. C. (2019) · Physical Review A · doi:10.1103/physreva.99.062323 · Cited by 57 · see citing works
Forrelation: A Problem That Optimally Separates Quantum from Classical Computing
Aaronson, S., & Ambainis, A. (2018) · SIAM Journal on Computing · doi:10.1137/15m1050902 · Cited by 55 · see citing works
Verified Compilation of Space-Efficient Reversible Circuits
Amy, M., Rötteler, M., & Svore, K. (2016) · International Conference on Computer Aided Verification · doi:10.1007/978-3-319-63390-9_1 · Cited by 54 · see citing works
Introduction to Quantum Algorithms for Physics and Chemistry
Yung, M. H., Whitfield, J. D., Boixo, S., Tempel, D. G., & Aspuru‐Guzik, A. (2014) · Advances in chemical physics · doi:10.1002/9781118742631.ch03 · Cited by 53 · see citing works
Scheduling physical operations in a quantum information processor
Metodi, T. S., Thaker, D., Cross, A. W., Chong, F. T., & Chuang, I. L. (2006) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.666419 · Cited by 51 · see citing works
Self-citationA Case for Variability-Aware Policies for NISQ-Era Quantum ComputersPreprint
Tannu, S., & Qureshi, M. K. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.10224 · Cited by 49 · see citing works
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Mehrpoo, M., Patra, B., Gong, J., van Dijk, J. P. G., Homulle, H., Kiene, G., Vladimirescu, A., Sebastiano, F., Edoardo Charbon, A., & Babaie, M. (2019) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2019.8702452 · Cited by 49 · see citing works
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Rosenberg, D., Weber, S. J., Conway, D., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.11146 · Cited by 34 · see citing works
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Peterson, E. C., Crooks, G. E., & Smith, R. S. (2020) · Quantum · doi:10.22331/q-2020-03-26-247 · Cited by 32 · see citing works
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Bouland, A., Fitzsimons, J. F., & Koh, D. E. (2017) · arXiv (Cornell University) · doi:10.4230/lipics.ccc.2018.21 · Cited by 29 · see citing works
An upper bound on the threshold quantum decoherence rate
Razborov, A. A. (2004) · CERN Document Server (European Organization for Nuclear Research) · doi:10.5555/2011617.2011624 · Cited by 25 · see citing works
Preparing topological projected entangled pair states on a quantum computer
Schwarz, M., Temme, K., Verstraete, F., Pérez-Garcı́a, D., & Cubitt, T. S. (2013) · Physical Review A · doi:10.1103/physreva.88.032321 · Cited by 24 · see citing works
Self-citationOptimal ancilla-free Clifford+T approximation of z-rotationsPreprint
Ross, N. J., & Selinger, P. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1403.2975 · Cited by 21 · see citing works
Qubit Allocation for Noisy Intermediate-Scale Quantum ComputersPreprint
Finigan, W., Cubeddu, M., Lively, T., Flick, J., & Narang, P. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1810.08291 · Cited by 17 · see citing works
Experimental verification of five-qubit quantum error correction with superconducting qubitsPreprint
Gong, M., Yuan, X., Wang, S., Wu, Y., Zhao, Y., Zha, C., Li, S., Zhang, Z., Zhao, Q., Liu, Y., et al. (2019) · arXiv (Cornell University) · Cited by 16 · see citing works
Predicting substrate resonance mode frequency shifts using conductive, through-substrate vias
Murray, C. E., & Abraham, D. W. (2016) · Applied Physics Letters · doi:10.1063/1.4942453 · Cited by 10 · see citing works
CertiQ: A Mostly-automated Verification of a Realistic Quantum CompilerPreprint
Shi, Y., Tao, R., Li, X., Javadi-Abhari, A., Cross, A. W., Chong, F. T., & Gu, R. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.08963 · Cited by 10 · see citing works
