Login

NuXTract 2023 - Towards a consensus in neutrino cross sections

2–6 Oct 2023
CERN
Europe/Zurich timezone

Contact

Session

Methods

3 Oct 2023, 13:40
222/R-001 (CERN)

222/R-001

CERN

200
Show room on map

Conveners

Methods

  • Adi Ashkenazi (Tel Aviv University (IL))

Methods

  • Adi Ashkenazi (Tel Aviv University (IL))

Presentation materials

There are no materials yet.

  1. 13. Binned log-likelihood template fitting with T2K
    Nick Latham
    03/10/2023, 13:40

    When performing neutrino cross section extractions, it is desirable to avoid dependence on the interaction model used in Monte-Carlo generation. Log-likelihood template fitting is a method which can be used to explore the input parameter space and find the best ways of describing data. This method has several advantages, including straightforward background constraining and informative...

    Go to contribution page
  2. 30. Forward folding
    Lukas Koch (Johannes Gutenberg Universitaet Mainz (DE))
    03/10/2023, 14:00

    Statistical methods

    Go to contribution page
  3. 16. Unbiased reconstruction of calorimetric variables in cross-section analyses
    Katharina Lachner (University of Warwick)
    03/10/2023, 14:30

    Neutrino cross-sections are often extracted purely in terms of lepton kinematics. In recent years more detailed analyses have been developed that additionally make use of kinematics in the hadronic system, which has proven very successful. However, even with new detector technologies of unparalleled precision, pattern recognition and reconstruction algorithms still require particle momenta...

    Go to contribution page
  4. 29. Unfolding: Machine learning approaches
    Ben Nachman (Lawrence Berkeley National Lab. (US))
    03/10/2023, 14:50

    OmniFold: A Method to Simultaneously Unfold All Observables

    Go to contribution page
  5. 6. Machine Learning-Assisted Unfolding for Neutrino Cross-section Measurements
    Andrew Cudd (University of Colorado Boulder)
    03/10/2023, 15:10

    The choice of unfolding method for a cross-section measurement is tightly coupled to the model dependence of the efficiency correction and the overall impact of cross-section modeling uncertainties in the analysis. A key issue is the dimensionality used, as the kinematics of all outgoing particles in an event typically affects the reconstruction performance in a neutrino detector. OmniFold is...

    Go to contribution page
  6. 28. Unfolding: a statistician's perspective
    Mikael Kuusela (Carnegie Mellon University (US))
    03/10/2023, 16:00

    Unfolding: a statistician's perspective

    Go to contribution page
  7. 10. Treating Detector Systematics via a Likelihood Free Inference Method
    Ms Alexandra Trettin (University of Manchester)
    03/10/2023, 16:25

    Estimating the impact of systematic uncertainties in particle physics experiments is challenging, especially since the detector response is unknown analytically in most situations and needs to be estimated through Monte Carlo (MC) simulations. Typically, detector property variations are parameterized in ways that implicitly assume a specific physics model, which can introduce biases on...

    Go to contribution page
Building timetable...