论文标题
基于分数的生成型生成型淋浴模拟
Score-based Generative Models for Calorimeter Shower Simulation
论文作者
论文摘要
基于得分的生成模型是一类新的生成算法，即使在高维空间中也可以产生逼真的图像，目前超过了其他基准类别和应用程序的其他最新模型。在这项工作中，我们介绍了Caloscore，这是一种基于分数的生成模型，用于应用于量热计淋浴的生成物。使用快速热量量表仿真挑战2022数据集研究了三个不同的扩散模型。 Caloscore是对撞机物理学中基于得分的生成模型的第一个应用，并且能够为所有数据集生成高保真量热计图像，为热量计淋浴模拟提供了替代性范式。
Score-based generative models are a new class of generative algorithms that have been shown to produce realistic images even in high dimensional spaces, currently surpassing other state-of-the-art models for different benchmark categories and applications. In this work we introduce CaloScore, a score-based generative model for collider physics applied to calorimeter shower generation. Three different diffusion models are investigated using the Fast Calorimeter Simulation Challenge 2022 dataset. CaloScore is the first application of a score-based generative model in collider physics and is able to produce high-fidelity calorimeter images for all datasets, providing an alternative paradigm for calorimeter shower simulation.
