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.
Recent developments. After the work described in this paper, the results and ideas from this paper have been used to construct several other quantum algorithms. @cite_4 have used our element distinctness algorithm to give an @math query quantum algorithm for finding triangles in a graph. @cite_32 have used ideas from the current paper to construct a faster algorithm for search on 2-dimensional grid. Childs and Eisenberg @cite_3 have given a different analysis of our algorithm.
@cite_4 @cite_32 @cite_3
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We present a new quantum algorithm that either finds a triangle (a copy of @math ) in an undirected graph @math on @math nodes, or it outputs reject'' if @math is triangle free. The algorithm uses @math queries, and it is based on a new design concept of Ambainis that incorporates the benefits of quantum walks into Grover search. The algorithm both improves on, and is simpler than a recent algorithm of Szegedy which has @math query complexity. The Triangle Problem was first treated in [BDH+01], where an algorithm with @math query complexity was presented (here @math is the number of edges of @math ). I show that for any number of oracle lookups up to about pi 4thinsp radical (N) , Grover close_quote s quantum searching algorithm gives the maximal possible probability of finding the desired element. I explain why this is also true for quantum algorithms which use measurements during the computation. I also show that unfortunately quantum searching cannot be parallelized better than by assigning different parts of the search space to independent quantum computers. copyright ital 1999 ital The American Physical Society We introduce a quantum algorithm that produces approximate solutions for combinatorial optimization problems. The algorithm depends on a positive integer p and the quality of the approximation improves as p is increased. The quantum circuit that implements the algorithm consists of unitary gates whose locality is at most the locality of the objective function whose optimum is sought. The depth of the circuit grows linearly with p times (at worst) the number of constraints. If p is fixed, that is, independent of the input size, the algorithm makes use of efficient classical preprocessing. If p grows with the input size a different strategy is proposed. We study the algorithm as applied to MaxCut on regular graphs and analyze its performance on 2-regular and 3-regular graphs for fixed p. For p = 1, on 3-regular graphs the quantum algorithm always finds a cut that is at least 0.6924 times the size of the optimal cut. 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.