Skip to main content

Efficient Implementation of LIMDDs for Quantum Circuit Simulation

  • Conference paper
  • First Online:
Model Checking Software (SPIN 2023)

Abstract

Realizing the promised advantage of quantum computers over classical computers requires both physical devices and corresponding methods for the design, verification and analysis of quantum circuits. In this regard, decision diagrams have proven themselves to be an indispensable tool due to their capability to represent both quantum states and unitaries (circuits) compactly. Nonetheless, recent results show that decision diagrams can grow to exponential size even for the ubiquitous stabilizer states, which are generated by Clifford circuits. Since Clifford circuits can be efficiently simulated classically, this is surprising. Moreover, since Clifford circuits play a crucial role in many quantum computing applications, from networking, to error correction, this limitation forms a major obstacle for using decision diagrams for the design, verification and analysis of quantum circuits. The recently proposed Local Invertible Map Decision Diagram (LIMDD) solves this problem by combining the strengths of decision diagrams and the stabilizer formalism that enables efficient simulation of Clifford circuits. However, LIMDDs have only been introduced on paper thus far and have not been implemented yet—preventing an investigation of their practical capabilities through experiments. In this work, we present the first implementation of LIMDDs for quantum circuit simulation. A case study confirms the improved performance in both worlds for the Quantum Fourier Transform applied to a stabilizer state. The resulting package is available under a free license at https://github.com/cda-tum/ddsim/tree/limdd.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Symposium on Theory of Computing, pp. 212–219 (1996). https://doi.org/10.1145/237814.237866

  2. Montanaro, A.: Quantum-walk speedup of backtracking algorithms. Theor. Comput. 14(1), 1–24 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  3. Ambainis, A., Gilyén, A., Jeffery, S., Kokainis, M.: Quadratic speedup for finding marked vertices by quantum walks. In: Symposium on Theory of Computing, pp. 412–424 (2020)

    Google Scholar 

  4. Shor, P.W.: Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM J. Comp. 26(5), 1484–1509 (1997). https://doi.org/10.1137/S0097539795293172

    Article  MathSciNet  MATH  Google Scholar 

  5. Lanyon, B.P., et al.: Towards quantum chemistry on a quantum computer. Nat. Chem. 2(2), 106 (2010)

    Article  Google Scholar 

  6. Burgholzer, L., Kueng, R., Wille, R.: Random stimuli generation for the verification of quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 767–772, New York, NY, USA,: Association for Computing Machinery. ISBN 9781450379991 (2021)

    Google Scholar 

  7. Burgholzer, L., Wille, R.: Advanced equivalence checking for quantum circuits. IEEE Trans. on CAD Integr. Circ. Sys., 40(9):1810–1824 (2021). https://doi.org/10.1109/TCAD.2020.3032630

  8. Burgholzer, L., Raymond, R., Wille, R.: Verifying results of the IBM Qiskit quantum circuit compilation flow. In: 2020 IEEE International Conference on Quantum Computing and Engineering (QCE), pp. 356–365. IEEE (2020)

    Google Scholar 

  9. Carette, J., Ortiz, G., Sabry, A.: Symbolic execution of hadamard-toffoli quantum circuits. In: Proceedings of the 2023 ACM SIGPLAN International Workshop on Partial Evaluation and Program Manipulation, pp. 14–26 (2023)

    Google Scholar 

  10. Guerreschi, G.G., Matsuura, A.Y.: Qaoa for max-cut requires hundreds of qubits for quantum speed-up. Scientific Reports, 9(1), 6903 (2019). ISSN 2045–2322. https://doi.org/10.1038/s41598-019-43176-9

  11. Jones, T., Brown, A., Bush, I., Benjamin, S.C.: Quest and high performance simulation of quantum computers. Scientific Reports, 9(1), 10736 (2019). ISSN 2045–2322. https://doi.org/10.1038/s41598-019-47174-9

  12. Gottesman, D.: Stabilizer codes and quantum error correction (1997)

    Google Scholar 

  13. Aaronson, S., Gottesman, D.: Improved simulation of stabilizer circuits. Phys. Rev. A 70(5), 052328 (2004)

    Article  Google Scholar 

  14. Gottesman, D.: Theory of fault-tolerant quantum computation. Phys. Rev. A 57, 127–137 (1998)

    Article  Google Scholar 

  15. Gottesman, D.: Stabilizer codes and quantum error correction. California Institute of Technology (1997)

    Google Scholar 

  16. Bennett, C.H., Bernstein, H.J., Popescu, S., Schumacher, B.: Concentrating partial entanglement by local operations. Phys. Rev. A, 53, (1996). https://doi.org/10.1103/PhysRevA.53.2046

  17. Browne, D., Briegel, H.: One-way quantum computation. Quantum information: From foundations to quantum technology applications, pp. 449–473 (2016)

    Google Scholar 

  18. Dijk, T.M., Wille, R., Meolic, R.: Tagged BDDs: Combining reduction rules from different decision diagram types. In: Stewart, D., Weissenbacher, G., editors, Formal Methods in CAD, 2017. https://doi.org/10.23919/FMCAD.2017.8102248

  19. Minato, S.: Zero-suppressed BDDs for set manipulation in combinational problems. In: Design Automation Conference, pp. 272–277 (1993)

    Google Scholar 

  20. Bryant, R.E.: Symbolic manipulation of Boolean functions using a graphical representation. In: Design Automation Conference, pp. 688–694 (1985)

    Google Scholar 

  21. Bryant, R.E., Chen, Y.A.: Verification of arithmetic circuits with binary moment diagrams. In: Design Automation Conference, pp. 535–541 (1995)

