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ARC 3.0: An expanded Python toolbox for atomic physics calculations
arXiv
Authors: Elizabeth J. Robertson, Nikola Šibalić, Robert M. Potvliege, Matthew P. A. Jones
Year
2020
Paper ID
22007
Status
Preprint
Abstract Read
~2 min
Abstract Words
149
Citations
N/A
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. 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.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
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- 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.
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