Speaker
Description
A Dark Matter Science Project is being developed in the context of the ESCAPE and EOSC-Future projects as a collaboration between scientists in European Research Infrastructures and experiments seeking to explain the nature of dark matter (such as HL-LHC, KM3NeT, CTA, DarkSide).
The goal of this ESCAPE Science Project is to highlight the synergies between different dark matter communities and experiments, by producing new scientific results as well as by making the necessary data and software tools fully available.
As part of this Science Project, we use experimental data and software algorithms from selected direct detection, indirect detection, and particle collider experiments involved in ESCAPE as prototypes for end-to-end analysis pipelines on a Virtual Research Environment that is being prepared as one of the building blocks of the European Open Science Cloud (EOSC).
This contribution focuses on the scientific results obtained over the course of this project, and on the implementation of the workflows on the Virtual Research Environment.
