An Approach for Identifying Patterns of Occurrence of Transient Solar Events Based on Muon Flux

• Mariana Teixeira UFF
• Daniel de Oliveira UFF

DOI: https://doi.org/10.5753/bresci.2018.3281

Abstract

The muon is an elementary particle with a negative charge, and is the most abundant charged component of cosmic radiation that penetrates deep into the Earth’s soil. Analyzing the flow of muons that reaches our planet is important to identify solar eruptions that can cause harm to the population. This paper presents an approach based on sequence mining algorithms to automate the process of identifying frequent patterns in the captured muon stream. Experiments carried out show that the approach is capable of identifying eruptions by means of the identified frequent patterns.

References

Augusto, C. R. A., Kopenkin, V., Navia, C. E., Tsui, K. H., and Sinzi, T. (2012). Search for a simultaneous signal from small transient events in the pierre auger observatory and the tupi muon telescopes. Phys. Rev. D, 86:022001.

Augusto, C. R. A., Navia, C. E., de Oliveira, M. N., Nepomuceno, A. A., Kopenkin, V., and Sinzi, T. (2017). Muon excess at sea level during the progress of a geomagnetic storm and high-speed stream impact near the time of earth’s heliospheric sheet crossing. Solar Physics, 292(8):107.

Ayres, J., Flannick, J., Gehrke, J., and Yiu, T. (2002). Sequential pattern mining using a bitmap representation. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 429–435. ACM.

Han, J., Pei, J., and Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.