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arXiv:1002.1274 · Physical Review A

Quantum-walk approach to searching on fractal structures

Elena Agliari, A. Blumen, Oliver Mülken

Published Jul 8, 2010• 89 citations
arXivHTMLPDF

Abstract

We study continuous-time quantum walks mimicking the quantum search based on Grover's procedure. This allows us to consider structures, that is, databases, with arbitrary topological arrangements of their entries. We show that the topological structure of the database plays a crucial role by analyzing, both analytically and numerically, the transition from the ground to the first excited state of the Hamiltonian associated with different (fractal) structures. Additionally, we use the probability of successfully finding a specific target as another indicator of the importance of the topological structure.

DOI
10.1103/physreva.82.012305

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We study continuous-time quantum walks mimicking the quantum search based on Grover's procedure. This allows us to consider structures, that is, databases, with arbitrary topological arrangements of their entries. We show that the topological structure of the database plays a crucial role by analyzing, both analytically and numerically, the transition from the ground to the first excited state of the Hamiltonian associated with different (fractal) structures. Additionally, we use the probability of successfully finding a specific target as another indicator of the importance of the topological structure.
Abstract In this paper, we study Grover’s search algorithm focusing on continuous-time quantum walk on graphs. We propose an alternative optimization approach to Grover’s algorithm on graphs that can be summarized as follows: Instead of finding specific graph topologies convenient for the related quantum walk, we fix the graph topology and vary the underlying graph Laplacians. As a result, we search for the most appropriate analytical structure on graphs endowed with fixed topologies yielding better search outcomes. We discuss strategies to investigate the optimality of Grover’s algorithm and provide an example with an easy tunable graph Laplacian to investigate our ideas.
Spatial search by continuous-time quantum walks on complex networks is focused on using a quantum walk in continuous time in order to find a single or multiple marked vertices within the complex network. The specific formalism used here is to consider a coupling constant that shifts the state of the quantum walker from the initial state to the target state, which is the marked vertex. The thesis begins with establishing the mathematical framework of network theory, quantum walks and numerical methods that will be used in the remainder of the thesis. Then spatial search by continuous-time quantum walk is studied on regular and semi-regular graphs, where most analytical results can be found. This will get us acquainted with spatial search by quantum walk. The complex networks studied are Barabasi-Albert graphs and the Internet network on the level of autonomous systems. Different renormalized and pruned versions of the Internet network are studied. The parameters of the quantum walk that are focused on are the optimal values for the coupling constant, success probability, time and search time.
This paper explores the application of quantum walk algorithms to graph traversal and search problems. Classical algorithms often struggle with the computational complexity of traversing and searching large graphs, leading to significant time and resource limitations. Quantum walks, utilizing superposition and interference, offer a potential pathway to achieve exponential speedups. This work details the theoretical framework for applying quantum walks to graph problems, specifically focusing on traversal and search tasks. We present a generalized approach for mapping graph structures onto quantum walk systems and discuss the key mathematical formulations involved. The core of our investigation revolves around the construction of quantum walk operators that mimic the movement and interaction rules inherent in graph traversal. We analyze the evolution of the quantum walk state and derive expressions for the probability of reaching a specific node in the graph. Furthermore, we examine the impact of graph topology on the performance of the quantum walk, highlighting the potential for tailored algorithms to exploit specific graph structures. The results demonstrate the theoretical feasibility of quantum walk algorithms for significantly accelerating graph traversal and search operations, contributing to advancements in areas such as network analysis, database management, and artificial intelligence.
Abstract Quantum search via continuous-time quantum walk on truncated simplex lattices is an important example of the quantum search on the structured database. In this letter, when the search target is a set of the marked vertices, the run time of the quantum search and the critical jumping rates are derived. Quantum search with the partial information of the location of the marked vertex is also discussed. Furthermore, with the edge weights suitably adjusted, the three-stage search process can be optimized into a two-stage quantum search algorithm on the second-order truncated simplex lattice.
We consider the quantum search problem with a continuous-time quantum walk for networks characterized by a finite spectral dimension ds{d}_{s}ds​ of the network Laplacian. For general networks of fractal (integer or noninteger) dimension df{d}_{f}df​, for which in general ${d}_{f}\ensuremath{\ne}{d}_{s}$, it suggests that it is ds{d}_{s}ds​ that determines the computational complexity of the quantum search. Our results continue those of A. M. Childs and J. Goldstone [Phys. Rev. A 70, 022314 (2004)] for lattices of integer dimension, where d=df=dsd={d}_{f}={d}_{s}d=df​=ds​. Thus, we find for general fractals that the Grover limit of quantum search can be obtained whenever ds>4{d}_{s}>4ds​>4. This complements the recent discussion of mean-field (i.e., ${d}_{s}\ensuremath{\rightarrow}\ensuremath{\infty}$) networks by S. Chakraborty et al. [Phys. Rev. Lett. 116, 100501 (2016)] showing that for all those networks, spatial search by quantum walk is optimal.