Simulation study of the cosmic ray Sun shadow with a time-dependent solar magnetic field model

TL;DR

This study uses Monte Carlo simulations with time-dependent magnetic field models to analyze the Sun's cosmic ray shadow, comparing results with LHAASO observations to understand magnetic field influences.

Contribution

It introduces a novel approach incorporating daily magnetic field variations in Sun shadow simulations, improving short-term predictive accuracy.

Findings

CSSS model aligns better with observed Sun shadow displacement.

Time-dependent magnetic field modeling enhances short-term Sun shadow analysis.

Simulation results are consistent with LHAASO observations from 2021.

Abstract

During the propagation of cosmic rays in the solar system, the Sun will block those particles and form a shadow whose position and depth are very important probe of the magnetic fields in the Sun's corona, in the interplanetary space, and the Earth's vicinity. In this work we carry out Monte Carlo studies of the Sun shadow, with a novel approach to take into account daily variations of the coronal and interplanetary magnetic field models. This treatment is suitable for studies of short-term variations of the Sun shadow, which become detectable by the Large High Altitude Air Shower Observatory (LHAASO) experiment. Two different coronal magnetic field models, the Potential Field Source Surface (PFSS) and Current Sheet Source Surface (CSSS) models, with observational time-varying photospheric magnetic fields as boundary conditions, are studied in this work. The interplanetary magnetic fields are then derived using the Parker spiral model based on the coronal ones. Furthermore, both the coronal and interplanetary magnetic field strengths are corrected using the Parker Solar Probe (PSP) measurements. We compare the simulation results with the daily observations of Sun shadow by LHAASO in 2021, and find that the CSSS model generally shows better consistency of the displacement of the Sun shadow than the PFSS model.