Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Quantum advantage for computations with limited space

Abstract

Quantum computers promise the ability to solve problems that are intractable in the classical setting1, but in many cases this is not rigorously proven. It is often possible to establish a provable theoretical advantage for quantum computations by restricting the computational power2,3,4,5,6,7,8. In multiple cases, quantum advantage over these restricted models was demonstrated experimentally9,10,11,12. Here we consider space-restricted computations that use only one computational classical or quantum bit with a read-only memory as input. We show that n-bit symmetric Boolean functions can be implemented exactly in this framework through the use of quantum signal processing13 and O(n2) gates, but in the analogous classical computations some of the functions may only be evaluated with probability \(1/2 + O\left(n/{\sqrt{2}}^n\right)\). We experimentally demonstrate computations of three-bit to six-bit symmetric Boolean functions by quantum circuits with an algorithmic success probability that exceeds the classical limit. This shows that in computations, quantum scrap space offers an advantage over analogous classical space, and calls for an in-depth exploration of space–time trade-offs in quantum circuits.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: True SLSB3 with 8 entangling gates, obtained using signal processing technique and local optimization.
Fig. 2: Relative-phase SLSBn using 2n − 1 entangling gates.
Fig. 3: Experimental results demonstrating quantum advantage.

Similar content being viewed by others

Data availability

All relevant data are available from the corresponding author upon request.

References

  1. Nielsen, M. A. & Chuang, I. L. Quantum Computation and Quantum Information (Cambridge Univ. Press, 2010).

  2. Bell, J. S. On the Einstein Podolsky Rosen paradox. Physics 1, 195–200 (1964).

    Article  MathSciNet  Google Scholar 

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

    Article  ADS  MathSciNet  Google Scholar 

  4. Bernstein, E. & Vazirani, U. Quantum complexity theory. SIAM J. Comput. 26, 1411–1473 (1997).

    Article  MathSciNet  Google Scholar 

  5. Grover, L. K. A fast quantum mechanical algorithm for database search. In Proc. 28th Annual ACM Symposium on Theory of Computing 212–219 (ACM, 1996).

  6. Trotter, H. F. On the product of semi-groups of operators. Proc. Am. Math. Soc. 10, 545–551 (1959).

    Article  MathSciNet  Google Scholar 

  7. Shor, P. W. Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Rev. 41, 303–332 (1999).

    Article  ADS  MathSciNet  Google Scholar 

  8. Bravyi, S., Gosset, D. & König, R. Quantum advantage with shallow circuits. Science 362, 308–311 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  9. Aspect, A., Dalibard, J. & Roger, G. Experimental test of Bell’s inequalities using time-varying analyzers. Phys. Rev. Lett. 49, 1804–1807 (1982).

    Article  ADS  MathSciNet  Google Scholar 

  10. Debnath, S. et al. Demonstration of a small programmable quantum computer with atomic qubits. Nature 536, 63–66 (2016).

    Article  ADS  Google Scholar 

  11. Figgatt, C. et al. Complete 3-qubit Grover search on a programmable quantum computer. Nat. Commun. 8, 1918 (2017).

    Article  ADS  Google Scholar 

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

    Article  ADS  Google Scholar 

  13. Low, G. H. & Chuang, I. L. Optimal Hamiltonian simulation by quantum signal processing. Phys. Rev. Lett. 118, 010501 (2017).

    Article  ADS  MathSciNet  Google Scholar 

  14. Clauser, J. F., Horne, M. A., Shimony, A. & Holt, R. A. Proposed experiment to test local hidden variable theories. Phys. Rev. Lett. 23, 880–884 (1969).

    Article  ADS  Google Scholar 

  15. Suzuki, M. Generalized Trotter’s formula and systematic approximants of exponential operators and inner derivations with applications to many-body problems. Commun. Math. Phys. 51, 183–190 (1976).

    Article  ADS  MathSciNet  Google Scholar 

  16. Nam, Y. & Maslov, D. Low-cost quantum circuits for classically intractable instances of the Hamiltonian dynamics simulation problem. npj Quantum Inf. 5, 44 (2019).

