Event



Experimental Particle Physics: Searching for Exotic and Rare Physics Processes with Liquid Argon Time Projection Chamber Detectors

Daisy Kalra (Columbia University)
- | David Rittenhouse Laboratory, 3W2
An image of Daisy Kalra

Neutrinos are some of the most abundant but elusive particles in the universe. The groundbreaking discovery of neutrino oscillations, recognized by the 2015 Nobel Prize, revealed the existence of non-zero neutrino masses, providing compelling evidence for new physics beyond the Standard Model (BSM). This discovery has sparked up a wealth of fascinating questions, including the hypothesized presence of additional neutrino states, the connection between neutrinos and cosmology, and the connection of neutrinos and astrophysics. This has prompted a wealth of neutrino experiments aiming to improve our understanding of neutrinos. At the same time, experiments designed with unparalleled precision to test neutrino properties can enable searches for other rare and exotic physics processes, such as neutron-antineutron transition, proton decay, or neutrinos from Supernova bursts.


This talk will highlight the capabilities of the current-generation Liquid Argon Time Projection Chamber (LArTPC)-based neutrino detectors in searching for BSM physics. Among various BSM physics processes, I will focus on recent results from a deep learning-based analysis of MicroBooNE data, making use of a sparse convolutional neural network and event topology information to search for argon-bound neutron-antineutron transition-like signals. This analysis demonstrates the capability of LArTPCs to achieve high signal efficiency and strong background rejection when leveraging advances in image analysis techniques. Furthermore, this talk will discuss ongoing research and development (R&D) aimed at developing data-driven data selection for LArTPC detectors—a major challenge particularly for large-scale detectors such as the future Deep Underground Neutrino Experiment (DUNE) due to its exorbitant data rate. The objective of this effort is to develop real-time data selection schemes as well as offline data analysis for rare signals with very high accuracy and computational performance. Drawing from my own research experience, I will describe how these required advancements will enable sensitive searches for exotic and rare physics signals in DUNE.