The DOI matches its Crossref record; 78 of the 80 references it cites were found in a registry or an index.
t|ket⟩: a retargetable compiler for NISQ devices
Open accessAbstract
We present t | ket ⟩, a quantum software development platform produced by Cambridge Quantum Computing Ltd. The heart of t | ket ⟩ is a language-agnostic optimising compiler designed to generate code for a variety of NISQ devices, which has several features designed to minimise the influence of device error. The compiler has been extensively benchmarked and outperforms most competitors in terms of circuit optimisation and qubit routing.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“It was recently proven [65] that at a fixed gate error, RCS is not a scalable route to quantum supremacy at large N”
From A Race-Track Trapped-Ion Quantum Processor (2023) · cites this paper as [65]
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
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 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
A single quantum cannot be cloned
Wootters, W. K., & Zurek, W. H. (1982) · Nature · doi:10.1038/299802a0 · Cited by 5,406 · cited 1×
“For qubits, this linear resource management is justified by the no-cloning [50] and no-deleting [51] theorems.”
MethodA 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
Quantum Algorithm for Linear Systems of Equations
Harrow, A. W., Hassidim, A., & Lloyd, S. (2009) · Physical Review Letters · doi:10.1103/physrevlett.103.150502 · Cited by 3,325
Georgescu, I. M., Ashhab, S., & Nori, F. (2014) · Reviews of Modern Physics · doi:10.1103/revmodphys.86.153 · Cited by 2,932
A Quantum Approximate Optimization Algorithm
Farhi, E., Goldstone, J., & Gutmann, S. (2014) · arXiv · doi:10.48550/arxiv.1411.4028 · Cited by 1,789
Improved simulation of stabilizer circuits
Aaronson, S., & Gottesman, D. (2004) · Physical Review A · doi:10.1103/physreva.70.052328 · Cited by 1,515
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
Fundamentals of Algebraic Graph Transformation
Ehrig, H., Ehrig, K., Prange, U., & Taentzer, G. (2006) · doi:10.1007/3-540-31188-2 · Cited by 849
PennyLane: Automatic differentiation of hybrid quantum-classical computations
Bergholm, V., Izaac, J., Schuld, M., Gogolin, C., Ahmed, S., Ajith, V., Alam, M. S., Alonso-Linaje, G., AkashNarayanan, B., Asadi, A., et al. (2018) · arXiv · doi:10.48550/arxiv.1811.04968 · Cited by 732
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
OpenFermion: the electronic structure package for quantum computers
McClean, J. R., Rubin, N. C., Sung, K. J., Kivlichan, I., Bonet-Monroig, X., Cao, Y., Dai, C., Fried, E., Gidney, C., Gimby, B., et al. (2020) · Quantum Science and Technology · doi:10.1088/2058-9565/ab8ebc · Cited by 621
Benchmarking an 11-qubit quantum computer
Wright, K., Beck, K. M., Debnath, S., Amini, J., Nam, Y., Grzesiak, N., Chen, J.-S., Pisenti, N. C., Chmielewski, M., Collins, C., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13534-2 · Cited by 575
Toward the first quantum simulation with quantum speedup
Childs, A. M., Maslov, D., Nam, Y., Ross, N. J., & Su, Y. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801723115 · Cited by 551
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
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
Interacting quantum observables: categorical algebra and diagrammatics
Coecke, B., & Duncan, R. (2011) · New Journal of Physics · doi:10.1088/1367-2630/13/4/043016 · Cited by 467
Self-citationDirect Fidelity Estimation from Few Pauli Measurements
Flammia, S. T., & Liu, Y.-K. (2011) · Physical Review Letters · doi:10.1103/physrevlett.106.230501 · Cited by 449
Quantum Computers Can Search Arbitrarily Large Databases by a Single Query
Grover, L. K. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.4709 · Cited by 432
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
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
Strawberry Fields: A Software Platform for Photonic Quantum Computing
Killoran, N., Izaac, J., Quesada, N., Bergholm, V., Amy, M., & Weedbrook, C. (2019) · Quantum · doi:10.22331/q-2019-03-11-129 · Cited by 395
The Heisenberg Representation of Quantum Computers
Gottesman, D. (1998) · University of North Texas Digital Library (University of North Texas) · Cited by 385
An Efficient Methodology for Mapping Quantum Circuits to the IBM QX Architectures
Zulehner, A., Paler, A., & Wille, R. (2018) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2018.2846658 · Cited by 382
Impossibility of deleting an unknown quantum state
Kumar Pati, A., & Braunstein, S. L. (2000) · Nature · doi:10.1038/404130b0 · Cited by 369
Why I am optimistic about the silicon-photonic route to quantum computing
Rudolph, T. (2017) · APL Photonics · doi:10.1063/1.4976737 · Cited by 350 · cited 1×
“Superconducting and ion-trap-based quantum processors are now available from multiple commercial companies [10–14], while other technologies such as photonics are not far behind [15, 16].”
