Quantum Circuit Compiler for a Shuttling-Based Trapped-Ion Quantum Computer

Fabian Kreppel1, Christian Melzer2, Diego Olvera Millán2, Janis Wagner2, Janine Hilder2, Ulrich Poschinger2, Ferdinand Schmidt-Kaler2, and André Brinkmann1

1Institute of Computer Science, Johannes Gutenberg University, Staudingerweg 9, 55128 Mainz, Germany
2Institute of Physics, Johannes Gutenberg University, Staudingerweg 7, 55128 Mainz, Germany

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The increasing capabilities of quantum computing hardware and the challenge of realizing deep quantum circuits require fully automated and efficient tools for compiling quantum circuits. To express arbitrary circuits in a sequence of native gates specific to the quantum computer architecture, it is necessary to make algorithms portable across the landscape of quantum hardware providers. In this work, we present a compiler capable of transforming and optimizing a quantum circuit targeting a shuttling-based trapped-ion quantum processor. It consists of custom algorithms set on top of the quantum circuit framework Pytket. The performance was evaluated for a wide range of quantum circuits and the results show that the gate counts can be reduced by factors up to 5.1 compared to standard Pytket and up to 2.2 compared to standard Qiskit compilation.

Several quantum computing platforms have been developed in recent years. One promising candidate for quantum computing is based on trapped ions. These particles are naturally perfectly identical and can be used to encode stable qubits. The ions are trapped in electric fields and manipulated by lasers. One way to scale such quantum devices is not to store all the ions in one large group, but to have many small groups that can be moved around to allow the ions to interact with each other.

To run an arbitrary algorithm on such a quantum computer, the quantum circuit describing the gate sequence to be executed must be translated into instructions which the quantum computer understands. This is similar to compiling code of a high-level language into assembler code for classical computers. Just as different processors of classical computers have different instruction sets and components, which a compiler must address during compilation, different quantum computers have different native gates and properties that can be exploited to improve the accuracy of the result.

In our paper, we present a quantum circuit compiler, which transforms a given quantum circuit into the native gate set of a trapped-ion quantum computer and performs optimizations on the code to increase the accuracy of the result. Such optimizations include various ways of reducing the number of gates performed, as well as rearranging them so that the circuit has more favorable properties, such as less ion movement.

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[1] F. Arute et al. ``Quantum supremacy using a programmable superconducting processor''. Nature 574, 505–510 (2019).

[2] L. Postler et al. ``Demonstration of fault-tolerant universal quantum gate operations''. Nature 605, 675–680 (2022). arXiv:2111.12654.

[3] L. Egan et al. ``Fault-tolerant control of an error-corrected qubit''. Nature 598, 281–286 (2021).

[4] J. Preskill. ``Quantum Computing in the NISQ era and beyond''. Quantum 2, 79 (2018). arXiv:1801.00862.

[5] D. Kielpinski, C. Monroe, and D. J. Wineland. ``Architecture for a large-scale ion-trap quantum computer''. Nature 417, 709 (2002).

[6] V. Kaushal et al. ``Shuttling-based trapped-ion quantum information processing''. AVS Quantum Science 2, 014101 (2020). arXiv:1912.04712.

[7] J. M. Pino et al. ``Demonstration of the trapped-ion quantum CCD computer architecture''. Nature 592, 209–213 (2021).

[8] P. Murali, D. M. Debroy, K. R. Brown, and M. Martonosi. ``Architecting Noisy Intermediate-Scale Trapped Ion Quantum Computers''. In Proceedings of the ACM/​IEEE 47th Annual International Symposium on Computer Architecture. Page 529–542. ISCA '20. IEEE Press (2020). arXiv:2004.04706.

[9] J. Hilder et al. ``Fault-Tolerant Parity Readout on a Shuttling-Based Trapped-Ion Quantum Computer''. Phys. Rev. X 12, 011032 (2022). arXiv:2107.06368.

[10] J. Wagner. ``Automated generation of shuttling schedules for a scalable trapped-ion quantum processor''. Master's thesis. Johannes Gutenberg University Mainz. (2022).

[11] J. Durandau. ``Automated Generation of Shuttling Sequences for a Linear Segmented Ion Trap Quantum Computer'' (2022). arXiv:2208.04881.

[12] A. A. Saki, R. O. Topaloglu, and S. Ghosh. ``Muzzle the Shuttle: Efficient Compilation for Multi-Trap Trapped-Ion Quantum Computers''. In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE). Pages 322–327. (2022). arXiv:2111.07961.

