Foundations of Physics

, Volume 44, Issue 8, pp 819–828 | Cite as

Quantum Computing’s Classical Problem, Classical Computing’s Quantum Problem

  • Rodney Van Meter


Tasked with the challenge to build better and better computers, quantum computing and classical computing face the same conundrum: the success of classical computing systems. Small quantum computing systems have been demonstrated, and intermediate-scale systems are on the horizon, capable of calculating numeric results or simulating physical systems far beyond what humans can do by hand. However, to be commercially viable, they must surpass what our wildly successful, highly advanced classical computers can already do. At the same time, those classical computers continue to advance, but those advances are now constrained by thermodynamics, and will soon be limited by the discrete nature of atomic matter and ultimately quantum effects. Technological advances benefit both quantum and classical machinery, altering the competitive landscape. Can we build quantum computing systems that out-compute classical systems capable of some \(10^{30}\) logic gates per month? This article will discuss the interplay in these competing and cooperating technological trends.


Quantum computing Moore’s Law 


  1. 1.
    Bacon, D., van Dam, W.: Commun. ACM 53(2), 84 (2010). doi: 10.1145/1646353.1646375 CrossRefGoogle Scholar
  2. 2.
    Feynman, R.P.: In: Hey, A.J.G. (ed.) Feynman and Computation. Westview Press, Boulder (2002)Google Scholar
  3. 3.
    L. Grover, in Proc. 28th Annual ACM Symposium on the Theory of Computation (1996), pp. 212–219.
  4. 4.
    S. Hallgren, Journal of the ACM (JACM) 54(1) (2007).Google Scholar
  5. 5.
    Harrow, A.W., Hassidim, A., Lloyd, S.: Phys. Rev. Lett. 103(15), 150502 (2009). doi: 10.1103/PhysRevLett.103.150502 ADSCrossRefMathSciNetGoogle Scholar
  6. 6.
    Jordan, S.P., Lee, K.S.M., Preskill, J.: Science 336, 1130 (2012)ADSCrossRefGoogle Scholar
  7. 7.
    Magniez, F., Santha, M., Szegedy, M.: Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms. Society for Industrial and Applied Mathematics 56, 1109–1117 (2005)MathSciNetGoogle Scholar
  8. 8.
    M. Mosca, Arxiv, preprint arXiv:0808.0369 (2008).
  9. 9.
    Shor, P.W.: Proceedings of 35th Symposium on Foundations of Computer Science, pp. 124–134. IEEE Computer Society Press, Los Alamitos (1994)CrossRefGoogle Scholar
  10. 10.
    Whitfield, J., Biamonte, J., Aspuru-Guzik, A.: Mol. Phys. 109(5), 735 (2011)ADSCrossRefGoogle Scholar
  11. 11.
    D. Anderson, in 5th IEEE/ACM International Workshop on Grid Computing (2004), pp. 365–372. Available translated into Japanese at
  12. 12.
    K. Asanovic, R. Bodik, B. Catanzaro, J. Gebis, P. Husbands, K. Keutzer, D. Patterson, W. Plishker, J. Shalf, S. Williams, et al., The landscape of parallel computing research: A view from Berkeley. Tech. rep., Technical Report UCB/EECS-2006-183, EECS Department, University of California, Berkeley (2006).Google Scholar
  13. 13.
    Coulouris, G., Dollimore, J., Kindberg, T.: Distributed Systems: Concepts and Design, 4th edn. Addison-Wesley, Menlo Park (2005)Google Scholar
  14. 14.
    Fox, G., Williams, R., Messina, P.: Parallel Computing Works!. Morgan Kaufmann Publication, San Francisco (1994)Google Scholar
  15. 15.
    Hennessy, J.L., Patterson, D.A.: Computer Architecture: A Quantitative Approach, 4th edn. Morgan Kaufman, San Francisco (2006)Google Scholar
  16. 16.
    Gustafson, J.L.: Commun. ACM 31(5), 532 (1988)CrossRefGoogle Scholar
  17. 17.
    Devitt, S.J., Fowler, A.G., Stephens, A.M., Greentree, A.D., Hollenberg, L.C.L., Munro, W.J., Nemoto, K.: N. J. Phys. 11, 083032 (2009)CrossRefGoogle Scholar
  18. 18.
    Jones, N.C., Van Meter, R., Fowler, A.G., McMahon, P.L., Kim, J., Ladd, T.D., Yamamoto, Y.: Phys. Rev. 2, 031007 (2012). doi: 10.1103/PhysRevX.2.031007.
  19. 19.
    Van Meter, R., Ladd, T.D., Fowler, A.G., Yamamoto, Y.: Int. J. Quantum Inf. 8, 295 (2010)CrossRefGoogle Scholar
  20. 20.
    M.G. Whitney, N. Isailovic, Y. Patel, J. Kubiatowicz, in Proc. 36th Annual International Symposium on Computer Architecture (2009).Google Scholar
  21. 21.
    A. Ambainis, A. Childs, B. Reichardt, in Foundations of Computer Science, 2007. FOCS’07. 48th Annual IEEE Symposium on (IEEE, 2007), pp. 363–372.Google Scholar
  22. 22.
