We propose a technique called Optimal Analysis-Specific Importance Sampling (OASIS) to reduce the number of simulated events required for a high-energy experimental analysis to reach a target sensitivity. We provide recipes to obtain the optimal sampling distributions which preferentially focus the event generation on the regions of phase space with high utility to the experimental analyses. OASIS leads to a conservation of resources at all stages of the Monte Carlo pipeline, including full-detector simulation, and is complementary to approaches which seek to speed-up the simulation pipeline.

中文翻译：

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OASIS：针对事件生成的最优分析特定重要性采样

我们提出了一种称为“最优分析专用重要性采样”（OASIS）的技术，以减少高能实验分析达到目标灵敏度所需的模拟事件数量。我们提供了获得最佳采样分布的方法，该方法优先将事件生成集中在相空间区域，对实验分析具有很高的实用性。OASIS导致在蒙特卡洛流水线的所有阶段（包括全探测器仿真）节省了资源，并补充了试图加快仿真流水线的方法。