370 research outputs found
Quantum algorithms for subset finding
Recently, Ambainis gave an O(N^(2/3))-query quantum walk algorithm for
element distinctness, and more generally, an O(N^(L/(L+1)))-query algorithm for
finding L equal numbers. We point out that this algorithm actually solves a
much more general problem, the problem of finding a subset of size L that
satisfies any given property. We review the algorithm and give a considerably
simplified analysis of its query complexity. We present several applications,
including two algorithms for the problem of finding an L-clique in an N-vertex
graph. One of these algorithms uses O(N^(2L/(L+1))) edge queries, and the other
uses \tilde{O}(N^((5L-2)/(2L+4))), which is an improvement for L <= 5. The
latter algorithm generalizes a recent result of Magniez, Santha, and Szegedy,
who considered the case L=3 (finding a triangle). We also pose two open
problems regarding continuous time quantum walk and lower bounds.Comment: 7 pages; note added on related results in quant-ph/031013
Improving Quantum Query Complexity of Boolean Matrix Multiplication Using Graph Collision
The quantum query complexity of Boolean matrix multiplication is typically
studied as a function of the matrix dimension, n, as well as the number of 1s
in the output, \ell. We prove an upper bound of O (n\sqrt{\ell}) for all values
of \ell. This is an improvement over previous algorithms for all values of
\ell. On the other hand, we show that for any \eps < 1 and any \ell <= \eps
n^2, there is an \Omega(n\sqrt{\ell}) lower bound for this problem, showing
that our algorithm is essentially tight.
We first reduce Boolean matrix multiplication to several instances of graph
collision. We then provide an algorithm that takes advantage of the fact that
the underlying graph in all of our instances is very dense to find all graph
collisions efficiently
On the relationship between continuous- and discrete-time quantum walk
Quantum walk is one of the main tools for quantum algorithms. Defined by
analogy to classical random walk, a quantum walk is a time-homogeneous quantum
process on a graph. Both random and quantum walks can be defined either in
continuous or discrete time. But whereas a continuous-time random walk can be
obtained as the limit of a sequence of discrete-time random walks, the two
types of quantum walk appear fundamentally different, owing to the need for
extra degrees of freedom in the discrete-time case.
In this article, I describe a precise correspondence between continuous- and
discrete-time quantum walks on arbitrary graphs. Using this correspondence, I
show that continuous-time quantum walk can be obtained as an appropriate limit
of discrete-time quantum walks. The correspondence also leads to a new
technique for simulating Hamiltonian dynamics, giving efficient simulations
even in cases where the Hamiltonian is not sparse. The complexity of the
simulation is linear in the total evolution time, an improvement over
simulations based on high-order approximations of the Lie product formula. As
applications, I describe a continuous-time quantum walk algorithm for element
distinctness and show how to optimally simulate continuous-time query
algorithms of a certain form in the conventional quantum query model. Finally,
I discuss limitations of the method for simulating Hamiltonians with negative
matrix elements, and present two problems that motivate attempting to
circumvent these limitations.Comment: 22 pages. v2: improved presentation, new section on Hamiltonian
oracles; v3: published version, with improved analysis of phase estimatio
Claw Finding Algorithms Using Quantum Walk
The claw finding problem has been studied in terms of query complexity as one
of the problems closely connected to cryptography. For given two functions, f
and g, as an oracle which have domains of size N and M (N<=M), respectively,
and the same range, the goal of the problem is to find x and y such that
f(x)=g(y). This paper describes an optimal algorithm using quantum walk that
solves this problem. Our algorithm can be generalized to find a claw of k
functions for any constant integer k>1, where the domains of the functions may
have different size.Comment: 12 pages. Introduction revised. A reference added. Weak lower bound
delete
Optimal quantum query bounds for almost all Boolean functions
We show that almost all n-bit Boolean functions have bounded-error quantum
query complexity at least n/2, up to lower-order terms. This improves over an
earlier n/4 lower bound of Ambainis, and shows that van Dam's oracle
interrogation is essentially optimal for almost all functions. Our proof uses
the fact that the acceptance probability of a T-query algorithm can be written
as the sum of squares of degree-T polynomials.Comment: 8 pages LaTe
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