Standard

Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder. / Bezyazeekov, P.; Budnev, N.; Fedorov, O. и др.

37th International Cosmic Ray Conference (ICRC2021): Proceedings in Science (PoS). 2021.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Bezyazeekov, P, Budnev, N, Fedorov, O, Gress, OA, Grishin, OG, Haungs, A, Huege, T, Kazarina, Y, Kleifges, M, Korosteleva, E, Kostunin, D, Kuzmichev, LA, Lenok, VV, Lubsandorzhiev, NB, Malakhov, S, Marshalkina, T, Monkhoev, R, Osipova, E, Pakhorukov, AL, Pankov, L, Prosin, V, Schröder, FG, Shipilov, D, Zagorodnikov, AV, Михайленко, АЮ, Turishcheva, P, Golovachev, S, Sotnikov, V & Сотникова, ЕВ 2021, Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder. в 37th International Cosmic Ray Conference (ICRC2021): Proceedings in Science (PoS). 37th International Cosmic Ray Conference, Берлин, Берлин, Германия, 12.07.2021. https://doi.org/10.22323/1.395.0223

APA

Bezyazeekov, P., Budnev, N., Fedorov, O., Gress, O. A., Grishin, O. G., Haungs, A., Huege, T., Kazarina, Y., Kleifges, M., Korosteleva, E., Kostunin, D., Kuzmichev, L. A., Lenok, V. V., Lubsandorzhiev, N. B., Malakhov, S., Marshalkina, T., Monkhoev, R., Osipova, E., Pakhorukov, A. L., ... Сотникова, Е. В. (2021). Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder. в 37th International Cosmic Ray Conference (ICRC2021): Proceedings in Science (PoS) https://doi.org/10.22323/1.395.0223

Vancouver

Bezyazeekov P, Budnev N, Fedorov O, Gress OA, Grishin OG, Haungs A и др. Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder. в 37th International Cosmic Ray Conference (ICRC2021): Proceedings in Science (PoS). 2021 doi: 10.22323/1.395.0223

Author

Bezyazeekov, P. ; Budnev, N. ; Fedorov, O. и др. / Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder. 37th International Cosmic Ray Conference (ICRC2021): Proceedings in Science (PoS). 2021.

BibTeX

@inproceedings{e6cae5848e744f928b70408cab01493d,
title = "Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder",
abstract = "Radio detection of air showers produced by ultra-high energy cosmic rays is a cost-effective technique for the next generation of sparse arrays. The performance of this technique strongly depends on the environmental background, which has different constituents, namely anthropogenic radio frequency interferences, synchrotron galactic radiation and others. These components have recognizable features, which can help for background suppression. A powerful method for handling this is the application of convolution neural networks with a specific architecture called autoencoder. By suppressing unwanted signatures, the autoencoder keeps the signal-like ones. We have successfully developed and trained an autoencoder, which is now applied to the data from Tunka-Rex. We show the procedures of the training and optimization of the network including benchmarks of different architectures. Using the autoencoder, we improved the standard analysis of Tunka-Rex in order to lower the threshold of the detection. This enables the reconstructing of sub-threshold events with energies lower than 0.1 EeV with satisfactory angular and energy resolutions.",
author = "P. Bezyazeekov and N. Budnev and O. Fedorov and Gress, {O. A.} and Grishin, {O. G.} and A. Haungs and T. Huege and Y. Kazarina and M. Kleifges and E. Korosteleva and D. Kostunin and Kuzmichev, {L. A.} and V.V. Lenok and Lubsandorzhiev, {N. B.} and S. Malakhov and T. Marshalkina and R. Monkhoev and E. Osipova and Pakhorukov, {A. L.} and L. Pankov and V. Prosin and Schr{\"o}der, {F. G.} and D. Shipilov and Zagorodnikov, {A. V.} and Михайленко, {Алина Юрьевна} and P. Turishcheva and S. Golovachev and V. Sotnikov and Сотникова, {Евгения Вадимовна}",
note = "The authors would like to express gratitude to the colleagues from KCDC team. The development and testing of the software was supported by the state contract with Institute of Thermophysics SB RAS.; 37th International Cosmic Ray Conference : The astroparticle physics conference, ICRC2021 ; Conference date: 12-07-2021 Through 23-07-2021",
year = "2021",
month = jul,
doi = "10.22323/1.395.0223",
language = "English",
booktitle = "37th International Cosmic Ray Conference (ICRC2021)",
url = "https://icrc2021.desy.de/",

}

RIS

TY - GEN

T1 - Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder

AU - Bezyazeekov, P.

AU - Budnev, N.

AU - Fedorov, O.

AU - Gress, O. A.

AU - Grishin, O. G.

AU - Haungs, A.

AU - Huege, T.

AU - Kazarina, Y.

AU - Kleifges, M.

AU - Korosteleva, E.

AU - Kostunin, D.

AU - Kuzmichev, L. A.

AU - Lenok, V.V.

AU - Lubsandorzhiev, N. B.

AU - Malakhov, S.

AU - Marshalkina, T.

AU - Monkhoev, R.

AU - Osipova, E.

AU - Pakhorukov, A. L.

AU - Pankov, L.

AU - Prosin, V.

AU - Schröder, F. G.

AU - Shipilov, D.

AU - Zagorodnikov, A. V.

AU - Михайленко, Алина Юрьевна

AU - Turishcheva, P.

AU - Golovachev, S.

AU - Sotnikov, V.

AU - Сотникова, Евгения Вадимовна

N1 - Conference code: 37

PY - 2021/7

Y1 - 2021/7

N2 - Radio detection of air showers produced by ultra-high energy cosmic rays is a cost-effective technique for the next generation of sparse arrays. The performance of this technique strongly depends on the environmental background, which has different constituents, namely anthropogenic radio frequency interferences, synchrotron galactic radiation and others. These components have recognizable features, which can help for background suppression. A powerful method for handling this is the application of convolution neural networks with a specific architecture called autoencoder. By suppressing unwanted signatures, the autoencoder keeps the signal-like ones. We have successfully developed and trained an autoencoder, which is now applied to the data from Tunka-Rex. We show the procedures of the training and optimization of the network including benchmarks of different architectures. Using the autoencoder, we improved the standard analysis of Tunka-Rex in order to lower the threshold of the detection. This enables the reconstructing of sub-threshold events with energies lower than 0.1 EeV with satisfactory angular and energy resolutions.

AB - Radio detection of air showers produced by ultra-high energy cosmic rays is a cost-effective technique for the next generation of sparse arrays. The performance of this technique strongly depends on the environmental background, which has different constituents, namely anthropogenic radio frequency interferences, synchrotron galactic radiation and others. These components have recognizable features, which can help for background suppression. A powerful method for handling this is the application of convolution neural networks with a specific architecture called autoencoder. By suppressing unwanted signatures, the autoencoder keeps the signal-like ones. We have successfully developed and trained an autoencoder, which is now applied to the data from Tunka-Rex. We show the procedures of the training and optimization of the network including benchmarks of different architectures. Using the autoencoder, we improved the standard analysis of Tunka-Rex in order to lower the threshold of the detection. This enables the reconstructing of sub-threshold events with energies lower than 0.1 EeV with satisfactory angular and energy resolutions.

U2 - 10.22323/1.395.0223

DO - 10.22323/1.395.0223

M3 - Conference contribution

BT - 37th International Cosmic Ray Conference (ICRC2021)

T2 - 37th International Cosmic Ray Conference

Y2 - 12 July 2021 through 23 July 2021

ER -

ID: 29046362