Synthesis of radio signals from extensive air showers using previously computed microscopic simulations
The detection of extensive air showers (EAS) through their radio signal is becoming one of the most promising techniques for the study of Neutrinos and Cosmic rays at the highest energies. For the design, optimization and characterization of radio arrays, and of their associated reconstruction algor...
Autores principales: | , |
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Formato: | Articulo Preprint |
Lenguaje: | Inglés |
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2021
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Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/124543 |
Aporte de: |
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I19-R120-10915-124543 |
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record_format |
dspace |
institution |
Universidad Nacional de La Plata |
institution_str |
I-19 |
repository_str |
R-120 |
collection |
SEDICI (UNLP) |
language |
Inglés |
topic |
Física Ciencias Exactas Simulation methods Neutrino detectors Large detector systems particle physics astroparticle physics Simulation programs |
spellingShingle |
Física Ciencias Exactas Simulation methods Neutrino detectors Large detector systems particle physics astroparticle physics Simulation programs Tueros, Matías Jorge Zilles, Anne Synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
topic_facet |
Física Ciencias Exactas Simulation methods Neutrino detectors Large detector systems particle physics astroparticle physics Simulation programs |
description |
The detection of extensive air showers (EAS) through their radio signal is becoming one of the most promising techniques for the study of Neutrinos and Cosmic rays at the highest energies. For the design, optimization and characterization of radio arrays, and of their associated reconstruction algorithms, tens of thousands of Monte Carlo simulations are needed. Current available simulation codes can take several days to compute the signals produced by a single shower, making it impossible to produce the required simulations in a reasonable amount of time, in a cost-effective and environmental-conscious way. In this article we present a method to synthesize the expected signals (the full time trace, not just the peak amplitude) at any point around the shower core, given a set of signals simulated in a finite number of antennas strategically located in a pattern that exploits the signature features of the radio wavefront. The method can be applied indistinctly to the electric field or to the antenna response to the electric field, in the three polarization directions. The synthesized signal can be used to evaluate trigger conditions, compute the fluence or reconstruct the shower incoming direction, allowing for the production of one single library of simulations that can be used and re-used for the characterization and optimization of radio arrays and their associated reconstruction methods, for a thousandth part of the otherwise required CPU time. |
format |
Articulo Preprint |
author |
Tueros, Matías Jorge Zilles, Anne |
author_facet |
Tueros, Matías Jorge Zilles, Anne |
author_sort |
Tueros, Matías Jorge |
title |
Synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
title_short |
Synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
title_full |
Synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
title_fullStr |
Synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
title_full_unstemmed |
Synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
title_sort |
synthesis of radio signals from extensive air showers using previously computed microscopic simulations |
publishDate |
2021 |
url |
http://sedici.unlp.edu.ar/handle/10915/124543 |
work_keys_str_mv |
AT tuerosmatiasjorge synthesisofradiosignalsfromextensiveairshowersusingpreviouslycomputedmicroscopicsimulations AT zillesanne synthesisofradiosignalsfromextensiveairshowersusingpreviouslycomputedmicroscopicsimulations |
bdutipo_str |
Repositorios |
_version_ |
1764820450596093952 |