References

  1. Miriam Backens, Simon Perdrix & Quanlong Wang (2017): A Simplified Stabilizer ZX-calculus. Electronic Proceedings in Theoretical Computer Science 236, pp. 1–20, doi:10.4204/eptcs.236.1.
  2. Niel de Beaudrap, Xiaoning Bian & Quanlong Wang (2020): Fast and Effective Techniques for T-Count Reduction via Spider Nest Identities. In: Steven T. Flammia: 15th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2020), Leibniz International Proceedings in Informatics (LIPIcs) 158. Schloss Dagstuhl–Leibniz-Zentrum für Informatik, Dagstuhl, Germany, pp. 11:1–11:23, doi:10.4230/LIPIcs.TQC.2020.11.
  3. Niel de Beaudrap, Aleks Kissinger & Konstantinos Meichanetzidis (2021): Tensor Network Rewriting Strategies for Satisfiability and Counting. Electronic Proceedings in Theoretical Computer Science 340, pp. 46–59, doi:10.4204/eptcs.340.3.
  4. Lucas Berent, Lukas Burgholzer & Robert Wille (2022): Towards a SAT Encoding for Quantum Circuits: A Journey From Classical Circuits to Clifford Circuits and Beyond, doi:10.48550/arXiv.2203.00698.
  5. Agustín Borgna, Simon Perdrix & Benoît Valiron (2021): Hybrid quantum-classical circuit simplification with the ZX-calculus. In: Hakjoo Oh: Programming Languages and Systems. Springer International Publishing, Cham, pp. 121–139, doi:10.1007/978-3-030-89051-3_8.
  6. Sergey Bravyi, Dan Browne, Padraic Calpin, Earl Campbell, David Gosset & Mark Howard (2019): Simulation of quantum circuits by low-rank stabilizer decompositions. Quantum 3, pp. 181, doi:10.22331/q-2019-09-02-181.
  7. Sergey Bravyi, Graeme Smith & John A. Smolin (2016): Trading classical and quantum computational resources. Physical Review X 6(2), pp. 021043, doi:10.1103/PhysRevX.6.021043.
  8. Tristan Cam & Simon Martiel (2023): Speeding up quantum circuits simulation using ZX-Calculus. arXiv preprint arXiv:2305.02669.
  9. Julien Codsi (2022): Cutting-Edge Graphical Stabiliser Decompositions for Classical Simulation of Quantum Circuits. University of Oxford. Available at https://www.cs.ox.ac.uk/people/aleks.kissinger/theses/codsi-thesis.pdf.
  10. Julien Codsi & John van de Wetering (2022): Classically Simulating Quantum Supremacy IQP Circuits trough a Random Graph Approach. arXiv preprint arXiv:2212.08609.
  11. Bob Coecke & Ross Duncan (2011): Interacting quantum observables: categorical algebra and diagrammatics. New Journal of Physics 13, pp. 043016, doi:10.1088/1367-2630/13/4/043016.
  12. Bob Coecke & Aleks Kissinger (2017): Picturing Quantum Processes. Cambridge University Press, doi:10.1017/9781316219317.
  13. Alexander Cowtan, Silas Dilkes, Ross Duncan, Will Simmons & Seyon Sivarajah (2020): Phase Gadget Synthesis for Shallow Circuits. In: Bob Coecke & Matthew Leifer: Proceedings 16th International Conference on Quantum Physics and Logic, Chapman University, Orange, CA, USA., 10-14 June 2019, Electronic Proceedings in Theoretical Computer Science 318. Open Publishing Association, pp. 213–228, doi:10.4204/EPTCS.318.13.
  14. Ross Duncan, Aleks Kissinger, Simon Perdrix & John van de Wetering (2020): Graph-theoretic Simplification of Quantum Circuits with the ZX-calculus. Quantum 4, pp. 279, doi:10.22331/q-2020-06-04-279.
