Rossi Luca, Torsello Andrea, Hancock Edwin R
School of Computer Science, University of Birmingham, United Kingdom.
Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca' Foscari Venezia, Venezia, Italy.
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Feb;91(2):022815. doi: 10.1103/PhysRevE.91.022815. Epub 2015 Feb 23.
In this paper we propose a quantum algorithm to measure the similarity between a pair of unattributed graphs. We design an experiment where the two graphs are merged by establishing a complete set of connections between their nodes and the resulting structure is probed through the evolution of continuous-time quantum walks. In order to analyze the behavior of the walks without causing wave function collapse, we base our analysis on the recently introduced quantum Jensen-Shannon divergence. In particular, we show that the divergence between the evolution of two suitably initialized quantum walks over this structure is maximum when the original pair of graphs is isomorphic. We also prove that under special conditions the divergence is minimum when the sets of eigenvalues of the Hamiltonians associated with the two original graphs have an empty intersection.
在本文中,我们提出了一种量子算法来测量一对无属性图之间的相似度。我们设计了一个实验,通过在两个图的节点之间建立一整套连接来合并这两个图,并通过连续时间量子游走的演化来探测所得结构。为了在不导致波函数坍缩的情况下分析游走的行为,我们基于最近引入的量子詹森 - 香农散度进行分析。特别地,我们表明,当原始的一对图同构时,在这个结构上两个适当初始化的量子游走演化之间的散度最大。我们还证明,在特殊条件下,当与两个原始图相关联的哈密顿量的特征值集的交集为空时,散度最小。