This work introduces two Monte Carlo (MC)-based sampling methods, known as line sampling and subset simulation, to improve the performance of standard MC analyses in the context of asteroid impact risk assessment. Both techniques sample the initial uncertainty region in different ways, with the result of either providing a more accurate estimate of the impact probability or reducing the number of required samples during the simulation with respect to standard MC techniques. The two methods are first described and then applied to some test cases, providing evidence of the increased accuracy or the reduced computational burden with respect to a standard MC simulation. Finally, a sensitivity analysis is carried out to show how parameter setting affects the accuracy of the results and the numerical efficiency of the two methods.

中文翻译：

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使用蒙特卡罗线采样和子集模拟计算近地物体的撞击概率

这项工作引入了两种基于蒙特卡罗 (MC) 的采样方法，称为线采样和子集模拟，以提高小行星撞击风险评估中标准 MC 分析的性能。两种技术都以不同的方式对初始不确定区域进行采样，结果要么提供对撞击概率的更准确估计，要么在模拟期间相对于标准 MC 技术减少所需的样本数量。这两种方法首先被描述，然后应用于一些测试用例，提供了相对于标准 MC 模拟提高准确性或减少计算负担的证据。最后，进行了敏感性分析，以说明参数设置如何影响结果的准确性和两种方法的数值效率。