Simulated events are key ingredients in almost all high-energy physics
analyses. However, imperfections in the simulation can lead to sizeable
differences between the observed data and simulated events. The effects of such
mismodelling on relevant observables must be corrected either effectively via
scale factors, with weights or by modifying the distributions of the
observables and their correlations. We introduce a correction method that
transforms one multidimensional distribution (simulation) into another one
(data) using a simple architecture based on a single normalising flow with a
boolean condition. We demonstrate the effectiveness of the method on a
physics-inspired toy dataset with non-trivial mismodelling of several
observables and their correlations.

在高能物理分析中，模拟事件是几乎所有研究的关键要素。本文介绍了一种基于单一归一化流和布尔条件的简单方法，用于将一个多维分布（模拟数据）转化为另一个多维分布（实际数据），以对相关可观测量进行校正。实验证明了该方法在包含多个可观测量及其相关性的模拟数据中的有效性。