  15. Stefano Gogioso & Richie Yeung (2023): Annealing Optimisation of Mixed ZX Phase Circuits. In: Stefano Gogioso & Matty Hoban: Proceedings 19th International Conference on Quantum Physics and Logic, Wolfson College, Oxford, UK, 27 June - 1 July 2022, Electronic Proceedings in Theoretical Computer Science 394. Open Publishing Association, pp. 415–431, doi:10.4204/EPTCS.394.20.
  16. Aleks Kissinger & John van de Wetering: PyZX. Available at https://github.com/Quantomatic/pyzx.
  17. Aleks Kissinger & John van de Wetering (2020): PyZX: Large Scale Automated Diagrammatic Reasoning. In: Bob Coecke & Matthew Leifer: Proceedings 16th International Conference on Quantum Physics and Logic, Chapman University, Orange, CA, USA., 10-14 June 2019, Electronic Proceedings in Theoretical Computer Science 318. Open Publishing Association, pp. 229–241, doi:10.4204/EPTCS.318.14.
  18. Aleks Kissinger & John van de Wetering (2020): Reducing the number of non-Clifford gates in quantum circuits. Physical Review A 102(2), doi:10.1103/physreva.102.022406.
  19. Aleks Kissinger & John van de Wetering (2022): Simulating quantum circuits with ZX-calculus reduced stabiliser decompositions. Quantum Science and Technology 7(4), pp. 044001, doi:10.1088/2058-9565/ac5d20.
  20. Aleks Kissinger & John van de Wetering (2023): Picturing Quantum Software [Preprint].
  21. Aleks Kissinger, John van de Wetering & Renaud Vilmart (2022): Classical Simulation of Quantum Circuits with Partial and Graphical Stabiliser Decompositions. In: François Le Gall & Tomoyuki Morimae: 17th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2022), Leibniz International Proceedings in Informatics (LIPIcs) 232. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl, Germany, pp. 5:1–5:13, doi:10.4230/LIPIcs.TQC.2022.5.
  22. Mark Koch, Richie Yeung & Quanlong Wang (2023): Speedy Contraction of ZX Diagrams with Triangles via Stabiliser Decompositions. arXiv preprint arXiv:2307.01803.
  23. Tommy McElvanney & Miriam Backens (2023): Flow-preserving ZX-calculus Rewrite Rules for Optimisation and Obfuscation. In: Shane Mansfield, Benoit Valîron & Vladimir Zamdzhiev: Proceedings of the Twentieth International Conference on Quantum Physics and Logic, Paris, France, 17-21st July 2023, Electronic Proceedings in Theoretical Computer Science 384. Open Publishing Association, pp. 203–219, doi:10.4204/EPTCS.384.12.
  24. Maximilian Nägele & Florian Marquardt (2023): Optimizing ZX-Diagrams with Deep Reinforcement Learning. arXiv preprint arXiv:2311.18588.
  25. John Preskill (2018): Quantum Computing in the NISQ era and beyond. Quantum 2, pp. 79, doi:10.22331/q-2018-08-06-79.
  26. Hammam Qassim, Hakop Pashayan & David Gosset (2021): Improved upper bounds on the stabilizer rank of magic states. Quantum 5, pp. 606, doi:10.22331/q-2021-12-20-606.
  27. Matthew Sutcliffe: ParamZX. Available at https://github.com/mjsutcliffe99/ParamZX.
  28. Matthew Sutcliffe: ProcOptCut. Available at https://github.com/mjsutcliffe99/ProcOptCut.
  29. Matthew Sutcliffe & Aleks Kissinger (2024): Fast classical simulation of quantum circuits via parametric rewriting in the ZX-calculus [Preprint].
  30. John van de Wetering (2020): ZX-calculus for the working quantum computer scientist, doi:10.48550/arXiv.2012.13966.
  31. Robert Wille, Lukas Burgholzer, Stefan Hillmich, Thomas Grurl, Alexander Ploier & Tom Peham (2022): The Basis of Design Tools for Quantum Computing: Arrays, Decision Diagrams, Tensor Networks, and ZX-Calculus. In: Proceedings of the 59th ACM/IEEE Design Automation Conference, DAC '22. Association for Computing Machinery, New York, NY, USA, pp. 1367–1370, doi:10.1145/3489517.3530627.
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