BackgroundIEEE Standard for Floating-Point Arithmetic
(2019) · doi:10.1109/ieeestd.2019.8766229 · Cited by 344
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
Cluster-state quantum computation
Nielsen, M. A. (2006) · Reports on Mathematical Physics · doi:10.1016/s0034-4877(06)80014-5 · Cited by 315
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
Universal quantum circuit for two-qubit transformations with three controlled-NOT gates
Vidal, G., & Dawson, C. M. (2004) · Physical Review A · doi:10.1103/physreva.69.010301 · Cited by 293
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
Efficient learning of quantum noise
Harper, R., Flammia, S. T., & Wallman, J. J. (2020) · Nature Physics · doi:10.1038/s41567-020-0992-8 · Cited by 267
Reducing the number of non-Clifford gates in quantum circuits
Kissinger, A., & van de Wetering, J. (2020) · Physical Review A · doi:10.1103/physreva.102.022406 · Cited by 255
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
Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers
Murali, P., Mckay, D. C., Martonosi, M., & Javadi-Abhari, A. (2020) · Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems · doi:10.1145/3373376.3378477 · Cited by 253
Cartan decomposition of SU(2n) and control of spin systems
Khaneja, N., & Glaser, S. J. (2001) · Chemical Physics · doi:10.1016/s0301-0104(01)00318-4 · Cited by 238
Toffoli network synthesis with templates
Maslov, D., Dueck, G. W., & Miller, D. M. (2005) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2005.847911 · Cited by 227
Jensen-Shannon divergence as a measure of distinguishability between mixed quantum states
Majtey, A. P., Lamberti, P. W., & Prato, D. P. (2005) · Physical Review A · doi:10.1103/physreva.72.052310 · Cited by 220
Demonstration of Fidelity Improvement Using Dynamical Decoupling with Superconducting Qubits
Pokharel, B., Anand, N., Fortman, B., & Lidar, D. A. (2018) · Physical Review Letters · doi:10.1103/physrevlett.121.220502 · Cited by 209
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
Self-citationOn the Qubit Routing ProblemPreprint
Cowtan, A., Dilkes, S., Duncan, R., Krajenbrink, A., Simmons, W., & Sivarajah, S. (2019) · arXiv (Cornell University) · doi:10.4230/lipics.tqc.2019.5 · Cited by 197
Self-citationConventions for quantum pseudocode
Lab., N. (. S. L. A. N., Knill, E., & USDOE, W. (1996) · doi:10.2172/366453 · Cited by 193
Green, A. S., Lumsdaine, P. L., Ross, N. J., Selinger, P., & Valiron, B. (2013) · ACM SIGPLAN Notices · doi:10.1145/2499370.2462177 · Cited by 191
Quantum phase estimation of multiple eigenvalues for small-scale (noisy) experiments
O’Brien, T. E., Tarasinski, B., & Terhal, B. M. (2019) · New Journal of Physics · doi:10.1088/1367-2630/aafb8e · Cited by 175
Phase Gadget Synthesis for Shallow Circuits
Cowtan, A., Dilkes, S., Duncan, R., Simmons, W., & Sivarajah, S. (2020) · Electronic Proceedings in Theoretical Computer Science · doi:10.4204/eptcs.318.13 · Cited by 173
Self-citationA software methodology for compiling quantum programs
Häner, T., Steiger, D. S., Svore, K. M., & Troyer, M. (2018) · Quantum Science and Technology · doi:10.1088/2058-9565/aaa5cc · Cited by 171
PyZX: Large Scale Automated Diagrammatic Reasoning
Kissinger, A., & van de Wetering, J. (2020) · Electronic Proceedings in Theoretical Computer Science · doi:10.4204/eptcs.318.14 · Cited by 160
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
Ball, H., Biercuk, M. J., Carvalho, A. R. R., Chen, J., Hush, M., de Castro, L. A., Li, L., Liebermann, P., Slatyer, H. J., Edmunds, C., et al. (2021) · Quantum Science and Technology · doi:10.1088/2058-9565/abdca6 · Cited by 134
Leung, N., Abdelhafez, M. R., Koch, J., & Schuster, D. (2017) · Physical Review A · doi:10.1103/physreva.95.042318 · 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
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
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
Extracting Success from IBM’s 20-Qubit Machines Using Error-Aware Compilation
Nishio, S., Pan, Y., Satoh, T., Amano, H., & Meter, R. V. (2020) · ACM Journal on Emerging Technologies in Computing Systems · doi:10.1145/3386162 · Cited by 114
Fermion-to-qubit mappings with varying resource requirements for quantum simulation
Steudtner, M., & Wehner, S. (2018) · New Journal of Physics · doi:10.1088/1367-2630/aac54f · Cited by 113
Non-Gaussian noise spectroscopy with a superconducting qubit sensor
Sung, Y., Beaudoin, F., Norris, L., Yan, F., Kim, D. K., Qiu, J. Y., von Lüpke, U., Yoder, J., Orlando, T. P., Gustavsson, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11699-4 · Cited by 108
Rewriting Measurement-Based Quantum Computations with Generalised Flow
