Letter | Published:

Demonstration of a small programmable quantum computer with atomic qubits

Nature volume 536, pages 6366 (04 August 2016) | Download Citation


Quantum computers can solve certain problems more efficiently than any possible conventional computer. Small quantum algorithms have been demonstrated on multiple quantum computing platforms, many specifically tailored in hardware to implement a particular algorithm or execute a limited number of computational paths1,2,3,4,5,6,7,8,9,10. Here we demonstrate a five-qubit trapped-ion quantum computer that can be programmed in software to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates. We compile algorithms into a fully connected set of gate operations that are native to the hardware and have a mean fidelity of 98 per cent. Reconfiguring these gate sequences provides the flexibility to implement a variety of algorithms without altering the hardware. As examples, we implement the Deutsch–Jozsa11 and Bernstein–Vazirani12 algorithms with average success rates of 95 and 90 per cent, respectively. We also perform a coherent quantum Fourier transform13,14 on five trapped-ion qubits for phase estimation and period finding with average fidelities of 62 and 84 per cent, respectively. This small quantum computer can be scaled to larger numbers of qubits within a single register, and can be further expanded by connecting several such modules through ion shuttling15 or photonic quantum channels16.

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  1. 1.

    , & An implementation of the Deutsch-Jozsa algorithm on a three-qubit NMR quantum computer. Chem. Phys. Lett. 296, 61–67 (1998)

  2. 2.

    et al. Experimental realization of Shor’s quantum factoring algorithm using nuclear magnetic resonance. Nature 414, 883–887 (2001)

  3. 3.

    et al. Implementation of the Deutsch-Jozsa algorithm on an ion-trap quantum computer. Nature 421, 48–50 (2003)

  4. 4.

    et al. Fiber-optics implementation of the Deutsch-Jozsa and Bernstein-Vazirani quantum algorithms with three qubits. Phys. Rev. Lett. 90, 157902 (2003)

  5. 5.

    et al. Implementation of the semiclassical quantum Fourier transform in a scalable system. Science 308, 997–1000 (2005)

  6. 6.

    et al. Implementation of Grover’s quantum search algorithm in a scalable system. Phys. Rev. A 72, 050306(R) (2005)

  7. 7.

    et al. Demonstration of two-qubit algorithms with a superconducting quantum processor. Nature 460, 240–244 (2009)

  8. 8.

    et al. Room-temperature implementation of the Deutsch-Jozsa algorithm with a single electronic spin in diamond. Phys. Rev. Lett. 105, 040504 (2010)

  9. 9.

    et al. Experimental realization of Shor’s quantum factoring algorithm using qubit recycling. Nat. Photon. 6, 773–776 (2012)

  10. 10.

    et al. Realization of a scalable Shor algorithm. Science 351, 1068–1070 (2016)

  11. 11.

    & Rapid solution of problems by quantum computation. Proc. R. Soc. Lond. A 439, 553–558 (1992)

  12. 12.

    & Quantum complexity theory. SIAM J. Comput. 26, 1411–1473 (1997)

  13. 13.

    Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM J. Comput. 26, 1484–1509 (1997)

  14. 14.

    & Quantum Computation and Quantum Information 1st edn (Cambridge Univ. Press, 2002)

  15. 15.

    , & Architecture for a large-scale ion-trap quantum computer. Nature 417, 709–711 (2002)

  16. 16.

    et al. Large scale modular quantum computer architecture with atomic memory and photonic interconnects. Phys. Rev. A 89, 022317 (2014)

  17. 17.

    & Quantum computations with cold trapped ions. Phys. Rev. Lett. 74, 4091–4094 (1995)

  18. 18.

    & Multipartite entanglement of hot trapped ions. Phys. Rev. Lett. 82, 1835–1838 (1999)

  19. 19.

    et al. Superconducting quantum circuits at the surface code threshold for fault tolerance. Nature 508, 500–503 (2014)

  20. 20.

    et al. A surface code quantum computer in silicon. Sci. Adv. 1, e1500707 (2015)

  21. 21.

    Fault-tolerant quantum computation with local gates. J. Mod. Opt. 47, 333–345 (2000)

  22. 22.

    & Phase-modulated decoupling and error suppression in qubit-oscillator systems. Phys. Rev. Lett. 114, 120502 (2015)

  23. 23.

    et al. Laser-driven quantum logic gates with precision beyond the fault-tolerant threshold. Preprint at (2016)

  24. 24.

    et al. Demonstration of integrated microscale optics in surface-electrode ion traps. New J. Phys. 13, 103005 (2011)

  25. 25.

    et al. High-fidelity universal gate set for 9Be+ ion qubits. Preprint at (2016)

  26. 26.

    et al. Optimal quantum control of multimode couplings between trapped ion qubits for scalable entanglement. Phys. Rev. Lett. 112, 190502 (2014)

  27. 27.

    et al. Manipulation and detection of a trapped Yb+ hyperfine qubit. Phys. Rev. A 76, 052314 (2007)

  28. 28.

    , , & Accurate measurement of the 12.6GHz “clock” transition in trapped 171Yb+ ions. IEEE Trans. Ultrasonics Ferroelectrics Frequency 44, 344–354 (1997)

  29. 29.

    et al. Entanglement of atomic qubits using an optical frequency comb. Phys. Rev. Lett. 104, 140501 (2010)

  30. 30.

    , , , & Entanglement-free Heisenberg-limited phase estimation. Nature 450, 393–396 (2007)

  31. 31.

    et al. Active stabilization of ion trap radiofrequency potentials. Rev. Sci. Instrum. 87, 053110 (2016)

  32. 32.

    , , & Individual addressing of trapped 171Yb+ ion qubits using a microelectromechanical systems-based beam steering system. Appl. Phys. Lett. 105, 181115 (2014)

  33. 33.

    Phase transitions in anisotropically confined ionic crystals. Phys. Rev. Lett. 70, 818–821 (1993)

  34. 34.

    , & Trapped ion quantum computation with transverse phonon modes. Phys. Rev. Lett. 97, 050505 (2006)

  35. 35.

    , & Deterministic Bell states and measurement of the motional state of two trapped ions. Phys. Rev. A 59, R2539–R2543 (1999)

  36. 36.

    , & Ion trap quantum computing with warm ions. Fortschr. Phys. 48, 801–810 (2000)

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We thank K. R. Brown, J. Kim, T. Choi, Z.-X. Gong, T. A. Manning, D. Maslov and C. Volin for discussions. This work was supported by the US Army Research Office with funds from the IARPA MQCO and LogiQ Programs, the Air Force Office of Scientific Research MURI on Quantum Measurement and Verification, and the National Science Foundation Physics Frontier Center at JQI.

Author information


  1. Joint Quantum Institute, Department of Physics, University of Maryland, College Park, Maryland 20742, USA

    • S. Debnath
    • , N. M. Linke
    • , C. Figgatt
    • , K. A. Landsman
    • , K. Wright
    •  & C. Monroe
  2. Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, Maryland 20742, USA

    • C. Monroe
  3. ionQ, Inc., College Park, Maryland 20742 USA

    • C. Monroe


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S.D., N.M.L, C.F., K.A.L., K.W. and C.M. all contributed to the experimental design, construction, data collection and analysis of this experiment. All authors contributed to this manuscript.

Competing interests

C.M. is a founding scientist of ionQ, Inc.

Corresponding author

Correspondence to S. Debnath.

Reviewer Information Nature thanks S. Bartlett and T. Northup for their contribution to the peer review of this work.

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