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Challenges and Opportunities of Near-Term Quantum Computing Systems
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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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Citations
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
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
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
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
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
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
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×
“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
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
Degen, C. L., Reinhard, F., & Cappellaro, P. (2017) · Reviews of Modern Physics · doi:10.1103/revmodphys.89.035002 · Cited by 4,045
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
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
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×
“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
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
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
Self-citationA 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 2,321
Gisin, N., & Thew, R. (2007) · Nature Photonics · doi:10.1038/nphoton.2007.22 · Cited by 2,223
Superconducting Circuits for Quantum Information: An Outlook
Devoret, M., & Schoelkopf, R. J. (2013) · Science · doi:10.1126/science.1231930 · Cited by 2,197
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
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
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
Dennis, E., Kitaev, A., Landahl, A., & Preskill, J. (2002) · Journal of Mathematical Physics · doi:10.1063/1.1499754 · Cited by 1,768
Improved simulation of stabilizer circuits
Aaronson, S., & Gottesman, D. (2004) · Physical Review A · doi:10.1103/physreva.70.052328 · Cited by 1,515
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
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
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
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
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
Bernstein, D. J., & Lange, T. (2017) · Nature · doi:10.1038/nature23461 · Cited by 1,242
Fault-tolerant quantum computation
Shor, P. W. (2002) · Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1996.548464 · Cited by 1,195
Wilde, M. M. (2013) · doi:10.1017/cbo9781139525343 · Cited by 1,138
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
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 1,022
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 947
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
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
Self-citationSynthesis 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 786
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
Validating 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
Self-citationThe Solovay-Kitaev algorithmPreprint
Dawson, C., & Nielsen, M. (2005) · Quantum information & computation · doi:10.48550/arxiv.quant-ph/0505030 · Cited by 694
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
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 680
Self-citationFault-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
Quantum 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 629
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 614
Self-citationFAULT-TOLERANT QUANTUM COMPUTATION
Preskill, J. P. (1998) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789812385253_0008 · Cited by 605
Roads towards fault-tolerant universal quantum computation
Campbell, E. T., Terhal, B. M., & Vuillot, C. (2017) · Nature · doi:10.1038/nature23460 · Cited by 596
Maintaining coherence in quantum computers
Unruh, W. G. (1995) · Physical Review A · doi:10.1103/physreva.51.992 · Cited by 594
How 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 566
A 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×
“For example, high-level program routines, such as an abstract unitary evolution, must first be synthesized into a quantum circuit [61]–[64].”
BackgroundNoise 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
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
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 495
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 491
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
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
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
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 420
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
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
Quantum advantage with shallow circuits
Bravyi, S. B., Gosset, D., & König, R. (2018) · Science · doi:10.1126/science.aar3106 · Cited by 406
Rigetti, C. T., & Devoret, M. (2010) · Physical Review B · doi:10.1103/physrevb.81.134507 · Cited by 368
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
Tapering off qubits to simulate fermionic HamiltoniansPreprint
Bravyi, S., Gambetta, J., Mezzacapo, A., & Temme, K. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.08213 · Cited by 356
Self-citationFast 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 327
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
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 319
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
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
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
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
Dawson, C. M., & Nielsen, M. A. (2006) · Quantum Information and Computation · doi:10.26421/qic6.1-6 · Cited by 288
Automated 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 274
Quantum implementation of the unitary coupled cluster for simulating molecular electronic structure
Shen, Y., Zhang, X., Zhang, S., Zhang, J.-N., Yung, M.-H., & Kim, K. (2015) · Physical Review A · doi:10.1103/physreva.95.020501 · Cited by 262
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
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
Error-Mitigated Digital Quantum Simulation
McArdle, S., Yuan, X., & Benjamin, S. C. (2019) · Physical Review Letters · doi:10.1103/physrevlett.122.180501 · Cited by 253
