Author:

Keywords:

Science & Technology, Technology, Physical Sciences, Computer Science, Interdisciplinary Applications, Physics, Mathematical, Computer Science, Physics, Data analysis, Counting experiment, Likelihood, Chi-square, Python, 01 Mathematical Sciences, 02 Physical Sciences, 08 Information and Computing Sciences, Nuclear & Particles Physics, 46 Information and computing sciences, 49 Mathematical sciences, 51 Physical sciences

Abstract:

SATLAS2 is a Python library that enables the user to fit counting data from laser spectroscopy experiments, in particular those that measure atomic hyperfine structures. In this analysis, the user can choose how the uncertainties are treated and can also opt to generate a random walk in order to present a fuller picture of the parameter space. The major upgrade compared to the previous version of SATLAS is the different architecture of the codebase, which enabled a performance boost, with speed-up factors ranging from 20 to 300 times for various use cases. For backward compatibility, a translation layer between the two architectures is available, implementing only the core functionality of SATLAS.