GRAPES-3的刚度相关CORSIKA模拟建模
Modeling of rigidity dependent CORSIKA simulations for GRAPES-3
摘要：
位于印度乌提的GRAPES-3 μ子望远镜每天记录4x10^9 μ子。这些μ子是由大气中的初级宇宙射线（PCR）相互作用产生的。高统计量的μ子使GRAPES-3能够精确测量各种太阳引起的现象，包括日冕物质抛射（CME）、Forbush减少、地磁暴（GMS）和雷暴上空通过时的大气加速。然而，观测数据的理解和解释需要蒙特卡罗（MC）模拟的PCR和随后的发展在大气中的阵雨。CORSIKA是广泛用于此目的的标准MC模拟代码。然而，这些模拟是耗时的，因为大量的相互作用和衰变需要考虑到从大气层顶部到地面的阵雨发展的各个阶段。因此，计算资源成为重要的考虑因素，特别是当需要模拟数十亿PCR以匹配数据的高统计准确性时。在GRAPES-3模拟过程中，观察到超过60%的模拟事件并没有真正到达地球大气层。地磁场（GMF）为PCR创建了一个阈值，称为截止刚度Rc，这是一个方向依赖参数，低于该参数，PCR无法到达地球大气层。然而，在CORSIKA中，没有设置方向相关阈值的规定。我们已经设计了一种有效的方法，已考虑到这种Rc的依赖性。GRAPES-3模拟的模拟时间减少了3倍，输出数据大小减少了2倍。这已纳入CORSIKA版本v75600及以后版本。在这项工作中讨论了这一点的详细实施以及潜在的好处。
英文摘要：
The GRAPES-3 muon telescope located in Ooty, India records 4x10^9 muons daily. These muons are produced by interaction of primary cosmic rays (PCRs) in the atmosphere. The high statistics of muons enables GRAPES-3 to make precise measurement of various sun-induced phenomenon including coronal mass ejections (CME), Forbush decreases, geomagnetic storms (GMS) and atmosphere acceleration during the overhead passage of thunderclouds. However, the understanding and interpretation of observed data requires Monte Carlo (MC) simulation of PCRs and subsequent development of showers in the atmosphere. CORSIKA is a standard MC simulation code widely used for this purpose. However, these simulations are time consuming as large number of interactions and decays need to be taken into account at various stages of shower development from top of the atmosphere down to ground level. Therefore, computing resources become an important consideration particularly when billion of PCRs need to be simulated to match the high statistical accuracy of the data. During the GRAPES-3 simulations, it was observed that over 60% of simulated events don't really reach the Earth's atmosphere. The geomagnetic field (GMF) creates a threshold to PCRs called cutoff rigidity Rc, a direction dependent parameter below which PCRs can't reach the Earth's atmosphere. However, in CORSIKA there is no provision to set a direction dependent threshold. We have devised an efficient method that has taken into account of this Rc dependence. A reduction by a factor ~3 in simulation time and ~2 in output data size was achieved for GRAPES-3 simulations. This has been incorporated in CORSIKA version v75600 onwards. Detailed implementation of this along the potential benefits are discussed in this work.
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