Muography in Colombia: simulation framework, instrumentation and data analysis

TL;DR

This paper introduces a comprehensive simulation framework and a hybrid muon telescope, MuTe, for volcano imaging in Colombia, including instrument design, data analysis, and machine learning techniques for improved internal density estimation.

Contribution

It presents the development of MuTe, a novel hybrid muon detector, and a simulation framework for volcano muography, integrating advanced data analysis and background rejection methods.

Findings

Successful characterization of instrument's structural behaviour

Preliminary results on background composition

Implementation of optimization and machine learning techniques

Abstract

We present the Colombo-Argentinian Muography Program for studying inland Latin-American volcanoes. It describes the implementation of a simulation framework covering various factors with different spatial and time scales: the geomagnetic effects at a particular geographic point, the development of extensive air showers in the atmosphere, the propagation through the scanned structure and the detector response. Next, we sketch the criteria adopted for designing, building, and commissioning MuTe: a hybrid Muon Telescope based on a composite detection technique. It combines a hodoscope for particle tracking and a water Cherenkov detector to enhance the muon-to-background-signal separation due to extensive air showers' soft and multiple-particle components. MuTe also discriminates inverse-trajectory and low-momentum muons by using a picosecond Time-of-Flight system. We also characterise the instrument's structural (mechanical and thermal) behaviour, discussing preliminary results from the background composition and the telescope-health monitoring variables. Finally, we discuss the implementations of an optimisation algorithm to improve the volcano internal density distribution estimation and machine learning techniques for background rejection.