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Quantitative approach to Grover’s quantum walk on graphs

Quantitative approach to Grover's quantum walk on graphs
Authors: Gamal Mograby; Radhakrishnan Balu; Kasso A. Okoudjou; Alexander Teplyaev;

Quantitative approach to Grover’s quantum walk on graphs

Abstract

AbstractIn 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.

Keywords

Quantum Physics, Grover's quantum walk, FOS: Physical sciences, weighted directed graphs, Mathematical Physics (math-ph), Signed and weighted graphs, probabilistic graph Laplacian, Quantum information, communication, networks (quantum-theoretic aspects), Quantum Physics (quant-ph), Quantum mechanics on special spaces: manifolds, fractals, graphs, lattices, Mathematical Physics, Selfadjoint operator theory in quantum theory, including spectral analysis, 81P45, 81Q35, 05C22, 81Q10

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average
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