In this paper, we expand on the previously proposed concept of energy Mover's distance. The resulting observables are shown to provide a way of identifying rare processes in proton-proton collider experiments. It is shown that different processes are grouped together differently and that this can contribute to the improvement of experimental analyses. The ttZ production at the Large Hadron Collider is used as a...
In this work we assess the transferability of deep learning models to detect beyond the standard model signals. For this we trained deep neural networks on three different signal models: tZ production via a flavor changing neutral current, pair production of vectorlike T-quarks via standard model gluon fusion and via a heavy gluon decay in a grid of three mass points: 1, 1.2 and 1.4 TeV. These networks were tra...