Monday, December 3, 2018, 1:30 pm — ISB Bldg. 734 Conf. Rm. 201 (upstairs)

The DFT+DMFT combined with the continuous-time quantum Monte Carlo (CT-QMC) impurity solver is one of the successful approaches to describe correlated electron materials. However, analytic continuation of the QMC data written in the imaginary frequency to the real axis is a difficult numeric problem mainly due to the ill-conditioned kernel matrix. While the maximum entropy method is one of the most suitable choices to gain information from the noisy input data, its applications to the materials with strong spin-orbit coupling are limited by the non-negative condition of the output spectral function. In the first part of this talk, I will discuss the newly developed methods for analytic continuation problem, the so-called maximum quantum entropy method (MQEM) [1]. It is the extension of the conventional method, introducing quantum relative entropy as a regularization function. The application of the MQEM for a prototype j_eff=1/2 Mott insulator, Sr2IrO4, shows that it provides a reasonable band structure without introducing a material specific base set. I will also introduce the application of machine learning technique to the same problem [2]. In the second part, a simple technique to branching ratio from the first-principles calculation will be discussed [3]. The calculated ?L·S? and branching ratio of the different 5d iridates, namely Sr2IrO4, Sr2MgIrO6, Sr2ScIrO6, and Sr2TiIrO6 are in good agreement with recent experimental data. Its reliability and applicability also be carefully examined in the recent study. [1] J.-H. Sim and M. J. Han, Phys. Rev. B 98, 205102 (2018). [2] H. Yoon, J.-H. Sim, and M. J. Han, Phys. Rev. B (in press). [3] J.-H. Sim, H. Yoon, S. H. Park, and M. J. Han, Phys. Rev. B 94, 115149 (2016).

Hosted by: Sangkook Choi

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