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An exact qubit allocation approach for NISQ architectures

Published: 01 November 2020 Publication History

Abstract

The noisy intermediate-scale quantum (NISQ) devices that have just emerged in recent years provide an opportunity for the physical realization of quantum circuits. As the first step of mapping quantum circuits to these devices, qubit allocation imposes a great impact on the number of additional quantum operations required throughout the mapping. The global optimization of qubit allocation is NP-hard, but since many current NISQ devices have very few qubits, it is possible to solve this problem exactly. In this paper, we propose an exact approach for qubit allocation, which takes advantage of the branch and bound algorithm as the basic framework. In order to further prune the considerably huge state space, three techniques have been proposed and integrated into the exact approach, including an optimized lower bound for quadratic assignment problem, prioritization of logical qubits, and branch pruning by structural symmetry of physical qubits. Moreover, based on the multiple optimal solutions obtained by the exact approach, we give an error-aware qubit allocation method. For problems that are too large to be solved by the exact approach, we also give a heuristic qubit allocation approach with polynomial time complexity. Experimental evaluations show that the exact approach proposed in this paper is feasible for the qubit allocation of current NISQ architectures. For all benchmarks considered, this exact approach can find multiple optimal solutions to the qubit allocation problem on IBM Melbourne, a 16-qubit NISQ architecture, in no more than 20 min. It can serve as a evaluation baseline of any heuristic approach. Experimental evaluations also show that the proposed heuristic approach is near-optimal in terms of routing cost. Both the exact approach and the heuristic approach can be integrated into existing quantum circuit mapping approaches.

References

[1]
Abdelbasset, M., Manogaran, G., Rashad, H., Zaied, A.N.H.: A comprehensive review of quadratic assignment problem: variants, hybrids and applications. J. Ambient Intell. Humaniz. Comput. (2018).
[2]
Arute F, Arya K, Babbush R, Bacon D, Bardin JC, Barends R, Biswas R, Boixo S, Brandao FGSL, Buell DA, et al. Quantum supremacy using a programmable superconducting processor Nature 2019 574 7779 505-510
[3]
Ash-Saki, A., Alam, M., Ghosh, S.: Qure: Qubit re-allocation in noisy intermediate-scale quantum computers. In: Proceedings of the 56th Annual Design Automation Conference 2019, pp. 1–6 (2019)
[4]
Chiesa A, Tacchino F, Grossi M, Santini P, Tavernelli I, Gerace D, and Carretta S Quantum hardware simulating four-dimensional inelastic neutron scattering Nat. Phys. 2019 15 5 455-459
[5]
Ganzhorn M, Egger D, Barkoutsos P, Ollitrault P, Salis G, Moll N, Roth M, Fuhrer A, Mueller P, Woerner S, et al. Gate-efficient simulation of molecular eigenstates on a quantum computer Phys. Rev. Appl. 2019 11 4 044092
[6]
Hahn P and Grant T Lower bounds for the quadratic assignment problem based upon a dual formulation Oper. Res. 1998 46 6 912-922
[7]
Havlicek V, Corcoles A, Temme K, Harrow AW, Kandala A, Chow JM, and Gambetta JM Supervised learning with quantum-enhanced feature spaces Nature 2019 567 7747 209-212
[8]
IBM: Defining the future of computing, again. https://www.ibm.com/quantum-computing/technology/systems. Accessed 20 April 2020
[9]
IBM: Quantum experience. https://quantum-computing.ibm.com/. Accessed: 20 April 2020
[10]
Kissinger, A., De Griend, A.M.: CNOT circuit extraction for topologically-constrained quantum memories. (2019). arXiv:1904.00633
[11]
Kole A, Datta K, and Sengupta I A heuristic for linear nearest neighbor realization of quantum circuits by swap gate insertion using n -gate lookahead IEEE J. Emerg. Sel. Topics Circuits Syst. 2016 6 1 62-72
[12]
Kole A, Datta K, and Sengupta I A new heuristic for n-dimensional nearest neighbor realization of a quantum circuit IEEE Trans. Comput.-Aided. Des. Integr. Circuits Syst. 2018 37 1 182-192
[13]
Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto NISQ superconducting processors. (2019). arXiv:1908.04226
[14]
Lao L, Wee Bv, Ashraf I, Someren Jv, Khammassi N, Bertels K, and Almudever CG Mapping of lattice surgery-based quantum circuits on surface code architectures Quantum Sci. Technol. 2018 4 1 015005
[15]
Li, G., Ding, Y., Xie, Y.: Tackling the qubit mapping problem for nisq-era quantum devices. In: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems (2019)
[16]
Loiola EM, De Abreu NMM, Boaventuranetto PO, Hahn PM, and Querido T A survey for the quadratic assignment problem Eur. J. Oper. Res. 2007 176 2 657-690
[17]
Mautor T and Roucairol C A new exact algorithm for the solution of quadratic assignment problems Discrete Appl. Math. 1994 55 3 281-293
[18]
Murali, P., Baker, J.M., Javadi-Abhari, A., Chong, F.T., Martonosi, M.: Noise-adaptive compiler mappings for noisy intermediate-scale quantum computers. In: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1015–1029 (2019)
[19]
Nash B, Gheorghiu V, and Mosca M Quantum circuit optimizations for nisq architectures Quantum Sci. Technol. 2020 5 2 025010
[20]
Nielsen MA and Chuang I Quantum Computation and Quantum Information 2011 10 Cambridge Cambridge University Press
[21]
Nishio S, Pan Y, Satoh T, Amano H, and Meter RV Extracting success from ibm’s 20-qubit machines using error-aware compilation ACM J. Emerg. Technol. Comput. Syst. (JETC) 2020 16 3 1-25
[22]
Paler, A.: On the influence of initial qubit placement during nisq circuit compilation. Lecture Notes in Computer Science, pp. 207–217 (2019)
[23]
Preskill J Quantum computing in the nisq era and beyond Bull. Am. Phys. Soc. 2018 2 79-98
[24]
Siraichi, M.Y., Santos, V.F.D., Collange, S.: Qubit allocation. In: Proceedings of the 2018 International Symposium on Code Generation and Optimization, pp. 113–125 (2018)
[25]
Wikipedia: Branch and bound. http://en.wikipedia.org/wiki/Branch_and_bound. Accessed 23 April 2020
[26]
Wille R, Lye A, and Drechsler R Exact reordering of circuit lines for nearest neighbor quantum architectures IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 2014 33 12 1818-1831
[27]
Zhou, X., Li, S., Feng, Y.: Quantum circuit transformation based on simulated annealing and heuristic search. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. (2020).
[28]
Zhu, P.: Resources of exact qubit allocation. https://github.com/joyofly/ExactQubitAllocation. Accessed 23 April 2020
[29]
Zhu, P., Guan, Z., Cheng, X.: A dynamic look-ahead heuristic for the qubit mapping problem of nisq computers. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. (2020).
[30]
Zulehner A, Paler A, and Wille R An efficient methodology for mapping quantum circuits to the ibm qx architectures IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 2019 38 7 1226-1236

