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Multi-qubit Lattice Surgery Scheduling

Authors Allyson Silva , Xiangyi Zhang , Zak Webb , Mia Kramer , Chan-Woo Yang , Xiao Liu , Jessica Lemieux , Ka-Wai Chen, Artur Scherer , Pooya Ronagh

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ACM Subject Classification
  • Computer systems organization → Quantum computing
  • Software and its engineering → Compilers
  • Hardware → Quantum error correction and fault tolerance
  • Software and its engineering → Scheduling
  • Hardware → Circuit optimization
Keywords
  • Scheduling
  • Large-Scale Optimization
  • Surface Code
  • Quantum Compilation
  • Circuit Optimization

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Abstract

Fault-tolerant quantum computation using two-dimensional topological quantum error correcting codes can benefit from multi-qubit long-range operations. By using simple commutation rules, a quantum circuit can be transpiled into a sequence of solely non-Clifford multi-qubit gates. Prior work on fault-tolerant compilation avoids optimal scheduling of such gates since they reduce the parallelizability of the circuit. We observe that the reduced parallelization potential is outweighed by the significant reduction in the number of gates. We therefore devise a method for scheduling multi-qubit lattice surgery using an earliest-available-first policy, solving the associated forest packing problem using a representation of the multi-qubit gates as Steiner trees. Our extensive testing on random and various Hamiltonian simulation circuits demonstrates the method’s scalability and performance. We show that the transpilation significantly reduces the circuit length on the set of circuits tested, and that the resulting circuit of multi-qubit gates has a further reduction in the expected circuit execution time compared to serial execution.

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Allyson Silva, Xiangyi Zhang, Zak Webb, Mia Kramer, Chan-Woo Yang, Xiao Liu, Jessica Lemieux, Ka-Wai Chen, Artur Scherer, and Pooya Ronagh. Multi-qubit Lattice Surgery Scheduling. In 19th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 310, pp. 1:1-1:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.TQC.2024.1

Author Details

Allyson Silva
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Xiangyi Zhang
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Zak Webb
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Mia Kramer
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Chan-Woo Yang
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Xiao Liu
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Jessica Lemieux
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Ka-Wai Chen
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Artur Scherer
  • 1QB Information Technologies (1QBit), Vancouver, Canada
Pooya Ronagh
  • 1QB Information Technologies (1QBit), Vancouver, Canada
  • Institute for Quantum Computing, University of Waterloo, Canada
  • Department of Physics & Astronomy, University of Waterloo, Canada
  • Perimeter Institute for Theoretical Physics, Waterloo, Canada

Funding

  • Ronagh, Pooya: Acknowledges the financial support of Mike and Ophelia Lazaridis, Innovation, Science and Economic Development Canada (ISED), and the Perimeter Institute for Theoretical Physics. Research at the Perimeter Institute is supported in part by the Government of Canada through ISED and by the Province of Ontario through the Ministry of Colleges and Universities.

Acknowledgements

We are grateful to our editor, Marko Bucyk, for his careful review and editing of the manuscript.

