论文标题
Caloflow for for calochallenge数据集1
CaloFlow for CaloChallenge Dataset 1
论文作者
论文摘要
Caloflow是一种基于归一化流量的快速量热模拟的新方法。将Caloflow应用于快速热量计仿真挑战2022的数据集1的光子和带电的Pion Geant4淋浴时，我们显示了如何以比Geant4快几个数量级的抽样时间生成高效率样品。我们使用量热计的淋浴图像，高级特征的直方图以及诸如经过训练的分类器训练，以区分Caloflow和Geant4样品的分类器，证明了样品的保真度。
CaloFlow is a new and promising approach to fast calorimeter simulation based on normalizing flows. Applying CaloFlow to the photon and charged pion Geant4 showers of Dataset 1 of the Fast Calorimeter Simulation Challenge 2022, we show how it can produce high-fidelity samples with a sampling time that is several orders of magnitude faster than Geant4. We demonstrate the fidelity of the samples using calorimeter shower images, histograms of high-level features, and aggregate metrics such as a classifier trained to distinguish CaloFlow from Geant4 samples.
