EPJ Web Conf.
Volume 245, 202024th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|Number of page(s)||8|
|Section||2 - Offline Computing|
|Published online||16 November 2020|
GTS – Garfield-based Triple-GEM Simulator
INFN, Sezione di Ferrara, via G. Saragat 1, 44122 Ferrara, Italy
* e-mail: firstname.lastname@example.org
Published online: 16 November 2020
Triple-GEM detectors are gaseous devices used in high energy physics to measure the path of the particles which cross them. The characterisation of triple GEM detectors and the estimation of the performance for real data experiments require a complete comprehension of the mechanisms which transform the passage of one particle in the detector into electric signals, and dedicated MonteCarlo simulations are needed. In this work we will describe GTS (Garfield-based Triple-gem Simulator), a MonteCarlo code which has been developed to simulate the detector response to the passage of particles inside triple GEMs. The software takes into account the processes from the primary ionization up to the signal formation, e.g. avalanche multiplication and the effects of the diffusion in the gas volume. It uses a parametrization of the variables of interest meant to reproduce the same detector response (i.e. the charge distribution at the anode) as provided by Garfield++, a well known software that already performs this kind of simulation more detailed and therefore with a high CPU time consumption. In addition to the detector response, the simulation of the APV-25 electronics is implemented and the output is used to reconstruct the particle position with the Charge Centroid (CC) and the microTime Projection Chamber (µTPC) methods. A comparison of the simulated performance and the one collected in testbeams is used to tune the parameters used in GTS. Results in different conditions of incident angle will be shown.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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