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arXiv quant-ph/0510174quant-ph
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基于邻接矩阵谱分布的连续时间量子行走研究

Investigation of Continuous-Time Quantum Walk Via Spectral Distribution Associated with Adjacency Matrix

M. A. Jafarizadeh, S. Salimi

摘要:

本文利用图的邻接矩阵的谱分布,给出了一种计算一些重要图,如直线图、圈图$C_n$、完全图$K_n$、图$G_n$、有限路以及其它一些有限图和无限图上连续时间量子行走振幅的新方法,这些图都是用正交多项式如Hermite,Laguerre,Tchebichef和其他一些正交多项式。结果表明,利用谱分布,可以得到振幅的无限时间渐近行为,简单地使用方法的驻相近似(WKB近似),其中作为一个例子,该方法被应用到星形,二维梳状格,无限Hermite和Laguerre图。利用高斯求积公式,可以用有限图逼近无限图,反之亦然,从而用WKB方法得到大时间渐近性态。同样地,利用这种方法,引入了一些新的图,其中它们的振幅与某些基本图的振幅的乘积成比例,即使这些图本身与它们的基本图的笛卡尔乘积不相同。最后,通过计算某些无限图在足够大次数下的平均端到端距离,证明了在不同无限图上的连续时间量子行走属于不同的普适类,这些普适类也不同于相应的经典普适类.

英文摘要:

Using the spectral distribution associated with the adjacency matrix of graphs, we introduce a new method of calculation of amplitudes of continuous-time quantum walk on some rather important graphs, such as line, cycle graph $C_n$, complete graph $K_n$, graph $G_n$, finite path and some other finite and infinite graphs, where all are connected with orthogonal polynomials such as Hermite, Laguerre, Tchebichef and some other orthogonal polynomials. It is shown that using the spectral distribution, one can obtain the infinite time asymptotic behavior of amplitudes simply by using the method of stationary phase approximation(WKB approximation), where as an example, the method is applied to star, two-dimensional comb lattices, infinite Hermite and Laguerre graphs. Also by using the Gauss quadrature formula one can approximate infinite graphs with finite ones and vice versa, in order to derive large time asymptotic behavior by WKB method. Likewise, using this method, some new graphs are introduced, where their amplitude are proportional to product of amplitudes of some elementary graphs, even though the graphs themselves are not the same as Cartesian product of their elementary graphs. Finally, via calculating mean end to end distance of some infinite graphs at large enough times, it is shown that continuous time quantum walk at different infinite graphs belong to different universality classes which are also different than those of the corresponding classical ones.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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