Abstract
We present a major update to ElecSus, a computer program and underlying model to calculate the electric susceptibility of an alkali-metal atomic vapour. Knowledge of the electric susceptibility of a medium is essential to predict its absorptive and dispersive properties. In this version we implement several changes which significantly extend the range of applications of ElecSus, the most important of which is support for non-axial magnetic fields (i.e. fields which are not aligned with the light propagation axis). Supporting this change requires a much more general approach to light propagation in the system, which we have now implemented. We exemplify many of these new applications by comparing ElecSus to experimental data. In addition, we have developed a graphical user interface front-end which makes the program much more accessible, and have improved on several other minor areas of the program structure. Program summaryProgram Title: ElecSusProgram Files doi:http://dx.doi.org/10.17632/h7cj8bz4bd.1Licensing provisions: Apache License, Version 2.0Programming language: PythonExternal routines/libraries: SciPy library [1] 0.15.0 or later, NumPy [1], matplotlib [2], sympy [3], lmfit 0.9.5 or later [4], wxpython (required for GUI only)Nature of problem: Calculating the weak-probe electric susceptibility of an alkali-metal vapour. The electric susceptibility can be used to calculate spectra such as transmission and Stokes parameters. Measurements of experimental parameters can be made by fitting the theory to data.Solution method: The transition frequencies and wavelengths are calculated using a matrix representation of the Hamiltonian in the completely uncoupled basis. A suite of fitting methods are provided in order to allow user supplied experimental data to be fit to the theory, thereby allowing experimental parameters to be extracted.Restrictions: Results are only valid in the weak-probe regime.[1] T. E. Oliphant, Comput. Sci. Eng. 9, 10 (2007). http://www.scipy.org/[2] J. D. Hunter, Comput. Sci. Eng. 9, 10 (2007). http://matplotlib.org/[3] A. Meurer et. al, PeerJ Comp. Sci. 3, e103 (2017) http://www.sympy.org/[4] M. Newville et al., LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python, Zenodo (2014). DOI:10.5281/zenodo.11813 https://lmfit.github.io/lmfit-py/
Highlights
The fundamental interaction between atoms and light continues to underpin a great deal of scientific research
We have presented an updated computer program to calculate the electric susceptibility of an alkali-metal vapour
In addition to the previous features of ElecSus, the program is able to account for magnetic fields with arbitrary orientation with respect to the light propagation axis, and electric field propagation
Summary
The fundamental interaction between atoms and light continues to underpin a great deal of scientific research. One can use these optimised filters in other applications, e.g. using the filter to make an intrinsically frequency-stable laser system [9], creating a dichroic beam splitter for Raman light [18] or filtering frequency-degenerate photon pairs from an optical parametric oscillator [19]. Since the first publication of ElecSus in 2015 [15], we have added significant functionality that adds to both the scientific scope and the accessibility of the program. In the remainder of the paper, we discuss the physics and computational implementation of the above additions
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