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dc.contributor.authorPytel, Krzysztof
dc.contributor.authorGłas, Dariusz
dc.contributor.authorSzadkowski, Zbigniew
dc.contributor.editorRosa, Joao Luis G.
dc.identifier.citationSzadkowski Z., Głas D., Pytel K., Artificial Neural Network as a FPGA Trigger for a Detection of Neutrino-Induced Air Showers [in:] Artificial Neural Networks - Models and Applications, ed. by Joao Luis G. Rosa, 2016, pp. 141-161, DOI: 10.5772/63110.pl_PL
dc.description.abstractNeutrinos play a fundamental role in the understanding of the origin of ultrahigh-energy cosmic rays (UHECR). They interact through charged and neutral currents in the atmosphere generating extensive air showers. However, the very low rate of events potentially generated by neutrinos is a significant challenge for detection techniques and requires both sophisticated algorithms and high-resolution hardware. We developed the FPGA trigger which is generated by a neural network. The algorithm can recognize various waveform types. It has been developed and tested on ADC traces of the Pierre Auger surface detectors. We developed the algorithm of artificial neural network on a MATLAB platform. Trained network that we implemented into the largest Cyclone V E FPGA was used for the prototype of the front-end board for the AugerPrime. We tested several variants, and the Levenberg–Marquardt algorithm (trainlm) was the most efficient. The network was trained: (a) to recognize ‘old’ very inclined showers (real Auger data were used as patterns for both positive and negative markers: for reconstructed inclined showers and for triggered by time over threshold (ToT), respectively, (b) to recognize ‘neutrino-induced showers’. Here, we used simulated data for positive markers and vertical real showers for negative ones.pl_PL
dc.description.sponsorshipThis work is supported by the National Science Centre (Poland) under NCN Grant No. 2013/08/ M/ST9/00322. The authors would like to thank the Pierre Auger Collaboration for an opportunity of using the CORSIKA and offline simulation packages.pl_PL
dc.relation.ispartofArtificial Neural Networks - Models and Applications;6
dc.rightsUznanie autorstwa 4.0 Międzynarodowe*
dc.subjectcosmic rayspl_PL
dc.subjectneural networkpl_PL
dc.subjectinclined showerspl_PL
dc.subjectPierre Auger Observatorypl_PL
dc.titleArtificial Neural Network as a FPGA Trigger for a Detection of Neutrino-Induced Air Showerspl_PL
dc.typeBook chapterpl_PL
dc.contributor.authorAffiliationUniwersytet Łódzki, Wydział Fizyki i Informatyki Stosowanejpl_PL
dc.contributor.authorAffiliationUniwersytet Łódzki, Wydział Fizyki i Informatyki Stosowanejpl_PL
dc.contributor.authorAffiliationUniwersytet Łódzki, Wydział Fizyki i Informatyki Stosowanejpl_PL
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dc.disciplinenauki fizycznepl_PL

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Uznanie autorstwa 4.0 Międzynarodowe
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