Grover's algorithm

In quantum computing, Grover's algorithm, also known as the quantum search algorithm, is a quantum algorithm for unstructured search that finds with high probability the unique input to a black box function that produces a particular output value, using just evaluations of the function, where is the size of the function's domain. It was devised by Lov Grover in 1996.[1]

The analogous problem in classical computation would have a query complexity (i.e., the function would have to be evaluated times: there is no better approach than trying out all input values one after the other, which, on average, takes steps).[1]

Charles H. Bennett, Ethan Bernstein, Gilles Brassard, and Umesh Vazirani proved that any quantum solution to the problem needs to evaluate the function times, so Grover's algorithm is asymptotically optimal.[2] Since classical algorithms for NP-complete problems require exponentially many steps, and Grover's algorithm provides at most a quadratic speedup over the classical solution for unstructured search, this suggests that Grover's algorithm by itself will not provide polynomial-time solutions for NP-complete problems (as the square root of an exponential function is still an exponential, not a polynomial function).[3]

Unlike other quantum algorithms, which may provide exponential speedup over their classical counterparts, Grover's algorithm provides only a quadratic speedup. However, even quadratic speedup is considerable when is large, and Grover's algorithm can be applied to speed up broad classes of algorithms.[3] Grover's algorithm could brute-force a 128-bit symmetric cryptographic key in roughly 264 iterations, or a 256-bit key in roughly 2128 iterations. It may not be the case that Grover's algorithm poses a significantly increased risk to encryption over existing classical algorithms, however.[4]

  1. ^ a b Grover, Lov K. (1996-07-01). "A fast quantum mechanical algorithm for database search". Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96. Philadelphia, Pennsylvania, USA: Association for Computing Machinery. pp. 212–219. arXiv:quant-ph/9605043. Bibcode:1996quant.ph..5043G. doi:10.1145/237814.237866. ISBN 978-0-89791-785-8. S2CID 207198067.
  2. ^ Bennett, C. H.; Bernstein, E.; Brassard, G.; Vazirani, U. (1997). "The strengths and weaknesses of quantum computation". SIAM Journal on Computing. 26 (5): 1510–1523. arXiv:quant-ph/9701001. doi:10.1137/s0097539796300933. S2CID 13403194.
  3. ^ a b Nielsen, Michael A.; Chuang, Isaac L. (2010). Quantum computation and quantum information. Cambridge: Cambridge University Press. pp. 276–305. ISBN 978-1-107-00217-3. OCLC 665137861.
  4. ^ Bernstein, Daniel J. (2010). "Grover vs. McEliece" (PDF). In Sendrier, Nicolas (ed.). Post-Quantum Cryptography, Third International Workshop, PQCrypto 2010, Darmstadt, Germany, May 25-28, 2010. Proceedings. Lecture Notes in Computer Science. Vol. 6061. Springer. pp. 73–80. doi:10.1007/978-3-642-12929-2_6.

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