[13] T. Schmale et al. ``Backend compiler phases for trapped-ion quantum computers''. In 2022 IEEE International Conference on Quantum Software (QSW). Pages 32–37. Los Alamitos, CA, USA (2022). IEEE Computer Society. arXiv:2206.00544.

[14] M. Webber, S. Herbert, S. Weidt, and W. K. Hensinger. ``Efficient Qubit Routing for a Globally Connected Trapped Ion Quantum Computer''. Advanced Quantum Technologies 3, 2000027 (2020). arXiv:2002.12782.

[15] S. Sivarajah et al. ``t$\vert$ket$\rangle$: a retargetable compiler for NISQ devices''. Quantum Science and Technology 6, 014003 (2020). arXiv:2003.10611.

[16] V. Bergholm et al. ``PennyLane: Automatic differentiation of hybrid quantum-classical computations'' (2018). arXiv:1811.04968.

[17] R. Wille, R. Van Meter, and Y. Naveh. ``IBM’s Qiskit Tool Chain: Working with and Developing for Real Quantum Computers''. In 2019 Design, Automation Test in Europe Conference Exhibition (DATE). Pages 1234–1240. (2019).

[18] E. A. Martinez, T. Monz, D. Nigg, P. Schindler, and R. Blatt. ``Compiling quantum algorithms for architectures with multi-qubit gates''. New J. Phys. 18, 063029 (2016). arXiv:1601.06819.

[19] T. Nguyen et al. ``Quantum Circuit Transformations with a Multi-Level Intermediate Representation Compiler'' (2021). arXiv:2112.10677.

[20] D. Maslov. ``Basic circuit compilation techniques for an ion-trap quantum machine''. New J. Phys. 19, 023035 (2017). arXiv:1603.07678.

[21] B. Coecke and R. Duncan. ``Interacting quantum observables: categorical algebra and diagrammatics''. New J. Phys. 13, 043016 (2011). arXiv:0906.4725.

[22] X. Zhou, S. Li, and Y. Feng. ``Quantum Circuit Transformation Based on Simulated Annealing and Heuristic Search''. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 39, 4683–4694 (2020). arXiv:1908.08853.

[23] A. Zulehner, A. Paler, and R. Wille. ``An Efficient Methodology for Mapping Quantum Circuits to the IBM QX Architectures''. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 38, 1226–1236 (2019). arXiv:1712.04722.

[24] A. Cowtan et al. ``On the Qubit Routing Problem''. In 14th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2019). Volume 135 of Leibniz International Proceedings in Informatics (LIPIcs), pages 5:1–5:32. Dagstuhl, Germany (2019). Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik. arXiv:1902.08091.

[25] G. Li, Y. Ding, and Y. Xie. ``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, ASPLOS. Pages 1001–1014. ACM (2019). arXiv:1809.02573.

[26] F. Zilk et al. ``A compiler for universal photonic quantum computers''. In 2022 IEEE/​ACM Third International Workshop on Quantum Computing Software (QCS). Pages 57–67. Los Alamitos, CA, USA (2022). IEEE Computer Society. arXiv:2210.09251.

[27] Y. Shi et al. ``Optimized Compilation of Aggregated Instructions for Realistic Quantum Computers''. In Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems. Page 1031–1044. ASPLOS '19New York, NY, USA (2019). Association for Computing Machinery. arXiv:1902.01474.

[28] J. van de Wetering. ``ZX-calculus for the working quantum computer scientist'' (2020). arXiv:2012.13966.

[29] Quantinuum Ltd. ``Extension Modules''. url: https:/​/​cqcl.github.io/​pytket-extensions/​api/​index.html. (accessed: 2023-10-25).

[30] A. Y. Kitaev. ``Quantum computations: algorithms and error correction''. Russian Mathematical Surveys 52, 1191–1249 (1997).

[31] C. M. Dawson and M. A. Nielsen. ``The Solovay-Kitaev algorithm''. Quantum Information and Computation 6, 81–95 (2006). arXiv:quant-ph/​0505030.

[32] A. Sørensen and K. Mølmer. ``Quantum Computation with Ions in Thermal Motion''. Phys. Rev. Lett. 82, 1971–1974 (1999). arXiv:quant-ph/​9810039.

