论文标题
ARC 3.0：用于原子物理计算的扩展的Python工具箱
ARC 3.0: An expanded Python toolbox for atomic physics calculations
论文作者
论文摘要
ARC 3.0是一个模块化的，面向对象的Python库，结合了数据和算法，可以计算碱和二价原子的一系列属性。建立在ARC库的初始版本[N. Šibalić等人，计算。物理。社区。 220，319（2017）]，重点关注碱原子的rydberg州，该重大升级引入了对二价原子的支持。它还添加了用于使用原子表面相互作用的新方法，用于对光学晶格中的超低原子进行建模以及计算价电子波函数和动态极性。此类计算在多个领域中具有应用，例如，在多体物理学的量子模拟中，基于原子的DC和AC场的感应（包括在微波炉和THZ计量学中）以及量子栅极协议的开发中。 ARC 3.0附带了广泛的文档，其中包括许多示例。它的模块化结构有助于其在基于原子的量子技术中的广泛问题中的应用。
ARC 3.0 is a modular, object-oriented Python library combining data and algorithms to enable the calculation of a range of properties of alkali and divalent atoms. Building on the initial version of the ARC library [N. Šibalić et al, Comput. Phys. Commun. 220, 319 (2017)], which focused on Rydberg states of alkali atoms, this major upgrade introduces support for divalent atoms. It also adds new methods for working with atom-surface interactions, for modelling ultracold atoms in optical lattices and for calculating valence electron wave functions and dynamic polarisabilities. Such calculations have applications in a variety of fields, e.g., in the quantum simulation of many-body physics, in atom-based sensing of DC and AC fields (including in microwave and THz metrology) and in the development of quantum gate protocols. ARC 3.0 comes with an extensive documentation including numerous examples. Its modular structure facilitates its application to a wide range of problems in atom-based quantum technologies.
