http://arxiv.org/abs/1906.10947
The Tunka Radio Extension (Tunka-Rex) is a digital antennaarray operating in the frequency band of 30-80 MHz, measuring the radioemission of air-showers induced by ultra-high energy cosmic rays. Tunka-Rex is co-located with the TAIGA experiment in Siberia and consistsof 63 antennas, 57 of them in a densely instrumented area of about1 km2. The signals from the air showers are short pulses, which havea duration of tens of nanoseconds and are recorded in traces of about5{\mu}s length. The Tunka-Rex analysis of cosmic-ray events is based onthe reconstruction of these signals, in particular, their positions in thetraces and amplitudes. This reconstruction suffers at low signal-to-noiseratios, i.e. when the recorded traces are dominated by background. Tolower the threshold of the detection and increase the efficiency, we applyadvanced methods of signal reconstruction, namely matched filtering anddeep neural networks with autoencoder architecture. In the present workwe show the comparison between the signal reconstructions obtainedwith these techniques, and give an example of the first reconstruction ofthe Tunka-Rex signals obtained with a deep neural networks.
P. Bezyazeekov, N. Budnev, O. Fedorov, et. al.
Thu, 27 Jun 19
25/62
Comments: Proceedings of the 3rd International Workshop on Data Life Cycle in Physics, Irkutsk, Russia, April 2-7, 2019