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Since the beginning of the space exploration era, solar activity was observed at its lowest level during 2006 to 2009. During this period, the PAMELA space experiment observed spectra for galactic cosmic rays, specifically for protons, electrons and positrons over a wide energy range, during what is called an A < 0 solar magnetic polarity cycle. Drift theory predicts a difference in the behaviour for these oppositely charge particles during A < 0 cycles. An opportunity was thus created to study the predicted charge-sign-dependent modulation, also now for very quiet heliospheric conditions. A comprehensive three-dimensional, drift modulation model has been used to study the solar modulation for cosmic rays in detail with extensive comparison to the observed PAMELA spectra for the mentioned period. First, this was done for protons and secondly for electrons, as already published, to test and to authenticate the modelling approach and then to come to a better understanding and appreciation of the underlying physics, such as diffusion and drift theory. The results were also used to make predictions of how cosmic rays are differently modulated down to low energies (1 MeV) for the two magnetic polarity cycles of the Sun, and what role drifts play in this process. All computed solutions are based on new very local interstellar spectra, now also done for positrons. This report is focussed on detailed aspects of the solar modulation of positrons during the extraordinary quiet solar modulation period from 2006 to 2009. For the first time, a meaningful modulation factor in the heliosphere is computed for positrons, from 50 GeV down to 1 MeV, as well as the electron to positron ratios as a function of time and rigidity for the mentioned period.
The 11-year and 22-year modulation of galactic cosmic rays (GCRs) in the inner heliosphere are studied using a numerical model developed by Qin and Shen in 2017. Based on the numerical solutions of Parkers transport equations, the model incorporates
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The scaling of the turbulent spectra provides a key measurement that allows to discriminate between different theoretical predictions of turbulence. In the solar wind, this has driven a large number of studies dedicated to this issue using in-situ da
We explore the tail of various waiting time datasets of processes that follow a nonstationary Poisson distribution with a sinusoidal driver. Analytically, we find that the distribution of large waiting times of such processes can be described using a