Supplementary Materials

References

  1. J. M. Arrazola, S. Jahangiri, A. Delgado, J. Ceroni, J. Izaac, A. Száva, U. Azad, R. A. Lang, Z. Niu, O. Di Matteo, R. Moyard, J. Soni, M. Schuld, R. A. Vargas-Hernández, T. Tamayo-Mendoza, C. Y.-Y. Lin, A. Aspuru-Guzik, and N. Killoran. Differentiable quantum computational chemistry with Pennylane, 2023. URL: https://arxiv.org/abs/2111.09967.
  2. M. Beverland, V. Kliuchnikov, and E. Schoute. Surface code compilation via edge-disjoint paths. PRX Quantum, 3(2):020342, 2022. URL: https://doi.org/10.48550/arXiv.2110.11493.
  3. A. Braunstein and A. P. Muntoni. The cavity approach for Steiner trees packing problems. Journal of Statistical Mechanics: Theory and Experiment, 2018(12):123401, 2018. URL: https://doi.org/10.48550/arXiv.1712.07041.
  4. S. Bravyi and J. Haah. Magic-state distillation with low overhead. Phys. Rev. A, 86(5):052329, 2012. URL: https://doi.org/10.1103/PhysRevA.86.052329.
  5. S. Bravyi and A. Kitaev. Universal quantum computation with ideal Clifford gates and noisy ancillas. Phys. Rev. A, 71(2):022316, 2005. URL: https://doi.org/10.1103/PhysRevA.71.022316.
  6. D. E. Drake and S. Hougardy. On approximation algorithms for the terminal Steiner tree problem. Information Processing Letters, 89(1):15-18, 2004. URL: https://doi.org/10.1016/j.ipl.2003.09.014.
  7. M. Fischetti, M. Leitner, I. Ljubić, M. Luipersbeck, M. Monaci, M. Resch, D. Salvagnin, and M. Sinnl. Thinning out Steiner trees: a node-based model for uniform edge costs. Mathematical Programming Computation, 9(2):203-229, 2017. URL: https://doi.org/10.1007/s12532-016-0111-0.
  8. A. G. Fowler, M. Mariantoni, J. M. Martinis, and A. N. Cleland. Surface codes: Towards practical large-scale quantum computation. Phys. Rev. A, 86(3):032324, 2012. URL: https://doi.org/10.1103/PhysRevA.86.032324.
  9. E. Gassner. The Steiner forest problem revisited. Journal of Discrete Algorithms, 8(2):154-163, 2010. URL: https://doi.org/10.1016/j.jda.2009.05.002.
  10. C. Gidney. Stim: a fast stabilizer circuit simulator. Quantum, 5:497, 2021. URL: https://doi.org/10.22331/q-2021-07-06-497.
  11. N.-D. Hoàng and T. Koch. Steiner tree packing revisited. Mathematical Methods of Operations Research, 76:95-123, 2012. URL: https://doi.org/10.1007/s00186-012-0391-8.
  12. D. Horsman, A. G. Fowler, S. Devitt, and R. V. Meter. Surface code quantum computing by lattice surgery. New Journal of Physics, 14(12):123011, 2012. URL: https://doi.org/10.1088/1367-2630/14/12/123011.
  13. I. H. Kim, Y.-H. Liu, S. Pallister, W. Pol, S. Roberts, and E. Lee. Fault-tolerant resource estimate for quantum chemical simulations: Case study on Li-ion battery electrolyte molecules. Phys. Rev. Res., 4(2):023019, 2022. URL: https://doi.org/10.1103/PhysRevResearch.4.023019.
  14. L. Lao, B. Van Wee, I. Ashraf, J. Van Someren, N. Khammassi, K. Bertels, and C. G. Almudever. Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology, 4(1):015005, 2018. URL: https://doi.org/10.1088/2058-9565/aadd1a.
  15. L. C. Lau. Packing Steiner forests. In International Conference on Integer Programming and Combinatorial Optimization, pages 362-376. Springer, 2005. URL: https://doi.org/10.1007/11496915_27.
  16. G. Lin and G. Xue. On the terminal Steiner tree problem. Information Processing Letters, 84(2):103-107, 2002. URL: https://doi.org/10.1016/S0020-0190(02)00227-2.
  17. D. Litinski. A game of surface codes: large-scale quantum computing with lattice surgery. Quantum, 3:128, 2019. URL: https://doi.org/10.22331/q-2019-03-05-128.
  18. D. Litinski. Magic state distillation: not as costly as you think. Quantum, 3:205, 2019. URL: https://doi.org/10.22331/q-2019-12-02-205.
  19. I. Ljubić. Solving Steiner trees: recent advances, challenges, and perspectives. Networks, 77(2):177-204, 2021. URL: https://doi.org/10.1002/net.22005.
  20. K. Mehlhorn. A faster approximation algorithm for the Steiner problem in graphs. Information Processing Letters, 27(3):125-128, 1988. URL: https://doi.org/10.1016/0020-0190(88)90066-X.
  21. T. Pajor, E. Uchoa, and R. F. Werneck. A robust and scalable algorithm for the Steiner problem in graphs. Mathematical Programming Computation, 10:69-118, 2018. URL: https://doi.org/10.1007/s12532-017-0123-4.
  22. C. C. Ribeiro, E. Uchoa, and R. F. Werneck. A hybrid GRASP with perturbations for the Steiner problem in graphs. INFORMS Journal on Computing, 14(3):228-246, 2002. URL: https://doi.org/10.1287/ijoc.14.3.228.116.
  23. V. Senicourt, J. Brown, A. Fleury, R. Day, E. Lloyd, M. P. Coons, K. Bieniasz, L. Huntington, A. J. Garza, S. Matsuura, R. Plesch, T. Yamazaki, and A. Zaribafiyan. Tangelo: An open-source Python package for end-to-end chemistry workflows on quantum computers, 2022. URL: https://arxiv.org/abs/2206.12424.
  24. Y. Sun, G. Gutin, and X. Zhang. Packing strong subgraph in digraphs. Discrete Optimization, 46:100745, 2022. URL: https://doi.org/10.1016/j.disopt.2022.100745.
  25. E. Uchoa and R. F. Werneck. Fast local search for the Steiner problem in graphs. ACM Journal of Experimental Algorithmics, 17:1-22, 2012. URL: https://doi.org/10.1145/2133803.2184448.
  26. G. Watkins, H. M. Nguyen, K. Watkins, S. Pearce, H.-K. Lau, and A. Paler. A high performance compiler for very large scale surface code computations. Quantum, 8:1354, 2024. URL: https://doi.org/10.22331/q-2024-05-22-1354.
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