    Article  ADS  Google Scholar 

  17. Bravyi, S., Gosset, D., König, R. & Tomamichel, M. Quantum advantage with noisy shallow circuits. Nat. Phys. 16, 1040–1045 (2020).

    Article  Google Scholar 

  18. Le Gall, F. Average-case quantum advantage with shallow circuits. In Proc. 34th Computational Complexity Conference (ed. Shpilka, A.) 21:1–21:20 (Schloss Dagstuhl–Leibniz-Zentrum für Informatik, 2019).

  19. Coudron, M., Stark, J. & Vidick, T. Trading locality for time: certifiable randomness from low-depth circuits. Commun. Math. Phys. 382, 49–86 (2021).

    Article  ADS  MathSciNet  Google Scholar 

  20. Bene Watts, A., Kothari, R., Schaeffer, L. & Tal, A. Exponential separation between shallow quantum circuits and unbounded fan-in shallow classical circuits. In Proc. 51st Annual ACM SIGACT Symposium on Theory of Computing 515–526 (ACM, 2019).

  21. Grier, D. & Schaeffer, L. Interactive shallow Clifford circuits: quantum advantage against NC1 and beyond. In Proc. 52nd Annual ACM SIGACT Symposium on Theory of Computing 875–888 (ACM, 2020).

  22. Ablayev, F., Gainutdinova, A., Karpinski, M., Moore, C. & Pollett, C. On the computational power of probabilistic and quantum branching program. Inf. Comput. 203, 145–162 (2005).

    Article  MathSciNet  Google Scholar 

  23. Barrington, D. A. Bounded-width polynomial-size branching programs recognize exactly those languages in NC1. J. Comput. Syst. Sci. 38, 150–164 (1989).

    Article  MathSciNet  Google Scholar 

  24. Low, G. H., Yoder, T. J. & Chuang, I. L. Methodology of resonant equiangular composite quantum gates. Phys. Rev. X 6, 041067 (2016).

    Google Scholar 

  25. Haah, J. Product decomposition of periodic functions in quantum signal processing. Quantum 3, 190 (2019).

    Article  Google Scholar 

  26. Aleksandrowicz, G. et al. Qiskit: an open-source framework for quantum computing. Zenodo https://doi.org/10.5281/zenodo.2562110 (2019).

  27. Chamberland, C., Zhu, G., Yoder, T. J., Hertzberg, J. B. & Cross, A. W. Topological and subsystem codes on low-degree graphs with flag qubits. Phys. Rev. X 10, 011022 (2020).

    Google Scholar 

  28. Alexander, T. et al. Qiskit pulse: programming quantum computers through the cloud with pulses. Quantum Sci. Technol. 5, 044006 (2020).

    Article  ADS  Google Scholar 

  29. Garion, S. et al. Experimental implementation of non-Clifford interleaved randomized benchmarking with a controlled-S gate. Phys. Rev. Res. 3, 013204 (2021).

    Article  Google Scholar 

  30. Rigetti, C. & Devoret, M. Fully microwave-tunable universal gates in superconducting qubits with linear couplings and fixed transition frequencies. Phys. Rev. B 81, 134507 (2010).

    Article  ADS  Google Scholar 

  31. Chow, J. M. et al. Simple all-microwave entangling gate for fixed-frequency superconducting qubits. Phys. Rev. Lett. 107, 080502 (2011).

    Article  ADS  Google Scholar 

  32. Sheldon, S., Magesan, E., Chow, J. M. & Gambetta, J. M. Procedure for systematically tuning up cross-talk in the cross-resonance gate. Phys. Rev. A 93, 060302(R) (2016).

    Article  ADS  Google Scholar 

  33. Sundaresan, N. et al. Reducing unitary and spectator errors in cross resonance with optimized rotary echoes. PRX Quantum 1, 020318 (2020).

    Article  Google Scholar 

  34. Magesan, E., Gambetta, J. M. & Emerson, J. Scalable and robust randomized benchmarking of quantum processes. Phys. Rev. Lett. 106, 180504 (2011).

