Dr Kirsty Duffy

Abstract:

We have developed a convolutional neural network that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a νμ charged-current neutral pion data samples.

Abstract:

We perform a search for light sterile neutrinos using the data from the T2K far detector at a baseline of 295 km, with an exposure of 14.7(7.6)×10^20 protons on target in neutrino (antineutrino) mode. A selection of neutral-current interaction samples is also used to enhance the sensitivity to sterile mixing. No evidence of sterile neutrino mixing in the 3+1 model was found from a simultaneous fit to the charged-current muon, electron and neutral-current neutrino samples. We set the most stringent limit on the sterile oscillation amplitude sin^2θ24 for the sterile neutrino mass splitting Δm^2v41<3×10^−3eV^2/c^4.

Abstract:

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT) . This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking.

Abstract:

The DUNE Near Detector design consists of multiple components, each designed to produce complementary constraints on flux and neutrino interaction systematic uncertainties for the oscillation analyses. One of these subdetectors is a magnetized high-pressure gaseous-argon TPC (HPgTPC), which will provide fine-grained tracking in a low-density detector, using the same target nucleus as the DUNE far detector. With its low momentum threshold for particle detection, the HPgTPC will be able to constrain one of the most crucial - and least-well understood - uncertainties for the oscillation analysis: nuclear effects in neutrino-argon interactions. These proceedings describe the current design, physics goals, and projected performance of the HPgTPC, as well as the ongoing R&D work at Fermilab, in which a test-stand TPC is being built and will be operated at up to 10 atm pressure.