2020-11-09, 17:45–18:00, Times in UTC
The Multi-Mission Maximum Likelihood framework (threeML) is a flexible python-based framework for multi-wavelength data analysis in astronomy. ThreeML allows joint likelihood fits of data recorded by many different instruments, from radio to gamma rays. This is achieved by encapsulating data access into instrument-specific plugins, leaving the rest of the analysis agnostic of the data format. In this talk, I will outline threeML's design and major components, with a focus on the modeling language (astromodels) and the data-access plugins. I will show use cases and analysis examples, as well as explain how to add new plugins for instruments/data formats that threeML does not yet support.