HEP Seminars

Ben Nachman (Berkeley LBNL): Anomaly detection with machine learning at the LHC


Abstract: Despite extensive experimental and theoretical evidence for new particles and forces of nature, there have been no new discoveries since the Higgs boson in 2012.  One possibility could be that we are not looking at our data in the right way to identify new fundamental structure.  Machine learning techniques offer an exciting opportunity to explore our complex data in their natural high dimensionality.  A variety of less-than-supervised methods have been proposed to be as model agnostic as possible in this search.  After introducing these new ideas, I will present the first application of weakly supervised anomaly detection at the LHC with a recent result from the ATLAS experiment in the all hadronic final state.  This search significantly extends the sensitivity of the ATLAS search program and is the start of a new class of searches that will broaden and deepen the potential for discovery.

Connection via Zoom:

Topic: Liverpool HEP Seminar

Meeting ID: 995 4201 4031
Password: 6R$m5uB#


Organized by

Jan Kretzschmar, Costas Andreopoulos