Publication:
Multiparticle Event Reconstruction Using Deep Learning Methods for Coordinate-Tracking Unit Based on Drift Chambers

Научные группы
Организационные подразделения
Организационная единица
Другие подразделения НИЯУ МИФИ
Структурные подразделения НИЯУ МИФИ, не включенные в состав институтов и факультетов.
Организационная единица
Институт ядерной физики и технологий
Цель ИЯФиТ и стратегия развития - создание и развитие научно-образовательного центра мирового уровня в области ядерной физики и технологий, радиационного материаловедения, физики элементарных частиц, астрофизики и космофизики.
Выпуск журнала
Аннотация
© 2021, Pleiades Publishing, Ltd.Abstract: The new coordinate-tracking detector TREK based on multiwire drift chambers is being developed in the National Research Nuclear University MEPhI to study the muon component of extensive air showers. Its prototype named the coordinate-tracking unit based on drift chambers (CTUDC) has been designed. Investigation of the multiparticle events registered by the unit has shown all the complexity of reconstruction of such events. The analytical reconstruction methods applied earlier demonstrate their inefficacy in dealing with these events. A new approach based on deep learning methods is being developed to solve this problem. The paper presents the results of application of artificial neural networks to experimental data obtained by the CTUDC.
Описание
Ключевые слова
Цитирование
Multiparticle Event Reconstruction Using Deep Learning Methods for Coordinate-Tracking Unit Based on Drift Chambers / Vorob'ev, V.S. [et al.] // Physics of Atomic Nuclei. - 2021. - 84. - № 10. - P. 1780-1788. - 10.1134/S1063778821090362
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