5,042 research outputs found
A different kind of quantum search
The quantum search algorithm consists of an alternating sequence of selective
inversions and diffusion type operations, as a result of which it can find a
target state in an unsorted database of size N in only sqrt(N) queries. This
paper shows that by replacing the selective inversions by selective phase
shifts of Pi/3, the algorithm gets transformed into something similar to a
classical search algorithm. Just like classical search algorithms this
algorithm has a fixed point in state-space toward which it preferentially
converges. In contrast, the original quantum search algorithm moves uniformly
in a two-dimensional state space. This feature leads to robust search
algorithms and also to conceptually new schemes for error correction.Comment: 13 pages, 4 figure
Grover Algorithm with zero theoretical failure rate
In standard Grover's algorithm for quantum searching, the probability of
finding the marked item is not exactly 1. In this Letter we present a modified
version of Grover's algorithm that searches a marked state with full successful
rate. The modification is done by replacing the phase inversion by two phase
rotation through angle . The rotation angle is given analytically to be
, where
, the number of items in the database, and
an integer equal to or greater than the integer part of . Upon measurement at -th iteration, the marked state
is obtained with certainty.Comment: 5 pages. Accepted for publication in Physical Review
Quantum search algorithms on a regular lattice
Quantum algorithms for searching one or more marked items on a d-dimensional
lattice provide an extension of Grover's search algorithm including a spatial
component. We demonstrate that these lattice search algorithms can be viewed in
terms of the level dynamics near an avoided crossing of a one-parameter family
of quantum random walks. We give approximations for both the level-splitting at
the avoided crossing and the effectively two-dimensional subspace of the full
Hilbert space spanning the level crossing. This makes it possible to give the
leading order behaviour for the search time and the localisation probability in
the limit of large lattice size including the leading order coefficients. For
d=2 and d=3, these coefficients are calculated explicitly. Closed form
expressions are given for higher dimensions
Quantum Mechanics helps in searching for a needle in a haystack
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.Comment: Postscript, 4 pages. This is a modified version of the STOC paper
(quant-ph/9605043) and is modified to make it more comprehensible to
physicists. It appeared in Phys. Rev. Letters on July 14, 1997. (This paper
was originally put out on quant-ph on June 13, 1997, the present version has
some minor typographical changes
Realization of generalized quantum searching using nuclear magnetic resonance
According to the theoretical results, the quantum searching algorithm can be
generalized by replacing the Walsh-Hadamard(W-H) transform by almost any
quantum mechanical operation. We have implemented the generalized algorithm
using nuclear magnetic resonance techniques with a solution of chloroform
molecules. Experimental results show the good agreement between theory and
experiment.Comment: 11 pages,3 figure. Accepted by Phys. Rev. A. Scheduled Issue: 01 Mar
200
Spatial search in a honeycomb network
The spatial search problem consists in minimizing the number of steps
required to find a given site in a network, under the restriction that only
oracle queries or translations to neighboring sites are allowed. In this paper,
a quantum algorithm for the spatial search problem on a honeycomb lattice with
sites and torus-like boundary conditions. The search algorithm is based on
a modified quantum walk on a hexagonal lattice and the general framework
proposed by Ambainis, Kempe and Rivosh is used to show that the time complexity
of this quantum search algorithm is .Comment: 10 pages, 2 figures; Minor typos corrected, one Reference added.
accepted in Math. Structures in Computer Science, special volume on Quantum
Computin
Optimization of Partial Search
Quantum Grover search algorithm can find a target item in a database faster
than any classical algorithm. One can trade accuracy for speed and find a part
of the database (a block) containing the target item even faster, this is
partial search. A partial search algorithm was recently suggested by Grover and
Radhakrishnan. Here we optimize it. Efficiency of the search algorithm is
measured by number of queries to the oracle. The author suggests new version of
Grover-Radhakrishnan algorithm which uses minimal number of queries to the
oracle. The algorithm can run on the same hardware which is used for the usual
Grover algorithm.Comment: 5 page
Spatial quantum search in a triangular network
The spatial search problem consists in minimizing the number of steps
required to find a given site in a network, under the restriction that only
oracle queries or translations to neighboring sites are allowed. We propose a
quantum algorithm for the spatial search problem on a triangular lattice with N
sites and torus-like boundary conditions. The proposed algortithm is a special
case of the general framework for abstract search proposed by Ambainis, Kempe
and Rivosh [AKR05] (AKR) and Tulsi [Tulsi08], applied to a triangular network.
The AKR-Tulsi formalism was employed to show that the time complexity of the
quantum search on the triangular lattice is O(sqrt(N logN)).Comment: 10 pages, 4 Postscript figures, uses sbc-template.sty, appeared in
Annals of WECIQ 2010, III Workshop of Quantum Computation and Quantum
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