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arXiv 1002.2513cond-mat.mes-hallcond-mat.str-el
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相互作用纳米结构的有效低能哈密顿量

Effective low-energy Hamiltonians for interacting nanostructures

Michael Kinza, Jutta Ortloff, Carsten Honerkamp

摘要:

我们提出了一个功能性的重整化群(fRG)处理三角形石墨烯纳米盘及其复合材料,建模与蜂窝晶格结构的有限尺寸哈伯德类哈密顿。在半填充时,这些结构的非相互作用谱包含一定数量的费米能级的半填充态。对于三角形纳米盘的情况下,包括这些简并状态之间的相互作用被认为导致一个大的基态自旋与潜在的自旋电子学应用。在这里,我们执行一个系统的fRG流,其中激发的单粒子状态被整合出一个减少的能量截止,产生一个重整化的低能量哈密顿量的零能量状态,包括激发能级的影响。数值实现证实了一个更简单的Hartree-Fock治疗的相互作用的影响内的零能量状态得到的结果。特别是,对于三角形纳米盘,具有零能量的单粒子态的简并性对于更高水平的影响是非常鲁棒的。作为一个解释,我们给出了一个一般的论点,在这个fRG计划的零能量简并保持不分裂在相当一般的条件下,任何大小的三角纳米盘。我们进一步讨论了单个纳米盘和复合蝴蝶结形系统的有效哈密顿量及其基态的差异。

英文摘要:

We present a functional renormalization group (fRG) treatment of trigonal graphene nanodiscs and composites thereof, modeled by finite-size Hubbard-like Hamiltonians with honeycomb lattice structure. At half filling, the noninteracting spectrum of these structures contains a certain number of half-filled states at the Fermi level. For the case of trigonal nanodiscs, including interactions between these degenerate states was argued to lead to a large ground state spin with potential spintronics applications. Here we perform a systematic fRG flow where the excited single-particle states are integrated out with a decreasing energy cutoff, yielding a renormalized low-energy Hamiltonian for the zero-energy states that includes effects of the excited levels. The numerical implementation corroborates the results obtained with a simpler Hartree-Fock treatment of the interaction effects within the zero-energy states only. In particular, for trigonal nanodiscs the degeneracy of the one-particle-states with zero-energy turns out to be very robust against influences of the higher levels. As an explanation, we give a general argument that within this fRG scheme the zero-energy degeneracy remains unsplit under quite general conditions and for any size of the trigonal nanodisc. We furthermore discuss the differences in the effective Hamiltonian and their ground states of single nanodiscs and composite bow-tie-shaped systems.

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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