    Childs, A., Cleve, R., Deotto, E., Farhi, E., Gutmann, S., Spielman, D.: Proceedings of the Thirty-Fifth Annual ACM Symposium on Theory of Computing, pp. 59–68. ACM, New York (2003)Google Scholar
  23. 23.
    O. Regev, in Foundations of Computer Science, 2002. Proceedings. The 43rd Annual IEEE Symposium on (IEEE, 2002), pp. 520–529.Google Scholar
  24. 24.
    A. Bocharov, K. Svore, Arxiv, preprint arXiv:1206.3223 (2012).
  25. 25.
    T.T. Pham, R. Van Meter, C. Horsman, arXiv preprint arXiv:1209/4139 (2012).Google Scholar
  26. 26.
    P. Selinger, arXiv:1212.6253 [quant-ph] (2012).
  27. 27.
    R.D. Van Meter III, Architecture of a quantum multicomputer optimized for Shor’s factoring algorithm. Ph.D. thesis, Keio University (2006). Available as arXiv:quant-ph/0607065.
  28. 28.
    R. Van Meter, C. Horsman, Communications of the ACM (2013). To appear.Google Scholar
  29. 29.
    ESIA, JEITIA, KSIA, TSIA, SIA, International technology roadmap for semiconductors. Tech. rep., ESIA and JEITIA and KSIA and TSIA and SIA (2012).
  30. 30.
    G.E. Moore, Electronics 38(8) (1965).Google Scholar
  31. 31.
    N. Forbes, M. Foster, Computing in Science & Engineering pp. 18–19 (2003).Google Scholar
  32. 32.
    Kish, L.: Phys. Lett. A 305(3–4), 144 (2002)ADSCrossRefGoogle Scholar
  33. 33.
    I. Tuomi, First Monday 7(11–4) (2002).Google Scholar
  34. 34.
    R. Landauer, IBM J. of Research and Development 5(3), 183 (1961). Reprinted in IBM J. R.&D. Vol. 44 No. 1/2, Jan./Mar. 2000, pp. 261–269.Google Scholar
  35. 35.
    Meindl, J.D., Chen, Q., Davis, J.A.: Science 293, 2044 (2001)ADSCrossRefGoogle Scholar
  36. 36.
    Swade, D.: The Difference Engine: Charles Babbage and the Quest to Build the First Computer. Penguin, Baltimore (2002)Google Scholar
  37. 37.
    Riordan, M., Hoddeson, L.: Crystal Fire: the Birth of the Information Age. W. W. Norton, New York (1997)Google Scholar
  38. 38.
    Ieong, M., Doris, B., Kedzierski, J., Rim, K., Yang, M.: Science 306, 2057 (2004)ADSCrossRefGoogle Scholar
  39. 39.
    M. Lundstrom. Moore’s Law forever? (2003).Google Scholar
  40. 40.
    E.P. DeBenedictis, in Proc. 2nd conference on Computing Frontiers (ACM, 2005), pp. 391–402.Google Scholar
  41. 41.
    Bennett, C.H.: IBM J. Res. Develop. 17, 525 (1973)CrossRefzbMATHMathSciNetGoogle Scholar
  42. 42.
    C.H. Bennett, IBM J. of Research and Development 32(1) (1988). Reprinted in IBM J. R.&D. Vol. 44 No. 1/2, Jan./Mar. 2000, pp. 270–277.Google Scholar
  43. 43.
    Feynman, R.P.: Feynman Lectures on Computation. Addison Wesley, Menlo Park (1996)Google Scholar
  44. 44.
    Fredkin, E., Toffoli, T.: Int. J. Theor. Phys. 21, 219 (1982)CrossRefzbMATHMathSciNetGoogle Scholar
  45. 45.
    W.C. Athas, L.J. Svensson, in Proc. IEEE 1994 Workshop on Physics and Computing (IEEE, 1994).Google Scholar
  46. 46.
    Burignat, S., Vos, A.D.: Int. J. Electron. Telecommun. 58(3), 205 (2012)Google Scholar
  47. 47.
    M.P. Frank, Reversibility for efficient computing. Ph.D. thesis, MIT (1999).Google Scholar
  48. 48.
    Peres, A.: Phys. Rev. A 32(6), 3266 (1985)ADSCrossRefMathSciNetGoogle Scholar
  49. 49.
    Shende, V.V., Prasad, A.K., Markov, I.L., Hayes, J.P.: IEEE Trans. CAD 22(6), 710 (2003)CrossRefGoogle Scholar
  50. 50.
    C. Vieri, M.J. Ammer, M. Frank, N. Margolus, T. Knight. A fully reversible asymptotically zero energy microprocessor. Scholar
  51. 51.
    G. Bourianoff, IEEE Computer pp. 44–53 (2003).Google Scholar
  52. 52.
    G. Tseng, J. Ellenbogen. Toward nanocomputers (2001).Google Scholar
  53. 53.
    Beckman, R., Johnston-Halperin, E., Luo, Y., Green, J.E., Heath, J.R.: Science 310, 465 (2005)ADSCrossRefGoogle Scholar
  54. 54.
    A. DeHon, IEEE Trans. Nanotechnol. 2(1) (2003).Google Scholar
  55. 55.
    S.J. Aaronson, Limits on efficient computation in the physical world. Ph.D. thesis, U.C. Berkeley (2004).Google Scholar
  56. 56.
    Topol, A., Tulipe, D.L., Shi, L., Frank, D., Bernstein, K., Steen, S., Kumar, A., Singco, G., Young, A., Guarini, K., et al.: IBM J. Res. Develop. 50(4.5), 491 (2006)CrossRefGoogle Scholar
  57. 57.
    M. Tsang, C.M. Caves, Phys. Rev. X 2, 031016 (2012). doi: 10.1103/PhysRevX.2.031016.
  58. 58.
    K. Capek, R.U.R.: Rossum’s Universal Robots (1920).Google Scholar
  59. 59.
    Christensen, C.M.: The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business Press, Cambridge (1997)Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Keio UniversityTokyoJapan

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