[33] H. Kaufmann et al. ``Fast ion swapping for quantum-information processing''. Phys. Rev. A 95, 052319 (2017). arXiv:1607.03734.

[34] H. Kaufmann, T. Ruster, C. T. Schmiegelow, F. Schmidt-Kaler, and U. G. Poschinger. ``Dynamics and control of fast ion crystal splitting in segmented Paul traps''. New J. Phys. 16, 073012 (2014). arXiv:1403.0097.

[35] M. W. van Mourik et al. ``Coherent rotations of qubits within a surface ion-trap quantum computer''. Phys. Rev. A 102, 022611 (2020). arXiv:2001.02440.

[36] Quantinuum Ltd. ``pytket.circuit.OpType — pytket 1.21.0 documentation''. url: https:/​/​cqcl.github.io/​tket/​pytket/​api/​optype.html. (accessed: 2023-10-25).

[37] M. A. Nielsen and I. L. Chuang. ``Quantum Computation and Quantum Information: 10th Anniversary Edition''. Pages 216–247. Cambridge University Press. (2010).

[38] A. Fagan and R. Duncan. ``Optimising Clifford Circuits with Quantomatic''. Electronic Proceedings in Theoretical Computer Science 287, 85–105 (2019). arXiv:1901.10114.

[39] R. R. Tucci. ``An Introduction to Cartan's KAK Decomposition for QC Programmers'' (2005). arXiv:QUANT-PH/​0507171.

[40] Quantinuum Ltd. ``Pytket User Manual – Compilation''. url: https:/​/​cqcl.github.io/​pytket/​manual/​manual_compiler.html#predefined-sequences. (accessed: 2023-10-25).

[41] D. C. McKay, C. J. Wood, S. Sheldon, J. M. Chow, and J. M. Gambetta. ``Efficient $Z$ gates for quantum computing''. Phys. Rev. A 96, 022330 (2017). arXiv:1612.00858.

[42] J. Biamonte et al. ``Quantum machine learning''. Nature 549, 195–202 (2017). arXiv:1611.09347.

[43] M. Cerezo et al. ``Variational quantum algorithms''. Nature Reviews Physics 3, 625–644 (2021). arXiv:2012.09265.

[44] A. Edgington et al. (2021). code: CQCL/​pytket commit:8867249.

[45] A. Anand et al. ``A quantum computing view on unitary coupled cluster theory''. Chem. Soc. Rev. 51, 1659–1684 (2022). arXiv:2109.15176.

[46] J. Tilly et al. ``The Variational Quantum Eigensolver: A review of methods and best practices''. Physics Reports 986, 1–128 (2022). arXiv:2111.05176.

[47] Z. Xiangzhen (2019). code: BensonZhou1991/​circuittransform commit:8e6e5b1.

[48] N. Moll et al. ``Quantum optimization using variational algorithms on near-term quantum devices''. Quantum Science and Technology 3, 030503 (2018). arXiv:1710.01022.

[49] S. Boixo et al. ``Characterizing quantum supremacy in near-term devices''. Nature Phys 14, 595–600 (2018). arXiv:1608.00263.

[50] S. Boixo (2019). code: sboixo/​GRCS commit:f4981a7.

[51] A. W. Cross, L. S. Bishop, S. Sheldon, P. D. Nation, and J. M. Gambetta. ``Validating quantum computers using randomized model circuits''. Phys. Rev. A 100, 032328 (2019). arXiv:1811.12926.

[52] T. Tomesh and G. Contreras (2021). code: teaguetomesh/​quantum_circuit_generator commit:0225dc5.

[53] I. Pogorelov et al. ``Compact Ion-Trap Quantum Computing Demonstrator''. PRX Quantum 2, 020343 (2021). arXiv:2101.11390.

[54] Y. Shapira et al. ``Theory of robust multiqubit nonadiabatic gates for trapped ions''. Phys. Rev. A 101, 032330 (2020). arXiv:1911.03073.

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[6] Remmy Zen, Jan Olle, Luis Colmenarez, Matteo Puviani, Markus Müller, and Florian Marquardt, "Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning", arXiv:2402.17761, (2024).

[7] Hanrui Wang, Daniel Bochen Tan, Pengyu Liu, Yilian Liu, Jiaqi Gu, Jason Cong, and Song Han, "Q-Pilot: Field Programmable Qubit Array Compilation with Flying Ancillas", arXiv:2311.16190, (2023).

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