Duncan, R., & Perdrix, S. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-14162-1_24 · Cited by 104
Self-citationShorter Stabilizer Circuits via Bruhat Decomposition and Quantum Circuit Transformations
Maslov, D., & Roetteler, M. (2018) · IEEE Transactions on Information Theory · doi:10.1109/tit.2018.2825602 · Cited by 90
Partial Compilation of Variational Algorithms for Noisy Intermediate-Scale Quantum Machines
Gokhale, P., Ding, Y., Propson, T., Winkler, C., Leung, N., Shi, Y., Schuster, D., Hoffmann, H., & Chong, F. T. (2019) · IEEE/ACM International Symposium on Microarchitecture (MICRO) · doi:10.1145/3352460.3358313 · Cited by 86
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
Generators and relations for n-qubit Clifford operators
Selinger, P. (2015) · Logical Methods in Computer Science · doi:10.2168/lmcs-11(2:10)2015 · Cited by 46
A language and hardware independent approach to quantum–classical computing
McCaskey, A. J., Dumitrescu, E. F., Liakh, D., Chen, M., Feng, W., & Humble, T. S. (2018) · SoftwareX · doi:10.1016/j.softx.2018.07.007 · Cited by 46
A Graphical Approach to Measurement-BasedQuantum Computing
Duncan, R. (2013) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199646296.003.0003 · Cited by 44
Self-citationOptimization of Clifford circuits
Kliuchnikov, V., & Maslov, D. A. (2013) · Physical Review A · doi:10.1103/physreva.88.052307 · Cited by 42
Two-Qubit Circuit Depth and the Monodromy Polytope
Peterson, E. C., Crooks, G. E., & Smith, R. S. (2020) · Quantum · doi:10.22331/q-2020-03-26-247 · Cited by 39
Hopper, G. M. (1952) · ACM National Meeting · doi:10.1145/609784.609818 · Cited by 36
A finite presentation of CNOT-dihedral operators
Amy, M., Chen, J.-X., & Ross, N. J. (2016) · QPL · doi:10.4204/eptcs.266.5 · Cited by 34
Optimising Clifford Circuits with Quantomatic
Fagan, A., & Duncan, R. (2019) · Electronic Proceedings in Theoretical Computer Science · doi:10.4204/eptcs.287.5 · Cited by 31
Self-citationQuantum Circuit Compilation: An Emerging Application for Automated Reasoning
Venturelli, D., Minh, N., O’Gorman, B., Frank, J., Rieffel, E. G., Booth, K. E. C., Nguyen, T. L., Narayan, P., & Nanda, S. (2019) · Cited by 30
An analytical decomposition protocol for optimal implementation of two-qubit entangling gates
Blaauboer, M., & de Visser, R. L. (2008) · Journal of Physics A: Mathematical and Theoretical · doi:10.1088/1751-8113/41/39/395307 · Cited by 20
Efficient characterization of correlated SPAM errorsPreprint
Sun, M., & Geller, M. R. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1810.10523 · Cited by 14
Structured Cospans.Preprint
Baez, J. C., & Courser, K. (2019) · arXiv (Cornell University) · Cited by 13
Optimizations in C++ Compilers
Godbolt, M. (2019) · Queue · doi:10.1145/3371595.3372264 · Cited by 3
Cited by
Sorted by citations
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
Quantum Simulation for High-Energy Physics
Bauer, C., Davoudi, Z., Balantekin, A. B., Tanmoy Bhattacharya, A., Carena, M. S., de Jong, W. A., Draper, P., El-Khadra, A. X., Gemelke, N., Hanada, M., et al. (2023) · PRX Quantum · doi:10.1103/prxquantum.4.027001 · Cited by 503
Qulacs: a fast and versatile quantum circuit simulator for research purpose
Suzuki, Y., Kawase, Y., Masumura, Y., Hiraga, Y., Nakadai, M., Chen, J., Nakanishi, K. M., Mitarai, K., Imai, R., Tamiya, S., et al. (2021) · Quantum · doi:10.22331/q-2021-10-06-559 · Cited by 357
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
The bitter truth about gate-based quantum algorithms in the NISQ era
Leymann, F., & Barzen, J. (2020) · Quantum Science and Technology · doi:10.1088/2058-9565/abae7d · Cited by 251
Metadata
- Authors
- Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., & Duncan, R.
- Affiliations
- Cambridge Quantum Computing (United Kingdom) (GB)
- University of Strathclyde (GB)
- Corresponding author
- Sivarajah, Seyon
- Dilkes, Silas
- Cowtan, Alexander
- Simmons, Will
- Edgington, Alec
- Duncan, Ross
- Venue
- Quantum Science and Technology
- Publisher
- IOP Publishing
- Published
- 2020-11-06
- Volume
- 6
- Issue
- 1
- Pages
- 014003
- ISSN
- 2058-9565 (ISSN-L)
- OpenAlex
- W3013348036
- Cited by
- 475
- References
- 80
- Citations by year
- 2026: 69 · 2025: 111 · 2024: 84 · 2023: 88 · 2022: 66 · 2021: 40 · 2020: 16
- FWCI
- 20.64
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Quantum Science and Technology (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (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 › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Keywords
- quantum compiler, NISQ devices, quantum circuit optimization, qubit routing, noise mitigation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
