IN2P3/IRFU Machine Learning workshop

Session

Wed afternoon

28 sept. 2022, 14:00

Amphithéatre Pierre Gilles de Gennes (sous-sol) (APC, Paris)

65. B decays reconstruction at Belle II using graph neural networks

Jacopo Cerasoli (CNRS - IPHC)

28/09/2022 14:00

2 ML for analysis : event classification, statistical analysis and inference, including anomaly detectio

The Belle II experiment has unique features that allow to study B meson decays with neutrinos in the final state. It is possible to deduce the presence of such particles from the energy-momentum imbalance obtained after reconstructing the companion B meson produced in the event. This task is complicated by the thousands of possible final states B mesons can decay into, and is currently...

89. A new method for the data driven estimation of background using GAN

Victor Lohezic (IRFU (CEA) / Université Paris-Saclay)

28/09/2022 14:20

In this contribution we present a novel data driven method for the estimation of background by generating a new misidentified object using generative adversarial networks (GAN). In High Energy Physics, characterizing signal hypothesis requires distinguishing its signature from a large number of background processes with similar final states. Machine learning (ML) classification algorithms are...

84. Gamma-ray spectrometry of fission fragments: ML analysis of multi-dimensional spectra

Mattéo Ballu

28/09/2022 14:40

2 ML for analysis : event classification, statistical analysis and inference, including anomaly detectio

The analysis of gamma radiation emitted by fission fragments has become an essential tool for studying the nuclear fission process. It allows to probe the intrinsic properties of the fragments or to explore effects little studied experimentally such as the sharing of excitation energy between fragments at nuclear fission. It also provides nuclear data directly useful for reactor...

101. AISSAI IN2P3 Machine Learning semester brain storm

28/09/2022 15:00

102. Wrap-up and Farewell

Alexandre Boucaud (APC / IN2P3), David Rousseau (IJCLab, CNRS/IN2P3, Université Paris-Saclay), Valérie Gautard (CEA-Irfu)

28/09/2022 15:30

62. GNN for hadronic flow calibration in ATLAS

Pierre-Antoine Delsart (LPSC)

1 ML for object identification and reconstruction

Hadronic jets are essential components of analysis at the LHC. Not only their Energy and mass needs to be precisely measured, their internal structure is also essential in order to distinguish signal jets from the common QCD initiated background jets. However jet constituents representing the energy flow insside jets do not have 1-to-1 correspondence with hadrons generated in simulations. In...