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61/1-007 - Room B (CERN)

61/1-007 - Room B

CERN

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Description

Studentgruppe ledet av Nils-Erik Bomark.

  • Thursday 13 April
    • 17:00
      Ankomst Genève — fritt opplegg
  • Friday 14 April
    • 08:45
      Oppmøte i resepsjonen, bygning 33 — utdeling av adgangskort Resepsjonen, bygning 33

      Resepsjonen, bygning 33

      CERN
    • 1
      CERN — en kort innføring 61/1-007 - Room B

      61/1-007 - Room B

      CERN

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      Overblikk over CERN og LHC, samt IT utfordringer på CERN.

      Speaker: Nils Høimyr (CERN)
      visit-agder.pdf
    • 10:00
      Muligheter for å hente seg kaffe Restaurant 1

      Restaurant 1

      CERN
    • 2
      Min erfaring på CERN som teknisk student 61/1-007 - Room B

      61/1-007 - Room B

      CERN

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      Student ved NTNU, fysikk og matematikk, integrert master.

      Speaker: Jenny Lunde (Norwegian University of Science and Technology (NTNU) (NO))
      UiA_presentasjon.pdf
    • 3
      Å finne nålen i nålstakken i løpet av nanosekunder 61/1-007 - Room B

      61/1-007 - Room B

      CERN

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      At the CERN Large Hadron Collider, protons are brought to collide hundreds of millions of times per second. The collision debris allows us to study the fundamental building blocks of the universe and look for hints of new forces and particles. The vast majority of the collision data are immediately discarded by a real-time event filtering system due to storage and computational limitations. While most of these data are uninterresting, signals of new physics might be inadvertendly thrown away in the process. The first stage of this event filtering system consists of hundreds of field-programmable gate arrays (FPGAs), tasked with rejecting over 98% of the proton collisions within a few microseconds. With the start of High Luminosity LHC in 2029, a more granular detector and more particles per collision will increase the event complexity significantly, and ultimately require the FPGA farm to process an amount of data comparable to 5% of the total internet traffic.

      In this talk, I will discuss how real-time Machine Learning (ML) is used to process and filter this enormous amount of data in order to improve physics acceptance, and how ML can be used to select data in ways never before performed at colliders.

      Speaker: Thea Aarrestad (ETH Zurich (CH))
      RealTimeML_UiA.pdf
    • 12:00
      Lunch Restaurant 1

      Restaurant 1

      CERN
    • 13:30
      Avreise til CMS. Sjåfører: Zein Zebib (+41754115338) og Odd Øyvind Andreassen (+41754115916). Parkeringen utenfor bygning 40

      Parkeringen utenfor bygning 40

      CERN
    • 4
      Besøk ved CMS CMS

      CMS

      CERN
    • 15:00
      Retur til CERN, Meyrin CMS

      CMS

      CERN
    • 5
      Besøk på utstillingen i "Globe of Science and Innovation" Globe — bygning 80

      Globe — bygning 80

      CERN
      Speaker: Marianne Brekkum (University of South-Eastern Norway (NO))
    • 16:15
      Muligheter for å hente seg kaffe Restaurant 1

      Restaurant 1

      CERN
    • 6
      Utbedring av simuleringsverktøyet ImpedanceWake2D 61/1-007 - Room B

      61/1-007 - Room B

      CERN

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      Speaker: Eskil Vik (Norwegian University of Science and Technology (NTNU) (NO))
      20230414_EskilVik_presentasjon_UiA.odp
      20230414_EskilVik_presentasjon_UiA.pdf
    • 7
      Validerings studier av ATLAS ITkPix 61/1-007 - Room B

      61/1-007 - Room B

      CERN

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      Speaker: Marianne Brekkum (University of South-Eastern Norway (NO))
      UiA.pdf
      UiA.pptx
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