Cited By

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  • (2022)Optimal Qubit Assignment and Routing via Integer ProgrammingACM Transactions on Quantum Computing10.1145/35445634:1(1-31)Online publication date: 21-Oct-2022
  • (2022)Quantum Circuit Transformation: A Monte Carlo Tree Search FrameworkACM Transactions on Design Automation of Electronic Systems10.1145/351423927:6(1-27)Online publication date: 27-Jun-2022
  • (2022)Limiting the Search Space in Optimal Quantum Circuit MappingProceedings of the 27th Asia and South Pacific Design Automation Conference10.1109/ASP-DAC52403.2022.9712555(466-471)Online publication date: 17-Jan-2022

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        Published In

        cover image Quantum Information Processing
        Quantum Information Processing  Volume 19, Issue 11
        Nov 2020
        459 pages

        Publisher

        Kluwer Academic Publishers

        United States

        Publication History

        Published: 01 November 2020
        Accepted: 20 October 2020
        Received: 23 April 2020

        Author Tags

        1. Quantum circuit
        2. Qubit allocation
        3. Exact approach
        4. Noisy intermediate-scale quantum (NISQ)
        5. Quantum circuit mapping

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        View all
        • (2022)Optimal Qubit Assignment and Routing via Integer ProgrammingACM Transactions on Quantum Computing10.1145/35445634:1(1-31)Online publication date: 21-Oct-2022
        • (2022)Quantum Circuit Transformation: A Monte Carlo Tree Search FrameworkACM Transactions on Design Automation of Electronic Systems10.1145/351423927:6(1-27)Online publication date: 27-Jun-2022
        • (2022)Limiting the Search Space in Optimal Quantum Circuit MappingProceedings of the 27th Asia and South Pacific Design Automation Conference10.1109/ASP-DAC52403.2022.9712555(466-471)Online publication date: 17-Jan-2022

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