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Catching Neutrinos with Python and KM3NeT


KM3NeT is the next generation underwater neutrino telescope located in the deepest seas of the Mediterranean. Once completed, it will have an instrumented volume of several cubic kilometres. One of the technical challenges in such a huge project is providing software tools, which can be rapidly developed and maintained while keeping a focus on portability, compatibility and usability. The area of application ranges from live monitoring over offline processing and analysis to data visualisation and 3D event displays. Python with it’s wonderful standard library combined with extraordinary open source frameworks proves to be able to handle all these different tasks with ease. This talk covers some of the projects used in our collaboration to make our lives easier, featuring technologies such as Cython, Numpy, Scipy, Pandas, Matplotlib, Jupyter, Tornado, PyOpenGL, urwid and more, and focusses on one of our key ingredients: a framework called KM3Pipe, which provides a pipeline-based workflow to allow us building complex analysis chains by stitching together modules.


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