Self-citationOptimization of Quantum Circuit Mapping using Gate Transformation and CommutationPreprint
Itoko, T., Raymond, R., Imamichi, T., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.02686 · Cited by 6 · see citing works
Contract-based verification of a realistic quantum compiler.Preprint
Shi, Y., Li, X., Tao, R., Javadi-Abhari, A., Cross, A. W., Chong, F. T., & Gu, R. (2019) · arXiv (Cornell University) · Cited by 5 · see citing works
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Bardin, J. C., Jeffrey, E. R., Lucero, E. A., Huang, T., Naaman, O., Barends, R., White, T., Giustina, M., Sank, D., Roushan, P., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.10864
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Childs, A. M., Schoute, E., & Unsal, C. M. (2019) · arXiv · doi:10.48550/arxiv.1902.09102
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Duncan, R., Kissinger, A., Perdrix, S., & van de Wetering, J. (2019) · arXiv · doi:10.48550/arxiv.1902.03178
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Gidney, C., & Ekerå, M. (2019) · arXiv · doi:10.48550/arxiv.1905.09749
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Nishio, S., Pan, Y., Satoh, T., Amano, H., & Meter, R. V. (2019) · arXiv · doi:10.48550/arxiv.1903.10963
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Peterson, E. C., Crooks, G. E., & Smith, R. S. (2019) · arXiv · doi:10.48550/arxiv.1904.10541
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Blume-Kohout, R., & Young, K. C. (2019) · arXiv · doi:10.48550/arxiv.1904.05546
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Erhard, A., Wallman, J. J., Postler, L., Meth, M., Stricker, R., Martinez, E. A., Schindler, P., Monz, T., Emerson, J., & Blatt, R. (2019) · arXiv · doi:10.48550/arxiv.1902.08543
Quantum computation with universal error mitigation on superconducting quantum processor
Song, C., Cui, J., Wang, H., Hao, J., Feng, H., & Li, Y. (2018) · arXiv · doi:10.48550/arxiv.1812.10903
Error-Mitigated Quantum Gates Exceeding Physical Fidelities in a Trapped-Ion System
Zhang, S., Lu, Y., Zhang, K., Chen, W., Li, Y., Zhang, J.-N., & Kim, K. (2019) · arXiv · doi:10.48550/arxiv.1905.10135
Experimental exploration of five-qubit quantum error correcting code with superconducting qubits
Gong, M., Yuan, X., Wang, S., Wu, Y., Zhao, Y., Zha, C., Li, S., Zhang, Z., Zhao, Q., Liu, Y., et al. (2019) · arXiv · doi:10.48550/arxiv.1907.04507
Topological and subsystem codes on low-degree graphs with flag qubits
Chamberland, C., Zhu, G., Yoder, T. J., Hertzberg, J. B., & Cross, A. W. (2019) · arXiv · doi:10.48550/arxiv.1907.09528
Self-citationSimulation of quantum circuits by low-rank stabilizer decompositions
Bravyi, S., Browne, D., Calpin, P., Campbell, E., Gosset, D., & Howard, M. (2018) · arXiv · doi:10.48550/arxiv.1808.00128
Izmaylov, A. F., Yen, T.-C., Lang, R. A., & Verteletskyi, V. (2019) · arXiv · doi:10.48550/arxiv.1907.09040
Engineering cryogenic setups for 100-qubit scale superconducting circuit systems
Krinner, S., Storz, S., Kurpiers, P., Magnard, P., Heinsoo, J., Keller, R., Luetolf, J., Eichler, C., & Wallraff, A. (2018) · arXiv · doi:10.48550/arxiv.1806.07862
Flagged first, then by citations
Research works printed but not linked: 4
- M. Nielsen and I. Chuang, Quantum Computation and Quantum Information. New York, NY, USA: Cambridge Univ. Press, 2000.
- A. Kandala, K. Temme, A. D. Corcoles, A. Mezzacapo, J. M. Chow, and J. M. Gambetta, "Extending the computational reach of a noisy superconducting quantum processor," Nature, vol. 567, p. 491, May 2019.
- D. Shepherd and M. J. Bremner, "Instantaneous quantum computation," Proc. Roy. Soc., vol. 465, pp. 1413-1439, Jan. 2009.