    Article  ADS  Google Scholar 

  35. Kivlichan, I. D. et al. Improved fault-tolerant quantum simulation of condensed-phase correlated electrons via Trotterization. Quantum 4, 296 (2020).

    Article  Google Scholar 

  36. Razborov, A. A. in International Symposium on Fundamentals of Computation Theory (ed. Budach, L.) 47–60 (Springer, 1991).

  37. Wegener, I. The Complexity of Boolean Functions 1st edn (Wiley & Teubner, 1987).

  38. Valiant, L. G. Short monotone formulae for the majority function. J. Algorithm. 5, 363–366 (1984).

    Article  MathSciNet  Google Scholar 

  39. Bravyi, S., Yoder, T. J. & Maslov, D. Efficient ancilla-free reversible and quantum circuits for the Hidden Weighted Bit function. IEEE Trans. Comput. https://doi.org/10.1109/TC.2021.3076435 (2021).

  40. O’Donnell, R. Analysis of Boolean Functions. (Cambridge Univ. Press, 2014).

  41. Rötteler, M. Quantum algorithms for highly non-linear Boolean functions. In Proc. 21st Annual ACM-SIAM Symposium on Discrete Algorithms 448–457 (SIAM, 2010).

  42. McKay, D. C., Wood, C. J., Sheldon, S., Chow, J. M. & Gambetta, J. M. Efficient Z gates for quantum computing. Phys. Rev. A 96, 022330 (2017).

    Article  ADS  Google Scholar 

Download references

Acknowledgements

We thank N. Kanazawa and E. Chen for experimental contributions and J. M. Gambetta for discussions. S.B. and T.J.Y. are partially supported by the IBM Research Frontiers Institute.

Author information

Authors and Affiliations

Authors

Contributions

D.M. designed the research, and S.B., D.M. and T.J.Y. developed the theory. J.-S.K. and S.S. ran the experiments. All authors contributed to writing the manuscript.

Corresponding author

Correspondence to Dmitri Maslov.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Physics thanks the anonymous reviewers for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Connectivity diagram of ibmq_berlin.

Connectivity diagram of ibmq_berlin with the qubits used in the experiment highlighted.

Extended Data Fig. 2 Pulse sequence and calibration.

a, Pulse diagram of the echoed CR sequence including the rotary echoes applied to the target qubit. The sampling time is 0.2222 ns per sample. ‘d10’ and ‘d12’ denote the drive channels for qubits Q10 and Q12 respectively, while ‘u21’ denotes the cross-resonance channel for the control qubit, 10. b, Fine amplitude calibration of the echoed ZXπ/4 CR pulse sequence for qubits Q15 and Q12. Initially the ZXπ/4 pulses are applied in repetitions of 2 to ensure a full rotation about the Bloch sphere. At 16 repetitions, the pulses are applied in repetitions of 4 to apply π pulses about the Bloch sphere equator in order to amplify amplitude errors. c, Rabi oscillations of the target qubit used to calibrate a 2π rotary echo for Q12.

Extended Data Fig. 3 Randomized benchmarking for decay curves characterizing the controlled-Rx(π/2) calibrated in Qiskit Pulse.

Pair (Q10, Q12) is shown in (a), (Q15, Q12) in (b), and (Q13, Q12) in (c). Data is shown in red and the fit is shown in blue. Error per Clifford (EPC) is shown in each plot and the error per controlled-Rx(π/2) is taken to be \(\frac{1}{3}\)EPC.

Extended Data Table 1 Qubit parameters and CNOT gate errors for the qubits used in the experiment

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maslov, D., Kim, JS., Bravyi, S. et al. Quantum advantage for computations with limited space. Nat. Phys. 17, 894–897 (2021). https://doi.org/10.1038/s41567-021-01271-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41567-021-01271-7

This article is cited by

Search

Quick links

Nature Briefing AI and Robotics

Sign up for the Nature Briefing: AI and Robotics newsletter — what matters in AI and robotics research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: AI and Robotics