Using Variational Autoenoder on particle collision data
Particles, in this case protons, are boosted to high energies inside the Large Hadron Collider (LHC) — each beam can reach 6.5 TeV giving a total of 13 TeV when colliding. Electromagnetic fields are used to accelerate the electrically charged protons in a 27 kilometers long loop. When the proton beams collide they produce a diverse set of subatomic byproducts which quickly decay, holding valuable information for some of the most fundamental questions in physics.
Particle accelerators generate huge volumes of data for example LHC at CERN produces 1.5 million signals events from a data of 2 TB per day
Various Machine Learning algorithm applied to Data for signal selection.
