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| Paper: |
The lstMCpipe Library |
| Volume: |
538, ADASS XXXII |
| Page: |
392 |
| Authors: |
Enrique García; Thomas Vuillaume; Lukas Nikel |
| DOI: |
10.26624/PXBD7025 |
| Abstract: |
The Cherenkov Telescope Array (CTA) is the next generation of ground-based gamma-ray astronomy observatories that will improve the sensitivity of current-generation instruments by one order of magnitude. The LST-1 is the first telescope
prototype built on-site on the Canary Island of La Palma, and data has been collected
for a few years already. Like all imaging atmospheric Cherenkov telescopes (IACTs),
the LST-1 captures the light produced by the Cherenkov process when high-energy particles enter the atmosphere. Analyzing the camera’s recorded snapshot allows us to
discriminate between gamma photons and hadrons and reconstruct the physical parameters of the selected photons. To build the models for the discrimination and reconstruction and estimate the telescope response (by simulating the atmospheric showers
and the telescope optics and electronics), extensive Monte Carlo simulations must be
performed. These trained models are later used to analyze data from real observations.
lstMCpipe is an open-source Python package developed to orchestrate the different stages of the analysis of the MC files on a computing facility. Currently, the library
is in production status, and the full pipeline is scheduled in a SLURM cluster. It greatly
simplifies the analysis workflow by adding a level of abstraction, allowing users to start
the entire pipeline using a simple configuration file. Moreover, members of the LST
collaboration can ask for a new analysis to be produced with their tuned parameters
through a pull request in the project repository, allowing careful review by other collaborators and central management of the productions, thus reducing human errors and
optimizing usage of the computing resources. |
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