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宇宙线的超新星遗迹起源

The Origin of Cosmic Rays from Supernova Remnants

  • 摘要: 宇宙线的起源是高能天体物理的核心问题之一. 一直以来, 超新星爆发被认为是能谱膝区以下宇宙线的主要来源. 多波段观测表明, 超新星遗迹有能力加速带电粒子至亚PeV ( 10^15 eV)能量. 扩散激波加速被认为是最有效的天体高能粒子加速机制之一, 而超新星遗迹的大尺度激波正好为这一机制提供平台. 近年来, 一系列较高精度的地面和空间实验极大地推动了对宇宙线以及超新星遗迹的研究. 新的观测事实挑战着传统的扩散激波加速模型以及其在银河系宇宙线超新星遗迹起源学说上的应用, 深化了人们对宇宙高能现象的认识.结合超新星遗迹辐射能谱的时间演化特性, 构建的时间依赖的超新星遗迹粒子加速模型, 不仅能够解释200 GV附近宇宙线的能谱反常, 还自然地形成能谱膝区, 甚至可以将超新星遗迹粒子加速对宇宙线能谱的贡献延伸至踝区. 该模型预期超新星遗迹中粒子的输运行为表现为湍流扩散, 这需要未来的观测以及与粒子输运相关的等离子体数值模拟工作来进一步验证.

     

    Abstract: The origin of cosmic rays is one of the key questions in high-ernergy astrophysics. Supernovae have been considered as the dominant sources of cosmic rays below the spectral knee. Multi-wavelength observations indeed show that supernova remnants are capable of accelerating particles into sub-knee energies. Diffusive shock acceleration is considered as one of the most efficient cosmic high-energy particle acceleration mechanisms, and may operate effectively in the large-scale shocks of supernova remnants. Recently, a series of high-precision ground and space experiments have greatly advanced the study of cosmic rays and supernova remnants. New observational features challenge the classical diffusive shock acceleration model and its application to the scenario of supernova remnants origin of the Galactic cosmic rays, and have advanced our understanding to cosmic high-energy phenomena. In combination with broadband spectral evolution of supernova remnants, we propose a time-dependent particle acceleration model, which can not only explain the anomalies in cosmic-ray distributions around 200 GV, but also naturally reproduce the cosmic-ray spectral knee with prominent contributions to cosmic ray flux up to the spectral ankle. This model requires that high-energy particle transport is dominated by turbulent convection with a diffusion coefficient weakly depending on the particle energy near supernova remnants, which needs to be verified by numerical simulations of the particle transportation in the future

     

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