The Non-equilibrium Green's function (NEGF) formalism is a particularly powerful method to simulate the quantum transport properties of nanoscale devices such as transistors, photo-diodes, or memory cells, in the ballistic limit of transport or in the presence of various scattering sources such as electronphonon, electron-photon, or even electron-electron interactions. The inclusion of all these mechanisms has been first demonstrated in small systems, composed of a few atoms, before being scaled up to larger structures made of thousands of atoms. Also, the accuracy of the models has kept improving, from empirical to fully ab-initio ones, e.g., density functional theory (DFT). This paper summarizes key (algorithmic) achievements that have allowed us to bring DFT+NEGF simulations closer to the dimensions and functionality of realistic systems. The possibility of leveraging graph neural networks and machine learning to speed up ab-initio device simulations is discussed as well.

翻译：非平衡格林函数（NEGF）形式体系是一种特别强大的方法，用于模拟纳米尺度器件（如晶体管、光电二极管或存储单元）在弹道输运极限下，或在存在各种散射源（如电子-声子、电子-光子甚至电子-电子相互作用）时的量子输运特性。所有这些机制的纳入最初在由少数原子组成的小型系统中得到验证，随后被扩展至由数千原子构成的更大结构。同时，模型的精度也在持续提升，从经验模型发展到完全从头算方法，例如密度泛函理论（DFT）。本文总结了关键（算法）进展，这些进展使我们能够将DFT+NEGF模拟推向更接近实际系统的尺寸与功能层面。文中还探讨了利用图神经网络和机器学习加速从头算器件模拟的可能性。