INFLUENCE OF IACT DATA PREPROCESSING METHODS ON THE ACCURACY OF EAS PARAMETERS RECONSTRUCTION
https://doi.org/10.56304/S2079562926010483
EDN: VWHAYS
Abstract
This work investigates the influence of data preprocessing methods on the accuracy of reconstructing the parameters of events detected by Imaging Atmospheric Cherenkov Telescopes (IACTs). The simulation of the events detected by the telescopes is described, taking into account the night background and the noise of the recording camera electronics. Two image cleaning algorithms for noise suppression and their efficiency are compared.
About the Authors
P. A. Volchugov
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
Russian Federation
Russian Federation
A. P. Kryukov
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
Russian Federation
Russian Federation
E. O. Gres
Research Institute of Applied Physics, Irkutsk State University
Russian Federation
Russian Federation
A. P. Demichev
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
Russian Federation
Russian Federation
J. J. Dubenskaya
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
Russian Federation
Russian Federation
D. P. Zhurov
Research Institute of Applied Physics, Irkutsk State University
Russian Federation
Russian Federation
S. P. Polyakov
Institute for Informatics and Automation Problems of the National Academy of Science of the Republic of Armenia
Armenia
Armenia
E. B. Postnikov
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
Russian Federation
Russian Federation
A. Y. Razumov
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
Russian Federation
Russian Federation
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Review
For citations:
Volchugov P.A., Kryukov A.P., Gres E.O., Demichev A.P., Dubenskaya J.J., Zhurov D.P., Polyakov S.P., Postnikov E.B., Razumov A.Y. INFLUENCE OF IACT DATA PREPROCESSING METHODS ON THE ACCURACY OF EAS PARAMETERS RECONSTRUCTION. Nuclear Physics and Engineering. 2026;17(2):245-250. (In Russ.) https://doi.org/10.56304/S2079562926010483. EDN: VWHAYS
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