We use quantum walks to construct a new quantum algorithm for element distinctness and its generalization. For element distinctness (the problem of finding two equal items among N given items), we get an O(N^ 2 3 ) query quantum algorithm. This improves the previous O(N^ 3 4 ) query quantum algorithm of Buhrman this http URL. (quant-ph 0007016) and matches the lower bound by Shi (quant-ph 0112086). The algorithm also solves the generalization of element distinctness in which we have to find k equal items among N items. For this problem, we get an O(N^ k (k+1) ) query quantum algorithm.
Quantum walks. There has been considerable amount of research on quantum walks (surveyed in @cite_25 ) and their applications (surveyed in @cite_35 ). Applications of walks @cite_35 mostly fall into two classes. The first class is exponentially faster hitting times @cite_21 @cite_7 @cite_30 . In these applications, quantum walks are used to find a certain vertex exponentially faster than classically. (The first results @cite_34 @cite_21 @cite_30 were quantum walk algorithms that are exponentially faster than classical algorithms based on classical random walks. The most recent result @cite_7 is a quantum walk algorithm which is exponentially faster than any classical algorithm.) Our result is quite different from those, both in the problem that we consider and the way how we solve. While polynomial speedup achieved in our paper is smaller than exponential speedup in @cite_7 , our result has the advantage that we solve a natural problem which has been widely studied in both classical and quantum computing. The second class is quantum walk search algorithms @cite_2 @cite_1 @cite_32 .
@cite_30 @cite_35 @cite_7 @cite_21 @cite_1 @cite_32 @cite_2 @cite_34 @cite_25
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Quantum random walks on graphs have been shown to display many interesting properties, including exponentially fast hitting times when compared with their classical counterparts. However, it is still unclear how to use these novel properties to gain an algorithmic speedup over classical algorithms. In this paper, we present a quantum search algorithm based on the quantum random-walk architecture that provides such a speedup. It will be shown that this algorithm performs an oracle search on a database of N items with O( radical (N)) calls to the oracle, yielding a speedup similar to other quantum search algorithms. It appears that the quantum random-walk formulation has considerable flexibility, presenting interesting opportunities for development of other, possibly novel quantum algorithms. Grover's quantum search algorithm provides a way to speed up combinatorial search, but is not directly applicable to searching a physical database. Nevertheless, Aaronson and Ambainis showed that a database of N items laid out in d spatial dimensions can be searched in time of order radical (N) for d>2, and in time of order radical (N) poly(log N) for d=2. We consider an alternative search algorithm based on a continuous-time quantum walk on a graph. The case of the complete graph gives the continuous-time search algorithm of Farhi and Gutmann, and other previously known results can be used to show that radical (N) speedup can also be achieved on the hypercube. We show that full radical (N) speedup can be achieved on a d-dimensional periodic lattice for d>4. In d=4, the quantum walk search algorithm takes time of order radical (N) poly(log N), and in d<4, the algorithm does not provide substantial speedup. We construct a black box graph traversal problem that can be solved exponentially faster on a quantum computer than on a classical computer. The quantum algorithm is based on a continuous time quantum walk, and thus employs a different technique from previous quantum algorithms based on quantum Fourier transforms. We show how to implement the quantum walk efficiently in our black box setting. We then show how this quantum walk solves our problem by rapidly traversing a graph. Finally, we prove that no classical algorithm can solve the problem in subexponential time. In his seminal paper, Grover points out the prospect of faster solutions for an NP-complete problem like SAT. If there are n variables, then an obvious classical deterministic algorithm checks out all 2n truth assignments in about 2n steps, while his quantum search algorithm can find a satisfying truth assignment in about 2n 2 steps. For several NP-complete problems, many sophisticated classical algorithms have been designed. They are still exponential, but much faster than the brute force algorithms. The question arises whether their running time can still be decreased from T(n) to O (√T(n)) by using a quantum computer. Isolated positive examples are known, and some speed-up has been obtained for wider classes. Here, we present a simple method to obtain the full T(n) to O(√T(n)) speed-up for most of the many nontrivial exponential time algorithms for NP-hard problems. The method works whenever the widely used technique of recursive decomposition is employed. This included all currently known algorithms for which such a speedup has not yet been known.