论文标题
理论不确定性的统计模式
Statistical Patterns of Theory Uncertainties
论文作者
论文摘要
全面的不确定性估计对于LHC的精确计划至关重要。尽管实验不确定性通常是通过随机过程和明确的滋扰参数来描述的，但理论上的不确定性缺乏这样的描述。我们研究了基于大量过程的规模变化的横截面预测的不确定性估计。我们发现类似于随机来源的模式，对于由强力介导的过程，具有准确的不确定性，但对电子的过程有系统地低估。我们根据参考过程的规模变化提出了一个改进的方案，该方案在摄动理论中从领先顺序降低到近代领导阶的映射中的异常值。
A comprehensive uncertainty estimation is vital for the precision program of the LHC. While experimental uncertainties are often described by stochastic processes and well-defined nuisance parameters, theoretical uncertainties lack such a description. We study uncertainty estimates for cross-section predictions based on scale variations across a large set of processes. We find patterns similar to a stochastic origin, with accurate uncertainties for processes mediated by the strong force, but a systematic underestimate for electroweak processes. We propose an improved scheme, based on the scale variation of reference processes, which reduces outliers in the mapping from leading order to next-to-leading-order in perturbation theory.
