论文标题
使用采样/重要性重采样的贝叶斯概率更新：核理论中的应用
Bayesian probability updates using Sampling/Importance Resampling: Applications in nuclear theory
论文作者
论文摘要
我们回顾了一种既定的贝叶斯抽样方法，称为采样/重要性重采样，并在核理论中突出情况下，当它特别有用时。为此，我们既分析了一个玩具问题，又证明了重要性重新采样的现实应用，以推断基于手性有效田间理论的$δ$ nlo相互作用模型参数的后验分布，并估计目标可观察物的后验概率分布。该方法的局限性还显示在重要性重新采样中断的极端情况下。
We review an established Bayesian sampling method called sampling/importance resampling and highlight situations in nuclear theory when it can be particularly useful. To this end we both analyse a toy problem and demonstrate realistic applications of importance resampling to infer the posterior distribution for parameters of $Δ$NNLO interaction model based on chiral effective field theory and to estimate the posterior probability distribution of target observables. The limitation of the method is also showcased in extreme situations where importance resampling breaks.
