3 documents found, page 1 of 1
Use of a generalized energy Mover's distance in the search for rare phenomena a...
Romão, M. Crispim; Castro, Nuno Filipe; Milhano, J. G.; Pedro, R.; Vale, T.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...
Deep learning for the classification of quenched jets
Apolinário,L.; Castro, Nuno Filipe; Romão, M. Crispim; Milhano, J. G.; Pedro, R.; Peres, F. C. R.An important aspect of the study of Quark-Gluon Plasma (QGP) in ultra-relativistic collisions of heavy ions is the ability to identify, in experimental data, a subset of the jets that were strongly modified by the interaction with the QGP. In this work, we propose studying deep learning techniques for this purpose. Samples of $Z+$jet events were simulated in vacuum and medium and used to train deep neural netwo...
Transferability of deep learning models in searches for new physics at colliders
Romão, M. Crispim; Castro, Nuno Filipe; Pedro, R.; Vale, T.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...