Algorithms for LArTPC data exploitation optimisation in the DUNE experiment

Pourvu: 

Non

The Deep Underground Neutrino Experiment (DUNE) is a long baseline neutrino experiment which aims to:

  • Discover CP Violation in the leptonic sector 

  • Determine the neutrino Mass Ordering 

  • Precisely measure neutrino oscillation parameters

  • Test the 3-flavour paradigm

This ambitious program also includes the search for Nucleon Decay and the astrophysical observations of Galactic Supernovae.  To do so, neutrinos produced by a high power wide-band neutrino beam produced at Fermilab, will be detected at a baseline of 1300 km, by 4 giant liquid argon (LAr) detector modules deep underground (SURF laboratory, South Dakota), each module containing 17ktons of LAr.

Two large-scale prototypes, the ProtoDUNEs have been constructed and operated at the CERN neutrino platform during the past years. The ProtoDUNEs will be re-instrumented and once more operated as of 2023. The proposed thesis is focused on the exploitation of the acquired data, and the development and improvement of the techniques used to reconstruct events in the Liquid Argon Time Projection Chamber detectors. The work involves the production of simulations, development of tools, and comparison with the real data from the prototypes. DUNE analysis relies heavily on the latest machine learning techniques, such as Convolutional Neural Networks,  for event reconstruction and particle identification. The candidate will become familiar with the use of these modern tools, in particular their tuning for specific analysis tasks.

With the now realistic simulation, the sensitivity of the Far Detector to key physics parameters such as the CP violating phase (δCP) will be determined. The systematic uncertainties will also be studied. Other physics analyses are also possible, which include amongst others, the capability to detect supernova neutrinos.

As well as simulation, the APC group is involved in the development of part of the electronics for the Photo-Detection System. A contribution towards the testing and characterization of this electronics is also possible. 

The candidate will participate in the data taking campaigns with the prototype detectors at CERN and to collaboration meetings in the US and in Europe.

Responsable: 

Thomas Patzak, Sabrina Sacerdoti

Services/Groupes: 

Année: 

2022

Formations: 

Thèse

Niveau demandé: 

M2

Email du responsable: