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arXiv 2004.06897cond-mat.str-elcond-mat.supr-conhep-th
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关联电子的全息幺正化群重整化群-- I:张量网络方法

Holographic unitary renormalization group for correlated electrons -- I: a tensor network approach

Anirban Mukherjee, Siddhartha Lal

摘要:

我们提出了一个统一的框架,重新正规化的相关电子系统的哈密顿量和本征基,从而揭示了电子相关性和多粒子纠缠之间的相互作用。为此,我们对文献[1]中的酉重整化群(URG)方案作了实质性的推广. \cite{anirbanmotti,anirbanmott2,mukherjee2020}。我们将RG重铸为哈密顿张量网络的离散流,即,各种$2n$ -点散射顶点张量的集合包括哈密顿量。重整化的进展通过幺正变换,块对角化的哈密顿迭代通过单粒子本征态的解纠缠。这个过程自然地包含了量子涨落的作用。RG流方程具有非平凡的结构,通过依赖于频率的动力学自能和相关能显示反馈机制。各种UV能量尺度之间的相互作用,使耦合RG方程流向一个稳定的固定点在IR。在IR固定点的有效哈密顿一般具有减少的参数空间,以及自由度的数量,相比微观哈密顿。重要的是,观察到顶点张量网络支配表示多粒子本征态系数的张量网络的RG流。本征基的各种多粒子纠缠特征的RG演化,反过来,量化通过系数张量网络。通过这种方式,我们表明,URG框架提供了一个微观的理解全息重整:RG流的顶点张量网络生成一个本征态系数张量网络拥有多粒子纠缠度量。我们发现,本征态张量网络容纳费米子交换所产生的符号因子。

英文摘要:

We present a unified framework for the renormalisation of the Hamiltonian and eigenbasis of a system of correlated electrons, unveiling thereby the interplay between electronic correlations and many-particle entanglement. For this, we extend substantially the unitary renormalization group (URG) scheme introduced in Refs.\cite{anirbanmotti,anirbanmott2,mukherjee2020}. We recast the RG as a discrete flow of the Hamiltonian tensor network, i.e., the collection of various $2n$-point scattering vertex tensors comprising the Hamiltonian. The renormalisation progresses via unitary transformations that block diagonalizes the Hamiltonian iteratively via the disentanglement of single-particle eigenstates. This procedure incorporates naturally the role of quantum fluctuations. The RG flow equations possess a non-trivial structure, displaying a feedback mechanism through frequency-dependent dynamical self-energies and correlation energies. The interplay between various UV energy scales enables the coupled RG equations to flow towards a stable fixed point in the IR. The effective Hamiltonian at the IR fixed point generically has a reduced parameter space, as well as number of degrees of freedom, compared to the microscopic Hamiltonian. Importantly, the vertex tensor network is observed to govern the RG flow of the tensor network that denotes the coefficients of the many-particle eigenstates. The RG evolution of various many-particle entanglement features of the eigenbasis are, in turn, quantified through the coefficient tensor network. In this way, we show that the URG framework provides a microscopic understanding of holographic renormalisation: the RG flow of the vertex tensor network generates a eigenstate coefficient tensor network possessing a many-particle entanglement metric. We find that the eigenstate tensor network accommodates sign factors arising from fermion exchange.

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