@inproceedings{ea7e30e0775e4ca6906ee28d0634fbd1,
title = "Node centrality for continuous-time quantum walks",
abstract = "The study of complex networks has recently attracted increasing interest because of the large variety of systems that can be modeled using graphs. A fundamental operation in the analysis of complex networks is that of measuring the centrality of a vertex. In this paper, we propose to measure vertex centrality using a continuous-time quantum walk. More specifically, we relate the importance of a vertex to the influence that its initial phase has on the interference patterns that emerge during the quantum walk evolution. To this end, we make use of the quantum Jensen-Shannon divergence between two suitably defined quantum states. We investigate how the importance varies as we change the initial state of the walk and the Hamiltonian of the system. We find that, for a suitable combination of the two, the importance of a vertex is almost linearly correlated with its degree. Finally, we evaluate the proposed measure on two commonly used networks.",
keywords = "Complex Network, Quantum Jensen-Shannon Divergence, Quantum Walk, Vertex Centrality",
author = "Luca Rossi and Andrea Torsello and Hancock, {Edwin R.}",
year = "2014",
month = aug,
doi = "10.1007/978-3-662-44415-3_11",
language = "English",
isbn = "9783662444146",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "103--112",
booktitle = "Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2014, Proceedings",
address = "Germany",
note = "Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2014 ; Conference date: 20-08-2014 Through 22-08-2014",
}