Conveners
Day 4 Morning
- Kazuhiro Terao (SLAC)
- Jianming Bian (University of California, Irvine)
The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions....
In the framework of three-active-neutrino mixing, the charge parity phase, the neutrino mass ordering and the octant of $\theta_{23}$ remain unknown. The primary goal of DUNE is to address these questions by measuring the oscillation patterns of $\nu_\mu$ and $\bar\nu_\mu$ over a range of energies spanning the first and second oscillation maxima, which requires precisely reconstructed neutrino...
Next generation long-baseline experiments will measure neutrino mixing parameters with unprecedented precision, requiring stringent constraints on systematic uncertainties. We present the methods used in the recently published DUNE technical design report to test the robustness of the experiment with respect to variations of the neutrino interaction model. A multivariate method was used to...
In this talk we will show the potential improvements in neutrino event reconstruction that a 3D pixelated readout could offer over a 2D projective wire readout for liquid argon time projection chambers. We simulated and studied events in two generic, idealized detector configurations for these two designs, classifying events in each sample with deep convolutional neural networks to compare the...
