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Lecture notes in computer science

Quantum Walks on Two-Dimensional Grids with Multiple Marked Locations

Nikolajs Nahimovs, Alexander Rivosh

Published Jan 1, 2016• 15 citations
Publisher
DOI
10.1007/978-3-662-49192-8_31

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Quantum Walks on Two-Dimensional Grids with Multiple Marked Locations

Nikolajs Nahimovs, Alexander Rivosh

The running time of a quantum walk search algorithm depends on both the structure of the search space (graph) and the configuration (the placement and the number) of marked locations. While the first dependence has been studied in a number of papers, the second dependence remains mostly unstudied. We study search by quantum walks on the two-dimensional grid using the algorithm of Ambainis, Kempe and Rivosh [3]. The original paper analyses one and two marked locations only. We move beyond two marked locations and study the behaviour of the algorithm for several configurations of multiple marked locations. In this paper, we prove two results showing the importance of how the marked locations are arranged. First, we present two placements of [Formula: see text] marked locations for which the number of steps of the algorithm differs by a factor of [Formula: see text]. Second, we present two configurations of [Formula: see text] and [Formula: see text] marked locations having the same number of steps and probability of finding a marked location.

International Journal of Foundations of Computer Science•Jun 1, 2018•3 citations
The running time of a quantum walk search algorithm depends on both the structure of the search space (graph) and the configuration (the placement and the number) of marked locations. While the first dependence has been studied in a number of papers, the second dependence remains mostly unstudied. We study search by quantum walks on the two-dimensional grid using the algorithm of Ambainis, Kempe and Rivosh [3]. The original paper analyses one and two marked locations only. We move beyond two marked locations and study the behaviour of the algorithm for several configurations of multiple marked locations. In this paper, we prove two results showing the importance of how the marked locations are arranged. First, we present two placements of [Formula: see text] marked locations for which the number of steps of the algorithm differs by a factor of [Formula: see text]. Second, we present two configurations of [Formula: see text] and [Formula: see text] marked locations having the same number of steps and probability of finding a marked location.