|Name:||Big Data & Machine Learning Techniques for the ATLAS experiment at the LHC.|
|Time:||Tuesday, June 20, 2017
02:15 pm - 02:45 pm
|Speaker:||Kerstin Tackmann, DESY|
The ATLAS experiment is one of the two multi-purpose experiments at the Large Hadron Collider at the European Organization for Nuclear Research in Geneva. Since the start of data taking in 2009, it has used proton-proton collisions at centre-of-mass energies of 7, 8, and 13 TeV to perform detailed studies of the processes described by the Standard Model of elementary particle physics, discover a Higgs boson, and to search for particles and phenomena beyond the Standard Model of particle physics. In this talk I will give an overview of the ATLAS experiment and its data flow, present some of its results, and give an overview of the usage of Big Data technologies to store, search and retrieve experimental data and metadata, including analytics tools and the use of machine learning techniques.