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      Quantum search with certainty based on modified Grover algorithms: optimum choice of parameters

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      Quantum Information Processing
      Springer Nature

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          Quantum Mechanics helps in searching for a needle in a haystack

          Lov Grover (1997)
          Quantum mechanics can speed up a range of search applications over unsorted data. For example imagine a phone directory containing N names arranged in completely random order. To find someone's phone number with a probability of 50%, any classical algorithm (whether deterministic or probabilistic) will need to access the database a minimum of O(N) times. Quantum mechanical systems can be in a superposition of states and simultaneously examine multiple names. By properly adjusting the phases of various operations, successful computations reinforce each other while others interfere randomly. As a result, the desired phone number can be obtained in only O(sqrt(N)) accesses to the database.
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            A fast quantum mechanical algorithm for database search

            Lov Grover (1996)
            Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a 50% probability, any classical algorithm (whether deterministic or probabilistic) will need to look at a minimum of N/2 names. Quantum mechanical systems can be in a superposition of states and simultaneously examine multiple names. By properly adjusting the phases of various operations, successful computations reinforce each other while others interfere randomly. As a result, the desired phone number can be obtained in only O(sqrt(N)) steps. The algorithm is within a small constant factor of the fastest possible quantum mechanical algorithm.
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              Strengths and Weaknesses of Quantum Computing

              Recently a great deal of attention has focused on quantum computation following a sequence of results suggesting that quantum computers are more powerful than classical probabilistic computers. Following Shor's result that factoring and the extraction of discrete logarithms are both solvable in quantum polynomial time, it is natural to ask whether all of NP can be efficiently solved in quantum polynomial time. In this paper, we address this question by proving that relative to an oracle chosen uniformly at random, with probability 1, the class NP cannot be solved on a quantum Turing machine in time \(o(2^{n/2})\). We also show that relative to a permutation oracle chosen uniformly at random, with probability 1, the class \(NP \cap coNP\) cannot be solved on a quantum Turing machine in time \(o(2^{n/3})\). The former bound is tight since recent work of Grover shows how to accept the class NP relative to any oracle on a quantum computer in time \(O(2^{n/2})\).
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                Author and article information

                Journal
                Quantum Information Processing
                Quantum Inf Process
                Springer Nature
                1570-0755
                1573-1332
                May 2013
                October 30 2012
                : 12
                : 5
                : 1897-1914
                Article
                10.1007/s11128-012-0498-0
                74359ab4-9507-4120-80ac-9c70e5d44465
                © 2012
                History

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