Présidents de session
Mardi matin
- David Rousseau (IJCLab, CNRS/IN2P3, Université Paris-Saclay)
.
The physics reach of the HL-LHC will be limited by how efficiently the experiments can use the available computing resources, i.e. affordable software and computing are essential. The development of novel methods for charged particle reconstruction at the HL-LHC incorporating machine learning techniques or based entirely on machine learning is a vibrant area of research. In the past two years,...
Because of the nature of QCD interactions with matter, the measured energies and masses of hadronic jets have to be calibrated before they are used in physics analysis. The correction depends on many characteristics of the jets, including the energy and mass themselves. Obtaining the correction is thus a multidimensionnal regression problem for wich DNN is a well suited approach.
In...
Reconstruction of di-$\tau$ mass in a faster and more accurate way than the existing methods is crucial to test any theory involving Higgs boson and Z boson which are decaying to $\tau^+ \tau^-$. However, it is an arduous task due to existence of neutrinos as decay product of each $\tau$ lepton which are invisible to detectors at LHC.
The present ongoing work aims at obtaining a di-$\tau$...
Machine Learning methods are extremely powerful but often function as black-box problem solvers, providing improved performance at the expense of clarity. Our work describes a new machine learning approach which translates the strategy of a deep neural network into simple functions that are meaningful and intelligible to the physicist, without sacrificing performance improvements. We apply...
Among all of the applications of Machine Learning in HEP, anomaly detection
methods have been receiving a growing interest over the last years. Their use
is especially promising in the development of model independent search tech-
niques. Following this trend line, we propose new algorithms based on the arti-
ficial neural network concept of the Auto-Encoder, augmented with...
Within the Phase-II upgrade of the LHC, the readout electronics of the ATLAS Liquid Argon (LAr) Calorimeters is prepared for high luminosity operation expecting a pile-up of up to 200 simultaneous pp interactions.
The Liquid Argon (LAr) calorimeters measure the energy of particles produced by LHC collisions, especially electrons and photons. The digitized signals from the LAr 182468...
Within the Phase-II upgrade of the LHC, the readout electronics of the ATLAS Liquid Argon (LAr) Calorimeters is prepared for high luminosity operation expecting a pile-up of up to 200 simultaneous pp interactions. The Liquid Argon calorimeters measure the energy of particles produced by LHC collisions, especially electrons and photons. The digitized signals from the LAr 182468 channels are...
Next generation experiments such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will provide an unprecedented volume of time-domain data opening a new era of big data in astronomy. To fully harness the power of these surveys, we require analysis methods capable of dealing with large data volumes that can identify promising transients within minutes for follow-up...
