In this note, we give a quantum algorithm that finds collisions in arbitrary τ-to-one functions after only O ( 3 √ N /τ) expected evaluations of the function. Assuming the function is given by a black box, this is more efficient than the best possible classical algorithm, even allowing probabilism. We also give a similar algorithm for finding claws in pairs of functions. Furthermore, we exhibit a space-time tradeoff for our technique. Our approach uses Grover's quantum searching algorithm in a novel way.
In this note, we give a quantum algorithm that finds collisions in arbitrary τ-to-one functions after only O ( 3 √ N /τ) expected evaluations of the function. Assuming the function is given by a black box, this is more efficient than the best possible classical algorithm, even allowing probabilism. We also give a similar algorithm for finding claws in pairs of functions. Furthermore, we exhibit a space-time tradeoff for our technique. Our approach uses Grover's quantum searching algorithm in a novel way.
In this article, we propose an efficient quantum k-collision search algorithm with low quantum memory O(n). The previous quantum k-collision algorithms can not be converted into a low quantum memory k-collision algorithm directly, because the time complexity of the converted algorithm is larger than the basic k-collision algorithm. To solve this problem, we shall not only divide our low memory quantum k-collision algorithm into several subroutines, but also need to achieve some balances between these subrou tines. The time complexity of our k-collision search algorithm is O(2(2k-2)n/2k+1-3 ), and the classical memory and quantum memory complexities are O(2(2k-2)n/2k+1-3 ) and O(n) respectively. In addition, we propose an efficient k-claw search algorithm, which can output a k-claw with O(n) qubits. Given 2squantum processors, we can construct our quantum k-collision and k-claw parallel algorithm with the time of O(2(2k-2)n-(2k+1-2k-1-3)s/2k+1-3 )while the classical memory and quantum memory complexities are O(2(2k-1-1)n+s-2k-2/2k+1-3 ) and O(n), respectively.
Given a function f as an oracle, the collision problem is to find two distinct inputs i and j such that f(i)=f(j), under the promise that such inputs exist. In this paper, we prove that any quantum algorithm for finding a collision in an r-to-one function must evaluate the function /spl Omega/ ((n/r)/sup 1/3/) times, where n is the size of the domain and r|n. This lower bound matches, up to a constant factor, the upper bound of Brassard, Hoyer and Tapp (1997), which uses the quantum algorithm of Grover (1996) in a novel way. The previously best quantum lower bound is /spl Omega/ ((n/r)/sup 1/5/) evaluations, due to Aaronson (2002). Our result implies a quantum lower bound of /spl Omega/ (n/sup 2/3/) queries to the inputs for another well studied problem, the element distinctness problem, which is to determine whether or not the given n real numbers are distinct. The previous best lower bound is /spl Omega/ (/spl radic/n) queries in the black-box model; and /spl Omega/ (/spl radic/n log n) comparisons in the comparisons-only model, due to Hoyer Neerbek, and Shi (2001).
IntroductionFor a search problem associated with a unsorted database, the remarkable Grover's quantum algorithm (1) provides a quadratic speedup over its classical counterpart.The search problem can be described as follows: for a given function f , there exists one unknown element in the set {0, 1, ..., N -1} that satisfies f (x)=-1, say x = τ, whereas the other N -1o n e sg i v e f (x)=1.How many times of evaluations of f are required to determine the element τ for f (τ)=-1?Through a conventional algorithm, one needs O(N) trials to achieve this aim.How about the utility of quantum algorithm for the search?For the scenario in the quantum world, the search problem can be rephrased in the quantum mechanical language: for a given unitary operator I τ , that is sometimes called the oracle operator, and a set of state vectors (orthonormal basis): s = {|0 , |1 , ..., |N -1 }, I τ |x = |x for all states in the set except I τ |x = -|x for x = τ.H owma n yqueriesofI τ are required to determine |τ ?By Grover's algorithm, one needs only O( √ N) quantum mechanical steps to find the marked state |τ out.It has been shown that Grover's algorithm is optimal since it needs minimal oracle calls to perform a quantum search (2).The quantum searching process will be briefly reviewed as follows.The first step of Grover's algorithm is to prepare a superposition state of all elements with uniform probability amplitude:Then apply the Grover kernel G = -I η I τ to |s ,w h er eI η is a unitary operator and contains no bias against the marked state.For large N,a f t e ra b o u tm = π √ N/4 repetitions of G operations, the probability to observe |τ is close to one, i.e., G m |s ∼ |τ .( 2 ) Since every single G involves one query of I τ ,onlyO( √ N) searching steps are required for a quantum search task.In what follows, we will first investigate on the general SU(2) formulation for the kernel of Grover's searching operator G.The discussions of quantum searching certainty, robustness, and the analog analogue version of the Grover's algorithm will be given afterwards.
In this paper, we consider a quantum algorithm for solving the following problem: ``Suppose f is a function given as a black box (that is also called an oracle) and f is invariant under some AND-mask. Examine a property of f by querying the oracle.'' We compare the efficiency of our quantum algorithm with that of classical algorithms by evaluating the expected number of queries for each algorithm. We show that our quantum algorithm is more efficient than any classical algorithm in some cases. However, our quantum algorithm does not exhibit an exponential speedup in the size of an input, compared with the best classical algorithm. Our algorithm extracts a global property of f (that is, invariance of f) while it neglects local properties of f (that is, outputs of f). We can regard our algorithm as an application of Simon's algorithm.
In this work, we present a quantum query algorithm for searching a word of length m in an unsorted dictionary of size n. The algorithm uses O(n) queries (Grover operators), like previously known algorithms. What is new is that the algorithm is based on the quantum fingerprinting-hashing technique, which (a) provides a first level of amplitude amplification before applying the sequence of Grover amplitude amplification operators and (b) makes the algorithm more efficient in terms of memory use -- it requires O(logn+logm) qubits. Note that previously developed algorithms by other researchers without hashing require O(logn+m) qubits.
How much memory is needed to retain the quantum speedup for collision finding? For a uniformly random function f:[N]→[N], the BHT algorithm finds a collision using O(N1/3) queries and a quantumly accessible classical table containing O(N1/3) input-output pairs, whereas a logarithmic-space Grover search uses O(N) queries. Determining the optimal query-space tradeoff between these extremes remains a major open problem.
We resolve this equation within the class of label-symmetric algorithms, which treat the function f's output labels as interchangeable. We prove that such algorithm that makes T queries, uses S qubits, and finds a collision in a uniformly random function f:[M]→[N] with constant probability satisfies T=Ω(N1/3)andT2S=Ω(NlogN). For the setting where M=N, these bounds are matched by a space-efficient implementation of the BHT algorithm. As a consequence of our tradeoff, any label-symmetric algorithm for the search version of Element Distinctness on f:[n]→[n2] must satisfy T=Ω(n2/3)andT2S=Ω(n2logn), matching Ambainis's quantum walk. Thus, both tradeoffs are optimal within the class of label-symmetric algorithms.
To prove these results, we develop a space-sensitive version of the compressed oracle technique. The compressed oracle records the information learned by the algorithm in an evolving superposition of databases. Using label symmetry and representation theory, we show that an algorithm using S qubits can effectively retain information about only O(S/logN) collision-free database entries. Substituting this estimate into the compressed oracle technique yields the stated tradeoffs.