Kinetic simulations of the cosmic ray pressure anisotropy instability: cosmic ray scattering rate in the saturated state

Xiaochen Sun, Xue-Ning Bai, Xihui Zhao
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Abstract

Cosmic ray (CR) feedback plays a vital role in shaping the formation and evolution of galaxies through their interaction with magnetohydrodynamic waves. In the CR self-confinement scenario, the waves are generated by the CR gyro-resonant instabilities via CR streaming or CR pressure anisotropy, and saturate by balancing wave damping. The resulting effective particle scattering rate by the waves, {\nu}eff, critically sets the coupling between the CRs and background gas, but the efficiency of CR feedback is yet poorly constrained. We employ 1D kinetic simulations under the Magnetohydrodynamic-Particle-In-Cell (MHD-PIC) framework with the adaptive {\delta}f method to quantify {\nu}eff for the saturated state of the CR pressure anisotropy instability (CRPAI) with ion-neutral friction. We drive CR pressure anisotropy by expanding/compressing box, mimicking background evolution of magnetic field strength, and the CR pressure anisotropy eventually reaches a quasi-steady state by balancing quasi-linear diffusion. At the saturated state, we measure {\nu}eff and the CR pressure anisotropy level, establishing a calibrated scaling relation with environmental parameters. The scaling relation is consistent with quasi-linear theory and can be incorporated to CR fluid models, in either the single-fluid or p-by-p treatments. Our results serve as a basis towards accurately calibrating the subgrid physics in macroscopic studies of CR feedback and transport.
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宇宙射线压力各向异性不稳定性的动力学模拟:饱和状态下的宇宙射线散射率
宇宙射线(CR)反馈通过与磁流体动力学波的相互作用,在塑造星系的形成和演化过程中发挥着至关重要的作用。在CR自约束情景中,波是由CR共振不稳定性通过CR流或CR压力各向异性产生的,并通过平衡波阻尼而饱和。由此产生的有效粒子散射率({\nu}eff)决定了CR与背景气体之间的耦合,但CR反馈的效率还没有得到很好的约束。我们在磁流体动力-粒子内胞(MHD-PIC)框架下采用自适应{delta}f方法进行了一维动力学模拟,量化了具有离子中性摩擦的CR压力各向异性不稳定性(CRPAI)饱和状态下的{\nu}eff。我们模拟磁场强度的背景演化,通过膨胀/压缩盒子来驱动CR压力各向异性,通过平衡准线性扩散,CR压力各向异性最终达到准稳态。在饱和状态下,我们测量了{\nu}eff和CR压力各向异性水平,建立了与环境参数的校准比例关系。该比例关系与准线性理论相一致,可纳入CR流体模型,无论是单流体还是p-by-p处理。我们的研究结果为在对 CR 反馈和传输的宏观研究中精确校准子网格物理学奠定了基础。
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