Charge–Sign Dependence of Cosmic Ray Modulation from the PAMELA Experiment

Charge–Sign Dependence of Cosmic Ray Modulation from the PAMELA Experiment

Machine learning is used to obtain ratios of 100–500-MeV positron-to-electron and electron-to-proton fluxes with rigidities of 1–1.7-GV from the PAMELA experimental data for 2006–2016 in order to study the solar modulation of cosmic-ray fluxes with energies below 1 GeV. Observed features of the data...

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Veröffentlicht in:Bulletin of the Russian Academy of Sciences. Physics 2023-07, Vol.87 (7), p.962-964
Hauptverfasser: Mukhin, P., Mikhailov, V. V., Mikhailova, A. V.
Format: Artikel
Sprache:eng
Schlagworte:
Cosmic rays
Fluxes
Hadrons
Heavy Ions
Machine learning
Modulation
Nuclear Physics
Physics
Physics and Astronomy
Sunspots
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Beschreibung
Zusammenfassung:Machine learning is used to obtain ratios of 100–500-MeV positron-to-electron and electron-to-proton fluxes with rigidities of 1–1.7-GV from the PAMELA experimental data for 2006–2016 in order to study the solar modulation of cosmic-ray fluxes with energies below 1 GeV. Observed features of the data and a comparison to AMS-02 experimental results allow study of the charge–sign dependence of modulation around the sunspot minimum in 2009 and the maximum in 2015.
ISSN:1062-8738
1934-9432
DOI:10.3103/S1062873823702544