VIRTUAL: Faster, deeper, stronger: Machines learn particle physics

  • Date: –11:30
  • Location: Zoom
  • Lecturer: Gregor Kasieczka (Universität Hamburg)
  • Organiser: Rebeca Gonzalez Suarez
  • Contact person: Rebeca Gonzalez Suarez
  • Seminarium

This will be a virtual seminar, and will be hosted in Zoom

Link: https://uu-se.zoom.us/j/63471603574

Meeting ID: 634 7160 3574

NOTE: This meeting is password protected, if you are interested in joining, send an email to rebeca.gonzalez.suarez@physics.uu.se

Many experimental results from both particle and astrophysics hint that the Standard Model (SM) of particle physics cannot be a complete theory of Nature. However, in its first years of operation, the Large Hadron Collider at CERN was very successful in excluding large regions of parameter space for potential models beyond the SM. We present how deep learning can be used to search for deviations from the SM in a model independent way. Beyond searching for new physics, we explore ways to increase the robustness and understanding of network decisions and show how generative models can speed up simulations.

VIRTUAL: Faster, deeper, stronger: Machines learn particle physics