Real-time Data Processing for High-rate 3D Particle Imaging
Video
Team Information
Team Members
Daisy Kalra, Postdoctoral Research Scientist, Department of Physics, Columbia University
Faculty Advisor: Georgia Karagiorgi, Assistant Professor of Physics, Faculty of Arts and Sciences
Abstract
Liquid Argon Time Projection Chamber (LArTPC) particle detectors such as MicroBooNE, SBND, and DUNE produce 3D images of particle interactions using ionization charge collected by anode sensor arrays. One of the physics goals of these experiments is to look for rare and faint signals produced by interactions of neutrinos from supernova bursts, or new fundamental physics such as baryon number violation processes so as to preferentially preserve those rare signals. DUNE is a gigantic particle detector, under construction, with millions of readout channels where data rates can be as large as 5 terabytes per second. To record interactions of interest with 100% live time while meeting data storage disk requirements, it is essential to reduce the data rates by implementing intelligent, real-time data selection techniques so as to preserve those rare signals. The existing MicroBooNE detector and its already collected data set provide a unique opportunity to demonstrate real-time data selection techniques using the DUNE data-selection strategy. This study will provide an important proof-of-principle for applying such techniques to DUNE and other upcoming LArTPC experiments. This poster will describe the MicroBooNE readout system and ongoing R&D efforts to develop and demonstrate real-time data processing and data selection.
Team Lead Contact
Daisy Kalra: dk3172@columbia.edu
