ARC 3.0: An expanded Python toolbox for atomic physics calculations

Robertson, EJ; Sibalic, N; Potvliege, RM; Jones, MPA

doi:10.1016/j.cpc.2020.107814

ARC 3.0: An expanded Python toolbox for atomic physics calculations

Robertson, EJ; Sibalic, N; Potvliege, RM; Jones, MPA

Authors

EJ Robertson

N Sibalic

Dr Robert Potvliege r.m.potvliege@durham.ac.uk
Associate Professor

Professor Matthew Jones m.p.a.jones@durham.ac.uk
Professor

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 (Šibalić et al., 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.

Citation

Robertson, E., Sibalic, N., Potvliege, R., & Jones, M. (2021). ARC 3.0: An expanded Python toolbox for atomic physics calculations. Computer Physics Communications, 261(107814), Article 107814. https://doi.org/10.1016/j.cpc.2020.107814

Journal Article Type	Article
Acceptance Date	Dec 5, 2020
Online Publication Date	Jan 1, 2021
Publication Date	Apr 30, 2021
Deposit Date	Jan 6, 2021
Publicly Available Date	Jan 8, 2021
Journal	Computer Physics Communications
Print ISSN	0010-4655
Publisher	Elsevier
Peer Reviewed	Peer Reviewed
Volume	261
Issue	107814
Article Number	107814
DOI	https://doi.org/10.1016/j.cpc.2020.107814
Related Public URLs	https://arxiv.org/abs/2007.12016v1

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Journal Pre-proof ©2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).