High Quality Automated LArTPC Reconstruction for Neutrino Experiments

by Haiwang Yu

Wednesday 30 Mar 2022, 15:00 → 16:00 Europe/Zurich

Liquid Argon time projection chamber or LArTPC is a scalable, tracking calorimeter that features rich event topology information. It provides the core detector technology for many current and next-gen large scale neutrino experiments, e.g., DUNE and the SBN program. For neutrino experiments, LArTPC faces many challenges in both hardware and software to achieve its optimum performance. On the software side, the main challenge is two-fold.  First, deep domain knowledge needs further accumulation. Second, the event degree of freedom is high due to its large scale and uncertainties in the initial neutrino-argon interactions. With LArTPC R&D as one of its main goals, MicroBooNE has made major advancements in the LArTPC reconstruction paradigm building. Multiple fully-automated event reconstruction paradigms have been established. With the publishing of the initial results from a search for an electron neutrino low-energy anomaly, the effectiveness of these reconstruction paradigms are validated with real experiment data. This seminar presents the algorithms for LArTPC reconstruction with particular highlights on the Wire-Cell event reconstruction paradigm. Meanwhile, the lessons learnt, e.g., how conventional and machine learning algorithms benefit from each other and fit into different tasks, will also be discussed.

Haiwang Yu is a Research Associate at Brookhaven National Lab. His research interests are in the development of reconstruction algorithms, computing frameworks, software for accelerators and in research on artificial intelligence / machine applications in High Energy Physics.

EP-IT-seminar-Haiwang-pub.pdf

EP-IT-seminar-Haiwang-pub.pptx

video1556796780.mp4