- B. Lienhard et al., "Microwave packaging for superconducting qubits," 2005, arXiv:1906.05425. [Online]. Available: https://arxiv.org/abs/ 1906.05425 · arXiv
Cited by
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Safari, A., & Badamchizadeh, M. A. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10201-6 · Cited by 22 · see citing works
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Melo, A., Earnest, N., & Tacchino, F. (2023) · Quantum · doi:10.22331/q-2023-10-09-1130 · Cited by 21 · see citing works
PANSATZ: pulse-based ansatz for variational quantum algorithms
Meirom, D., & Frankel, S. H. (2023) · Frontiers in Quantum Science and Technology · doi:10.3389/frqst.2023.1273581 · Cited by 23 · see citing works
Semiconductor Quantum Computing: Toward a CMOS quantum computer on chip
Nikandish, G., Blokhina, E., Leipold, D. R., & Staszewski, R. B. (2021) · IEEE Nanotechnology Magazine · doi:10.1109/mnano.2021.3113216 · Cited by 24 · see citing works
Neural network decoder for near-term surface-code experiments
Varbanov, B. M., Serra-Peralta, M., Byfield, D., & Terhal, B. M. (2025) · Physical Review Research · doi:10.1103/physrevresearch.7.013029 · Cited by 20 · see citing works
Quantum machine learning regression optimisation for full-scale sewage sludge anaerobic digestion
Mohamed, Y., Elghadban, A., Lei, H. I., Shih, A. A., & Lee, P.-H. H. (2025) · npj Clean Water · doi:10.1038/s41545-025-00440-y · Cited by 21 · see citing works
Advances in Quantum Computation and Quantum Technologies: A Design Automation Perspective
Micheli, G. D., Jiang, J.-H. R., Rand, R. W., Smith, K. N., & Soeken, M. (2022) · IEEE Journal on Emerging and Selected Topics in Circuits and Systems · doi:10.1109/jetcas.2022.3205174 · Cited by 21 · see citing works
Muqeet, A., Ali, S., Yue, T., & Arcaini, P. (2024) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3663529.3663830 · Cited by 20 · see citing works
Yamini, B., Nithyanandhan, R., Sudha, K., Nithya, T., Vijayakumar, K., & Siva Subramanian, R. (2024) · International Conference on Communications and Signal Processing (ICCSP) · doi:10.1109/iccsp60870.2024.10543947 · Cited by 20 · see citing works
Ali, S., Wadho, S. A., Talpur, K. R., Talpur, B. A., Alshudukhi, K. S., Humayun, M., Talpur, S. R., Mamun, M. A. A., Naseem, M., Abro, A., et al. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110649 · Cited by 26 · see citing works
VENUS: A Geometrical Representation for Quantum State Visualization
Ruan, S., Yuan, R., Guan, Q., Lin, Y., Mao, Y., Jiang, W., Wang, Z., Xu, W. F., & Wang, Y. (2023) · Computer Graphics Forum · doi:10.1111/cgf.14827 · Cited by 19 · see citing works
Hemmet, A. (2023) · American Journal of Smart Technology and Solutions · doi:10.54536/ajsts.v2i2.2239 · Cited by 19 · see citing works
Mounika, E. K., Shareef, S. K., Adudhodla, M., Sripada, N. K., Karuru, D., & Bhavsingh, M. (2025) · International Conference on Inventive Computation Technologies (ICICT) · doi:10.1109/icict64420.2025.11005048 · Cited by 20 · see citing works
AI Is Transforming Insurance With Five Emerging Business Models
Zarifis, A., & Cheng, X. (2022) · IGI Global eBooks · doi:10.4018/978-1-7998-9220-5.ch124 · Cited by 19 · see citing works
Quantum Hardware Devices (QHDs): Opportunities and Challenges
Oukaira, A. (2025) · IEEE Access · doi:10.1109/access.2025.3576216 · Cited by 19 · see citing works
1.4 The Future of Computing: Bits + Neurons + Qubits
Gil, D., & Green, W. M. J. (2020) · Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference · doi:10.1109/isscc19947.2020.9062918 · Cited by 17 · see citing works
Software Architecture for Quantum Computing Systems - A Systematic ReviewPreprint
Khan, A. A., Ahmad, A., Waseem, M., Liang, P., Fahmideh, M., Mikkonen, T., & Abrahamsson, P. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4191449 · Cited by 17 · see citing works
Efficient Implementation of Discrete-Time Quantum Walks on Quantum Computers
Razzoli, L., Cenedese, G., Bondani, M., & Benenti, G. (2024) · Entropy · doi:10.3390/e26040313 · Cited by 16 · see citing works
Inherent Thermal-Noise Problem in Addressing Qubits
Simbierowicz, S., Borrelli, M., Monarkha, V. Y., Nuutinen, V., & Lake, R. E. (2024) · PRX Quantum · doi:10.1103/prxquantum.5.030302 · Cited by 16 · see citing works
