arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1708.07652cond-mat.str-elcond-mat.dis-nnquant-ph
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无序系统的纠缠重整化

Entanglement renormalization for disordered systems

Andrew M. Goldsborough, Glen Evenbly

摘要:

我们提出了一种研究强无序系统的张量网络方法,该方法是基于纠缠重整化[G. Vidal,Phys. Rev. Lett. 99,220405(2007)]。该方法利用强无序重整化群来确定格点粗粒化的顺序,从而在使用变分能量最小化进行优化之前设置相应张量网络的整体结构。从无序XXZ模型的基准结果表明,这种方法准确地捕获在无序系统的基态纠缠,即使在很长的距离。这种方法得到了一类新的一维系统的有效收缩张量网络模型,它可以理解为无序系统的多尺度纠缠重整化模型的推广.

英文摘要:

We propose a tensor network method for investigating strongly disordered systems that is based on an adaptation of entanglement renormalization [G. Vidal, Phys. Rev. Lett. 99, 220405 (2007)]. This method makes use of the strong disorder renormalization group to determine the order in which lattice sites are coarse-grained, which sets the overall structure of the corresponding tensor network ansatz, before optimization using variational energy minimization. Benchmark results from the disordered XXZ model demonstrates that this approach accurately captures ground state entanglement in disordered systems, even at long distances. This approach leads to a new class of efficiently contractible tensor network ansatz for 1D systems, which may be understood as a generalization of the multi-scale entanglement renormalization ansatz for disordered systems.

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