ARC 3.0: An expanded Python toolbox for atomic physics calculations

TL;DR

ARC 3.0 is a comprehensive Python library that extends atomic physics calculations to divalent atoms and introduces new features for atom-surface interactions, ultracold atom modeling, and wave function analysis, aiding quantum technology research.

Contribution

The paper presents ARC 3.0, a major upgrade to the existing library, adding support for divalent atoms and new calculation methods for atom-surface interactions and ultracold atom modeling.

Findings

Supports calculations for divalent atoms.

Includes new methods for atom-surface interactions.

Facilitates quantum technology applications.

Abstract

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. \v{S}ibali\'c 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.