论文标题
基于Krylov方法的紧密结合系统中Majorana边缘模式的识别
Identification of the Majorana edge modes in tight-binding systems based on the Krylov method
论文作者
论文摘要
在非平凡拓扑阶段中的低维结构可以托管间隙主要束缚状态,在实验上被识别为差分电导中的零偏置峰。研究主要模式的理论方法主要基于有限系统的宽大对应关系或通过Bogoliubov-de Gennes形式主义的对角线化。在本文中,我们开发了一种有效的方法来通过寻找对称矩阵的极端特征值来识别Majoraana In-GAP(边缘)状态。提出的方法基于Krylov方法,允许研究模式的空间曲线以及系统的光谱。该方法的优点是计算成本,该计算成本显示了对晶格位点数量的线性依赖性。后一种问题可以解决非常大的任意形状/几何形状群。为了证明我们的方法的效率,我们研究了Kitaev和Rashba模型所描述的二维和三维集群,我们为此确定了Majoraana模式的数量并计算其空间结构。此外,我们讨论了系统大小对沉积在超导表面上的磁性纳米兰州拓扑阶段物理特性的影响。在这种情况下,我们已经表明,间隙状态的特征值取决于系统边缘的长度。
Low dimensional structures in the non-trivial topological phase can host the in-gap Majorana bound states, identified experimentally as zero-bias peaks in differential conductance. Theoretical methods for studying Majorana modes are mostly based on the bulk-boundary correspondence or exact diagonalization of finite systems via, e.g., Bogoliubov-de Gennes formalism. In this paper, we develop an efficient method for identifying the Majorana in-gap (edge) states via looking for extreme eigenvalues of symmetric matrices. The presented approach is based on the Krylov method and allows for study the spatial profile of the modes as well as the spectrum of the system. The advantage of this method is the calculation cost, which shows linear dependence on the number of lattice sites. The latter problem may be solved for very large clusters of arbitrary shape/geometry. In order to demonstrate the efficiency of our approach, we study two- and three-dimensional clusters described by the Kitaev and Rashba models for which we determine the number of Majorana modes and calculate their spatial structures. Additionally, we discuss the impact of the system size on the physical properties of the topological phase of the magnetic nanoisland deposited on the superconducting surface. In this case, we have shown that the eigenvalues of the in-gap states depend on the length of the system edge.