发表机构
Center for Computational Quantum Physics, Flatiron Institute; Department of Physics, National Chung Cheng University; Physics Division, National Center for Theoretical Sciences; Ames National Laboratory; Department of Physics and Astronomy, Iowa State University; School of Physics and Astronomy, Rochester Institute of Technology; Université Paris-Saclay, CNRS, CEA, Institut de physique théorique（Flatiron研究所计算量子物理中心; 国立中正大学物理系; 国家理论科学中心物理组; 艾姆斯国家实验室; 爱荷华州立大学物理与天文系; 罗切斯特理工学院物理与天文学院; 巴黎萨克雷大学、法国国家科学研究中心、法国原子能和替代能源委员会、理论物理研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文介绍开源Python软件包GEM，它实现ghost-Gutzwiller近似，用于高效计算强关联电子系统的平衡性质，支持多轨道、零温和有限温度及对称破缺相，并验证了其性能。
AI 中文摘要
我们在此介绍GEM（Ghost Embedding Method，幽灵嵌入方法），一个用Python编写的开源软件包，用于在ghost-Gutzwiller近似方法内计算强关联电子系统的平衡性质。GEM为研究多轨道晶格模型提供了一个计算高效的框架。它支持零温和有限温度计算以及对称破缺相。它与TRIQS生态系统集成，提供了模型构建、自洽求解和物理可观测量评估的工具。我们首先详细阐述该方法的理论表述，然后介绍软件架构，最后介绍一些实际工作流程，该流程也针对已有结果验证了实现。特别是，我们通过多轨道和有限温度应用展示了GEM的能力，并讨论了其相对于更苛刻的量子嵌入方法的计算成本。
英文摘要
We present GEM (Ghost Embedding Method), an open-source software package written in Python for computing equilibrium properties of strongly correlated electronic systems within the ghost-Gutzwiller approximation method. GEM provides a computationally efficient framework for studying multi-orbital lattice models. It supports zero- and finite-temperature calculations and symmetry broken phases. It is integrated with the TRIQS ecosystem, providing tools for model construction, self-consistent solution, and evaluation of physical observables. We first detail the method's theoretical formulation, then we present the software architecture, and finally we introduce some practical workflow, which also validates the implementation against established results. In particular, we illustrate the capabilities of GEM through multiorbital and finite-temperature applications and discuss its computational cost relative to more demanding quantum embedding approaches.
Comments21 pages, 4 figures
