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SUMMARY:Searching better\, searching for more: helping HEP out of the new-
 physics crisis
DTSTART:20180322T163000
DTEND:20180322T173000
DTSTAMP:20260916T054958Z
UID:51566176b43f587ac06b9ee122bec8f304b4698dd2b77c733502b88f
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Maurizio Pierini\, CERN\nAbstract: The standard model of 
 particle physics is one of the pillars of our understanding of the fundame
 ntal laws of nature. Proposed in the ‘70s\, this model passed 40 years o
 f high-precision tests\, culminating with the discovery of the Higgs boson
  by ATLAS and CMS in 2012. Despite this successful record\, the standard m
 odel comes short in several ways\, e.g. not describing gravity or not pred
 icting dark matter. This is the reason why particle physicists are intensi
 vely looking for a discrepancy between theory predictions and experimental
  observations at colliders and in underground  experiments around the wor
 ld. In this seminar\, I will cover the last decade of searches for new phy
 sics at the LHC: what we learned from the LHC data\, the limitations we fa
 ced and how we improved our techniques to overcome these limitations. With
  no signal of new physics found at the LHC or elsewhere\, the HEP communit
 y is proposing a new generation of large-statistics experiments\, to turn 
 new physics searches into high-precision data analyses. Doing so with the 
 current approach and the current online/offline computing technology will 
 not scale. Even maintaining the current performances is not guaranteed. At
  the same time\, one would need even more resources to extend the explorat
 ion into new directions. In this seminar\, I will discuss how deep learnin
 g could be used as a tool to boost our physics reach in a cost-effective w
 ay\, turning the HEP Big Data crisis into an opportunity for new research 
 directions and\, hopefully\, new discoveries.
LOCATION:BSP 234 https://plan.epfl.ch/?room==BSP%20234
STATUS:CONFIRMED
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