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This research establishes new theoretical bounds for spatial search using continuous-time quantum walks, demonstrating that specific graph structures can be optimized to achieve optimal performance for arbitrary states. The study further reveals that adding edges to a graph consistently improves search efficiency, offering concrete guidance for designing high-performance quantum algorithms on complex networks.
The optimal search on graph by continuous-time quantum walks
arXiv:1711.01765v5 Announce Type: replace Abstract: Chakraborty and Leonardo have shown that a spatial search by quantum walk is optimal for almost all graphs. However, we observed that on some graphs, certain states cannot be searched optimally. We present a method for constructing an optimal graph that searches an arbitrary state and provides the optimal condition. We also analyze the monotonicity of the search performance and conclude that the search performance can be improved by adding edges.
Abstract:Chakraborty and Leonardo have shown that a spatial search by quantum walk is optimal for almost all graphs. However, we observed that on some graphs, certain states cannot be searched optimally. We present a method for constructing an optimal graph that searches an arbitrary state and provides the optimal condition. We also analyze the monotonicity of the search performance and conclude that the search performance can be improved by adding edges.
arXiv:1711.01765 [quant-ph]
(or arXiv:1711.01765v5 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.1711.01765 Focus to learn more arXiv-issued DOI via DataCite
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