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PHYSTAT-nu 2019

22–25 Jan 2019
CERN
Europe/Zurich timezone

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Session

Contributed talks session

24 Jan 2019, 16:10
CERN

CERN

Tuesday 22nd 1:30-4pm : Course - TH Auditorium (4-3-006) Tuesday 22nd 5pm: Bayesian Techniques - Filtration Plant (222-R-001) Wed 23rd: Filtration plant (222-R-001) Thurs 24th: Filtration plant (222-R-001) Friday 25th: Council Chamber (503-1-001)

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  1. 86. Regularisation for T2K cross-section analyses
    Stephen Dolan (University of Oxford)
    24/01/2019, 16:10
  2. 87. A new unified perspective on the problem of limited Monte Carlo for likelihood calculations
    Thorsten Glüsenkamp (Universität Erlangen-Nürnberg)
    24/01/2019, 16:35
  3. 88. Statistical Models with Uncertain Error Parameters
    Glen Cowan (Royal Holloway, University of London)
    24/01/2019, 17:00
  4. 89. Review of Linear Algebra Applications in Some Recent Neutrino Experiments
    Xin Qian (Brookhaven National Laboratory)
    24/01/2019, 17:25
  5. 63. \texttt{GooStats}: A GPU-based framework for multi-variate analysis in particle physics
    Xuefeng Ding (Gran Sasso Science Insitute (INFN))

    \texttt{GooStats} is a software framework that provides a flexible environment and common tools to implement multi-variate statistical analysis. The framework is based on C++11, CERN ROOT, MINUIT, and \texttt{GooFit}, a popular minimization engine that can run on general purpose graphics processing units. Running a multi-variate analysis in parallel on graphics processing units yields a huge...

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  6. 56. Machine Learning methods for JUNO Experiment
    Mr Yu Xu (IKP2 FZJ)

    Jiangmen Underground Neutrino Observatory (JUNO) experiment is a multipurpose neutrino experiment, aiming to determine the unknown neutrino mass ordering and precisely measure the neutrino oscillation parameters. JUNO consists of a central detector with 20 kt liquid-scintillator target and muon veto detectors. 18,000 20-inch PMTs will be installed in central detector, in order to achieve 3%...

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  7. 75. Reactor Anti-neutrino Data in Global Analyses
    Alvaro Hernandez Cabezudo

    I will explain the role of reactor anti-neutrino data in the global analyses performed for standard neutrino oscillations (within the NuFit collaboration) and in scenarios involving sterile neutrinos.

    The modern medium baseline reactor experiments, L~Km, can determine the neutrino mixing angle \theta_{13} and give a complementary determination to the long baseline experiments of the...

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  8. 64. Statistical Models with Uncertain Error Parameters
    Glen Cowan (Royal Holloway, University of London)

    In a statistical analysis in Particle Physics, nuisance parameters can be introduced to take into account various types of systematic uncertainties. The best estimate of such a parameter is often modeled as a Gaussian distributed variable with a given standard deviation (the corresponding "systematic error"). Although the assigned systematic errors are usually treated as constants, in...

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