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SUMMARY:Searching for new physics with machine learning at the Large Hadro
 n Collider - William Fawcett
DTSTART:20230119T130000Z
DTEND:20230119T153000Z
UID:TALK193295@talks.cam.ac.uk
CONTACT:James Fergusson
DESCRIPTION:The Standard Model of particle physics has been incredibly suc
 cessful at predicting the properties and interactions of the known fundame
 ntal particles. However\, there are several major flaws with the model\, o
 ne being the lack of explanation for dark matter. We know there is more to
  be discovered\, and this is why the Large Hadron Collider – the world
 ’s most powerful particle collider – was built at CERN. The ATLAS expe
 riment is one of the main detectors at the LHC and collects petabytes of d
 ata each year. In this talk I will describe recent attempts to build autom
 atic “structure-finding” models using tensor-attention networks\, whic
 h will help tease out hints of rare signals of new particles from the delu
 ge of background data.
LOCATION:Kavli Large Meeting Room\, Kavli Building
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