Machine learning-based predictions of directionality and charge of cosmic muons—a simulation study using the mICAL detector
Nov 18, 2019
12 pages
Published in:
- JINST 14 (2019) 11, P11020
- Published: Nov 18, 2019
Citations per year
Abstract: (IOP)
The Iron Calorimeter (ICAL) is a neutrino physics experiment proposed by the India-based Neutrino Observatory (INO) collaboration to measure the oscillation parameters. The mini Iron Calorimeter (mICAL) detector is a small-scale prototype of ICAL built at the Inter-Institutional Centre for High Energy Physics (IICHEP), Madurai, India. In this paper, we present the simulation study of machine learning-based predictions of directionality and charge of cosmic muons using the mICAL detector geometry.- Analysis and statistical methods
- Pattern recognition
- cluster finding
- calibration and fitting methods
- Simulation methods and programs
- calorimeter: iron
- India based Neutrino Observatory
- neutrino/mu: particle identification
- antineutrino/mu: particle identification
- track data analysis
References(30)
Figures(0)
- [1]
- [2]
- [3]
- [4]
- [5]
- [6]
- [7]
- [8]
- [9]
- [10]
- [11]
- [12]
- [13]
- [14]
- [15]
- [16]
- [17]
- [18]
- [19]
- [20]
- [21]
- [22]
- [23]
- [24]
- [25]