• DocumentCode
    2356751
  • Title

    On the power of quantum computation

  • Author

    Simon, Daniel R.

  • Author_Institution
    Microsoft Corp., Redmond, WA, USA
  • fYear
    1994
  • fDate
    20-22 Nov 1994
  • Firstpage
    116
  • Lastpage
    123
  • Abstract
    The quantum model of computation is a probabilistic model, similar to the probabilistic Turing Machine, in which the laws of chance are those obeyed by particles on a quantum mechanical scale, rather than the rules familiar to us from the macroscopic world. We present here a problem of distinguishing between two fairly natural classes of function, which can provably be solved exponentially faster in the quantum model than in the classical probabilistic one, when the function is given as an oracle drawn equiprobably from the uniform distribution on either class. We thus offer compelling evidence that the quantum model may have significantly more complexity theoretic power than the probabilistic Turing Machine. In fact, drawing on this work, Shor (1994) has recently developed remarkable new quantum polynomial-time algorithms for the discrete logarithm and integer factoring problems
  • Keywords
    computational complexity; probabilistic automata; complexity theory; discrete logarithm; integer factoring; probabilistic Turing Machine; probabilistic model; quantum computation; quantum model of computation; Computational modeling; Computer errors; Computer simulation; Lakes; Physics computing; Polynomials; Quantum computing; Quantum mechanics; Relativistic quantum mechanics; Turing machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Foundations of Computer Science, 1994 Proceedings., 35th Annual Symposium on
  • Conference_Location
    Santa Fe, NM
  • Print_ISBN
    0-8186-6580-7
  • Type

    conf

  • DOI
    10.1109/SFCS.1994.365701
  • Filename
    365701