Neutrino Transport with the Monte Carlo Method. II. Quantum Kinetic Equations
Neutrino Transport with the Monte Carlo Method. II. Quantum Kinetic Equations
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DOI：
10.3847/1538-4365/ac2aa4
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
Chinami Kato;H. Nagakura;Taiki Morinaga
中科院分区：
文献类型：
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作者：
Chinami Kato;H. Nagakura;Taiki Morinaga
作为味道转换，中微子具有独特的量子特征。最近的研究表明，集体中微子振荡在高能天体物理现象中起着重要作用。量子动力学方程(QKE)能够自洽地描述中微子味的转换、输运和物质碰撞。然而，在它们的数值实现过程中，我们遇到了许多技术困难。本文提出一种新的基于蒙特卡罗(MC)方法的QKE求解器。这是我们的经典MC中微子输运解算器的升级版本；本质上，在每个MC粒子中添加了包括混合态在内的味道自由度。这一扩展需要更新碰撞项的数值处理，特别是对于散射过程。我们通过在每个散射事件中生成一个新的MC粒子来解决这个技术问题。为了减少MC方法中固有的统计噪声，我们发展了有效平均自由程方法。这在不增加MC颗粒数量的情况下抑制了由于碰撞而引起的风味状态的突然改变。我们提供了一套代码测试来验证这些新模块，并与以前研究中报告的结果进行了比较。我们的QKE-MC求解器的开发理念和设计与其他确定性方法和网格方法完全不同，这表明它将是其他方法的补充，并可能为中微子动力学的物理过程提供新的见解。
Neutrinos have a unique quantum feature as flavor conversions. Recent studies suggested that collective neutrino oscillations play important roles in high-energy astrophysical phenomena. The quantum kinetic equation (QKE) is capable of describing the neutrino flavor conversion, transport, and matter collision self-consistently. However, we have experienced many technical difficulties in their numerical implementation. In this paper, we present a new QKE solver based on a Monte Carlo (MC) approach. This is an upgraded version of our classical MC neutrino transport solver; in essence, a flavor degree of freedom including mixing state is added into each MC particle. This extension requires updating numerical treatments of collision terms, in particular for scattering processes. We deal with the technical problem by generating a new MC particle at each scattering event. To reduce statistical noise inherent in MC methods, we develop the effective mean free path method. This suppresses a sudden change of flavor state due to collisions without increasing the number of MC particles. We present a suite of code tests to validate these new modules with comparison to the results reported in previous studies. Our QKE-MC solver is developed with fundamentally different philosophy and design from other deterministic and mesh methods, suggesting that it will be complementary to others and potentially provide new insights into physical processes of neutrino dynamics.