    Google Scholar 

  22. Drechsler, R., Sarabi, A., Theobald, M., Becker, B., Perkowski, M.A.: Efficient representation and manipulation of switching functions based on Ordered Kronecker Functional Decision Diagrams. In: Lorenzetti, M.J., editor, Design Automation Conference, pp. 415–419 (1994). https://doi.org/10.1145/196244.196444

  23. Abdollahi, A., Pedram, M.: Analysis and synthesis of quantum circuits by using quantum decision diagrams. In: Design, Automation and Test in Europe, pp. 317–322 (2006)

    Google Scholar 

  24. Wang, S.-A., Lu, C.-Y., Tsai, I.-M., Kuo, S.-Y.: An XQDD-based verification method for quantum circuits. IEICE Trans. Fundamentals, 91-A(2), 584–594 (2008)

    Google Scholar 

  25. Viamontes, G.F., Markov, I.L., Hayes J.P.: Quantum Circuit Simulation. Springer (2009). ISBN 978-90-481-3064-1. https://doi.org/10.1007/978-90-481-3065-8

  26. Niemann, P., Wille, R., Miller, D.M., Thornton, M.A., Drechsler, R.: QMDDs: Efficient quantum function representation and manipulation. IEEE Trans. on CAD of Integr. Circ. Sys. 35(1), 86–99 (2016). https://doi.org/10.1109/TCAD.2015.2459034

  27. Vinkhuijzen, L., Coopmans, T., Elkouss, D., Dunjko, V., Laarman, A.: LIMDD: A decision diagram for simulation of quantum computing including stabilizer states. CoRR, abs/2108.00931, 2021. arxiv.org/abs/2108.00931

  28. Zulehner, A., Hillmich, S., Wille, R.: How to efficiently handle complex values? Implementing decision diagrams for quantum computing. In: David Z. Pan, editor, International Conference on CAD, pp. 1–7, 2019. https://doi.org/10.1109/ICCAD45719.2019.8942057

  29. Miller, D.M., Thornton, M.A.: QMDD: A decision diagram structure for reversible and quantum circuits. In: 36th International Symposium on Multiple-Valued Logic (ISMVL’06), pp. 30–30. IEEE (2006)

    Google Scholar 

  30. Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information (10th Anniversary edition). Cambridge University Press (2016). ISBN 978-1-10-700217-3. www.cambridge.org/de/academic/subjects/physics/quantum-physics-quantum-information-and-quantum-computation/quantum-computation-and-quantum-information-10th-anniversary-edition?format=HB

  31. Jozsa, R.: Quantum algorithms and the fourier transform. Royal Society London. Series A 454(1969), 323–337 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  32. Kueng, R., Gross, D.: Qubit stabilizer states are complex projective 3-designs. arXiv preprint arXiv:1510.02767 (2015)

  33. Zulehner, A., Wille, R.: Advanced simulation of quantum computations. IEEE Trans. on CAD of Integr. Circ. and Sys. 38(5), 848–859 (2019). https://doi.org/10.1109/TCAD.2018.2834427

  34. Somenzi, F.: CUDD: CU decision diagram package release 3.0.0. http://www.vlsi.colorado.edu/~fabio/

  35. Van Dijk, T., Laarman, A., Van De Pol, J.: Multi-core BDD operations for symbolic reachability. Electronic Notes Theor. Comput. Sci. 296, 127–143 (2013)

    Article  Google Scholar 

  36. Lv, G., Chen, Y., Feng, Y., Chen, Q.L., Su, K.: A succinct and efficient implementation of a \(2^{32}\) BDD package. In: Margaria, T., Qiu, Z., Yang, H., eds, International Symposium on Theoretical Aspects of Software Engineering, pp. 241–244, 2012. https://doi.org/10.1109/TASE.2012.22

  37. Herbstritt, M.: wld: A C++ library for decision diagrams. http://www.ira.informatik.uni-freiburg.de/software/wld/ (2004)

  38. Knuth, D.E.: The art of computer programming: Binary decision diagrams. http://www-cs-faculty.stanford.edu/knuth/programs.html (2011)

  39. Brace, K.S., Rudell, R.L., Bryant, R.E.: Efficient implementation of a BDD package. In: Smith, R.C., editor, Design Automation Conference, pp. 40–45, 1990. https://doi.org/10.1145/123186.123222

  40. Hillmich, S., Markov, I.L., Wille, R.: Just like the real thing: Fast weak simulation of quantum computation. In: Design Automation Conference, pp. 1–6. IEEE (2020). https://doi.org/10.1109/DAC18072.2020.9218555

  41. Wille, R., Hillmich, S., Burgholzer, L.: JKQ: JKU tools for quantum computing. In Int’l Conference on CAD, pp. 154:1–154:5 (2020). https://doi.org/10.1145/3400302.3415746

Download references

Acknowledgment

This work received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101001318) and was part of the Munich Quantum Valley, which is supported by the Bavarian state government with funds from the Hightech Agenda Bayern Plus.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lieuwe Vinkhuijzen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vinkhuijzen, L., Grurl, T., Hillmich, S., Brand, S., Wille, R., Laarman, A. (2023). Efficient Implementation of LIMDDs for Quantum Circuit Simulation. In: Caltais, G., Schilling, C. (eds) Model Checking Software. SPIN 2023. Lecture Notes in Computer Science, vol 13872. Springer, Cham. https://doi.org/10.1007/978-3-031-32157-3_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-32157-3_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-32156-6

  • Online ISBN: 978-3-031-32157-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics