论文标题
库酸酯超导体的峰值结构
Peak-structure in self-energy of cuprate superconductors
论文作者
论文摘要
通过机器学习技术从库酸酯超导体的光发射光谱中推导出的正常和异常的自我呼吸，这呼吁进行解释。在这里，在动力学驱动的超导率的框架内分析了铜土超导体中的正常和异常的自我能量。结果表明，交换的旋转激发产生了正常和异常的自我功能中发音良好的低能峰结构，但是，它们在总的自我能源中不会取消。特别是，正常自我能源中的峰值结构主要负责单粒子激发光谱中的峰值浸入结构，并且可以持续到正常状态，而异常的自我能源中的尖峰则产生了至关重要的贡献。此外，还分析了随着掺杂和动量的峰值结构的演变。
The recently deduced normal and anomalous self-energies from photoemission spectra of cuprate superconductors via the machine learning technique are calling for an explanation. Here the normal and anomalous self-energies in cuprate superconductors are analyzed within the framework of the kinetic-energy-driven superconductivity. It is shown that the exchanged spin excitations give rise to the well-pronounced low-energy peak-structures in both the normal and anomalous self-energies, however, they do not cancel in the total self-energy. In particular, the peak-structure in the normal self-energy is mainly responsible for the peak-dip-hump structure in the single-particle excitation spectrum, and can persist into the normal-state, while the sharp peak in the anomalous self-energy gives rise to a crucial contribution to the superconducting gap, and vanishes in the normal-state. Moreover, the evolution of the peak-structure with doping and momentum are also analyzed.