Dukalski, M., Rovetta, D., van der Linde, S., Möller, M., Neumann, N. M. P., & Phillipson, F. (2022) · Geophysics · doi:10.1190/geo2022-0253.1 · Cited by 16 · see citing works
A compiler for universal photonic quantum computers
Zilk, F., Staudacher, K., Guggemos, T., Fürlinger, K., Kranzlmüller, D. A., & Walther, P. J. (2022) · IEEE/ACM International Workshop on Quantum Computing Software (QCS) · doi:10.1109/qcs56647.2022.00012 · Cited by 15 · see citing works
Oonishi, K., Tanaka, T., Uno, S., Satoh, T., Meter, R. V., & Kunihiro, N. (2021) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2021.3136195 · Cited by 17 · see citing works
Quantum error correction with the color-Gottesman-Kitaev-Preskill code
Zhang, J., Zhao, J., Wu, Y.-C., & Guo, G. (2021) · Physical Review A · doi:10.1103/physreva.104.062434 · Cited by 15 · see citing works
Chen, W. J., Marcus, G. S., & Leesburg, D. (2021) · International Journal of Enterprise Modelling · doi:10.35335/emod.v15i3.48 · Cited by 16 · see citing works
Fewer Measurements from Shadow Tomography with N -Representability Conditions
Avdic, I., & Mazziotti, D. A. (2024) · Physical Review Letters · doi:10.1103/physrevlett.132.220802 · Cited by 13 · see citing works
Analyzing the research impact in post quantum cryptography through scientometric evaluation
Hanafi, B., & Ali, M. (2025) · Discover Computing · doi:10.1007/s10791-025-09507-3 · Cited by 18 · see citing works
Wave Function Adapted Hamiltonians for Quantum Computing
Ratini, L., Capecci, C., Benfenati, F., & Guidoni, L. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c01170 · Cited by 13 · see citing works
Natural Orbitals and Sparsity of Quantum Mutual Information
Ratini, L., Capecci, C., & Guidoni, L. (2024) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c01325 · Cited by 12 · see citing works
Simulating a ring-like Hubbard system with a quantum computer
Suchsland, P., Barkoutsos, P. K., Tavernelli, I., Fischer, M. H., & Neupert, T. (2022) · Physical Review Research · doi:10.1103/physrevresearch.4.013165 · Cited by 12 · see citing works
Automatic Qubit Characterization and Gate Optimization with QubiC
Xu, Y., Huang, G., Balewski, J. T., Morvan, A., Nowrouzi, K., Santiago, D., Naik, R., Mitchell, B., & Siddiqi, I. A. (2022) · ACM Transactions on Quantum Computing · doi:10.1145/3529397 · Cited by 11 · see citing works
Accelerating Variational Quantum Algorithms Using Circuit ConcurrencyPreprint
Resch, S., Gutierrez, A., Huh, J. S., Bharadwaj, S., Eckert, Y., Loh, G. H., Oskin, M., & Tannu, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.01714 · Cited by 17 · see citing works
Hierarchy of multipartite correlations based on concentratable entanglement
Schatzki, L., Liu, G., Cerezo, M., & Chitambar, E. (2024) · Physical Review Research · doi:10.1103/physrevresearch.6.023019 · Cited by 12 · see citing works
Hardware Trojans in Quantum Circuits, Their Impacts, and Defense
Roy, R., Das, S. K., & Ghosh, S. (2024) · International Symposium on Quality Electronic Design (ISQED) · doi:10.1109/isqed60706.2024.10528740 · Cited by 12 · see citing works
Deterministic algorithms for compiling quantum circuits with recurrent patterns
Ferrari, D., Tavernelli, I., & Amoretti, M. (2021) · Quantum Information Processing · doi:10.1007/s11128-021-03150-9 · Cited by 10 · see citing works
Landa, H., Meirom, D., Kanazawa, N., Fitzpatrick, M., & Wood, C. J. (2022) · Physical Review Research · doi:10.1103/physrevresearch.4.013199 · Cited by 10 · see citing works
Cryogenic CMOS Design for Qubit Control: Present Status, Challenges, and Future Directions [Feature]
Chakraborty, S., & Joshi, R. (2024) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2024.3383808 · Cited by 9 · see citing works
Monarkha, V. Y., Simbierowicz, S., Borrelli, M., van Gulik, R. J. J., Борисович, Д. Н., Kuitenbrouwer, D., Bouman, D., Datta, D., Eskelinen, P., Mannila, E. T., et al. (2024) · Applied Physics Letters · doi:10.1063/5.0203101 · Cited by 9 · see citing works
Fast, universal scheme for calibrating microwave crosstalk in superconducting circuits
