Abstract
Solar bright points (BPs) are small-scale magnetic features observed on the solar surface. They play a significant role in the transfer of energy and mass between the solar photosphere and the corona. This article presents a comprehensive statistical analysis of BPs in different solar areas: quiet Sun (QS), active regions (AR), and coronal holes (CH). We separate the BPs into two categories: network and internetwork. Our study aims to understand the spatial distribution and properties of BPs in these areas, which can help improve our knowledge of the Sun’s magnetic activity and energy transfer processes. Our research highlights the close relationship between the spatial distribution and characteristics of BPs and the solar magnetic field. Using machine learning, we achieved efficient and accurate BP detection, enabling analysis of a larger dataset. The prevalence of network BPs in the QS and internetwork BPs in CH suggests differences in magnetic field concentration. In AR, BPs are evenly distributed between network and internetwork areas, reflecting the complex nature of the magnetic field.
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