2–7 Jan 2018
Skeikampen, Norway
Europe/Oslo timezone

Session

Thursday PM

4 Jan 2018, 15:30
Skeikampen, Norway

Skeikampen, Norway

Hotellvegen 3, 2652 Svingvoll, Norway

Conveners

Thursday PM: Machine learning in the era of Artificial Intelligence

  • Poul Damgaard (Technical University of Denmark)

Thursday PM: European Spallation Source - Neutrino Super Beam

  • Poul Damgaard (Technical University of Denmark)

Thursday PM: Contributed talks

  • Stefania Xella (University of Copenhagen (DK))

Thursday PM: Particle Physics and Education

  • Anders Tranberg

Presentation materials

There are no materials yet.

  1. Kyle Stuart Cranmer (New York University (US))
    04/01/2018, 15:30
    Particle Physics and Artificial Intelligence
    Invited

    The present landscape and the open questions in particle physics will be briefly reviewed, showing that they call for new means of investigation both towards higher energy and towards more sensitivity to small couplings.
    CERN is preparing actively, according to the recommendation of the 2013 European Strategy, for an ambitious post-LHC accelerator complex. The 100km circumference Future...

    Go to contribution page
  2. Tord Johan Carl Ekelof (Uppsala University (SE))
    04/01/2018, 16:15
    Future accelerators
    Invited

    Searching for a difference between neutrino and anti-neutrino oscillations may open the way towards new fundamental physics and an explanation of why the world is made of only matter and no anti-matter. To discover such a difference, the development of a very large neutrino detector and a high-intensity neutrino beam is needed. The same detector will make possible investigations of...

    Go to contribution page
  3. Are Raklev (University of Oslo (NO))
    04/01/2018, 17:30
    Particle physics - theory
    Contributed talk

    I will present the first Beyond the Standard Model (BSM) global fit results obtained using the new Global And Modular BSM Inference Tool (GAMBIT). With GAMBIT we have analysed the GUT-motivated supersymmetry models CMSSM, NUHM1 and NUHM2; the weak-scale MSSM7; and a scalar singlet dark matter model. Our analyses improve on existing results in terms of the number of included observables and the...

    Go to contribution page
  4. Tomas Gonzalo
    04/01/2018, 17:45
    Particle physics - theory
    Contributed talk

    The type-I seesaw mechanism, able to explain the lightness of the three active neutrinos, requires the existence of exotic heavy neutral fermions, with a mass ranging from a few MeV to around a TeV. We propose a model with three such sterile neutrinos where the mixing matrices are parametrized using the Casas-Ibarra scheme. Direct dectection constrains coming from DELPHI and ATLAS among others...

    Go to contribution page
  5. Inga Strumke (University of Bergen (NO))
    04/01/2018, 18:00
    Particle Physics and Artificial Intelligence
    Contributed talk

    We study the prospects for using deep neural networks to distinguish collider signals from heavy and mass degenerate CP-odd and CP-even Higgs bosons. The close overlap in the kinematic features highlights a challenge related to the bias introduced by training data.

    Go to contribution page
  6. Joona Juhani Havukainen (Helsinki Institute of Physics (FI))
    04/01/2018, 18:15
    Particle Physics and Artificial Intelligence
    Contributed talk

    In order to improve track reconstruction in Run 2 and to prepare for the increasingly difficult detector conditions of Run 3 at the Compact Muon Solenoid (CMS) detector, the use of novel machine learning methods in the CMS tracking are being studied. These methods provide ways to deal with for example the high particle densities, growing combinatorics and track quality assignments in the...

    Go to contribution page
  7. Jon Vegard Sparre (University of Oslo)
    04/01/2018, 18:30
    Particle Physics and Artificial Intelligence
    Contributed talk

    In this Masters thesis we have developed a faster way to calculate
    supersymmetric cross sections at next-to-leading order (NLO) by using
    machine learning techniques. This method teaches the computer software
    to imitate the cross section function, facilitating the evaluation of a
    large number of parameter points in a short period of time. Training is
    carried out based on data generated with...

    Go to contribution page
  8. Santeri Henrikki Laurila (Helsinki Institute of Physics (FI))
    04/01/2018, 18:45
    Particle physics - experiment
    Contributed talk

    Particle physics experiments typically require that background processes affecting the measurement are taken into account in the data analysis. In collider experiments, this means estimating how large fraction of the observed collision events actually originate from background processes and not from signal events.

    The background event yields are usually estimated from simulation or with a...

    Go to contribution page
  9. Nils-Erik Bomark
    04/01/2018, 20:45
    Particle Physics and Education
    Contributed talk

    Since Norwegian high school teacher are required to teach particle physics, it is important to give them as good an understanding of the topic as possible. Since also many students who does not venture into more advanced physics courses, show an interest in particle physics, we face a challenge in how to teach these topics in a non-technical fashion. I will discuss aspects of coming to grips...

    Go to contribution page
  10. Eirik Gramstad (University of Oslo (NO))
    04/01/2018, 21:15
    Particle Physics and Education
    Contributed talk

    With the advent of higher energies and higher collision rates, the LHC continues the exciting voyage towards new physics, allowing physicists all over the world to explore a previously unknown territory full of promise. So far the International Particle Physics Outreach Group (IPPOG) international masterclass developers, with the help of physicists and in close contact with teachers, have been...

    Go to contribution page
Building timetable...