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arXiv:1205.0529 · IEEE Information Theory Workshop (ITW)

Quantum search algorithms on hierarchical networks

Franklin de Lima Marquezino, Renato Portugal, Stefan Boettcher

Published Oct 1, 2011• 7 citations
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Abstract

The “abstract search algorithm” is a well known quantum method to find a marked vertex in a graph. It has been applied with success to searching algorithms for the hypercube and the two-dimensional grid. In this work we provide an example for which that method fails to provide the best algorithm in terms of time complexity. We analyze search algorithms in degree-3 hierarchical networks using quantum walks driven by non-groverian coins. Our conclusions are based on numerical simulations, but the hierarchical structures of the graphs seems to allow analytical results.

DOI
10.1109/itw.2011.6089429

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The “abstract search algorithm” is a well known quantum method to find a marked vertex in a graph. It has been applied with success to searching algorithms for the hypercube and the two-dimensional grid. In this work we provide an example for which that method fails to provide the best algorithm in terms of time complexity. We analyze search algorithms in degree-3 hierarchical networks using quantum walks driven by non-groverian coins. Our conclusions are based on numerical simulations, but the hierarchical structures of the graphs seems to allow analytical results.
The quantum walk is a powerful tool to develop quantum algorithms, which usually are based on searching for a vertex in a graph with multiple marked vertices, with Ambainis's quantum algorithm for solving the element distinctness problem being the most shining example. In this work, we address the problem of calculating analytical expressions of the time complexity of finding a marked vertex using quantum-walk-based search algorithms with multiple marked vertices on arbitrary graphs, extending previous analytical methods based on Szegedy's quantum walk, which can be applied only to bipartite graphs. Two examples based on the coined quantum walk on two-dimensional lattices and hypercubes show the details of our method.
Recently several quantum search algorithms based on quantum walks were proposed. Those algorithms differ from Grover's algorithm in many aspects. The goal is to find a marked vertex in a graph faster than classical algorithms. Since the implementation of those new algorithms in quantum computers or in other quantum devices is error-prone, it is important to analyze their robustness under decoherence. In this work we analyze the impact of decoherence on quantum search algorithms implemented on two-dimensional grids and on hypercubes.
We use the abstract search algorithm and its extension due to Tulsi to analyze a spatial quantum search algorithm that finds a marked vertex in Hanoi networks of degree 4 faster than classical algorithms. We also analyze the effect of using non-Groverian coins that take advantage of the small-world structure of the Hanoi networks. We obtain the scaling of the total cost of the algorithm as a function of the number of vertices. We show that Tulsi's technique plays an important role to speed up the searching algorithm. We can improve the algorithm's efficiency by choosing a non-Groverian coin if we do not implement Tulsi's method. Our conclusions are based on numerical implementations.
There exist two types of configurations of marked vertices on a two-dimensional grid, known as the exceptional configurations, which are hard to find by the discrete-time quantum walk algorithms. In this article, we provide a comparative study of the quantum walk algorithm with different coins to search these exceptional configurations on a two-dimensional grid. We further extend the analysis to the hypercube, where only one type of exceptional configurations are present. Our observation, backed by numerical results, is that our recently proposed modified coin operator is the only coin which can search both types of exceptional configurations as well as nonexceptional configurations successfully. As a consequence, we observe that the existence of exceptional configurations are not a quantum phenomenon, rather a mere limitation of some of the coin operators.
We provide first evidence that some families of nonlinear quantum systems, rephrased in terms of coined quantum walks with effective nonlinear phase, display a strong computational advantage for search algorithms, over graphs having sets of vertices of constant size, e.g. the infinite square grid. The numerical simulations show that the walker finds the marked vertex in O(N1/4log⁡3/4N)O(N^{1/4} \log^{3/4} N)O(N1/4log3/4N) steps with probability O(1/log⁡N)O(1/\log N)O(1/logN), for an overall complexity of O(N1/4log⁡7/4N)O(N^{1/4}\log^{7/4}N)O(N1/4log7/4N). We also confirm this result analytically. Moreover the algorithm is implemented without the need for a specific oracle step, but by topological hole defect in the grid. From a quantum computing perspective, however, this hints at novel applications of quantum walk search: instead of using them to look for good solutions within the configuration space of a problem, we could use them to look for topological properties of the entire configuration space.
This study investigates the multi-solution search of the optimized quantum random-walk search algorithm on the hypercube. Through generalizing the abstract search algorithm which is a general tool for analyzing the search on the graph to the multi-solution case, it can be applied to analyze the multi-solution case of quantum random-walk search on the graph directly. Thus, the computational complexity of the optimized quantum random-walk search algorithm for the multi-solution search is obtained. Through numerical simulations and analysis, we obtain a critical value of the proportion of solutions q . For a given q , we derive the relationship between the success rate of the algorithm and the number of iterations when q is no longer than the critical value.