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
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
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
Self-citationQuantum Computational Complexity
Watrous, J. (2009) · Springer eBooks · doi:10.1007/978-0-387-30440-3_428 · Cited by 226
Topological 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
Self-citationQuantum 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
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
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
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
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 180
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
Microwave-induced coupling of superconducting qubits
Paraoanu, G. S. (2006) · Physical Review B · doi:10.1103/physrevb.74.140504 · Cited by 174
Izmaylov, 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
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 171
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
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
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 155
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
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
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 140
Experimental 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 136
Temporally unstructured quantum computation
Shepherd, D., & Bremner, M. J. (2009) · Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rspa.2008.0443 · Cited by 135
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 134
Quantum computation with universal error mitigation on a superconducting quantum processor
Song, C., Cui, J., Wang, H., Hao, J., Feng, H., & Li, Y. (2019) · Science Advances · doi:10.1126/sciadv.aaw5686 · Cited by 131
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
Self-citationFault-tolerant quantum computationPreprint
Preskill, J. P. (1997) · arXiv (Cornell University) · doi:10.48550/arxiv.quant-ph/9712048 · Cited by 124
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 123
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 122
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 122
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 120
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 120
Self-citation(2019) · doi:10.1145/3297858.3304018 · Cited by 118
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 115
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 115
On the controlled-NOT complexity of controlled-NOT–phase circuits
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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
$O(N^3)$ Measurement Cost for Variational Quantum Eigensolver on Molecular Hamiltonians
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
Self-citationForrelation: A Problem That Optimally Separates Quantum from Classical Computing
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Two-step approach to scheduling quantum circuits
Guerreschi, G. G., & Park, J. (2018) · Quantum Science and Technology · doi:10.1088/2058-9565/aacf0b · Cited by 80
A 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 78
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
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 69
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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 60
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
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 54
Self-citationBenefits and Challenges of Designing Cryogenic CMOS RF Circuits for Quantum Computers
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Preparing topological projected entangled pair states on a quantum computer
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Predicting substrate resonance mode frequency shifts using conductive, through-substrate vias
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CertiQ: A Mostly-automated Verification of a Realistic Quantum CompilerPreprint
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A volumetric framework for quantum computer benchmarks
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Characterizing large-scale quantum computers via cycle benchmarking
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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
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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
Research works printed but not linked: 15
- 10.1017/cbo9780511976667 · DOI · Paper page
- Jordan, Quantum Algorithm Zoo
- 2017, Qiskit Terra
- 2019, Qiskit Aer
- 2019, Qiskit Ignis
- 2019, Qiskit Aqua
- 2018, PyQuil
- 2018, Cirq
- 10.1145/2597917.2597939 · DOI
- 10.5753/ctd.2020.11368 · DOI
- 2019, Quantum Algorithm Zoo
- 10.26421/QIC4.3-7 · DOI
- Shepherd, 2009, Instantaneous quantum computation, Proc. Roy. Soc., 465, 1413
- Lienhard, 2005, Microwave packaging for superconducting qubits
- 10.1007/springerreference_60600 · DOI
Cited by
Sorted by citations
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Distributed quantum computing: A survey
Caleffi, M., Amoretti, M., Ferrari, D., Illiano, J., Manzalini, A., & Cacciapuoti, A. S. (2024) · Computer Networks · doi:10.1016/j.comnet.2024.110672 · Cited by 361
Bosonic quantum error correction codes in superconducting quantum circuits
Cai, W., Ma, Y., Wang, W., Zou, C.-L., & Sun, L. (2021) · Fundamental Research · doi:10.1016/j.fmre.2020.12.006 · Cited by 251
Laser-annealing Josephson junctions for yielding scaled-up superconducting quantum processors
Hertzberg, J. B., Zhang, E. J., Rosenblatt, S., Magesan, E., Smolin, J. A., Yau, J.-B., Adiga, V. P., Sandberg, M., Brink, M., Chow, J. M., et al. (2021) · npj Quantum Information · doi:10.1038/s41534-021-00464-5 · Cited by 216
Modern computing: Vision and challenges
Gill, S. S., Wu, H., Patros, P., Ottaviani, C., Arora, P., Pujol, V. C., Haunschild, D., Parlikad, A. K., Cetinkaya, O., Lutfiyya, H., et al. (2024) · Telematics and Informatics Reports · doi:10.1016/j.teler.2024.100116 · Cited by 197
Metadata
- 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
- 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 › Physics and Astronomy › Atomic and Molecular Physics, and Optics › 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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