Yang, X., Zhang, H.-F., Du, L., Tao, H.-R., Guo, L.-L., Wang, T.-L., Jia, Z.-L., Kong, W., Chen, Z., Duan, P., et al. (2024) · Applied Physics Letters · doi:10.1063/5.0211159 · Cited by 9 · see citing works
Atlas: Hierarchical Partitioning for Quantum Circuit Simulation on GPUs
Xu, M., Cao, S., Miao, X., Acar, U. A., & Jia, Z. (2024) · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1109/sc41406.2024.00087 · Cited by 9 · see citing works
A quantum procedure for map generation
Wootton, J. R. (2020) · IEEE Conference on Games (CoG) · doi:10.1109/cog47356.2020.9231571 · Cited by 10 · see citing works
Many-qubit protection-operation dilemma from the perspective of many-body localization
Silveri, M., & Orell, T. (2022) · Nature Communications · doi:10.1038/s41467-022-33657-3 · Cited by 9 · see citing works
Mahmoudi, Y., Zioui, N., Belbachir, H., Tadjine, M., & Rezgui, A. (2022) · Emerging Science Journal · doi:10.28991/esj-2023-07-01-020 · Cited by 9 · see citing works
Scheduling of Operations in Quantum Compiler
Itoko, T., & Imamichi, T. (2020) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce49297.2020.00049 · Cited by 9 · see citing works
Heterogeneous Computing Systems for Complex Scientific Discovery Workflows
Hagleitner, C., Diamantopoulos, D., Ringlein, B., Evangelinos, C., Johns, C., Chang, R., D’Amora, B., Kahle, J. A., Sexton, J., Johnston, M. A., et al. (2021) · Design, Automation, and Test in Europe · doi:10.23919/date51398.2021.9474061 · Cited by 9 · see citing works
Scaling up to problem sizes: an environmental life cycle assessment of quantum computing
Cordier, S., Thibault, K., Arpin, M.-L., & Amor, B. (2025) · Quantum Science and Technology · doi:10.1088/2058-9565/adc0ba · Cited by 8 · see citing works
Leveraging quantum science and technology for sustainable development in Africa
Mazhandu, F., & Mafu, M. (2025) · African Journal of Science Technology Innovation and Development · doi:10.1080/20421338.2025.2504259 · Cited by 8 · see citing works
Quantum Computing in Transportation Engineering: A Survey
Somvanshi, S., Islam, M. M., Polock, S. B. B., Chhetri, G., Anderson, D., Anandi, D., & Das, S. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3662626 · Cited by 8 · see citing works
Noise-adaptive quantum compilation strategies evaluated with application-motivated benchmarks
Ferrari, D., & Amoretti, M. (2022) · ACM International Conference on Computing Frontiers (CF) · doi:10.1145/3528416.3530250 · Cited by 8 · see citing works
Performance of Grover’s search algorithm with diagonalizable collective noises
Pan, M., Xiong, T., & Zheng, S. (2023) · Quantum Information Processing · doi:10.1007/s11128-023-03994-3 · Cited by 8 · see citing works
Quantum Computing in The Cloud - A Systematic Literature Review
Zhahir, A. A., Mohd, S. M., Shuhud, M. I. M., Idrus, B., Zainuddin, H. B., Jan, N. M., & Wahiddin, M. R. (2024) · International journal of electrical and computer engineering systems · doi:10.32985/ijeces.15.2.7 · Cited by 8 · see citing works
GraFeyn: Efficient Parallel Sparse Simulation of Quantum Circuits
Westrick, S., Liu, P., Kang, B., McDonald, C., Rainey, M., Xu, M., Arora, J., Ding, Y., & Acar, U. A. (2024) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce60285.2024.00132 · Cited by 7 · see citing works
Ye, L., Wang, Y., & Zheng, X. H. (2025) · The Journal of Chemical Physics · doi:10.1063/5.0242648 · Cited by 7 · see citing works
- Authors
- Corcoles, A. D., Kandala, A., Javadi-Abhari, A., McClure, D. T., Cross, A. W., Temme, K., Nation, P. D., Steffen, M., & Gambetta, J. M.
- Affiliations
- IBM (United States) (US)
- Venue
- Proceedings of the IEEE
- Published
- 2020-08
- Volume
- 108
- Issue
- 8
- Pages
- 1338-1352
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2978630019
- Cited by
- 203
- References
- 133
- Citations by year
- 2026: 21 · 2025: 44 · 2024: 44 · 2023: 25 · 2022: 22 · 2021: 34 · 2020: 12 · 2019: 1
- FWCI
- 7.86
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Proceedings of the IEEE (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Keywords
- near-term quantum computing, noisy intermediate-scale quantum computing, quantum computing software, cloud quantum computing, quantum benchmarking, quantum circuit complexity
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